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Top 10 real-world data science case studies.

Aditya Sharma

Aditya is a content writer with 5+ years of experience writing for various industries including Marketing, SaaS, B2B, IT, and Edtech among others. You can find him watching anime or playing games when he’s not writing.

Frequently Asked Questions

Real-world data science case studies differ significantly from academic examples. While academic exercises often feature clean, well-structured data and simplified scenarios, real-world projects tackle messy, diverse data sources with practical constraints and genuine business objectives. These case studies reflect the complexities data scientists face when translating data into actionable insights in the corporate world.

Real-world data science projects come with common challenges. Data quality issues, including missing or inaccurate data, can hinder analysis. Domain expertise gaps may result in misinterpretation of results. Resource constraints might limit project scope or access to necessary tools and talent. Ethical considerations, like privacy and bias, demand careful handling.

Lastly, as data and business needs evolve, data science projects must adapt and stay relevant, posing an ongoing challenge.

Real-world data science case studies play a crucial role in helping companies make informed decisions. By analyzing their own data, businesses gain valuable insights into customer behavior, market trends, and operational efficiencies.

These insights empower data-driven strategies, aiding in more effective resource allocation, product development, and marketing efforts. Ultimately, case studies bridge the gap between data science and business decision-making, enhancing a company's ability to thrive in a competitive landscape.

Key takeaways from these case studies for organizations include the importance of cultivating a data-driven culture that values evidence-based decision-making. Investing in robust data infrastructure is essential to support data initiatives. Collaborating closely between data scientists and domain experts ensures that insights align with business goals.

Finally, continuous monitoring and refinement of data solutions are critical for maintaining relevance and effectiveness in a dynamic business environment. Embracing these principles can lead to tangible benefits and sustainable success in real-world data science endeavors.

Data science is a powerful driver of innovation and problem-solving across diverse industries. By harnessing data, organizations can uncover hidden patterns, automate repetitive tasks, optimize operations, and make informed decisions.

In healthcare, for example, data-driven diagnostics and treatment plans improve patient outcomes. In finance, predictive analytics enhances risk management. In transportation, route optimization reduces costs and emissions. Data science empowers industries to innovate and solve complex challenges in ways that were previously unimaginable.

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10 Business Analytics Case Studies [2024]

In today’s data-driven world, the strategic application of business analytics stands as a cornerstone for enterprise success across various industries. From retail giants optimizing inventory through predictive algorithms to healthcare systems enhancing patient care with personalized treatments, the transformative power of business analytics is undeniable. This compilation of ten business analytics case studies showcases how leading companies leverage data to drive decision-making, streamline operations, and deliver unprecedented value to customers. Each case study reveals unique insights into the practical challenges and innovative solutions that define cutting-edge business strategy, offering a window into the profound impact of data analytics in shaping global business landscapes.

Related: Business Analytics Vs. Data Analytics

Case Study 1: Walmart’s Inventory Management

Predictive Analytics for Inventory Efficiency

Walmart employs sophisticated predictive analytics to manage and optimize inventory across its extensive network of stores globally. This system uses historical sales data, weather predictions, and trending consumer behavior to forecast demand accurately. Walmart’s approach allows for dynamic adjustment of stock levels, ensuring that each store has just the right amount of inventory. This reduces the cost associated with excess inventory and minimizes instances of stockouts, thereby enhancing customer satisfaction.

Real-Time Data Integration for Strategic Decisions

The integration of real-time data from various sources, including point-of-sale systems, online transactions, and external market dynamics, enables Walmart to respond swiftly to changing market conditions. This commitment to security helps reduce risks and strengthens consumer confidence and trust in the brand, which is essential for retaining customers and ensuring satisfaction in the competitive financial services market. By leveraging this data, Walmart can launch targeted promotions and adjust pricing strategically to maximize sales and profitability, showcasing the power of real-time analytics in retail operations.

Case Study 2: UnitedHealth Group’s Predictive Analytics in Healthcare

Enhancing Patient Outcomes with Predictive Models

UnitedHealth Group utilizes predictive analytics to improve patient care within its network significantly. The healthcare provider can identify patients at risk of developing chronic diseases or those likely to experience rehospitalization by analyzing extensive datasets that include patient medical histories, treatment outcomes, and lifestyle choices. This proactive approach allows for early intervention through customized care plans, which enhances patient outcomes and optimizes resource allocation within the healthcare system.

Data-Driven Healthcare Management

UnitedHealth’s analytics capabilities extend to managing healthcare costs and improving service delivery. They can better manage staffing and resource needs by leveraging data to predict patient admission rates and peak times for different treatments. Furthermore, predictive analytics aids in developing new health services and programs that target the specific requirements of their patient population, leading to more efficient healthcare delivery and reduced operational costs. This strategic use of data ensures that patients receive the right care at the right time, enhancing overall patient satisfaction and loyalty.

Case Study 3: American Express Fraud Detection

Machine Learning for Advanced Fraud Prevention

American Express harnesses machine learning algorithms to enhance its fraud detection capabilities. By analyzing patterns in transaction data across millions of accounts, these algorithms can detect unusual behavior that may indicate fraud. Real-time processing of transactions allows American Express to quickly flag suspicious activities and prevent unauthorized transactions, protecting both the consumer and the institution from potential losses.

Building Consumer Trust Through Robust Security Measures

Advanced analytics helps American Express refine its customer verification processes and risk assessments. By continuously updating and training its models on new fraud tactics and scenarios, American Express stays ahead of fraudsters, ensuring robust security measures are in place. This robust emphasis on security reduces risks and enhances consumer confidence and trust in the organization, which is essential for maintaining client loyalty and satisfaction in the competitive financial services market.

Case Study 4: Zara’s Supply Chain Optimization

Responsive Supply Chain to Meet Fast Fashion Demands

Zara utilizes advanced analytics to create a highly responsive supply chain that keeps pace with the fast-changing fashion industry. Zara can quickly adjust production plans and inventory distribution by analyzing real-time sales data and customer feedback. This agility ensures that popular items are swiftly restocked and production of less popular items is curtailed, minimizing waste and maximizing profitability.

Streamlined Operations for Market Responsiveness

Zara’s analytics-driven approach extends to logistics and distribution strategies. Data analytics helps Zara optimize shipping routes and warehouse operations, reducing lead times from design to store shelves. This streamlined process meets consumer demand more efficiently and strengthens Zara’s position in the market by enabling rapid response to the latest fashion trends. This capability is a key differentiator in the competitive fast fashion market, where speed and responsiveness are critical to success.

Related: How to use Business Analytics to Improve Customer Retention?

Case Study 5: Netflix’s Recommendation Engine

Enhancing User Experience Through Personalized Recommendations

Netflix’s advanced machine learning algorithms are the powerhouse behind its highly acclaimed recommendation engine. This system delves deep into individual viewing histories, preferences, and interactive behaviors, such as pausing or rewinding, to customize content suggestions for each user. By tailoring viewing experiences to personal tastes, Netflix significantly enhances user engagement and satisfaction. This personalization makes it easier for subscribers to discover content that resonates with them, increasing their time on the platform and fostering a deeper connection to the Netflix brand.

Data-Driven Insights for Content Strategy

Beyond simply personalizing user experiences, Netflix employs a strategic content development and acquisition approach. Utilizing comprehensive data analytics, Netflix identifies trends and preferences in viewer behavior, such as popular genres or series, to inform its decisions on what new content to create or purchase. This systematic use of viewer data ensures that Netflix’s content library continuously evolves to match the preferences of its audience, maximizing viewer satisfaction and engagement. Moreover, this data-driven strategy enables Netflix to allocate its budget more effectively, investing in projects more likely to succeed and appeal to its user base, optimizing its return on investment.

Through these sophisticated analytics and machine learning applications, Netflix retains its position as a leader in the streaming industry. It sets the standard for media companies leveraging data to revolutionize user experience and drive business success.

Case Study 6: Coca-Cola’s Marketing Optimization

Leveraging Big Data for Targeted Marketing

Coca-Cola effectively utilizes big data analytics to refine its global marketing strategies. Coca-Cola gains deep insights into consumer behavior and preferences by analyzing diverse data sources, including social media interactions, point-of-sale transactions, and extensive market research. This valuable information enables the company to craft marketing campaigns tailored to various demographics and geographic regions. As a result, Coca-Cola enhances its advertisements’ relevance and appeal, significantly boosting its promotional activities’ effectiveness. This targeted approach increases consumer engagement and strengthens brand loyalty and market presence.

Optimizing Marketing Spend and ROI

Beyond enhancing customer engagement, Coca-Cola applies analytics to optimize its marketing expenditures. By meticulously analyzing the performance of different marketing channels and campaigns, Coca-Cola identifies which initiatives yield the highest return on investment. This strategic use of analytics allows the company to allocate its budget more effectively, concentrating resources on the most profitable activities. This efficiency not only reduces wasted expenditure but also maximizes the impact of each marketing dollar. Consequently, Coca-Cola maintains its competitive edge in the fiercely contested beverage industry, continually adapting to changing market dynamics and consumer trends.

Through these strategic big data applications, Coca-Cola sustains and amplifies its leadership in the global beverage market. The company’s adept use of analytics to drive marketing decisions exemplifies how traditional businesses can leverage modern technology to stay ahead in an evolving industry landscape, ensuring continued growth and success.

Case Study 7: Barclays’ Risk Management

Advanced Analytics for Credit Risk Assessment

Barclays uses predictive analytics to enhance its risk management practices, particularly in assessing credit and loan applications. By analyzing a comprehensive set of data, including applicants’ financial histories, transaction behaviors, and economic trends, Barclays can accurately predict the risk associated with each loan. This reduces the likelihood of defaults, protecting the bank’s assets and financial health.

Strategic Decision-Making to Minimize Financial Risks

The insights gained from analytics also aid Barclays in making strategic decisions about product offerings and market expansions. By understanding risk profiles across different demographics and regions, Barclays can tailor its financial products to meet the needs of its customers while managing risk effectively. This careful balance of risk and opportunity is crucial for sustainable growth in the competitive banking sector.

Related: Implementing Business Analytics in Healthcare

Case Study 8: Starbucks’ Strategic Use of Data for Expansion and Localization

Data-Driven Site Selection for Maximum Market Penetration

Starbucks uses advanced geographic information systems (GIS) and analytics to strategically pinpoint the optimal locations for new stores. By evaluating extensive demographic data, performance metrics of existing stores, and competitive landscapes, Starbucks is able to identify sites with the maximum success potential. This systematic approach helps maintain dense market coverage and ensures customer convenience, vital for driving consistent growth. The precision in site selection allows Starbucks to expand its global footprint strategically, optimizing market penetration and maximizing investment returns.

Enhancing Local Market Strategies Through Analytics

Beyond the strategic site selection, Starbucks extensively uses data analytics to tailor each store to its local context. This involves adapting store layouts, product offerings, and marketing strategies to match local consumer preferences and cultural nuances. By deeply analyzing customer behavior data and feedback within specific locales, Starbucks fine-tunes its offerings to resonate more strongly with local tastes and preferences. This localization strategy not only improves the customer experience but also increases customer loyalty and enhances the strength of the Starbucks brand in diverse markets.

These strategic data analytics applications underscore Starbucks’ ability to consistently align its business practices with customer expectations across various regions. By leveraging data-driven insights for macro decisions on new store locations and micro-level adjustments to store-specific offerings, Starbucks ensures its brand remains relevant and preferred worldwide. This comprehensive approach to using data solidifies Starbucks’ position as a leader in the global coffeehouse market, renowned for its forward-thinking and customer-centric business model.

Case Study 9: Nike’s Supply Chain Management

Dynamic Supply Chain Optimization Using Predictive Analytics

Nike employs advanced analytics to manage its global supply chain, ensuring efficient operation and timely delivery of products. Nike’s predictive models optimize manufacturing workflows and inventory distribution by analyzing data from production, distribution, and retail channels. This agile approach enables Nike to quickly adapt to shifting market demands and trends, ensuring that popular products are readily accessible while keeping surplus inventory to a minimum.

Sustainability Integration in Operations

Nike also leverages analytics to enhance the sustainability of its operations. Using data to monitor and optimize energy use, waste production, and material sourcing, Nike aims to reduce its environmental footprint while maintaining production efficiency. This focus on sustainable supply chain practices helps Nike meet its corporate responsibility goals and appeals to increasingly eco-conscious consumers.

Case Study 10: Google’s Data-Driven Decision Making

Harnessing Big Data for Strategic Insights

Google expertly leverages big data to inform its decision-making across its vast services. By analyzing extensive data collected from user interactions, market trends, and technological developments, Google identifies key opportunities for innovation and enhancements. This robust data analysis supports Google’s ability to maintain a leadership position in the tech industry, continually evolving its products to meet the dynamic needs of users globally. Insights derived from big data guide the development of cutting-edge technologies and refine existing services, ensuring Google sustains a competitive advantage.

Enhancing User Experience Through Personalization

Google utilizes advanced analytics to personalize the user experience across all its platforms comprehensively. By understanding detailed user preferences, behaviors, and engagement patterns, Google tailors its services to improve relevance and usability. This dedication to personalization is showcased in customized search results, targeted advertising, and tailored app recommendations to boost user satisfaction and engagement. Based on deep data insights, these adjustments ensure that Google’s services are intuitive and responsive, integral to users’ daily digital interactions.

Optimizing Marketing and Operations with Predictive Analytics 

Beyond product refinement, Google applies its data-driven approach to optimize marketing strategies and operational efficiencies. Using predictive analytics, Google forecasts future trends and user behaviors, enabling proactive responses to market demands. This strategic foresight enhances overall user experiences and drives operational efficiency, minimizing waste and maximizing the effectiveness of its initiatives. By consistently integrating data-driven insights into its operations, Google meets current market needs and shapes future trends, reinforcing its dominance in the global technology landscape. This strategic use of big data is crucial to Google’s enduring success and expansive influence in the digital world.

Related: Role of Business Analytics in Digital Transformation

The diverse business analytics applications illustrated in these ten case studies underscore their vital role in modern business strategy. Through the intelligent analysis of data, companies not only solve complex problems but also gain competitive advantages, driving growth and innovation. From improving customer satisfaction to optimizing logistical operations and managing risk, the case studies highlight how data-driven decisions are integral to achieving business objectives. As companies maneuver through the complexities of the digital era, the strategic use of analytics will continue to be a crucial factor in driving success, converting challenges into opportunities, and leading the way toward a smarter, more efficient future.

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10 Real World Data Science Case Studies Projects with Example

Top 10 Data Science Case Studies Projects with Examples and Solutions in Python to inspire your data science learning in 2023.

BelData science has been a trending buzzword in recent times. With wide applications in various sectors like healthcare , education, retail, transportation, media, and banking -data science applications are at the core of pretty much every industry out there. The possibilities are endless: analysis of frauds in the finance sector or the personalization of recommendations on eCommerce businesses.  We have developed ten exciting data science case studies to explain how data science is leveraged across various industries to make smarter decisions and develop innovative personalized products tailored to specific customers.

Walmart Sales Forecasting Data Science Project

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Table of Contents

Data science case studies in retail , data science case study examples in entertainment industry , data analytics case study examples in travel industry , case studies for data analytics in social media , real world data science projects in healthcare, data analytics case studies in oil and gas, what is a case study in data science, how do you prepare a data science case study, 10 most interesting data science case studies with examples.

So, without much ado, let's get started with data science business case studies !

With humble beginnings as a simple discount retailer, today, Walmart operates in 10,500 stores and clubs in 24 countries and eCommerce websites, employing around 2.2 million people around the globe. For the fiscal year ended January 31, 2021, Walmart's total revenue was $559 billion showing a growth of $35 billion with the expansion of the eCommerce sector. Walmart is a data-driven company that works on the principle of 'Everyday low cost' for its consumers. To achieve this goal, they heavily depend on the advances of their data science and analytics department for research and development, also known as Walmart Labs. Walmart is home to the world's largest private cloud, which can manage 2.5 petabytes of data every hour! To analyze this humongous amount of data, Walmart has created 'Data Café,' a state-of-the-art analytics hub located within its Bentonville, Arkansas headquarters. The Walmart Labs team heavily invests in building and managing technologies like cloud, data, DevOps , infrastructure, and security.

Walmart is experiencing massive digital growth as the world's largest retailer . Walmart has been leveraging Big data and advances in data science to build solutions to enhance, optimize and customize the shopping experience and serve their customers in a better way. At Walmart Labs, data scientists are focused on creating data-driven solutions that power the efficiency and effectiveness of complex supply chain management processes. Here are some of the applications of data science  at Walmart:

i) Personalized Customer Shopping Experience

Walmart analyses customer preferences and shopping patterns to optimize the stocking and displaying of merchandise in their stores. Analysis of Big data also helps them understand new item sales, make decisions on discontinuing products, and the performance of brands.

ii) Order Sourcing and On-Time Delivery Promise

Millions of customers view items on Walmart.com, and Walmart provides each customer a real-time estimated delivery date for the items purchased. Walmart runs a backend algorithm that estimates this based on the distance between the customer and the fulfillment center, inventory levels, and shipping methods available. The supply chain management system determines the optimum fulfillment center based on distance and inventory levels for every order. It also has to decide on the shipping method to minimize transportation costs while meeting the promised delivery date.

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iii) Packing Optimization 

Also known as Box recommendation is a daily occurrence in the shipping of items in retail and eCommerce business. When items of an order or multiple orders for the same customer are ready for packing, Walmart has developed a recommender system that picks the best-sized box which holds all the ordered items with the least in-box space wastage within a fixed amount of time. This Bin Packing problem is a classic NP-Hard problem familiar to data scientists .

Whenever items of an order or multiple orders placed by the same customer are picked from the shelf and are ready for packing, the box recommendation system determines the best-sized box to hold all the ordered items with a minimum of in-box space wasted. This problem is known as the Bin Packing Problem, another classic NP-Hard problem familiar to data scientists.

Here is a link to a sales prediction data science case study to help you understand the applications of Data Science in the real world. Walmart Sales Forecasting Project uses historical sales data for 45 Walmart stores located in different regions. Each store contains many departments, and you must build a model to project the sales for each department in each store. This data science case study aims to create a predictive model to predict the sales of each product. You can also try your hands-on Inventory Demand Forecasting Data Science Project to develop a machine learning model to forecast inventory demand accurately based on historical sales data.

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Amazon is an American multinational technology-based company based in Seattle, USA. It started as an online bookseller, but today it focuses on eCommerce, cloud computing , digital streaming, and artificial intelligence . It hosts an estimate of 1,000,000,000 gigabytes of data across more than 1,400,000 servers. Through its constant innovation in data science and big data Amazon is always ahead in understanding its customers. Here are a few data analytics case study examples at Amazon:

i) Recommendation Systems

Data science models help amazon understand the customers' needs and recommend them to them before the customer searches for a product; this model uses collaborative filtering. Amazon uses 152 million customer purchases data to help users to decide on products to be purchased. The company generates 35% of its annual sales using the Recommendation based systems (RBS) method.

Here is a Recommender System Project to help you build a recommendation system using collaborative filtering. 

ii) Retail Price Optimization

Amazon product prices are optimized based on a predictive model that determines the best price so that the users do not refuse to buy it based on price. The model carefully determines the optimal prices considering the customers' likelihood of purchasing the product and thinks the price will affect the customers' future buying patterns. Price for a product is determined according to your activity on the website, competitors' pricing, product availability, item preferences, order history, expected profit margin, and other factors.

Check Out this Retail Price Optimization Project to build a Dynamic Pricing Model.

iii) Fraud Detection

Being a significant eCommerce business, Amazon remains at high risk of retail fraud. As a preemptive measure, the company collects historical and real-time data for every order. It uses Machine learning algorithms to find transactions with a higher probability of being fraudulent. This proactive measure has helped the company restrict clients with an excessive number of returns of products.

You can look at this Credit Card Fraud Detection Project to implement a fraud detection model to classify fraudulent credit card transactions.

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Let us explore data analytics case study examples in the entertainment indusry.

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Netflix started as a DVD rental service in 1997 and then has expanded into the streaming business. Headquartered in Los Gatos, California, Netflix is the largest content streaming company in the world. Currently, Netflix has over 208 million paid subscribers worldwide, and with thousands of smart devices which are presently streaming supported, Netflix has around 3 billion hours watched every month. The secret to this massive growth and popularity of Netflix is its advanced use of data analytics and recommendation systems to provide personalized and relevant content recommendations to its users. The data is collected over 100 billion events every day. Here are a few examples of data analysis case studies applied at Netflix :

i) Personalized Recommendation System

Netflix uses over 1300 recommendation clusters based on consumer viewing preferences to provide a personalized experience. Some of the data that Netflix collects from its users include Viewing time, platform searches for keywords, Metadata related to content abandonment, such as content pause time, rewind, rewatched. Using this data, Netflix can predict what a viewer is likely to watch and give a personalized watchlist to a user. Some of the algorithms used by the Netflix recommendation system are Personalized video Ranking, Trending now ranker, and the Continue watching now ranker.

ii) Content Development using Data Analytics

Netflix uses data science to analyze the behavior and patterns of its user to recognize themes and categories that the masses prefer to watch. This data is used to produce shows like The umbrella academy, and Orange Is the New Black, and the Queen's Gambit. These shows seem like a huge risk but are significantly based on data analytics using parameters, which assured Netflix that they would succeed with its audience. Data analytics is helping Netflix come up with content that their viewers want to watch even before they know they want to watch it.

iii) Marketing Analytics for Campaigns

Netflix uses data analytics to find the right time to launch shows and ad campaigns to have maximum impact on the target audience. Marketing analytics helps come up with different trailers and thumbnails for other groups of viewers. For example, the House of Cards Season 5 trailer with a giant American flag was launched during the American presidential elections, as it would resonate well with the audience.

Here is a Customer Segmentation Project using association rule mining to understand the primary grouping of customers based on various parameters.

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In a world where Purchasing music is a thing of the past and streaming music is a current trend, Spotify has emerged as one of the most popular streaming platforms. With 320 million monthly users, around 4 billion playlists, and approximately 2 million podcasts, Spotify leads the pack among well-known streaming platforms like Apple Music, Wynk, Songza, amazon music, etc. The success of Spotify has mainly depended on data analytics. By analyzing massive volumes of listener data, Spotify provides real-time and personalized services to its listeners. Most of Spotify's revenue comes from paid premium subscriptions. Here are some of the examples of case study on data analytics used by Spotify to provide enhanced services to its listeners:

i) Personalization of Content using Recommendation Systems

Spotify uses Bart or Bayesian Additive Regression Trees to generate music recommendations to its listeners in real-time. Bart ignores any song a user listens to for less than 30 seconds. The model is retrained every day to provide updated recommendations. A new Patent granted to Spotify for an AI application is used to identify a user's musical tastes based on audio signals, gender, age, accent to make better music recommendations.

Spotify creates daily playlists for its listeners, based on the taste profiles called 'Daily Mixes,' which have songs the user has added to their playlists or created by the artists that the user has included in their playlists. It also includes new artists and songs that the user might be unfamiliar with but might improve the playlist. Similar to it is the weekly 'Release Radar' playlists that have newly released artists' songs that the listener follows or has liked before.

ii) Targetted marketing through Customer Segmentation

With user data for enhancing personalized song recommendations, Spotify uses this massive dataset for targeted ad campaigns and personalized service recommendations for its users. Spotify uses ML models to analyze the listener's behavior and group them based on music preferences, age, gender, ethnicity, etc. These insights help them create ad campaigns for a specific target audience. One of their well-known ad campaigns was the meme-inspired ads for potential target customers, which was a huge success globally.

iii) CNN's for Classification of Songs and Audio Tracks

Spotify builds audio models to evaluate the songs and tracks, which helps develop better playlists and recommendations for its users. These allow Spotify to filter new tracks based on their lyrics and rhythms and recommend them to users like similar tracks ( collaborative filtering). Spotify also uses NLP ( Natural language processing) to scan articles and blogs to analyze the words used to describe songs and artists. These analytical insights can help group and identify similar artists and songs and leverage them to build playlists.

Here is a Music Recommender System Project for you to start learning. We have listed another music recommendations dataset for you to use for your projects: Dataset1 . You can use this dataset of Spotify metadata to classify songs based on artists, mood, liveliness. Plot histograms, heatmaps to get a better understanding of the dataset. Use classification algorithms like logistic regression, SVM, and Principal component analysis to generate valuable insights from the dataset.

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Below you will find case studies for data analytics in the travel and tourism industry.

Airbnb was born in 2007 in San Francisco and has since grown to 4 million Hosts and 5.6 million listings worldwide who have welcomed more than 1 billion guest arrivals in almost every country across the globe. Airbnb is active in every country on the planet except for Iran, Sudan, Syria, and North Korea. That is around 97.95% of the world. Using data as a voice of their customers, Airbnb uses the large volume of customer reviews, host inputs to understand trends across communities, rate user experiences, and uses these analytics to make informed decisions to build a better business model. The data scientists at Airbnb are developing exciting new solutions to boost the business and find the best mapping for its customers and hosts. Airbnb data servers serve approximately 10 million requests a day and process around one million search queries. Data is the voice of customers at AirBnB and offers personalized services by creating a perfect match between the guests and hosts for a supreme customer experience. 

i) Recommendation Systems and Search Ranking Algorithms

Airbnb helps people find 'local experiences' in a place with the help of search algorithms that make searches and listings precise. Airbnb uses a 'listing quality score' to find homes based on the proximity to the searched location and uses previous guest reviews. Airbnb uses deep neural networks to build models that take the guest's earlier stays into account and area information to find a perfect match. The search algorithms are optimized based on guest and host preferences, rankings, pricing, and availability to understand users’ needs and provide the best match possible.

ii) Natural Language Processing for Review Analysis

Airbnb characterizes data as the voice of its customers. The customer and host reviews give a direct insight into the experience. The star ratings alone cannot be an excellent way to understand it quantitatively. Hence Airbnb uses natural language processing to understand reviews and the sentiments behind them. The NLP models are developed using Convolutional neural networks .

Practice this Sentiment Analysis Project for analyzing product reviews to understand the basic concepts of natural language processing.

iii) Smart Pricing using Predictive Analytics

The Airbnb hosts community uses the service as a supplementary income. The vacation homes and guest houses rented to customers provide for rising local community earnings as Airbnb guests stay 2.4 times longer and spend approximately 2.3 times the money compared to a hotel guest. The profits are a significant positive impact on the local neighborhood community. Airbnb uses predictive analytics to predict the prices of the listings and help the hosts set a competitive and optimal price. The overall profitability of the Airbnb host depends on factors like the time invested by the host and responsiveness to changing demands for different seasons. The factors that impact the real-time smart pricing are the location of the listing, proximity to transport options, season, and amenities available in the neighborhood of the listing.

Here is a Price Prediction Project to help you understand the concept of predictive analysis which is widely common in case studies for data analytics. 

Uber is the biggest global taxi service provider. As of December 2018, Uber has 91 million monthly active consumers and 3.8 million drivers. Uber completes 14 million trips each day. Uber uses data analytics and big data-driven technologies to optimize their business processes and provide enhanced customer service. The Data Science team at uber has been exploring futuristic technologies to provide better service constantly. Machine learning and data analytics help Uber make data-driven decisions that enable benefits like ride-sharing, dynamic price surges, better customer support, and demand forecasting. Here are some of the real world data science projects used by uber:

i) Dynamic Pricing for Price Surges and Demand Forecasting

Uber prices change at peak hours based on demand. Uber uses surge pricing to encourage more cab drivers to sign up with the company, to meet the demand from the passengers. When the prices increase, the driver and the passenger are both informed about the surge in price. Uber uses a predictive model for price surging called the 'Geosurge' ( patented). It is based on the demand for the ride and the location.

ii) One-Click Chat

Uber has developed a Machine learning and natural language processing solution called one-click chat or OCC for coordination between drivers and users. This feature anticipates responses for commonly asked questions, making it easy for the drivers to respond to customer messages. Drivers can reply with the clock of just one button. One-Click chat is developed on Uber's machine learning platform Michelangelo to perform NLP on rider chat messages and generate appropriate responses to them.

iii) Customer Retention

Failure to meet the customer demand for cabs could lead to users opting for other services. Uber uses machine learning models to bridge this demand-supply gap. By using prediction models to predict the demand in any location, uber retains its customers. Uber also uses a tier-based reward system, which segments customers into different levels based on usage. The higher level the user achieves, the better are the perks. Uber also provides personalized destination suggestions based on the history of the user and their frequently traveled destinations.

You can take a look at this Python Chatbot Project and build a simple chatbot application to understand better the techniques used for natural language processing. You can also practice the working of a demand forecasting model with this project using time series analysis. You can look at this project which uses time series forecasting and clustering on a dataset containing geospatial data for forecasting customer demand for ola rides.

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7) LinkedIn 

LinkedIn is the largest professional social networking site with nearly 800 million members in more than 200 countries worldwide. Almost 40% of the users access LinkedIn daily, clocking around 1 billion interactions per month. The data science team at LinkedIn works with this massive pool of data to generate insights to build strategies, apply algorithms and statistical inferences to optimize engineering solutions, and help the company achieve its goals. Here are some of the real world data science projects at LinkedIn:

i) LinkedIn Recruiter Implement Search Algorithms and Recommendation Systems

LinkedIn Recruiter helps recruiters build and manage a talent pool to optimize the chances of hiring candidates successfully. This sophisticated product works on search and recommendation engines. The LinkedIn recruiter handles complex queries and filters on a constantly growing large dataset. The results delivered have to be relevant and specific. The initial search model was based on linear regression but was eventually upgraded to Gradient Boosted decision trees to include non-linear correlations in the dataset. In addition to these models, the LinkedIn recruiter also uses the Generalized Linear Mix model to improve the results of prediction problems to give personalized results.

ii) Recommendation Systems Personalized for News Feed

The LinkedIn news feed is the heart and soul of the professional community. A member's newsfeed is a place to discover conversations among connections, career news, posts, suggestions, photos, and videos. Every time a member visits LinkedIn, machine learning algorithms identify the best exchanges to be displayed on the feed by sorting through posts and ranking the most relevant results on top. The algorithms help LinkedIn understand member preferences and help provide personalized news feeds. The algorithms used include logistic regression, gradient boosted decision trees and neural networks for recommendation systems.

iii) CNN's to Detect Inappropriate Content

To provide a professional space where people can trust and express themselves professionally in a safe community has been a critical goal at LinkedIn. LinkedIn has heavily invested in building solutions to detect fake accounts and abusive behavior on their platform. Any form of spam, harassment, inappropriate content is immediately flagged and taken down. These can range from profanity to advertisements for illegal services. LinkedIn uses a Convolutional neural networks based machine learning model. This classifier trains on a training dataset containing accounts labeled as either "inappropriate" or "appropriate." The inappropriate list consists of accounts having content from "blocklisted" phrases or words and a small portion of manually reviewed accounts reported by the user community.

Here is a Text Classification Project to help you understand NLP basics for text classification. You can find a news recommendation system dataset to help you build a personalized news recommender system. You can also use this dataset to build a classifier using logistic regression, Naive Bayes, or Neural networks to classify toxic comments.

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Pfizer is a multinational pharmaceutical company headquartered in New York, USA. One of the largest pharmaceutical companies globally known for developing a wide range of medicines and vaccines in disciplines like immunology, oncology, cardiology, and neurology. Pfizer became a household name in 2010 when it was the first to have a COVID-19 vaccine with FDA. In early November 2021, The CDC has approved the Pfizer vaccine for kids aged 5 to 11. Pfizer has been using machine learning and artificial intelligence to develop drugs and streamline trials, which played a massive role in developing and deploying the COVID-19 vaccine. Here are a few data analytics case studies by Pfizer :

i) Identifying Patients for Clinical Trials

Artificial intelligence and machine learning are used to streamline and optimize clinical trials to increase their efficiency. Natural language processing and exploratory data analysis of patient records can help identify suitable patients for clinical trials. These can help identify patients with distinct symptoms. These can help examine interactions of potential trial members' specific biomarkers, predict drug interactions and side effects which can help avoid complications. Pfizer's AI implementation helped rapidly identify signals within the noise of millions of data points across their 44,000-candidate COVID-19 clinical trial.

ii) Supply Chain and Manufacturing

Data science and machine learning techniques help pharmaceutical companies better forecast demand for vaccines and drugs and distribute them efficiently. Machine learning models can help identify efficient supply systems by automating and optimizing the production steps. These will help supply drugs customized to small pools of patients in specific gene pools. Pfizer uses Machine learning to predict the maintenance cost of equipment used. Predictive maintenance using AI is the next big step for Pharmaceutical companies to reduce costs.

iii) Drug Development

Computer simulations of proteins, and tests of their interactions, and yield analysis help researchers develop and test drugs more efficiently. In 2016 Watson Health and Pfizer announced a collaboration to utilize IBM Watson for Drug Discovery to help accelerate Pfizer's research in immuno-oncology, an approach to cancer treatment that uses the body's immune system to help fight cancer. Deep learning models have been used recently for bioactivity and synthesis prediction for drugs and vaccines in addition to molecular design. Deep learning has been a revolutionary technique for drug discovery as it factors everything from new applications of medications to possible toxic reactions which can save millions in drug trials.

You can create a Machine learning model to predict molecular activity to help design medicine using this dataset . You may build a CNN or a Deep neural network for this data analyst case study project.

Access Data Science and Machine Learning Project Code Examples

9) Shell Data Analyst Case Study Project

Shell is a global group of energy and petrochemical companies with over 80,000 employees in around 70 countries. Shell uses advanced technologies and innovations to help build a sustainable energy future. Shell is going through a significant transition as the world needs more and cleaner energy solutions to be a clean energy company by 2050. It requires substantial changes in the way in which energy is used. Digital technologies, including AI and Machine Learning, play an essential role in this transformation. These include efficient exploration and energy production, more reliable manufacturing, more nimble trading, and a personalized customer experience. Using AI in various phases of the organization will help achieve this goal and stay competitive in the market. Here are a few data analytics case studies in the petrochemical industry:

i) Precision Drilling

Shell is involved in the processing mining oil and gas supply, ranging from mining hydrocarbons to refining the fuel to retailing them to customers. Recently Shell has included reinforcement learning to control the drilling equipment used in mining. Reinforcement learning works on a reward-based system based on the outcome of the AI model. The algorithm is designed to guide the drills as they move through the surface, based on the historical data from drilling records. It includes information such as the size of drill bits, temperatures, pressures, and knowledge of the seismic activity. This model helps the human operator understand the environment better, leading to better and faster results will minor damage to machinery used. 

ii) Efficient Charging Terminals

Due to climate changes, governments have encouraged people to switch to electric vehicles to reduce carbon dioxide emissions. However, the lack of public charging terminals has deterred people from switching to electric cars. Shell uses AI to monitor and predict the demand for terminals to provide efficient supply. Multiple vehicles charging from a single terminal may create a considerable grid load, and predictions on demand can help make this process more efficient.

iii) Monitoring Service and Charging Stations

Another Shell initiative trialed in Thailand and Singapore is the use of computer vision cameras, which can think and understand to watch out for potentially hazardous activities like lighting cigarettes in the vicinity of the pumps while refueling. The model is built to process the content of the captured images and label and classify it. The algorithm can then alert the staff and hence reduce the risk of fires. You can further train the model to detect rash driving or thefts in the future.

Here is a project to help you understand multiclass image classification. You can use the Hourly Energy Consumption Dataset to build an energy consumption prediction model. You can use time series with XGBoost to develop your model.

10) Zomato Case Study on Data Analytics

Zomato was founded in 2010 and is currently one of the most well-known food tech companies. Zomato offers services like restaurant discovery, home delivery, online table reservation, online payments for dining, etc. Zomato partners with restaurants to provide tools to acquire more customers while also providing delivery services and easy procurement of ingredients and kitchen supplies. Currently, Zomato has over 2 lakh restaurant partners and around 1 lakh delivery partners. Zomato has closed over ten crore delivery orders as of date. Zomato uses ML and AI to boost their business growth, with the massive amount of data collected over the years from food orders and user consumption patterns. Here are a few examples of data analyst case study project developed by the data scientists at Zomato:

i) Personalized Recommendation System for Homepage

Zomato uses data analytics to create personalized homepages for its users. Zomato uses data science to provide order personalization, like giving recommendations to the customers for specific cuisines, locations, prices, brands, etc. Restaurant recommendations are made based on a customer's past purchases, browsing history, and what other similar customers in the vicinity are ordering. This personalized recommendation system has led to a 15% improvement in order conversions and click-through rates for Zomato. 

You can use the Restaurant Recommendation Dataset to build a restaurant recommendation system to predict what restaurants customers are most likely to order from, given the customer location, restaurant information, and customer order history.

ii) Analyzing Customer Sentiment

Zomato uses Natural language processing and Machine learning to understand customer sentiments using social media posts and customer reviews. These help the company gauge the inclination of its customer base towards the brand. Deep learning models analyze the sentiments of various brand mentions on social networking sites like Twitter, Instagram, Linked In, and Facebook. These analytics give insights to the company, which helps build the brand and understand the target audience.

iii) Predicting Food Preparation Time (FPT)

Food delivery time is an essential variable in the estimated delivery time of the order placed by the customer using Zomato. The food preparation time depends on numerous factors like the number of dishes ordered, time of the day, footfall in the restaurant, day of the week, etc. Accurate prediction of the food preparation time can help make a better prediction of the Estimated delivery time, which will help delivery partners less likely to breach it. Zomato uses a Bidirectional LSTM-based deep learning model that considers all these features and provides food preparation time for each order in real-time. 

Data scientists are companies' secret weapons when analyzing customer sentiments and behavior and leveraging it to drive conversion, loyalty, and profits. These 10 data science case studies projects with examples and solutions show you how various organizations use data science technologies to succeed and be at the top of their field! To summarize, Data Science has not only accelerated the performance of companies but has also made it possible to manage & sustain their performance with ease.

FAQs on Data Analysis Case Studies

A case study in data science is an in-depth analysis of a real-world problem using data-driven approaches. It involves collecting, cleaning, and analyzing data to extract insights and solve challenges, offering practical insights into how data science techniques can address complex issues across various industries.

To create a data science case study, identify a relevant problem, define objectives, and gather suitable data. Clean and preprocess data, perform exploratory data analysis, and apply appropriate algorithms for analysis. Summarize findings, visualize results, and provide actionable recommendations, showcasing the problem-solving potential of data science techniques.

About the Author

ProjectPro is the only online platform designed to help professionals gain practical, hands-on experience in big data, data engineering, data science, and machine learning related technologies. Having over 270+ reusable project templates in data science and big data with step-by-step walkthroughs,

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15 Real-Life Case Study Examples & Best Practices

Written by: Oghale Olori

Case studies are more than just success stories.

They are powerful tools that demonstrate the practical value of your product or service. Case studies help attract attention to your products, build trust with potential customers and ultimately drive sales.

It’s no wonder that 73% of successful content marketers utilize case studies as part of their content strategy. Plus, buyers spend 54% of their time reviewing case studies before they make a buying decision.

To ensure you’re making the most of your case studies, we’ve put together 15 real-life case study examples to inspire you. These examples span a variety of industries and formats. We’ve also included best practices, design tips and templates to inspire you.

Let’s dive in!

Table of Contents

What is a case study, 15 real-life case study examples, sales case study examples, saas case study examples, product case study examples, marketing case study examples, business case study examples, case study faqs.

• A case study is a compelling narrative that showcases how your product or service has positively impacted a real business or individual. 
• Case studies delve into your customer's challenges, how your solution addressed them and the quantifiable results they achieved.
• Your case study should have an attention-grabbing headline, great visuals and a relevant call to action. Other key elements include an introduction, problems and result section.
• Visme provides easy-to-use tools, professionally designed templates and features for creating attractive and engaging case studies.

A case study is a real-life scenario where your company helped a person or business solve their unique challenges. It provides a detailed analysis of the positive outcomes achieved as a result of implementing your solution.

Case studies are an effective way to showcase the value of your product or service to potential customers without overt selling. By sharing how your company transformed a business, you can attract customers seeking similar solutions and results.

Case studies are not only about your company's capabilities; they are primarily about the benefits customers and clients have experienced from using your product.

Every great case study is made up of key elements. They are;

• Attention-grabbing headline: Write a compelling headline that grabs attention and tells your reader what the case study is about. For example, "How a CRM System Helped a B2B Company Increase Revenue by 225%.
• Introduction/Executive Summary: Include a brief overview of your case study, including your customer’s problem, the solution they implemented and the results they achieved.
• Problem/Challenge: Case studies with solutions offer a powerful way to connect with potential customers. In this section, explain how your product or service specifically addressed your customer's challenges.
• Solution: Explain how your product or service specifically addressed your customer's challenges.
• Results/Achievements : Give a detailed account of the positive impact of your product. Quantify the benefits achieved using metrics such as increased sales, improved efficiency, reduced costs or enhanced customer satisfaction.
• Graphics/Visuals: Include professional designs, high-quality photos and videos to make your case study more engaging and visually appealing.
• Quotes/Testimonials: Incorporate written or video quotes from your clients to boost your credibility.
• Relevant CTA: Insert a call to action (CTA) that encourages the reader to take action. For example, visiting your website or contacting you for more information. Your CTA can be a link to a landing page, a contact form or your social media handle and should be related to the product or service you highlighted in your case study.

Now that you understand what a case study is, let’s look at real-life case study examples. Among these, you'll find some simple case study examples that break down complex ideas into easily understandable solutions.

In this section, we’ll explore SaaS, marketing, sales, product and business case study examples with solutions. Take note of how these companies structured their case studies and included the key elements.

We’ve also included professionally designed case study templates to inspire you.

1. Georgia Tech Athletics Increase Season Ticket Sales by 80%

Georgia Tech Athletics, with its 8,000 football season ticket holders, sought for a way to increase efficiency and customer engagement.

Their initial sales process involved making multiple outbound phone calls per day with no real targeting or guidelines. Georgia Tech believed that targeting communications will enable them to reach more people in real time.

Salesloft improved Georgia Tech’s sales process with an inbound structure. This enabled sales reps to connect with their customers on a more targeted level. The use of dynamic fields and filters when importing lists ensured prospects received the right information, while communication with existing fans became faster with automation.

As a result, Georgia Tech Athletics recorded an 80% increase in season ticket sales as relationships with season ticket holders significantly improved. Employee engagement increased as employees became more energized to connect and communicate with fans.

Why Does This Case Study Work?

In this case study example , Salesloft utilized the key elements of a good case study. Their introduction gave an overview of their customers' challenges and the results they enjoyed after using them. After which they categorized the case study into three main sections: challenge, solution and result.

Salesloft utilized a case study video to increase engagement and invoke human connection.

Incorporating videos in your case study has a lot of benefits. Wyzol’s 2023 state of video marketing report showed a direct correlation between videos and an 87% increase in sales.

The beautiful thing is that creating videos for your case study doesn’t have to be daunting.

With an easy-to-use platform like Visme, you can create top-notch testimonial videos that will connect with your audience. Within the Visme editor, you can access over 1 million stock photos , video templates, animated graphics and more. These tools and resources will significantly improve the design and engagement of your case study.

Simplify content creation and brand management for your team

• Collaborate on designs , mockups and wireframes with your non-design colleagues
• Lock down your branding to maintain brand consistency throughout your designs
• Why start from scratch? Save time with 1000s of professional branded templates

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2. WeightWatchers Completely Revamped their Enterprise Sales Process with HubSpot

WeightWatchers, a 60-year-old wellness company, sought a CRM solution that increased the efficiency of their sales process. With their previous system, Weightwatchers had limited automation. They would copy-paste message templates from word documents or recreate one email for a batch of customers.

This required a huge effort from sales reps, account managers and leadership, as they were unable to track leads or pull customized reports for planning and growth.

WeightWatchers transformed their B2B sales strategy by leveraging HubSpot's robust marketing and sales workflows. They utilized HubSpot’s deal pipeline and automation features to streamline lead qualification. And the customized dashboard gave leadership valuable insights.

As a result, WeightWatchers generated seven figures in annual contract value and boosted recurring revenue. Hubspot’s impact resulted in 100% adoption across all sales, marketing, client success and operations teams.

Hubspot structured its case study into separate sections, demonstrating the specific benefits of their products to various aspects of the customer's business. Additionally, they integrated direct customer quotes in each section to boost credibility, resulting in a more compelling case study.

Getting insight from your customer about their challenges is one thing. But writing about their process and achievements in a concise and relatable way is another. If you find yourself constantly experiencing writer’s block, Visme’s AI writer is perfect for you.

Visme created this AI text generator tool to take your ideas and transform them into a great draft. So whether you need help writing your first draft or editing your final case study, Visme is ready for you.

3. Immi’s Ram Fam Helps to Drive Over $200k in Sales

Immi embarked on a mission to recreate healthier ramen recipes that were nutritious and delicious. After 2 years of tireless trials, Immi finally found the perfect ramen recipe. However, they envisioned a community of passionate ramen enthusiasts to fuel their business growth.

This vision propelled them to partner with Shopify Collabs. Shopify Collabs successfully cultivated and managed Immi’s Ramen community of ambassadors and creators.

As a result of their partnership, Immi’s community grew to more than 400 dedicated members, generating over $200,000 in total affiliate sales.

The power of data-driven headlines cannot be overemphasized. Chili Piper strategically incorporates quantifiable results in their headlines. This instantly sparks curiosity and interest in readers.

While not every customer success story may boast headline-grabbing figures, quantifying achievements in percentages is still effective. For example, you can highlight a 50% revenue increase with the implementation of your product.

Take a look at the beautiful case study template below. Just like in the example above, the figures in the headline instantly grab attention and entice your reader to click through.

Having a case study document is a key factor in boosting engagement. This makes it easy to promote your case study in multiple ways. With Visme, you can easily publish, download and share your case study with your customers in a variety of formats, including PDF, PPTX, JPG and more!

4. How WOW! is Saving Nearly 79% in Time and Cost With Visme

This case study discusses how Visme helped WOW! save time and money by providing user-friendly tools to create interactive and quality training materials for their employees. Find out what your team can do with Visme. Request a Demo

WOW!'s learning and development team creates high-quality training materials for new and existing employees. Previous tools and platforms they used had plain templates, little to no interactivity features, and limited flexibility—that is, until they discovered Visme.

Now, the learning and development team at WOW! use Visme to create engaging infographics, training videos, slide decks and other training materials.

This has directly reduced the company's turnover rate, saving them money spent on recruiting and training new employees. It has also saved them a significant amount of time, which they can now allocate to other important tasks.

Visme's customer testimonials spark an emotional connection with the reader, leaving a profound impact. Upon reading this case study, prospective customers will be blown away by the remarkable efficiency achieved by Visme's clients after switching from PowerPoint.

Visme’s interactivity feature was a game changer for WOW! and one of the primary reasons they chose Visme.

“Previously we were using PowerPoint, which is fine, but the interactivity you can get with Visme is so much more robust that we’ve all steered away from PowerPoint.” - Kendra, L&D team, Wow!

Visme’s interactive feature allowed them to animate their infographics, include clickable links on their PowerPoint designs and even embed polls and quizzes their employees could interact with.

By embedding the slide decks, infographics and other training materials WOW! created with Visme, potential customers get a taste of what they can create with the tool. This is much more effective than describing the features of Visme because it allows potential customers to see the tool in action.

To top it all off, this case study utilized relevant data and figures. For example, one part of the case study said, “In Visme, where Kendra’s team has access to hundreds of templates, a brand kit, and millions of design assets at their disposal, their team can create presentations in 80% less time.”

Who wouldn't want that?

Including relevant figures and graphics in your case study is a sure way to convince your potential customers why you’re a great fit for their brand. The case study template below is a great example of integrating relevant figures and data.

This colorful template begins with a captivating headline. But that is not the best part; this template extensively showcases the results their customer had using relevant figures.

The arrangement of the results makes it fun and attractive. Instead of just putting figures in a plain table, you can find interesting shapes in your Visme editor to take your case study to the next level.

5. Lyte Reduces Customer Churn To Just 3% With Hubspot CRM

While Lyte was redefining the ticketing industry, it had no definite CRM system . Lyte utilized 12–15 different SaaS solutions across various departments, which led to a lack of alignment between teams, duplication of work and overlapping tasks.

Customer data was spread across these platforms, making it difficult to effectively track their customer journey. As a result, their churn rate increased along with customer dissatisfaction.

Through Fuelius , Lyte founded and implemented Hubspot CRM. Lyte's productivity skyrocketed after incorporating Hubspot's all-in-one CRM tool. With improved efficiency, better teamwork and stronger client relationships, sales figures soared.

The case study title page and executive summary act as compelling entry points for both existing and potential customers. This overview provides a clear understanding of the case study and also strategically incorporates key details like the client's industry, location and relevant background information.

Having a good summary of your case study can prompt your readers to engage further. You can achieve this with a simple but effective case study one-pager that highlights your customer’s problems, process and achievements, just like this case study did in the beginning.

Moreover, you can easily distribute your case study one-pager and use it as a lead magnet to draw prospective customers to your company.

Take a look at this case study one-pager template below.

This template includes key aspects of your case study, such as the introduction, key findings, conclusion and more, without overcrowding the page. The use of multiple shades of blue gives it a clean and dynamic layout.

Our favorite part of this template is where the age group is visualized.

With Visme’s data visualization tool , you can present your data in tables, graphs, progress bars, maps and so much more. All you need to do is choose your preferred data visualization widget, input or import your data and click enter!

6. How Workato Converts 75% of Their Qualified Leads

Workato wanted to improve their inbound leads and increase their conversion rate, which ranged from 40-55%.

At first, Workato searched for a simple scheduling tool. They soon discovered that they needed a tool that provided advanced routing capabilities based on zip code and other criteria. Luckily, they found and implemented Chili Piper.

As a result of implementing Chili Piper, Workato achieved a remarkable 75–80% conversion rate and improved show rates. This led to a substantial revenue boost, with a 10-15% increase in revenue attributed to Chili Piper's impact on lead conversion.

This case study example utilizes the power of video testimonials to drive the impact of their product.

Chili Piper incorporates screenshots and clips of their tool in use. This is a great strategy because it helps your viewers become familiar with how your product works, making onboarding new customers much easier.

In this case study example, we see the importance of efficient Workflow Management Systems (WMS). Without a WMS, you manually assign tasks to your team members and engage in multiple emails for regular updates on progress.

However, when crafting and designing your case study, you should prioritize having a good WMS.

Visme has an outstanding Workflow Management System feature that keeps you on top of all your projects and designs. This feature makes it much easier to assign roles, ensure accuracy across documents, and track progress and deadlines.

Visme’s WMS feature allows you to limit access to your entire document by assigning specific slides or pages to individual members of your team. At the end of the day, your team members are not overwhelmed or distracted by the whole document but can focus on their tasks.

7. Rush Order Helps Vogmask Scale-Up During a Pandemic

Vomask's reliance on third-party fulfillment companies became a challenge as demand for their masks grew. Seeking a reliable fulfillment partner, they found Rush Order and entrusted them with their entire inventory.

Vomask's partnership with Rush Order proved to be a lifesaver during the COVID-19 pandemic. Rush Order's agility, efficiency and commitment to customer satisfaction helped Vogmask navigate the unprecedented demand and maintain its reputation for quality and service.

Rush Order’s comprehensive support enabled Vogmask to scale up its order processing by a staggering 900% while maintaining a remarkable customer satisfaction rate of 92%.

Rush Order chose one event where their impact mattered the most to their customer and shared that story.

While pandemics don't happen every day, you can look through your customer’s journey and highlight a specific time or scenario where your product or service saved their business.

The story of Vogmask and Rush Order is compelling, but it simply is not enough. The case study format and design attract readers' attention and make them want to know more. Rush Order uses consistent colors throughout the case study, starting with the logo, bold square blocks, pictures, and even headers.

Take a look at this product case study template below.

Just like our example, this case study template utilizes bold colors and large squares to attract and maintain the reader’s attention. It provides enough room for you to write about your customers' backgrounds/introductions, challenges, goals and results.

The right combination of shapes and colors adds a level of professionalism to this case study template.

8. AMR Hair & Beauty leverages B2B functionality to boost sales by 200%

With limits on website customization, slow page loading and multiple website crashes during peak events, it wasn't long before AMR Hair & Beauty began looking for a new e-commerce solution.

Their existing platform lacked effective search and filtering options, a seamless checkout process and the data analytics capabilities needed for informed decision-making. This led to a significant number of abandoned carts.

Upon switching to Shopify Plus, AMR immediately saw improvements in page loading speed and average session duration. They added better search and filtering options for their wholesale customers and customized their checkout process.

Due to this, AMR witnessed a 200% increase in sales and a 77% rise in B2B average order value. AMR Hair & Beauty is now poised for further expansion and growth.

This case study example showcases the power of a concise and impactful narrative.

To make their case analysis more effective, Shopify focused on the most relevant aspects of the customer's journey. While there may have been other challenges the customer faced, they only included those that directly related to their solutions.

Take a look at this case study template below. It is perfect if you want to create a concise but effective case study. Without including unnecessary details, you can outline the challenges, solutions and results your customers experienced from using your product.

Don’t forget to include a strong CTA within your case study. By incorporating a link, sidebar pop-up or an exit pop-up into your case study, you can prompt your readers and prospective clients to connect with you.

9. How a Marketing Agency Uses Visme to Create Engaging Content With Infographics

SmartBox Dental , a marketing agency specializing in dental practices, sought ways to make dental advice more interesting and easier to read. However, they lacked the design skills to do so effectively.

Visme's wide range of templates and features made it easy for the team to create high-quality content quickly and efficiently. SmartBox Dental enjoyed creating infographics in as little as 10-15 minutes, compared to one hour before Visme was implemented.

By leveraging Visme, SmartBox Dental successfully transformed dental content into a more enjoyable and informative experience for their clients' patients. Therefore enhancing its reputation as a marketing partner that goes the extra mile to deliver value to its clients.

Visme creatively incorporates testimonials In this case study example.

By showcasing infographics and designs created by their clients, they leverage the power of social proof in a visually compelling way. This way, potential customers gain immediate insight into the creative possibilities Visme offers as a design tool.

This example effectively showcases a product's versatility and impact, and we can learn a lot about writing a case study from it. Instead of focusing on one tool or feature per customer, Visme took a more comprehensive approach.

Within each section of their case study, Visme explained how a particular tool or feature played a key role in solving the customer's challenges.

For example, this case study highlighted Visme’s collaboration tool . With Visme’s tool, the SmartBox Dental content team fostered teamwork, accountability and effective supervision.

Visme also achieved a versatile case study by including relevant quotes to showcase each tool or feature. Take a look at some examples;

Visme’s collaboration tool: “We really like the collaboration tool. Being able to see what a co-worker is working on and borrow their ideas or collaborate on a project to make sure we get the best end result really helps us out.”

Visme’s library of stock photos and animated characters: “I really love the images and the look those give to an infographic. I also really like the animated little guys and the animated pictures. That’s added a lot of fun to our designs.”

Visme’s interactivity feature: “You can add URLs and phone number links directly into the infographic so they can just click and call or go to another page on the website and I really like adding those hyperlinks in.”

You can ask your customers to talk about the different products or features that helped them achieve their business success and draw quotes from each one.

10. Jasper Grows Blog Organic Sessions 810% and Blog-Attributed User Signups 400X

Jasper, an AI writing tool, lacked a scalable content strategy to drive organic traffic and user growth. They needed help creating content that converted visitors into users. Especially when a looming domain migration threatened organic traffic.

To address these challenges, Jasper partnered with Omniscient Digital. Their goal was to turn their content into a growth channel and drive organic growth. Omniscient Digital developed a full content strategy for Jasper AI, which included a content audit, competitive analysis, and keyword discovery.

Through their collaboration, Jasper’s organic blog sessions increased by 810%, despite the domain migration. They also witnessed a 400X increase in blog-attributed signups. And more importantly, the content program contributed to over $4 million in annual recurring revenue.

The combination of storytelling and video testimonials within the case study example makes this a real winner. But there’s a twist to it. Omniscient segmented the video testimonials and placed them in different sections of the case study.

Video marketing , especially in case studies, works wonders. Research shows us that 42% of people prefer video testimonials because they show real customers with real success stories. So if you haven't thought of it before, incorporate video testimonials into your case study.

Take a look at this stunning video testimonial template. With its simple design, you can input the picture, name and quote of your customer within your case study in a fun and engaging way.

Try it yourself! Customize this template with your customer’s testimonial and add it to your case study!

11. How Meliá Became One of the Most Influential Hotel Chains on Social Media

Meliá Hotels needed help managing their growing social media customer service needs. Despite having over 500 social accounts, they lacked a unified response protocol and detailed reporting. This largely hindered efficiency and brand consistency.

Meliá partnered with Hootsuite to build an in-house social customer care team. Implementing Hootsuite's tools enabled Meliá to decrease response times from 24 hours to 12.4 hours while also leveraging smart automation.

In addition to that, Meliá resolved over 133,000 conversations, booking 330 inquiries per week through Hootsuite Inbox. They significantly improved brand consistency, response time and customer satisfaction.

The need for a good case study design cannot be over-emphasized.

As soon as anyone lands on this case study example, they are mesmerized by a beautiful case study design. This alone raises the interest of readers and keeps them engaged till the end.

If you’re currently saying to yourself, “ I can write great case studies, but I don’t have the time or skill to turn it into a beautiful document.” Say no more.

Visme’s amazing AI document generator can take your text and transform it into a stunning and professional document in minutes! Not only do you save time, but you also get inspired by the design.

With Visme’s document generator, you can create PDFs, case study presentations , infographics and more!

Take a look at this case study template below. Just like our case study example, it captures readers' attention with its beautiful design. Its dynamic blend of colors and fonts helps to segment each element of the case study beautifully.

12. Tea’s Me Cafe: Tamika Catchings is Brewing Glory

Tamika's journey began when she purchased Tea's Me Cafe in 2017, saving it from closure. She recognized the potential of the cafe as a community hub and hosted regular events centered on social issues and youth empowerment.

One of Tamika’s business goals was to automate her business. She sought to streamline business processes across various aspects of her business. One of the ways she achieves this goal is through Constant Contact.

Constant Contact became an integral part of Tamika's marketing strategy. They provided an automated and centralized platform for managing email newsletters, event registrations, social media scheduling and more.

This allowed Tamika and her team to collaborate efficiently and focus on engaging with their audience. They effectively utilized features like WooCommerce integration, text-to-join and the survey builder to grow their email list, segment their audience and gather valuable feedback.

The case study example utilizes the power of storytelling to form a connection with readers. Constant Contact takes a humble approach in this case study. They spotlight their customers' efforts as the reason for their achievements and growth, establishing trust and credibility.

This case study is also visually appealing, filled with high-quality photos of their customer. While this is a great way to foster originality, it can prove challenging if your customer sends you blurry or low-quality photos.

If you find yourself in that dilemma, you can use Visme’s AI image edit tool to touch up your photos. With Visme’s AI tool, you can remove unwanted backgrounds, erase unwanted objects, unblur low-quality pictures and upscale any photo without losing the quality.

Constant Contact offers its readers various formats to engage with their case study. Including an audio podcast and PDF.

In its PDF version, Constant Contact utilized its brand colors to create a stunning case study design.  With this, they increase brand awareness and, in turn, brand recognition with anyone who comes across their case study.

With Visme’s brand wizard tool , you can seamlessly incorporate your brand assets into any design or document you create. By inputting your URL, Visme’s AI integration will take note of your brand colors, brand fonts and more and create branded templates for you automatically.

You don't need to worry about spending hours customizing templates to fit your brand anymore. You can focus on writing amazing case studies that promote your company.

13. How Breakwater Kitchens Achieved a 7% Growth in Sales With Thryv

Breakwater Kitchens struggled with managing their business operations efficiently. They spent a lot of time on manual tasks, such as scheduling appointments and managing client communication. This made it difficult for them to grow their business and provide the best possible service to their customers.

David, the owner, discovered Thryv. With Thryv, Breakwater Kitchens was able to automate many of their manual tasks. Additionally, Thryv integrated social media management. This enabled Breakwater Kitchens to deliver a consistent brand message, captivate its audience and foster online growth.

As a result, Breakwater Kitchens achieved increased efficiency, reduced missed appointments and a 7% growth in sales.

This case study example uses a concise format and strong verbs, which make it easy for readers to absorb the information.

At the top of the case study, Thryv immediately builds trust by presenting their customer's complete profile, including their name, company details and website. This allows potential customers to verify the case study's legitimacy, making them more likely to believe in Thryv's services.

However, manually copying and pasting customer information across multiple pages of your case study can be time-consuming.

To save time and effort, you can utilize Visme's dynamic field feature . Dynamic fields automatically insert reusable information into your designs.  So you don’t have to type it out multiple times.

14. Zoom’s Creative Team Saves Over 4,000 Hours With Brandfolder

Zoom experienced rapid growth with the advent of remote work and the rise of the COVID-19 pandemic. Such growth called for agility and resilience to scale through.

At the time, Zoom’s assets were disorganized which made retrieving brand information a burden. Zoom’s creative manager spent no less than 10 hours per week finding and retrieving brand assets for internal teams.

Zoom needed a more sustainable approach to organizing and retrieving brand information and came across Brandfolder. Brandfolder simplified and accelerated Zoom’s email localization and webpage development. It also enhanced the creation and storage of Zoom virtual backgrounds.

With Brandfolder, Zoom now saves 4,000+ hours every year. The company also centralized its assets in Brandfolder, which allowed 6,800+ employees and 20-30 vendors to quickly access them.

Brandfolder infused its case study with compelling data and backed it up with verifiable sources. This data-driven approach boosts credibility and increases the impact of their story.

Bradfolder's case study goes the extra mile by providing a downloadable PDF version, making it convenient for readers to access the information on their own time. Their dedication to crafting stunning visuals is evident in every aspect of the project.

From the vibrant colors to the seamless navigation, everything has been meticulously designed to leave a lasting impression on the viewer. And with clickable links that make exploring the content a breeze, the user experience is guaranteed to be nothing short of exceptional.

The thing is, your case study presentation won’t always sit on your website. There are instances where you may need to do a case study presentation for clients, partners or potential investors.

Visme has a rich library of templates you can tap into. But if you’re racing against the clock, Visme’s AI presentation maker is your best ally.

15. How Cents of Style Made $1.7M+ in Affiliate Sales with LeadDyno

Cents of Style had a successful affiliate and influencer marketing strategy. However, their existing affiliate marketing platform was not intuitive, customizable or transparent enough to meet the needs of their influencers.

Cents of Styles needed an easy-to-use affiliate marketing platform that gave them more freedom to customize their program and implement a multi-tier commission program.

After exploring their options, Cents of Style decided on LeadDyno.

LeadDyno provided more flexibility, allowing them to customize commission rates and implement their multi-tier commission structure, switching from monthly to weekly payouts.

Also, integrations with PayPal made payments smoother And features like newsletters and leaderboards added to the platform's success by keeping things transparent and engaging.

As a result, Cents of Style witnessed an impressive $1.7 million in revenue from affiliate sales with a substantial increase in web sales by 80%.

LeadDyno strategically placed a compelling CTA in the middle of their case study layout, maximizing its impact. At this point, readers are already invested in the customer's story and may be considering implementing similar strategies.

A well-placed CTA offers them a direct path to learn more and take action.

LeadDyno also utilized the power of quotes to strengthen their case study. They didn't just embed these quotes seamlessly into the text; instead, they emphasized each one with distinct blocks.

Are you looking for an easier and quicker solution to create a case study and other business documents? Try Visme's AI designer ! This powerful tool allows you to generate complete documents, such as case studies, reports, whitepapers and more, just by providing text prompts. Simply explain your requirements to the tool, and it will produce the document for you, complete with text, images, design assets and more.

Still have more questions about case studies? Let's look at some frequently asked questions.

How to Write a Case Study?

• Choose a compelling story: Not all case studies are created equal. Pick one that is relevant to your target audience and demonstrates the specific benefits of your product or service.
• Outline your case study: Create a case study outline and highlight how you will structure your case study to include the introduction, problem, solution and achievements of your customer.
• Choose a case study template: After you outline your case study, choose a case study template . Visme has stunning templates that can inspire your case study design.
• Craft a compelling headline: Include figures or percentages that draw attention to your case study.
• Work on the first draft: Your case study should be easy to read and understand. Use clear and concise language and avoid jargon.
• Include high-quality visual aids: Visuals can help to make your case study more engaging and easier to read. Consider adding high-quality photos, screenshots or videos.
• Include a relevant CTA: Tell prospective customers how to reach you for questions or sign-ups.

What Are the Stages of a Case Study?

The stages of a case study are;

• Planning & Preparation: Highlight your goals for writing the case study. Plan the case study format, length and audience you wish to target.
• Interview the Client: Reach out to the company you want to showcase and ask relevant questions about their journey and achievements.
• Revision & Editing: Review your case study and ask for feedback. Include relevant quotes and CTAs to your case study.
• Publication & Distribution: Publish and share your case study on your website, social media channels and email list!
• Marketing & Repurposing: Turn your case study into a podcast, PDF, case study presentation and more. Share these materials with your sales and marketing team.

What Are the Advantages and Disadvantages of a Case Study?

Advantages of a case study:

• Case studies showcase a specific solution and outcome for specific customer challenges.
• It attracts potential customers with similar challenges.
• It builds trust and credibility with potential customers.
• It provides an in-depth analysis of your company’s problem-solving process.

Disadvantages of a case study:

• Limited applicability. Case studies are tailored to specific cases and may not apply to other businesses.
• It relies heavily on customer cooperation and willingness to share information.
• It stands a risk of becoming outdated as industries and customer needs evolve.

What Are the Types of Case Studies?

There are 7 main types of case studies. They include;

• Illustrative case study.
• Instrumental case study.
• Intrinsic case study.
• Descriptive case study.
• Explanatory case study.
• Exploratory case study.
• Collective case study.

How Long Should a Case Study Be?

The ideal length of your case study is between 500 - 1500 words or 1-3 pages. Certain factors like your target audience, goal or the amount of detail you want to share may influence the length of your case study. This infographic has powerful tips for designing winning case studies

What Is the Difference Between a Case Study and an Example?

Case studies provide a detailed narrative of how your product or service was used to solve a problem. Examples are general illustrations and are not necessarily real-life scenarios.

Case studies are often used for marketing purposes, attracting potential customers and building trust. Examples, on the other hand, are primarily used to simplify or clarify complex concepts.

Where Can I Find Case Study Examples?

You can easily find many case study examples online and in industry publications. Many companies, including Visme, share case studies on their websites to showcase how their products or services have helped clients achieve success. You can also search online libraries and professional organizations for case studies related to your specific industry or field.

If you need professionally-designed, customizable case study templates to create your own, Visme's template library is one of the best places to look. These templates include all the essential sections of a case study and high-quality content to help you create case studies that position your business as an industry leader.

Get More Out Of Your Case Studies With Visme

Case studies are an essential tool for converting potential customers into paying customers. By following the tips in this article, you can create compelling case studies that will help you build trust, establish credibility and drive sales.

Visme can help you create stunning case studies and other relevant marketing materials. With our easy-to-use platform, interactive features and analytics tools , you can increase your content creation game in no time.

There is no limit to what you can achieve with Visme. Connect with Sales to discover how Visme can boost your business goals.

Easily create beautiful case studies and more with Visme

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8 case studies and real world examples of how Big Data has helped keep on top of competition

Fast, data-informed decision-making can drive business success. Managing high customer expectations, navigating marketing challenges, and global competition – many organizations look to data analytics and business intelligence for a competitive advantage.

Using data to serve up personalized ads based on browsing history, providing contextual KPI data access for all employees and centralizing data from across the business into one digital ecosystem so processes can be more thoroughly reviewed are all examples of business intelligence.

Organizations invest in data science because it promises to bring competitive advantages.

Data is transforming into an actionable asset, and new tools are using that reality to move the needle with ML. As a result, organizations are on the brink of mobilizing data to not only predict the future but also to increase the likelihood of certain outcomes through prescriptive analytics.

Here are some case studies that show some ways BI is making a difference for companies around the world:

1) Starbucks:

With 90 million transactions a week in 25,000 stores worldwide the coffee giant is in many ways on the cutting edge of using big data and artificial intelligence to help direct marketing, sales and business decisions

Through its popular loyalty card program and mobile application, Starbucks owns individual purchase data from millions of customers. Using this information and BI tools, the company predicts purchases and sends individual offers of what customers will likely prefer via their app and email. This system draws existing customers into its stores more frequently and increases sales volumes.

The same intel that helps Starbucks suggest new products to try also helps the company send personalized offers and discounts that go far beyond a special birthday discount. Additionally, a customized email goes out to any customer who hasn’t visited a Starbucks recently with enticing offers—built from that individual’s purchase history—to re-engage them.

2) Netflix:

The online entertainment company’s 148 million subscribers give it a massive BI advantage.

Netflix has digitized its interactions with its 151 million subscribers. It collects data from each of its users and with the help of data analytics understands the behavior of subscribers and their watching patterns. It then leverages that information to recommend movies and TV shows customized as per the subscriber’s choice and preferences.

As per Netflix, around 80% of the viewer’s activity is triggered by personalized algorithmic recommendations. Where Netflix gains an edge over its peers is that by collecting different data points, it creates detailed profiles of its subscribers which helps them engage with them better.

The recommendation system of Netflix contributes to more than 80% of the content streamed by its subscribers which has helped Netflix earn a whopping one billion via customer retention. Due to this reason, Netflix doesn’t have to invest too much on advertising and marketing their shows. They precisely know an estimate of the people who would be interested in watching a show.

3) Coca-Cola:

Coca Cola is the world’s largest beverage company, with over 500 soft drink brands sold in more than 200 countries. Given the size of its operations, Coca Cola generates a substantial amount of data across its value chain – including sourcing, production, distribution, sales and customer feedback which they can leverage to drive successful business decisions.

Coca Cola has been investing extensively in research and development, especially in AI, to better leverage the mountain of data it collects from customers all around the world. This initiative has helped them better understand consumer trends in terms of price, flavors, packaging, and consumer’ preference for healthier options in certain regions.

With 35 million Twitter followers and a whopping 105 million Facebook fans, Coca-Cola benefits from its social media data. Using AI-powered image-recognition technology, they can track when photographs of its drinks are posted online. This data, paired with the power of BI, gives the company important insights into who is drinking their beverages, where they are and why they mention the brand online. The information helps serve consumers more targeted advertising, which is four times more likely than a regular ad to result in a click.

Coca Cola is increasingly betting on BI, data analytics and AI to drive its strategic business decisions. From its innovative free style fountain machine to finding new ways to engage with customers, Coca Cola is well-equipped to remain at the top of the competition in the future. In a new digital world that is increasingly dynamic, with changing customer behavior, Coca Cola is relying on Big Data to gain and maintain their competitive advantage.

4) American Express GBT

The American Express Global Business Travel company, popularly known as Amex GBT, is an American multinational travel and meetings programs management corporation which operates in over 120 countries and has over 14,000 employees.

Challenges:

Scalability – Creating a single portal for around 945 separate data files from internal and customer systems using the current BI tool would require over 6 months to complete. The earlier tool was used for internal purposes and scaling the solution to such a large population while keeping the costs optimum was a major challenge

Performance – Their existing system had limitations shifting to Cloud. The amount of time and manual effort required was immense

Data Governance – Maintaining user data security and privacy was of utmost importance for Amex GBT

The company was looking to protect and increase its market share by differentiating its core services and was seeking a resource to manage and drive their online travel program capabilities forward. Amex GBT decided to make a strategic investment in creating smart analytics around their booking software.

The solution equipped users to view their travel ROI by categorizing it into three categories cost, time and value. Each category has individual KPIs that are measured to evaluate the performance of a travel plan.

Reducing travel expenses by 30%

Time to Value – Initially it took a week for new users to be on-boarded onto the platform. With Premier Insights that time had now been reduced to a single day and the process had become much simpler and more effective.

Savings on Spends – The product notifies users of any available booking offers that can help them save on their expenditure. It recommends users of possible saving potential such as flight timings, date of the booking, date of travel, etc.

Adoption – Ease of use of the product, quick scale-up, real-time implementation of reports, and interactive dashboards of Premier Insights increased the global online adoption for Amex GBT

5) Airline Solutions Company: BI Accelerates Business Insights

Airline Solutions provides booking tools, revenue management, web, and mobile itinerary tools, as well as other technology, for airlines, hotels and other companies in the travel industry.

Challenge: The travel industry is remarkably dynamic and fast paced. And the airline solution provider’s clients needed advanced tools that could provide real-time data on customer behavior and actions.

They developed an enterprise travel data warehouse (ETDW) to hold its enormous amounts of data. The executive dashboards provide near real-time insights in user-friendly environments with a 360-degree overview of business health, reservations, operational performance and ticketing.

Results: The scalable infrastructure, graphic user interface, data aggregation and ability to work collaboratively have led to more revenue and increased client satisfaction.

6) A specialty US Retail Provider: Leveraging prescriptive analytics

Challenge/Objective: A specialty US Retail provider wanted to modernize its data platform which could help the business make real-time decisions while also leveraging prescriptive analytics. They wanted to discover true value of data being generated from its multiple systems and understand the patterns (both known and unknown) of sales, operations, and omni-channel retail performance.

We helped build a modern data solution that consolidated their data in a data lake and data warehouse, making it easier to extract the value in real-time. We integrated our solution with their OMS, CRM, Google Analytics, Salesforce, and inventory management system. The data was modeled in such a way that it could be fed into Machine Learning algorithms; so that we can leverage this easily in the future.

The customer had visibility into their data from day 1, which is something they had been wanting for some time. In addition to this, they were able to build more reports, dashboards, and charts to understand and interpret the data. In some cases, they were able to get real-time visibility and analysis on instore purchases based on geography!

7) Logistics startup with an objective to become the “Uber of the Trucking Sector” with the help of data analytics

Challenge: A startup specializing in analyzing vehicle and/or driver performance by collecting data from sensors within the vehicle (a.k.a. vehicle telemetry) and Order patterns with an objective to become the “Uber of the Trucking Sector”

Solution: We developed a customized backend of the client’s trucking platform so that they could monetize empty return trips of transporters by creating a marketplace for them. The approach used a combination of AWS Data Lake, AWS microservices, machine learning and analytics.

• Reduced fuel costs
• Optimized Reloads
• More accurate driver / truck schedule planning
• Smarter Routing
• Fewer empty return trips
• Deeper analysis of driver patterns, breaks, routes, etc.

8) Challenge/Objective: A niche segment customer competing against market behemoths looking to become a “Niche Segment Leader”

Solution: We developed a customized analytics platform that can ingest CRM, OMS, Ecommerce, and Inventory data and produce real time and batch driven analytics and AI platform. The approach used a combination of AWS microservices, machine learning and analytics.

• Reduce Customer Churn
• Optimized Order Fulfillment
• More accurate demand schedule planning
• Improve Product Recommendation
• Improved Last Mile Delivery

How can we help you harness the power of data?

At Systems Plus our BI and analytics specialists help you leverage data to understand trends and derive insights by streamlining the searching, merging, and querying of data. From improving your CX and employee performance to predicting new revenue streams, our BI and analytics expertise helps you make data-driven decisions for saving costs and taking your growth to the next level.

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Top 20 Analytics Case Studies in 2024

Cem is the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per Similarweb) including 60% of Fortune 500 every month.

Cem's work focuses on how enterprises can leverage new technologies in AI, automation, cybersecurity(including network security, application security), data collection including web data collection and process intelligence.

Although the potential of Big Data and business intelligence are recognized by organizations, Gartner analyst Nick Heudecker says that the failure rate of analytics projects is close to 85%. Uncovering the power of analytics improves business operations, reduces costs, enhances decision-making , and enables the launching of more personalized products.

In this article, our research covers:

How to measure analytics success?

What are some analytics case studies.

According to  Gartner CDO Survey,  the top 3 critical success factors of analytics projects are:

• Creation of a data-driven culture within the organization,
• Data integration and data skills training across the organization,
• And implementation of a data management and analytics strategy.

The success of the process of analytics depends on asking the right question. It requires an understanding of the appropriate data required for each goal to be achieved. We’ve listed 20 successful analytics applications/case studies from different industries.

During our research, we examined that partnering with an analytics consultant helps organizations boost their success if organizations’ tech team lacks certain data skills.

*Vendors have not shared the client name

For more on analytics

If your organization is willing to implement an analytics solution but doesn’t know where to start, here are some of the articles we’ve written before that can help you learn more:

• AI in analytics: How AI is shaping analytics
• Edge Analytics in 2022: What it is, Why it matters & Use Cases
• Application Analytics: Tracking KPIs that lead to success

Finally, if you believe that your business would benefit from adopting an analytics solution, we have data-driven lists of vendors on our analytics hub and analytics platforms

We will help you choose the best solution tailored to your needs:

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Cem's hands-on enterprise software experience contributes to the insights that he generates. He oversees AIMultiple benchmarks in dynamic application security testing (DAST), data loss prevention (DLP), email marketing and web data collection. Other AIMultiple industry analysts and tech team support Cem in designing, running and evaluating benchmarks.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised enterprises on their technology decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

AIMultiple.com Traffic Analytics, Ranking & Audience , Similarweb. Why Microsoft, IBM, and Google Are Ramping up Efforts on AI Ethics , Business Insider. Microsoft invests $1 billion in OpenAI to pursue artificial intelligence that’s smarter than we are , Washington Post. Data management barriers to AI success , Deloitte. Empowering AI Leadership: AI C-Suite Toolkit , World Economic Forum. Science, Research and Innovation Performance of the EU , European Commission. Public-sector digitization: The trillion-dollar challenge , McKinsey & Company. Hypatos gets $11.8M for a deep learning approach to document processing , TechCrunch. We got an exclusive look at the pitch deck AI startup Hypatos used to raise $11 million , Business Insider.

To stay up-to-date on B2B tech & accelerate your enterprise:

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• Data Science

Top 12 Data Science Case Studies: Across Various Industries

Home Blog Data Science Top 12 Data Science Case Studies: Across Various Industries

Data science has become popular in the last few years due to its successful application in making business decisions. Data scientists have been using data science techniques to solve challenging real-world issues in healthcare, agriculture, manufacturing, automotive, and many more. For this purpose, a data enthusiast needs to stay updated with the latest technological advancements in AI . An excellent way to achieve this is through reading industry data science case studies. I recommend checking out Data Science With Python course syllabus to start your data science journey. In this discussion, I will present some case studies to you that contain detailed and systematic data analysis of people, objects, or entities focusing on multiple factors present in the dataset. Aspiring and practising data scientists can motivate themselves to learn more about the sector, an alternative way of thinking, or methods to improve their organization based on comparable experiences. Almost every industry uses data science in some way. You can learn more about data science fundamentals in this data science course content . From my standpoint, data scientists may use it to spot fraudulent conduct in insurance claims. Automotive data scientists may use it to improve self-driving cars. In contrast, e-commerce data scientists can use it to add more personalization for their consumers—the possibilities are unlimited and unexplored. Let’s look at the top eight data science case studies in this article so you can understand how businesses from many sectors have benefitted from data science to boost productivity, revenues, and more. Read on to explore more or use the following links to go straight to the case study of your choice.

Examples of Data Science Case Studies

• Hospitality:  Airbnb focuses on growth by  analyzing  customer voice using data science.  Qantas uses predictive analytics to mitigate losses  
• Healthcare:  Novo Nordisk  is  Driving innovation with NLP.  AstraZeneca harnesses data for innovation in medicine  
• Covid 19:  Johnson and Johnson use s  d ata science  to fight the Pandemic  
• E-commerce:  Amazon uses data science to personalize shop p ing experiences and improve customer satisfaction  
• Supply chain management :  UPS optimizes supp l y chain with big data analytics
• Meteorology:  IMD leveraged data science to achieve a rec o rd 1.2m evacuation before cyclone ''Fani''  
• Entertainment Industry:  Netflix  u ses data science to personalize the content and improve recommendations.  Spotify uses big   data to deliver a rich user experience for online music streaming  
• Banking and Finance:  HDFC utilizes Big  D ata Analytics to increase income and enhance  the  banking experience  

Top 8 Data Science Case Studies  [For Various Industries]

1. data science in hospitality industry.

In the hospitality sector, data analytics assists hotels in better pricing strategies, customer analysis, brand marketing , tracking market trends, and many more.

Airbnb focuses on growth by analyzing customer voice using data science.  A famous example in this sector is the unicorn '' Airbnb '', a startup that focussed on data science early to grow and adapt to the market faster. This company witnessed a 43000 percent hypergrowth in as little as five years using data science. They included data science techniques to process the data, translate this data for better understanding the voice of the customer, and use the insights for decision making. They also scaled the approach to cover all aspects of the organization. Airbnb uses statistics to analyze and aggregate individual experiences to establish trends throughout the community. These analyzed trends using data science techniques impact their business choices while helping them grow further.  

Travel industry and data science

Predictive analytics benefits many parameters in the travel industry. These companies can use recommendation engines with data science to achieve higher personalization and improved user interactions. They can study and cross-sell products by recommending relevant products to drive sales and increase revenue. Data science is also employed in analyzing social media posts for sentiment analysis, bringing invaluable travel-related insights. Whether these views are positive, negative, or neutral can help these agencies understand the user demographics, the expected experiences by their target audiences, and so on. These insights are essential for developing aggressive pricing strategies to draw customers and provide better customization to customers in the travel packages and allied services. Travel agencies like Expedia and Booking.com use predictive analytics to create personalized recommendations, product development, and effective marketing of their products. Not just travel agencies but airlines also benefit from the same approach. Airlines frequently face losses due to flight cancellations, disruptions, and delays. Data science helps them identify patterns and predict possible bottlenecks, thereby effectively mitigating the losses and improving the overall customer traveling experience.  

How Qantas uses predictive analytics to mitigate losses  

Qantas , one of Australia's largest airlines, leverages data science to reduce losses caused due to flight delays, disruptions, and cancellations. They also use it to provide a better traveling experience for their customers by reducing the number and length of delays caused due to huge air traffic, weather conditions, or difficulties arising in operations. Back in 2016, when heavy storms badly struck Australia's east coast, only 15 out of 436 Qantas flights were cancelled due to their predictive analytics-based system against their competitor Virgin Australia, which witnessed 70 cancelled flights out of 320.  

2. Data Science in Healthcare

The  Healthcare sector  is immensely benefiting from the advancements in AI. Data science, especially in medical imaging, has been helping healthcare professionals come up with better diagnoses and effective treatments for patients. Similarly, several advanced healthcare analytics tools have been developed to generate clinical insights for improving patient care. These tools also assist in defining personalized medications for patients reducing operating costs for clinics and hospitals. Apart from medical imaging or computer vision,  Natural Language Processing (NLP)  is frequently used in the healthcare domain to study the published textual research data.     

A. Pharmaceutical

Driving innovation with NLP: Novo Nordisk.  Novo Nordisk  uses the Linguamatics NLP platform from internal and external data sources for text mining purposes that include scientific abstracts, patents, grants, news, tech transfer offices from universities worldwide, and more. These NLP queries run across sources for the key therapeutic areas of interest to the Novo Nordisk R&D community. Several NLP algorithms have been developed for the topics of safety, efficacy, randomized controlled trials, patient populations, dosing, and devices. Novo Nordisk employs a data pipeline to capitalize the tools' success on real-world data and uses interactive dashboards and cloud services to visualize this standardized structured information from the queries for exploring commercial effectiveness, market situations, potential, and gaps in the product documentation. Through data science, they are able to automate the process of generating insights, save time and provide better insights for evidence-based decision making.  

How AstraZeneca harnesses data for innovation in medicine.  AstraZeneca  is a globally known biotech company that leverages data using AI technology to discover and deliver newer effective medicines faster. Within their R&D teams, they are using AI to decode the big data to understand better diseases like cancer, respiratory disease, and heart, kidney, and metabolic diseases to be effectively treated. Using data science, they can identify new targets for innovative medications. In 2021, they selected the first two AI-generated drug targets collaborating with BenevolentAI in Chronic Kidney Disease and Idiopathic Pulmonary Fibrosis.   

Data science is also helping AstraZeneca redesign better clinical trials, achieve personalized medication strategies, and innovate the process of developing new medicines. Their Center for Genomics Research uses  data science and AI  to analyze around two million genomes by 2026. Apart from this, they are training their AI systems to check these images for disease and biomarkers for effective medicines for imaging purposes. This approach helps them analyze samples accurately and more effortlessly. Moreover, it can cut the analysis time by around 30%.   

AstraZeneca also utilizes AI and machine learning to optimize the process at different stages and minimize the overall time for the clinical trials by analyzing the clinical trial data. Summing up, they use data science to design smarter clinical trials, develop innovative medicines, improve drug development and patient care strategies, and many more.

C. Wearable Technology  

Wearable technology is a multi-billion-dollar industry. With an increasing awareness about fitness and nutrition, more individuals now prefer using fitness wearables to track their routines and lifestyle choices.  

Fitness wearables are convenient to use, assist users in tracking their health, and encourage them to lead a healthier lifestyle. The medical devices in this domain are beneficial since they help monitor the patient's condition and communicate in an emergency situation. The regularly used fitness trackers and smartwatches from renowned companies like Garmin, Apple, FitBit, etc., continuously collect physiological data of the individuals wearing them. These wearable providers offer user-friendly dashboards to their customers for analyzing and tracking progress in their fitness journey.

3. Covid 19 and Data Science

In the past two years of the Pandemic, the power of data science has been more evident than ever. Different  pharmaceutical companies  across the globe could synthesize Covid 19 vaccines by analyzing the data to understand the trends and patterns of the outbreak. Data science made it possible to track the virus in real-time, predict patterns, devise effective strategies to fight the Pandemic, and many more.  

How Johnson and Johnson uses data science to fight the Pandemic   

The  data science team  at  Johnson and Johnson  leverages real-time data to track the spread of the virus. They built a global surveillance dashboard (granulated to county level) that helps them track the Pandemic's progress, predict potential hotspots of the virus, and narrow down the likely place where they should test its investigational COVID-19 vaccine candidate. The team works with in-country experts to determine whether official numbers are accurate and find the most valid information about case numbers, hospitalizations, mortality and testing rates, social compliance, and local policies to populate this dashboard. The team also studies the data to build models that help the company identify groups of individuals at risk of getting affected by the virus and explore effective treatments to improve patient outcomes.

4. Data Science in E-commerce  

In the  e-commerce sector , big data analytics can assist in customer analysis, reduce operational costs, forecast trends for better sales, provide personalized shopping experiences to customers, and many more.  

Amazon uses data science to personalize shopping experiences and improve customer satisfaction.  Amazon  is a globally leading eCommerce platform that offers a wide range of online shopping services. Due to this, Amazon generates a massive amount of data that can be leveraged to understand consumer behavior and generate insights on competitors' strategies. Amazon uses its data to provide recommendations to its users on different products and services. With this approach, Amazon is able to persuade its consumers into buying and making additional sales. This approach works well for Amazon as it earns 35% of the revenue yearly with this technique. Additionally, Amazon collects consumer data for faster order tracking and better deliveries.     

Similarly, Amazon's virtual assistant, Alexa, can converse in different languages; uses speakers and a   camera to interact with the users. Amazon utilizes the audio commands from users to improve Alexa and deliver a better user experience. 

5. Data Science in Supply Chain Management

Predictive analytics and big data are driving innovation in the Supply chain domain. They offer greater visibility into the company operations, reduce costs and overheads, forecasting demands, predictive maintenance, product pricing, minimize supply chain interruptions, route optimization, fleet management , drive better performance, and more.     

Optimizing supply chain with big data analytics: UPS

UPS  is a renowned package delivery and supply chain management company. With thousands of packages being delivered every day, on average, a UPS driver makes about 100 deliveries each business day. On-time and safe package delivery are crucial to UPS's success. Hence, UPS offers an optimized navigation tool ''ORION'' (On-Road Integrated Optimization and Navigation), which uses highly advanced big data processing algorithms. This tool for UPS drivers provides route optimization concerning fuel, distance, and time. UPS utilizes supply chain data analysis in all aspects of its shipping process. Data about packages and deliveries are captured through radars and sensors. The deliveries and routes are optimized using big data systems. Overall, this approach has helped UPS save 1.6 million gallons of gasoline in transportation every year, significantly reducing delivery costs.    

6. Data Science in Meteorology

Weather prediction is an interesting  application of data science . Businesses like aviation, agriculture and farming, construction, consumer goods, sporting events, and many more are dependent on climatic conditions. The success of these businesses is closely tied to the weather, as decisions are made after considering the weather predictions from the meteorological department.   

Besides, weather forecasts are extremely helpful for individuals to manage their allergic conditions. One crucial application of weather forecasting is natural disaster prediction and risk management.  

Weather forecasts begin with a large amount of data collection related to the current environmental conditions (wind speed, temperature, humidity, clouds captured at a specific location and time) using sensors on IoT (Internet of Things) devices and satellite imagery. This gathered data is then analyzed using the understanding of atmospheric processes, and machine learning models are built to make predictions on upcoming weather conditions like rainfall or snow prediction. Although data science cannot help avoid natural calamities like floods, hurricanes, or forest fires. Tracking these natural phenomena well ahead of their arrival is beneficial. Such predictions allow governments sufficient time to take necessary steps and measures to ensure the safety of the population.  

IMD leveraged data science to achieve a record 1.2m evacuation before cyclone ''Fani''   

Most  d ata scientist’s responsibilities  rely on satellite images to make short-term forecasts, decide whether a forecast is correct, and validate models. Machine Learning is also used for pattern matching in this case. It can forecast future weather conditions if it recognizes a past pattern. When employing dependable equipment, sensor data is helpful to produce local forecasts about actual weather models. IMD used satellite pictures to study the low-pressure zones forming off the Odisha coast (India). In April 2019, thirteen days before cyclone ''Fani'' reached the area,  IMD  (India Meteorological Department) warned that a massive storm was underway, and the authorities began preparing for safety measures.  

It was one of the most powerful cyclones to strike India in the recent 20 years, and a record 1.2 million people were evacuated in less than 48 hours, thanks to the power of data science.   

7. Data Science in the Entertainment Industry

Due to the Pandemic, demand for OTT (Over-the-top) media platforms has grown significantly. People prefer watching movies and web series or listening to the music of their choice at leisure in the convenience of their homes. This sudden growth in demand has given rise to stiff competition. Every platform now uses data analytics in different capacities to provide better-personalized recommendations to its subscribers and improve user experience.   

How Netflix uses data science to personalize the content and improve recommendations  

Netflix  is an extremely popular internet television platform with streamable content offered in several languages and caters to various audiences. In 2006, when Netflix entered this media streaming market, they were interested in increasing the efficiency of their existing ''Cinematch'' platform by 10% and hence, offered a prize of $1 million to the winning team. This approach was successful as they found a solution developed by the BellKor team at the end of the competition that increased prediction accuracy by 10.06%. Over 200 work hours and an ensemble of 107 algorithms provided this result. These winning algorithms are now a part of the Netflix recommendation system.  

Netflix also employs Ranking Algorithms to generate personalized recommendations of movies and TV Shows appealing to its users.   

Spotify uses big data to deliver a rich user experience for online music streaming  

Personalized online music streaming is another area where data science is being used.  Spotify  is a well-known on-demand music service provider launched in 2008, which effectively leveraged big data to create personalized experiences for each user. It is a huge platform with more than 24 million subscribers and hosts a database of nearly 20million songs; they use the big data to offer a rich experience to its users. Spotify uses this big data and various algorithms to train machine learning models to provide personalized content. Spotify offers a "Discover Weekly" feature that generates a personalized playlist of fresh unheard songs matching the user's taste every week. Using the Spotify "Wrapped" feature, users get an overview of their most favorite or frequently listened songs during the entire year in December. Spotify also leverages the data to run targeted ads to grow its business. Thus, Spotify utilizes the user data, which is big data and some external data, to deliver a high-quality user experience.  

8. Data Science in Banking and Finance

Data science is extremely valuable in the Banking and  Finance industry . Several high priority aspects of Banking and Finance like credit risk modeling (possibility of repayment of a loan), fraud detection (detection of malicious or irregularities in transactional patterns using machine learning), identifying customer lifetime value (prediction of bank performance based on existing and potential customers), customer segmentation (customer profiling based on behavior and characteristics for personalization of offers and services). Finally, data science is also used in real-time predictive analytics (computational techniques to predict future events).    

How HDFC utilizes Big Data Analytics to increase revenues and enhance the banking experience    

One of the major private banks in India,  HDFC Bank , was an early adopter of AI. It started with Big Data analytics in 2004, intending to grow its revenue and understand its customers and markets better than its competitors. Back then, they were trendsetters by setting up an enterprise data warehouse in the bank to be able to track the differentiation to be given to customers based on their relationship value with HDFC Bank. Data science and analytics have been crucial in helping HDFC bank segregate its customers and offer customized personal or commercial banking services. The analytics engine and SaaS use have been assisting the HDFC bank in cross-selling relevant offers to its customers. Apart from the regular fraud prevention, it assists in keeping track of customer credit histories and has also been the reason for the speedy loan approvals offered by the bank.  

9. Data Science in Urban Planning and Smart Cities  

Data Science can help the dream of smart cities come true! Everything, from traffic flow to energy usage, can get optimized using data science techniques. You can use the data fetched from multiple sources to understand trends and plan urban living in a sorted manner.  

The significant data science case study is traffic management in Pune city. The city controls and modifies its traffic signals dynamically, tracking the traffic flow. Real-time data gets fetched from the signals through cameras or sensors installed. Based on this information, they do the traffic management. With this proactive approach, the traffic and congestion situation in the city gets managed, and the traffic flow becomes sorted. A similar case study is from Bhubaneswar, where the municipality has platforms for the people to give suggestions and actively participate in decision-making. The government goes through all the inputs provided before making any decisions, making rules or arranging things that their residents actually need.  

10. Data Science in Agricultural Yield Prediction   

Have you ever wondered how helpful it can be if you can predict your agricultural yield? That is exactly what data science is helping farmers with. They can get information about the number of crops they can produce in a given area based on different environmental factors and soil types. Using this information, the farmers can make informed decisions about their yield and benefit the buyers and themselves in multiple ways.  

Farmers across the globe and overseas use various data science techniques to understand multiple aspects of their farms and crops. A famous example of data science in the agricultural industry is the work done by Farmers Edge. It is a company in Canada that takes real-time images of farms across the globe and combines them with related data. The farmers use this data to make decisions relevant to their yield and improve their produce. Similarly, farmers in countries like Ireland use satellite-based information to ditch traditional methods and multiply their yield strategically.  

11. Data Science in the Transportation Industry   

Transportation keeps the world moving around. People and goods commute from one place to another for various purposes, and it is fair to say that the world will come to a standstill without efficient transportation. That is why it is crucial to keep the transportation industry in the most smoothly working pattern, and data science helps a lot in this. In the realm of technological progress, various devices such as traffic sensors, monitoring display systems, mobility management devices, and numerous others have emerged.  

Many cities have already adapted to the multi-modal transportation system. They use GPS trackers, geo-locations and CCTV cameras to monitor and manage their transportation system. Uber is the perfect case study to understand the use of data science in the transportation industry. They optimize their ride-sharing feature and track the delivery routes through data analysis. Their data science approach enabled them to serve more than 100 million users, making transportation easy and convenient. Moreover, they also use the data they fetch from users daily to offer cost-effective and quickly available rides.  

12. Data Science in the Environmental Industry    

Increasing pollution, global warming, climate changes and other poor environmental impacts have forced the world to pay attention to environmental industry. Multiple initiatives are being taken across the globe to preserve the environment and make the world a better place. Though the industry recognition and the efforts are in the initial stages, the impact is significant, and the growth is fast.  

The popular use of data science in the environmental industry is by NASA and other research organizations worldwide. NASA gets data related to the current climate conditions, and this data gets used to create remedial policies that can make a difference. Another way in which data science is actually helping researchers is they can predict natural disasters well before time and save or at least reduce the potential damage considerably. A similar case study is with the World Wildlife Fund. They use data science to track data related to deforestation and help reduce the illegal cutting of trees. Hence, it helps preserve the environment.  

Where to Find Full Data Science Case Studies?  

Data science is a highly evolving domain with many practical applications and a huge open community. Hence, the best way to keep updated with the latest trends in this domain is by reading case studies and technical articles. Usually, companies share their success stories of how data science helped them achieve their goals to showcase their potential and benefit the greater good. Such case studies are available online on the respective company websites and dedicated technology forums like Towards Data Science or Medium.  

Additionally, we can get some practical examples in recently published research papers and textbooks in data science.  

What Are the Skills Required for Data Scientists?  

Data scientists play an important role in the data science process as they are the ones who work on the data end to end. To be able to work on a data science case study, there are several skills required for data scientists like a good grasp of the fundamentals of data science, deep knowledge of statistics, excellent programming skills in Python or R, exposure to data manipulation and data analysis, ability to generate creative and compelling data visualizations, good knowledge of big data, machine learning and deep learning concepts for model building & deployment. Apart from these technical skills, data scientists also need to be good storytellers and should have an analytical mind with strong communication skills.    

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Conclusion  

These were some interesting  data science case studies  across different industries. There are many more domains where data science has exciting applications, like in the Education domain, where data can be utilized to monitor student and instructor performance, develop an innovative curriculum that is in sync with the industry expectations, etc.   

Almost all the companies looking to leverage the power of big data begin with a swot analysis to narrow down the problems they intend to solve with data science. Further, they need to assess their competitors to develop relevant data science tools and strategies to address the challenging issue. This approach allows them to differentiate themselves from their competitors and offer something unique to their customers.  

With data science, the companies have become smarter and more data-driven to bring about tremendous growth. Moreover, data science has made these organizations more sustainable. Thus, the utility of data science in several sectors is clearly visible, a lot is left to be explored, and more is yet to come. Nonetheless, data science will continue to boost the performance of organizations in this age of big data.  

Frequently Asked Questions (FAQs)

A case study in data science requires a systematic and organized approach for solving the problem. Generally, four main steps are needed to tackle every data science case study: 

• Defining the problem statement and strategy to solve it  
• Gather and pre-process the data by making relevant assumptions  
• Select tool and appropriate algorithms to build machine learning /deep learning models 
• Make predictions, accept the solutions based on evaluation metrics, and improve the model if necessary. 

Getting data for a case study starts with a reasonable understanding of the problem. This gives us clarity about what we expect the dataset to include. Finding relevant data for a case study requires some effort. Although it is possible to collect relevant data using traditional techniques like surveys and questionnaires, we can also find good quality data sets online on different platforms like Kaggle, UCI Machine Learning repository, Azure open data sets, Government open datasets, Google Public Datasets, Data World and so on.  

Data science projects involve multiple steps to process the data and bring valuable insights. A data science project includes different steps - defining the problem statement, gathering relevant data required to solve the problem, data pre-processing, data exploration & data analysis, algorithm selection, model building, model prediction, model optimization, and communicating the results through dashboards and reports.  

Devashree Madhugiri

Devashree holds an M.Eng degree in Information Technology from Germany and a background in Data Science. She likes working with statistics and discovering hidden insights in varied datasets to create stunning dashboards. She enjoys sharing her knowledge in AI by writing technical articles on various technological platforms. She loves traveling, reading fiction, solving Sudoku puzzles, and participating in coding competitions in her leisure time.

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• Knowledge Base

Methodology

• What Is a Case Study? | Definition, Examples & Methods

What Is a Case Study? | Definition, Examples & Methods

Published on May 8, 2019 by Shona McCombes . Revised on November 20, 2023.

A case study is a detailed study of a specific subject, such as a person, group, place, event, organization, or phenomenon. Case studies are commonly used in social, educational, clinical, and business research.

A case study research design usually involves qualitative methods , but quantitative methods are sometimes also used. Case studies are good for describing , comparing, evaluating and understanding different aspects of a research problem .

Table of contents

When to do a case study, step 1: select a case, step 2: build a theoretical framework, step 3: collect your data, step 4: describe and analyze the case, other interesting articles.

A case study is an appropriate research design when you want to gain concrete, contextual, in-depth knowledge about a specific real-world subject. It allows you to explore the key characteristics, meanings, and implications of the case.

Case studies are often a good choice in a thesis or dissertation . They keep your project focused and manageable when you don’t have the time or resources to do large-scale research.

You might use just one complex case study where you explore a single subject in depth, or conduct multiple case studies to compare and illuminate different aspects of your research problem.

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Once you have developed your problem statement and research questions , you should be ready to choose the specific case that you want to focus on. A good case study should have the potential to:

• Provide new or unexpected insights into the subject
• Challenge or complicate existing assumptions and theories
• Propose practical courses of action to resolve a problem
• Open up new directions for future research

TipIf your research is more practical in nature and aims to simultaneously investigate an issue as you solve it, consider conducting action research instead.

Unlike quantitative or experimental research , a strong case study does not require a random or representative sample. In fact, case studies often deliberately focus on unusual, neglected, or outlying cases which may shed new light on the research problem.

Example of an outlying case studyIn the 1960s the town of Roseto, Pennsylvania was discovered to have extremely low rates of heart disease compared to the US average. It became an important case study for understanding previously neglected causes of heart disease.

However, you can also choose a more common or representative case to exemplify a particular category, experience or phenomenon.

Example of a representative case studyIn the 1920s, two sociologists used Muncie, Indiana as a case study of a typical American city that supposedly exemplified the changing culture of the US at the time.

While case studies focus more on concrete details than general theories, they should usually have some connection with theory in the field. This way the case study is not just an isolated description, but is integrated into existing knowledge about the topic. It might aim to:

• Exemplify a theory by showing how it explains the case under investigation
• Expand on a theory by uncovering new concepts and ideas that need to be incorporated
• Challenge a theory by exploring an outlier case that doesn’t fit with established assumptions

To ensure that your analysis of the case has a solid academic grounding, you should conduct a literature review of sources related to the topic and develop a theoretical framework . This means identifying key concepts and theories to guide your analysis and interpretation.

There are many different research methods you can use to collect data on your subject. Case studies tend to focus on qualitative data using methods such as interviews , observations , and analysis of primary and secondary sources (e.g., newspaper articles, photographs, official records). Sometimes a case study will also collect quantitative data.

Example of a mixed methods case studyFor a case study of a wind farm development in a rural area, you could collect quantitative data on employment rates and business revenue, collect qualitative data on local people’s perceptions and experiences, and analyze local and national media coverage of the development.

The aim is to gain as thorough an understanding as possible of the case and its context.

In writing up the case study, you need to bring together all the relevant aspects to give as complete a picture as possible of the subject.

How you report your findings depends on the type of research you are doing. Some case studies are structured like a standard scientific paper or thesis , with separate sections or chapters for the methods , results and discussion .

Others are written in a more narrative style, aiming to explore the case from various angles and analyze its meanings and implications (for example, by using textual analysis or discourse analysis ).

In all cases, though, make sure to give contextual details about the case, connect it back to the literature and theory, and discuss how it fits into wider patterns or debates.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Ecological validity

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

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Business growth

Marketing tips

16 case study examples (+ 3 templates to make your own)

I like to think of case studies as a business's version of a resume. It highlights what the business can do, lends credibility to its offer, and contains only the positive bullet points that paint it in the best light possible.

Imagine if the guy running your favorite taco truck followed you home so that he could "really dig into how that burrito changed your life." I see the value in the practice. People naturally prefer a tried-and-true burrito just as they prefer tried-and-true products or services.

To help you showcase your success and flesh out your burrito questionnaire, I've put together some case study examples and key takeaways.

What is a case study?

A case study is an in-depth analysis of how your business, product, or service has helped past clients. It can be a document, a webpage, or a slide deck that showcases measurable, real-life results.

For example, if you're a SaaS company, you can analyze your customers' results after a few months of using your product to measure its effectiveness. You can then turn this analysis into a case study that further proves to potential customers what your product can do and how it can help them overcome their challenges.

It changes the narrative from "I promise that we can do X and Y for you" to "Here's what we've done for businesses like yours, and we can do it for you, too."

16 case study examples 

While most case studies follow the same structure, quite a few try to break the mold and create something unique. Some businesses lean heavily on design and presentation, while others pursue a detailed, stat-oriented approach. Some businesses try to mix both.

There's no set formula to follow, but I've found that the best case studies utilize impactful design to engage readers and leverage statistics and case details to drive the point home. A case study typically highlights the companies, the challenges, the solution, and the results. The examples below will help inspire you to do it, too.

1. .css-12hxxzz-Link{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-12hxxzz-Link[data-color='ocean']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='ocean']:hover{outline-color:var(--zds-text-link-hover, #2b2358);}.css-12hxxzz-Link[data-color='ocean']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='white']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='white']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='white']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='primary']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='primary']:hover{color:var(--zds-text-link, #2b2358);}.css-12hxxzz-Link[data-color='primary']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='secondary']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='secondary']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='secondary']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-weight='inherit']{font-weight:inherit;}.css-12hxxzz-Link[data-weight='normal']{font-weight:400;}.css-12hxxzz-Link[data-weight='bold']{font-weight:700;} Volcanica Coffee and AdRoll

People love a good farm-to-table coffee story, and boy am I one of them. But I've shared this case study with you for more reasons than my love of coffee. I enjoyed this study because it was written as though it was a letter.

In this case study, the founder of Volcanica Coffee talks about the journey from founding the company to personally struggling with learning and applying digital marketing to finding and enlisting AdRoll's services.

It felt more authentic, less about AdRoll showcasing their worth and more like a testimonial from a grateful and appreciative client. After the story, the case study wraps up with successes, milestones, and achievements. Note that quite a few percentages are prominently displayed at the top, providing supporting evidence that backs up an inspiring story.

Takeaway: Highlight your goals and measurable results to draw the reader in and provide concise, easily digestible information.

2. .css-12hxxzz-Link{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-12hxxzz-Link[data-color='ocean']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='ocean']:hover{outline-color:var(--zds-text-link-hover, #2b2358);}.css-12hxxzz-Link[data-color='ocean']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='white']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='white']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='white']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='primary']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='primary']:hover{color:var(--zds-text-link, #2b2358);}.css-12hxxzz-Link[data-color='primary']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='secondary']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='secondary']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='secondary']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-weight='inherit']{font-weight:inherit;}.css-12hxxzz-Link[data-weight='normal']{font-weight:400;}.css-12hxxzz-Link[data-weight='bold']{font-weight:700;} Taylor Guitars and Airtable

This Airtable case study on Taylor Guitars comes as close as one can to an optimal structure. It features a video that represents the artistic nature of the client, highlighting key achievements and dissecting each element of Airtable's influence.

It also supplements each section with a testimonial or quote from the client, using their insights as a catalyst for the case study's narrative. For example, the case study quotes the social media manager and project manager's insights regarding team-wide communication and access before explaining in greater detail.

Takeaway: Highlight pain points your business solves for its client, and explore that influence in greater detail.

3. .css-12hxxzz-Link{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-12hxxzz-Link[data-color='ocean']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='ocean']:hover{outline-color:var(--zds-text-link-hover, #2b2358);}.css-12hxxzz-Link[data-color='ocean']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='white']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='white']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='white']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='primary']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='primary']:hover{color:var(--zds-text-link, #2b2358);}.css-12hxxzz-Link[data-color='primary']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='secondary']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='secondary']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='secondary']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-weight='inherit']{font-weight:inherit;}.css-12hxxzz-Link[data-weight='normal']{font-weight:400;}.css-12hxxzz-Link[data-weight='bold']{font-weight:700;} EndeavourX and Figma

My favorite part of Figma's case study is highlighting why EndeavourX chose its solution. You'll notice an entire section on what Figma does for teams and then specifically for EndeavourX.

It also places a heavy emphasis on numbers and stats. The study, as brief as it is, still manages to pack in a lot of compelling statistics about what's possible with Figma.

Takeaway: Showcase the "how" and "why" of your product's differentiators and how they benefit your customers.

4. .css-12hxxzz-Link{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-12hxxzz-Link[data-color='ocean']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='ocean']:hover{outline-color:var(--zds-text-link-hover, #2b2358);}.css-12hxxzz-Link[data-color='ocean']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='white']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='white']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='white']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='primary']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='primary']:hover{color:var(--zds-text-link, #2b2358);}.css-12hxxzz-Link[data-color='primary']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='secondary']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='secondary']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='secondary']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-weight='inherit']{font-weight:inherit;}.css-12hxxzz-Link[data-weight='normal']{font-weight:400;}.css-12hxxzz-Link[data-weight='bold']{font-weight:700;} ActiveCampaign and Zapier

Zapier's case study leans heavily on design, using graphics to present statistics and goals in a manner that not only remains consistent with the branding but also actively pushes it forward, drawing users' eyes to the information most important to them. 

The graphics, emphasis on branding elements, and cause/effect style tell the story without requiring long, drawn-out copy that risks boring readers. Instead, the cause and effect are concisely portrayed alongside the client company's information for a brief and easily scannable case study.

Takeaway: Lean on design to call attention to the most important elements of your case study, and make sure it stays consistent with your branding.

5. .css-12hxxzz-Link{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-12hxxzz-Link[data-color='ocean']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='ocean']:hover{outline-color:var(--zds-text-link-hover, #2b2358);}.css-12hxxzz-Link[data-color='ocean']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='white']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='white']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='white']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='primary']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='primary']:hover{color:var(--zds-text-link, #2b2358);}.css-12hxxzz-Link[data-color='primary']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='secondary']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='secondary']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='secondary']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-weight='inherit']{font-weight:inherit;}.css-12hxxzz-Link[data-weight='normal']{font-weight:400;}.css-12hxxzz-Link[data-weight='bold']{font-weight:700;} Ironclad and OpenAI

In true OpenAI fashion, this case study is a block of text. There's a distinct lack of imagery, but the study features a narrated video walking readers through the product.

The lack of imagery and color may not be the most inviting, but utilizing video format is commendable. It helps thoroughly communicate how OpenAI supported Ironclad in a way that allows the user to sit back, relax, listen, and be impressed. 

Takeaway: Get creative with the media you implement in your case study. Videos can be a very powerful addition when a case study requires more detailed storytelling.

6. .css-12hxxzz-Link{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-12hxxzz-Link[data-color='ocean']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='ocean']:hover{outline-color:var(--zds-text-link-hover, #2b2358);}.css-12hxxzz-Link[data-color='ocean']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='white']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='white']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='white']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='primary']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='primary']:hover{color:var(--zds-text-link, #2b2358);}.css-12hxxzz-Link[data-color='primary']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='secondary']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='secondary']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='secondary']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-weight='inherit']{font-weight:inherit;}.css-12hxxzz-Link[data-weight='normal']{font-weight:400;}.css-12hxxzz-Link[data-weight='bold']{font-weight:700;} Shopify and GitHub

GitHub's case study on Shopify is a light read. It addresses client pain points and discusses the different aspects its product considers and improves for clients. It touches on workflow issues, internal systems, automation, and security. It does a great job of representing what one company can do with GitHub.

To drive the point home, the case study features colorful quote callouts from the Shopify team, sharing their insights and perspectives on the partnership, the key issues, and how they were addressed.

Takeaway: Leverage quotes to boost the authoritativeness and trustworthiness of your case study. 

7 . .css-12hxxzz-Link{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-12hxxzz-Link[data-color='ocean']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='ocean']:hover{outline-color:var(--zds-text-link-hover, #2b2358);}.css-12hxxzz-Link[data-color='ocean']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='white']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='white']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='white']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='primary']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='primary']:hover{color:var(--zds-text-link, #2b2358);}.css-12hxxzz-Link[data-color='primary']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='secondary']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='secondary']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='secondary']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-weight='inherit']{font-weight:inherit;}.css-12hxxzz-Link[data-weight='normal']{font-weight:400;}.css-12hxxzz-Link[data-weight='bold']{font-weight:700;} Audible and Contentful

Contentful's case study on Audible features almost every element a case study should. It includes not one but two videos and clearly outlines the challenge, solution, and outcome before diving deeper into what Contentful did for Audible. The language is simple, and the writing is heavy with quotes and personal insights.

This case study is a uniquely original experience. The fact that the companies in question are perhaps two of the most creative brands out there may be the reason. I expected nothing short of a detailed analysis, a compelling story, and video content. 

Takeaway: Inject some brand voice into the case study, and create assets that tell the story for you.

8 . .css-12hxxzz-Link{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-12hxxzz-Link[data-color='ocean']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='ocean']:hover{outline-color:var(--zds-text-link-hover, #2b2358);}.css-12hxxzz-Link[data-color='ocean']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='white']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='white']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='white']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='primary']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='primary']:hover{color:var(--zds-text-link, #2b2358);}.css-12hxxzz-Link[data-color='primary']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='secondary']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='secondary']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='secondary']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-weight='inherit']{font-weight:inherit;}.css-12hxxzz-Link[data-weight='normal']{font-weight:400;}.css-12hxxzz-Link[data-weight='bold']{font-weight:700;} Zoom and Asana

Asana's case study on Zoom is longer than the average piece and features detailed data on Zoom's growth since 2020. Instead of relying on imagery and graphics, it features several quotes and testimonials. 

It's designed to be direct, informative, and promotional. At some point, the case study reads more like a feature list. There were a few sections that felt a tad too promotional for my liking, but to each their own burrito.

Takeaway: Maintain a balance between promotional and informative. You want to showcase the high-level goals your product helped achieve without losing the reader.

9 . .css-12hxxzz-Link{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-12hxxzz-Link[data-color='ocean']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='ocean']:hover{outline-color:var(--zds-text-link-hover, #2b2358);}.css-12hxxzz-Link[data-color='ocean']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='white']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='white']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='white']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='primary']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='primary']:hover{color:var(--zds-text-link, #2b2358);}.css-12hxxzz-Link[data-color='primary']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='secondary']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='secondary']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='secondary']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-weight='inherit']{font-weight:inherit;}.css-12hxxzz-Link[data-weight='normal']{font-weight:400;}.css-12hxxzz-Link[data-weight='bold']{font-weight:700;} Hickies and Mailchimp

I've always been a fan of Mailchimp's comic-like branding, and this case study does an excellent job of sticking to their tradition of making information easy to understand, casual, and inviting.

It features a short video that briefly covers Hickies as a company and Mailchimp's efforts to serve its needs for customer relationships and education processes. Overall, this case study is a concise overview of the partnership that manages to convey success data and tell a story at the same time. What sets it apart is that it does so in a uniquely colorful and brand-consistent manner.

Takeaway: Be concise to provide as much value in as little text as possible.

10. .css-12hxxzz-Link{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-12hxxzz-Link[data-color='ocean']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='ocean']:hover{outline-color:var(--zds-text-link-hover, #2b2358);}.css-12hxxzz-Link[data-color='ocean']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='white']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='white']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='white']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='primary']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='primary']:hover{color:var(--zds-text-link, #2b2358);}.css-12hxxzz-Link[data-color='primary']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='secondary']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='secondary']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='secondary']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-weight='inherit']{font-weight:inherit;}.css-12hxxzz-Link[data-weight='normal']{font-weight:400;}.css-12hxxzz-Link[data-weight='bold']{font-weight:700;} NVIDIA and Workday

The gaming industry is notoriously difficult to recruit for, as it requires a very specific set of skills and experience. This case study focuses on how Workday was able to help fill that recruitment gap for NVIDIA, one of the biggest names in the gaming world.

Though it doesn't feature videos or graphics, this case study stood out to me in how it structures information like "key products used" to give readers insight into which tools helped achieve these results.

Takeaway: If your company offers multiple products or services, outline exactly which ones were involved in your case study, so readers can assess each tool.

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I'm personally not a big KFC fan, but that's only because I refuse to eat out of a bucket. My aversion to the bucket format aside, Contentful follows its consistent case study format in this one, outlining challenges, solutions, and outcomes before diving into the nitty-gritty details of the project.

Say what you will about KFC, but their primary product (chicken) does present a unique opportunity for wordplay like "Continuing to march to the beat of a digital-first drum(stick)" or "Delivering deep-fried goodness to every channel."

Takeaway: Inject humor into your case study if there's room for it and if it fits your brand. 

12. .css-12hxxzz-Link{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-12hxxzz-Link[data-color='ocean']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='ocean']:hover{outline-color:var(--zds-text-link-hover, #2b2358);}.css-12hxxzz-Link[data-color='ocean']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='white']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='white']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='white']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='primary']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='primary']:hover{color:var(--zds-text-link, #2b2358);}.css-12hxxzz-Link[data-color='primary']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='secondary']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='secondary']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='secondary']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-weight='inherit']{font-weight:inherit;}.css-12hxxzz-Link[data-weight='normal']{font-weight:400;}.css-12hxxzz-Link[data-weight='bold']{font-weight:700;} Intuit and Twilio

Twilio does an excellent job of delivering achievements at the very beginning of the case study and going into detail in this two-minute read. While there aren't many graphics, the way quotes from the Intuit team are implemented adds a certain flair to the study and breaks up the sections nicely.

It's simple, concise, and manages to fit a lot of information in easily digestible sections.

Takeaway: Make sure each section is long enough to inform but brief enough to avoid boring readers. Break down information for each section, and don't go into so much detail that you lose the reader halfway through.

13. .css-12hxxzz-Link{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-12hxxzz-Link[data-color='ocean']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='ocean']:hover{outline-color:var(--zds-text-link-hover, #2b2358);}.css-12hxxzz-Link[data-color='ocean']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='white']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='white']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='white']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='primary']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='primary']:hover{color:var(--zds-text-link, #2b2358);}.css-12hxxzz-Link[data-color='primary']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='secondary']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='secondary']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='secondary']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-weight='inherit']{font-weight:inherit;}.css-12hxxzz-Link[data-weight='normal']{font-weight:400;}.css-12hxxzz-Link[data-weight='bold']{font-weight:700;} Spotify and Salesforce

Salesforce created a video that accurately summarizes the key points of the case study. Beyond that, the page itself is very light on content, and sections are as short as one paragraph.

I especially like how information is broken down into "What you need to know," "Why it matters," and "What the difference looks like." I'm not ashamed of being spoon-fed information. When it's structured so well and so simply, it makes for an entertaining read.

14. .css-12hxxzz-Link{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-12hxxzz-Link[data-color='ocean']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='ocean']:hover{outline-color:var(--zds-text-link-hover, #2b2358);}.css-12hxxzz-Link[data-color='ocean']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='white']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='white']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='white']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='primary']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='primary']:hover{color:var(--zds-text-link, #2b2358);}.css-12hxxzz-Link[data-color='primary']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='secondary']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='secondary']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='secondary']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-weight='inherit']{font-weight:inherit;}.css-12hxxzz-Link[data-weight='normal']{font-weight:400;}.css-12hxxzz-Link[data-weight='bold']{font-weight:700;} Benchling and Airtable

Benchling is an impressive entity in its own right. Biotech R&D and health care nuances go right over my head. But the research and digging I've been doing in the name of these burritos (case studies) revealed that these products are immensely complex. 

And that's precisely why this case study deserves a read—it succeeds at explaining a complex project that readers outside the industry wouldn't know much about.

Takeaway: Simplify complex information, and walk readers through the company's operations and how your business helped streamline them.

15. .css-12hxxzz-Link{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-12hxxzz-Link[data-color='ocean']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='ocean']:hover{outline-color:var(--zds-text-link-hover, #2b2358);}.css-12hxxzz-Link[data-color='ocean']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='white']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='white']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='white']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='primary']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='primary']:hover{color:var(--zds-text-link, #2b2358);}.css-12hxxzz-Link[data-color='primary']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='secondary']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='secondary']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='secondary']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-weight='inherit']{font-weight:inherit;}.css-12hxxzz-Link[data-weight='normal']{font-weight:400;}.css-12hxxzz-Link[data-weight='bold']{font-weight:700;} Chipotle and Hubble

The concision of this case study is refreshing. It features two sections—the challenge and the solution—all in 316 words. This goes to show that your case study doesn't necessarily need to be a four-figure investment with video shoots and studio time. 

Sometimes, the message is simple and short enough to convey in a handful of paragraphs.

Takeaway: Consider what you should include instead of what you can include. Assess the time, resources, and effort you're able and willing to invest in a case study, and choose which elements you want to include from there.

16. .css-12hxxzz-Link{all:unset;box-sizing:border-box;-webkit-text-decoration:underline;text-decoration:underline;cursor:pointer;-webkit-transition:all 300ms ease-in-out;transition:all 300ms ease-in-out;outline-offset:1px;-webkit-text-fill-color:currentColor;outline:1px solid transparent;}.css-12hxxzz-Link[data-color='ocean']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='ocean']:hover{outline-color:var(--zds-text-link-hover, #2b2358);}.css-12hxxzz-Link[data-color='ocean']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='white']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='white']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='white']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='primary']{color:var(--zds-text-link, #3d4592);}.css-12hxxzz-Link[data-color='primary']:hover{color:var(--zds-text-link, #2b2358);}.css-12hxxzz-Link[data-color='primary']:focus{color:var(--zds-text-link-hover, #3d4592);outline-color:var(--zds-text-link-hover, #3d4592);}.css-12hxxzz-Link[data-color='secondary']{color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-color='secondary']:hover{color:var(--zds-gray-warm-5, #a8a5a0);}.css-12hxxzz-Link[data-color='secondary']:focus{color:var(--zds-gray-warm-1, #fffdf9);outline-color:var(--zds-gray-warm-1, #fffdf9);}.css-12hxxzz-Link[data-weight='inherit']{font-weight:inherit;}.css-12hxxzz-Link[data-weight='normal']{font-weight:400;}.css-12hxxzz-Link[data-weight='bold']{font-weight:700;} Hudl and Zapier

I may be biased, but I'm a big fan of seeing metrics and achievements represented in branded graphics. It can be a jarring experience to navigate a website, then visit a case study page and feel as though you've gone to a completely different website.

The case study is essentially the summary, and the blog article is the detailed analysis that provides context beyond X achievement or Y goal.

Takeaway: Keep your case study concise and informative. Create other resources to provide context under your blog, media or press, and product pages.

3 case study templates

Now that you've had your fill of case studies (if that's possible), I've got just what you need: an infinite number of case studies, which you can create yourself with these case study templates.

Case study template 1

If you've got a quick hit of stats you want to show off, try this template. The opening section gives space for a short summary and three visually appealing stats you can highlight, followed by a headline and body where you can break the case study down more thoroughly. This one's pretty simple, with only sections for solutions and results, but you can easily continue the formatting to add more sections as needed.

Case study template 2

For a case study template with a little more detail, use this one. Opening with a striking cover page for a quick overview, this one goes on to include context, stakeholders, challenges, multiple quote callouts, and quick-hit stats. 

Case study template 3

Whether you want a little structural variation or just like a nice dark green, this template has similar components to the last template but is designed to help tell a story. Move from the client overview through a description of your company before getting to the details of how you fixed said company's problems.

Tips for writing a case study

Examples are all well and good, but you don't learn how to make a burrito just by watching tutorials on YouTube without knowing what any of the ingredients are. You could , but it probably wouldn't be all that good.

Have an objective: Define your objective by identifying the challenge, solution, and results. Assess your work with the client and focus on the most prominent wins. You're speaking to multiple businesses and industries through the case study, so make sure you know what you want to say to them.

Focus on persuasive data: Growth percentages and measurable results are your best friends. Extract your most compelling data and highlight it in your case study.

Use eye-grabbing graphics: Branded design goes a long way in accurately representing your brand and retaining readers as they review the study. Leverage unique and eye-catching graphics to keep readers engaged. 

Simplify data presentation: Some industries are more complex than others, and sometimes, data can be difficult to understand at a glance. Make sure you present your data in the simplest way possible. Make it concise, informative, and easy to understand.

Use automation to drive results for your case study

A case study example is a source of inspiration you can leverage to determine how to best position your brand's work. Find your unique angle, and refine it over time to help your business stand out. Ask anyone: the best burrito in town doesn't just appear at the number one spot. They find their angle (usually the house sauce) and leverage it to stand out.

Case study FAQ

Got your case study template? Great—it's time to gather the team for an awkward semi-vague data collection task. While you do that, here are some case study quick answers for you to skim through while you contemplate what to call your team meeting.

What is an example of a case study?

An example of a case study is when a software company analyzes its results from a client project and creates a webpage, presentation, or document that focuses on high-level results, challenges, and solutions in an attempt to showcase effectiveness and promote the software.

How do you write a case study?

To write a good case study, you should have an objective, identify persuasive and compelling data, leverage graphics, and simplify data. Case studies typically include an analysis of the challenge, solution, and results of the partnership.

What is the format of a case study?

While case studies don't have a set format, they're often portrayed as reports or essays that inform readers about the partnership and its results. 

Related reading:

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Hachem Ramki

Hachem is a writer and digital marketer from Montreal. After graduating with a degree in English, Hachem spent seven years traveling around the world before moving to Canada. When he's not writing, he enjoys Basketball, Dungeons and Dragons, and playing music for friends and family.

• Content marketing

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28 Case Study Examples Every Marketer Should See

Published: March 08, 2023

Putting together a compelling case study is one of the most powerful strategies for showcasing your product and attracting future customers. But it's not easy to create case studies that your audience can’t wait to read.

In this post, we’ll go over the definition of a case study and the best examples to inspire you.

What is a case study?

A case study is a detailed story of something your company did. It includes a beginning — often discussing a conflict, an explanation of what happened next, and a resolution that explains how the company solved or improved on something.

A case study proves how your product has helped other companies by demonstrating real-life results. Not only that, but marketing case studies with solutions typically contain quotes from the customer. This means that they’re not just ads where you praise your own product. Rather, other companies are praising your company — and there’s no stronger marketing material than a verbal recommendation or testimonial. A great case study is also filled with research and stats to back up points made about a project's results.

There are myriad ways to use case studies in your marketing strategy . From featuring them on your website to including them in a sales presentation, a case study is a strong, persuasive tool that shows customers why they should work with you — straight from another customer. Writing one from scratch is hard, though, which is why we’ve created a collection of case study templates for you to get started.

Fill out the form below to access the free case study templates.

Free Case Study Templates

Showcase your company's success using these three free case study templates.

• Data-Driven Case Study Template
• Product-Specific Case Study Template
• General Case Study Template

Download Free

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Click this link to access this resource at any time.

There’s no better way to generate more leads than by writing case studies . But without case study examples to draw inspiration from, it can be difficult to write impactful studies that convince visitors to submit a form.

Marketing Case Study Examples

To help you create an attractive and high-converting case study, we've put together a list of some of our favorites. This list includes famous case studies in marketing, technology, and business.

These studies can show you how to frame your company offers in a way that is both meaningful and useful to your audience. So, take a look, and let these examples inspire your next brilliant case study design.

These marketing case studies with solutions show the value proposition of each product. They also show how each company benefited in both the short and long term using quantitative data. In other words, you don’t get just nice statements, like "This company helped us a lot." You see actual change within the firm through numbers and figures.

You can put your learnings into action with HubSpot's Free Case Study Templates . Available as custom designs and text-based documents, you can upload these templates to your CMS or send them to prospects as you see fit.

1. " How Handled Scaled from Zero to 121 Locations with the Help of HubSpot ," by HubSpot

What's interesting about this case study is the way it leads with the customer. That reflects a major HubSpot cornerstone, which is to always solve for the customer first. The copy leads with a brief description of why the CEO of Handled founded the company and why he thought Handled could benefit from adopting a CRM. The case study also opens up with one key data point about Handled’s success using HubSpot, namely that it grew to 121 locations.

Notice that this case study uses mixed media. Yes, there is a short video, but it's elaborated upon in the other text on the page. So while your case studies can use one or the other, don't be afraid to combine written copy with visuals to emphasize the project's success.

Key Learnings from the HubSpot Case Study Example

• Give the case study a personal touch by focusing on the CEO rather than the company itself.
• Use multimedia to engage website visitors as they read the case study.

2. " The Whole Package ," by IDEO

Here's a design company that knows how to lead with simplicity in its case studies. As soon as the visitor arrives at the page, they’re greeted with a big, bold photo and the title of the case study — which just so happens to summarize how IDEO helped its client. It summarizes the case study in three snippets: The challenge, the impact, and the outcome.

Immediately, IDEO communicates its impact — the company partnered with H&M to remove plastic from its packaging — but it doesn't stop there. As the user scrolls down, the challenge, impact, and progress are elaborated upon with comprehensive (but not overwhelming) copy that outlines what that process looked like, replete with quotes and intriguing visuals.

Key Learnings from the IDEO Case Study Example

• Split up the takeaways of your case studies into bite-sized sections.
• Always use visuals and images to enrich the case study experience, especially if it’s a comprehensive case study.

3. " Rozum Robotics intensifies its PR game with Awario ," by Awario

In this case study, Awario greets the user with a summary straight away — so if you’re feeling up to reading the entire case study, you can scan the snapshot and understand how the company serves its customers. The case study then includes jump links to several sections, such as "Company Profile," "Rozum Robotics' Pains," "Challenge," "Solution," and "Results and Improvements."

The sparse copy and prominent headings show that you don’t need a lot of elaborate information to show the value of your products and services. Like the other case study examples on this list, it includes visuals and quotes to demonstrate the effectiveness of the company’s efforts. The case study ends with a bulleted list that shows the results.

Key Learnings from the Awario Robotics Case Study Example

• Create a table of contents to make your case study easier to navigate.
• Include a bulleted list of the results you achieved for your client.

4. " Chevrolet DTU ," by Carol H. Williams

If you’ve worked with a company that’s well-known, use only the name in the title — like Carol H. Williams, one of the nation’s top advertising agencies, does here. The "DTU," stands for "Discover the Unexpected." It generates interest because you want to find out what the initials mean.

They keep your interest in this case study by using a mixture of headings, images, and videos to describe the challenges, objectives, and solutions of the project. The case study closes with a summary of the key achievements that Chevrolet’s DTU Journalism Fellows reached during the project.

Key Learnings from the Carol H. Williams Case Study Example

• If you’ve worked with a big brand before, consider only using the name in the title — just enough to pique interest.
• Use a mixture of headings and subheadings to guide users through the case study.

5. " How Fractl Earned Links from 931 Unique Domains for Porch.com in a Single Year ," by Fractl

Fractl uses both text and graphic design in their Porch.com case study to immerse the viewer in a more interesting user experience. For instance, as you scroll, you'll see the results are illustrated in an infographic-design form as well as the text itself.

Further down the page, they use icons like a heart and a circle to illustrate their pitch angles, and graphs to showcase their results. Rather than writing which publications have mentioned Porch.com during Fractl’s campaign, they incorporated the media outlets’ icons for further visual diversity.

Key Learnings from the Fractl Case Study Example

• Let pictures speak for you by incorporating graphs, logos, and icons all throughout the case study.
• Start the case study by right away stating the key results, like Fractl does, instead of putting the results all the way at the bottom.

6. " The Met ," by Fantasy

What's the best way to showcase the responsiveness and user interface of a website? Probably by diving right into it with a series of simple showcases— which is exactly what Fantasy does on their case study page for the Metropolitan Museum of Art. They keep the page simple and clean, inviting you to review their redesign of the Met’s website feature-by-feature.

Each section is simple, showing a single piece of the new website's interface so that users aren’t overwhelmed with information and can focus on what matters most.

If you're more interested in text, you can read the objective for each feature. Fantasy understands that, as a potential customer, this is all you need to know. Scrolling further, you're greeted with a simple "Contact Us" CTA.

Key Learnings from the Fantasy Case Study Example

• You don’t have to write a ton of text to create a great case study. Focus on the solution you delivered itself.
• Include a CTA at the bottom inviting visitors to contact you.

7. " Rovio: How Rovio Grew Into a Gaming Superpower ," by App Annie

If your client had a lot of positive things to say about you, take a note from App Annie’s Rovio case study and open up with a quote from your client. The case study also closes with a quote, so that the case study doesn’t seem like a promotion written by your marketing team but a story that’s taken straight from your client’s mouth. It includes a photo of a Rovio employee, too.

Another thing this example does well? It immediately includes a link to the product that Rovio used (namely, App Annie Intelligence) at the top of the case study. The case study closes with a call-to-action button prompting users to book a demo.

Key Learnings from the App Annie Case Study Example

• Feature quotes from your client at the beginning and end of the case study.
• Include a mention of the product right at the beginning and prompt users to learn more about the product.

8. " Embracing first-party data: 3 success stories from HubSpot ," by Think with Google

Google takes a different approach to text-focused case studies by choosing three different companies to highlight.

The case study is clean and easily scannable. It has sections for each company, with quotes and headers that clarify the way these three distinct stories connect. The simple format also uses colors and text that align with the Google brand.

Another differentiator is the focus on data. This case study is less than a thousand words, but it's packed with useful data points. Data-driven insights quickly and clearly show how the value of leveraging first-party data while prioritizing consumer privacy.

Key Learnings from the Think with Google Case Study Example

• A case study doesn’t need to be long or complex to be powerful.
• Clear data points are a quick and effective way to prove value.

9. " In-Depth Performance Marketing Case Study ," by Switch

Switch is an international marketing agency based in Malta that knocks it out of the park with this case study. Its biggest challenge is effectively communicating what it did for its client without ever revealing the client’s name. It also effectively keeps non-marketers in the loop by including a glossary of terms on page 4.

The PDF case study reads like a compelling research article, including titles like "In-Depth Performance Marketing Case Study," "Scenario," and "Approach," so that readers get a high-level overview of what the client needed and why they approached Switch. It also includes a different page for each strategy. For instance, if you’d only be interested in hiring Switch for optimizing your Facebook ads, you can skip to page 10 to see how they did it.

The PDF is fourteen pages long but features big fonts and plenty of white space, so viewers can easily skim it in only a few minutes.

Key Learnings from the Switch Case Study Example

• If you want to go into specialized information, include a glossary of terms so that non-specialists can easily understand.
• Close with a CTA page in your case study PDF and include contact information for prospective clients.

10. " Gila River ," by OH Partners

Let pictures speak for you, like OH Partners did in this case study. While you’ll quickly come across a heading and some text when you land on this case study page, you’ll get the bulk of the case study through examples of actual work OH Partners did for its client. You will see OH Partners’ work in a billboard, magazine, and video. This communicates to website visitors that if they work with OH Partners, their business will be visible everywhere.

And like the other case studies here, it closes with a summary of what the firm achieved for its client in an eye-catching way.

Key Learnings from the OH Partners Case Study Example

• Let the visuals speak by including examples of the actual work you did for your client — which is especially useful for branding and marketing agencies.
• Always close out with your achievements and how they impacted your client.

11. " Facing a Hater ," by Digitas

Digitas' case study page for Sprite’s #ILOVEYOUHATER campaign keeps it brief while communicating the key facts of Digitas’ work for the popular soda brand. The page opens with an impactful image of a hundred people facing a single man. It turns out, that man is the biggest "bully" in Argentina, and the people facing him are those whom he’s bullied before.

Scrolling down, it's obvious that Digitas kept Sprite at the forefront of their strategy, but more than that, they used real people as their focal point. They leveraged the Twitter API to pull data from Tweets that people had actually tweeted to find the identity of the biggest "hater" in the country. That turned out to be @AguanteElCofler, a Twitter user who has since been suspended.

Key Learnings from the Digitas Case Study Example

• If a video was part of your work for your client, be sure to include the most impactful screenshot as the heading.
• Don’t be afraid to provide details on how you helped your client achieve their goals, including the tools you leveraged.

12. " Better Experiences for All ," by HermanMiller

HermanMiller sells sleek, utilitarian furniture with no frills and extreme functionality, and that ethos extends to its case study page for a hospital in Dubai.

What first attracted me to this case study was the beautiful video at the top and the clean user experience. User experience matters a lot in a case study. It determines whether users will keep reading or leave. Another notable aspect of this case study is that the video includes closed-captioning for greater accessibility, and users have the option of expanding the CC and searching through the text.

HermanMiller’s case study also offers an impressive amount of information packed in just a few short paragraphs for those wanting to understand the nuances of their strategy. It closes out with a quote from their client and, most importantly, the list of furniture products that the hospital purchased from the brand.

Key Learnings from the HermanMiller Case Study Example

• Close out with a list of products that users can buy after reading the case study.
• Include accessibility features such as closed captioning and night mode to make your case study more user-friendly.

13. " Capital One on AWS ," by Amazon

Do you work continuously with your clients? Consider structuring your case study page like Amazon did in this stellar case study example. Instead of just featuring one article about Capital One and how it benefited from using AWS, Amazon features a series of articles that you can then access if you’re interested in reading more. It goes all the way back to 2016, all with different stories that feature Capital One’s achievements using AWS.

This may look unattainable for a small firm, but you don’t have to go to extreme measures and do it for every single one of your clients. You could choose the one you most wish to focus on and establish a contact both on your side and your client’s for coming up with the content. Check in every year and write a new piece. These don’t have to be long, either — five hundred to eight hundred words will do.

Key Learnings from the Amazon AWS Case Study Example

• Write a new article each year featuring one of your clients, then include links to those articles in one big case study page.
• Consider including external articles as well that emphasize your client’s success in their industry.

14. " HackReactor teaches the world to code #withAsana ," by Asana

While Asana's case study design looks text-heavy, there's a good reason. It reads like a creative story, told entirely from the customer's perspective.

For instance, Asana knows you won't trust its word alone on why this product is useful. So, they let Tony Phillips, HackReactor CEO, tell you instead: "We take in a lot of information. Our brains are awful at storage but very good at thinking; you really start to want some third party to store your information so you can do something with it."

Asana features frequent quotes from Phillips to break up the wall of text and humanize the case study. It reads like an in-depth interview and captivates the reader through creative storytelling. Even more, Asana includes in-depth detail about how HackReactor uses Asana. This includes how they build templates and workflows:

"There's a huge differentiator between Asana and other tools, and that’s the very easy API access. Even if Asana isn’t the perfect fit for a workflow, someone like me— a relatively mediocre software engineer—can add functionality via the API to build a custom solution that helps a team get more done."

Key Learnings from the Asana Example

• Include quotes from your client throughout the case study.
• Provide extensive detail on how your client worked with you or used your product.

15. " Rips Sewed, Brand Love Reaped ," by Amp Agency

Amp Agency's Patagonia marketing strategy aimed to appeal to a new audience through guerrilla marketing efforts and a coast-to-coast road trip. Their case study page effectively conveys a voyager theme, complete with real photos of Patagonia customers from across the U.S., and a map of the expedition. I liked Amp Agency's storytelling approach best. It captures viewers' attention from start to finish simply because it's an intriguing and unique approach to marketing.

Key Learnings from the Amp Agency Example

• Open up with a summary that communicates who your client is and why they reached out to you.
• Like in the other case study examples, you’ll want to close out with a quantitative list of your achievements.

16. " NetApp ," by Evisort

Evisort opens up its NetApp case study with an at-a-glance overview of the client. It’s imperative to always focus on the client in your case study — not on your amazing product and equally amazing team. By opening up with a snapshot of the client’s company, Evisort places the focus on the client.

This case study example checks all the boxes for a great case study that’s informative, thorough, and compelling. It includes quotes from the client and details about the challenges NetApp faced during the COVID pandemic. It closes out with a quote from the client and with a link to download the case study in PDF format, which is incredibly important if you want your case study to be accessible in a wider variety of formats.

Key Learnings from the Evisort Example

• Place the focus immediately on your client by including a snapshot of their company.
• Mention challenging eras, such as a pandemic or recession, to show how your company can help your client succeed even during difficult times.

17. " Copernicus Land Monitoring – CLC+ Core ," by Cloudflight

Including highly specialized information in your case study is an effective way to show prospects that you’re not just trying to get their business. You’re deep within their industry, too, and willing to learn everything you need to learn to create a solution that works specifically for them.

Cloudflight does a splendid job at that in its Copernicus Land Monitoring case study. While the information may be difficult to read at first glance, it will capture the interest of prospects who are in the environmental industry. It thus shows Cloudflight’s value as a partner much more effectively than a general case study would.

The page is comprehensive and ends with a compelling call-to-action — "Looking for a solution that automates, and enhances your Big Data system? Are you struggling with large datasets and accessibility? We would be happy to advise and support you!" The clean, whitespace-heavy page is an effective example of using a case study to capture future leads.

Key Learnings from the Cloudflight Case Study Example

• Don’t be afraid to get technical in your explanation of what you did for your client.
• Include a snapshot of the sales representative prospects should contact, especially if you have different sales reps for different industries, like Cloudflight does.

18. " Valvoline Increases Coupon Send Rate by 76% with Textel’s MMS Picture Texting ," by Textel

If you’re targeting large enterprises with a long purchasing cycle, you’ll want to include a wealth of information in an easily transferable format. That’s what Textel does here in its PDF case study for Valvoline. It greets the user with an eye-catching headline that shows the value of using Textel. Valvoline saw a significant return on investment from using the platform.

Another smart decision in this case study is highlighting the client’s quote by putting it in green font and doing the same thing for the client’s results because it helps the reader quickly connect the two pieces of information. If you’re in a hurry, you can also take a look at the "At a Glance" column to get the key facts of the case study, starting with information about Valvoline.

Key Learnings from the Textel Case Study Example

• Include your client’s ROI right in the title of the case study.
• Add an "At a Glance" column to your case study PDF to make it easy to get insights without needing to read all the text.

19. " Hunt Club and Happeo — a tech-enabled love story ," by Happeo

In this blog-post-like case study, Happeo opens with a quote from the client, then dives into a compelling heading: "Technology at the forefront of Hunt Club's strategy." Say you’re investigating Happeo as a solution and consider your firm to be technology-driven. This approach would spark your curiosity about why the client chose to work with Happeo. It also effectively communicates the software’s value proposition without sounding like it’s coming from an in-house marketing team.

Every paragraph is a quote written from the customer’s perspective. Later down the page, the case study also dives into "the features that changed the game for Hunt Club," giving Happeo a chance to highlight some of the platform’s most salient features.

Key Learnings from the Happeo Case Study Example

• Consider writing the entirety of the case study from the perspective of the customer.
• Include a list of the features that convinced your client to go with you.

20. " Red Sox Season Campaign ," by CTP Boston

What's great about CTP's case study page for their Red Sox Season Campaign is their combination of video, images, and text. A video automatically begins playing when you visit the page, and as you scroll, you'll see more embedded videos of Red Sox players, a compilation of print ads, and social media images you can click to enlarge.

At the bottom, it says "Find out how we can do something similar for your brand." The page is clean, cohesive, and aesthetically pleasing. It invites viewers to appreciate the well-roundedness of CTP's campaign for Boston's beloved baseball team.

Key Learnings from the CTP Case Study Example

• Include a video in the heading of the case study.
• Close with a call-to-action that makes leads want to turn into prospects.

21. " Acoustic ," by Genuine

Sometimes, simple is key. Genuine's case study for Acoustic is straightforward and minimal, with just a few short paragraphs, including "Reimagining the B2B website experience," "Speaking to marketers 1:1," and "Inventing Together." After the core of the case study, we then see a quote from Acoustic’s CMO and the results Genuine achieved for the company.

The simplicity of the page allows the reader to focus on both the visual aspects and the copy. The page displays Genuine's brand personality while offering the viewer all the necessary information they need.

• You don’t need to write a lot to create a great case study. Keep it simple.
• Always include quantifiable data to illustrate the results you achieved for your client.

22. " Using Apptio Targetprocess Automated Rules in Wargaming ," by Apptio

Apptio’s case study for Wargaming summarizes three key pieces of information right at the beginning: The goals, the obstacles, and the results.

Readers then have the opportunity to continue reading — or they can walk away right then with the information they need. This case study also excels in keeping the human interest factor by formatting the information like an interview.

The piece is well-organized and uses compelling headers to keep the reader engaged. Despite its length, Apptio's case study is appealing enough to keep the viewer's attention. Every Apptio case study ends with a "recommendation for other companies" section, where the client can give advice for other companies that are looking for a similar solution but aren’t sure how to get started.

Key Learnings from the Apptio Case Study Example

• Put your client in an advisory role by giving them the opportunity to give recommendations to other companies that are reading the case study.
• Include the takeaways from the case study right at the beginning so prospects quickly get what they need.

23. " Airbnb + Zendesk: building a powerful solution together ," by Zendesk

Zendesk's Airbnb case study reads like a blog post, and focuses equally on Zendesk and Airbnb, highlighting a true partnership between the companies. To captivate readers, it begins like this: "Halfway around the globe is a place to stay with your name on it. At least for a weekend."

The piece focuses on telling a good story and provides photographs of beautiful Airbnb locations. In a case study meant to highlight Zendesk's helpfulness, nothing could be more authentic than their decision to focus on Airbnb's service in such great detail.

Key Learnings from the Zendesk Case Study Example

• Include images of your client’s offerings — not necessarily of the service or product you provided. Notice how Zendesk doesn’t include screenshots of its product.
• Include a call-to-action right at the beginning of the case study. Zendesk gives you two options: to find a solution or start a trial.

24. " Biobot Customer Success Story: Rollins College, Winter Park, Florida ," by Biobot

Like some of the other top examples in this list, Biobot opens its case study with a quote from its client, which captures the value proposition of working with Biobot. It mentions the COVID pandemic and goes into detail about the challenges the client faced during this time.

This case study is structured more like a news article than a traditional case study. This format can work in more formal industries where decision-makers need to see in-depth information about the case. Be sure to test different methods and measure engagement .

Key Learnings from the Biobot Case Study Example

• Mention environmental, public health, or economic emergencies and how you helped your client get past such difficult times.
• Feel free to write the case study like a normal blog post, but be sure to test different methods to find the one that best works for you.

25. " Discovering Cost Savings With Efficient Decision Making ," by Gartner

You don't always need a ton of text or a video to convey your message — sometimes, you just need a few paragraphs and bullet points. Gartner does a fantastic job of quickly providing the fundamental statistics a potential customer would need to know, without boggling down their readers with dense paragraphs. The case study closes with a shaded box that summarizes the impact that Gartner had on its client. It includes a quote and a call-to-action to "Learn More."

Key Learnings from the Gartner Case Study Example

• Feel free to keep the case study short.
• Include a call-to-action at the bottom that takes the reader to a page that most relates to them.

26. " Bringing an Operator to the Game ," by Redapt

This case study example by Redapt is another great demonstration of the power of summarizing your case study’s takeaways right at the start of the study. Redapt includes three easy-to-scan columns: "The problem," "the solution," and "the outcome." But its most notable feature is a section titled "Moment of clarity," which shows why this particular project was difficult or challenging.

The section is shaded in green, making it impossible to miss. Redapt does the same thing for each case study. In the same way, you should highlight the "turning point" for both you and your client when you were working toward a solution.

Key Learnings from the Redapt Case Study Example

• Highlight the turning point for both you and your client during the solution-seeking process.
• Use the same structure (including the same headings) for your case studies to make them easy to scan and read.

27. " Virtual Call Center Sees 300% Boost In Contact Rate ," by Convoso

Convoso’s PDF case study for Digital Market Media immediately mentions the results that the client achieved and takes advantage of white space. On the second page, the case study presents more influential results. It’s colorful and engaging and closes with a spread that prompts readers to request a demo.

Key Learnings from the Convoso Case Study Example

• List the results of your work right at the beginning of the case study.
• Use color to differentiate your case study from others. Convoso’s example is one of the most colorful ones on this list.

28. " Ensuring quality of service during a pandemic ," by Ericsson

Ericsson’s case study page for Orange Spain is an excellent example of using diverse written and visual media — such as videos, graphs, and quotes — to showcase the success a client experienced. Throughout the case study, Ericsson provides links to product and service pages users might find relevant as they’re reading the study.

For instance, under the heading "Preloaded with the power of automation," Ericsson mentions its Ericsson Operations Engine product, then links to that product page. It closes the case study with a link to another product page.

Key Learnings from the Ericsson Case Study Example

• Link to product pages throughout the case study so that readers can learn more about the solution you offer.
• Use multimedia to engage users as they read the case study.

Start creating your case study.

Now that you've got a great list of examples of case studies, think about a topic you'd like to write about that highlights your company or work you did with a customer.

A customer’s success story is the most persuasive marketing material you could ever create. With a strong portfolio of case studies, you can ensure prospects know why they should give you their business.

Editor's note: This post was originally published in August 2018 and has been updated for comprehensiveness.

Don't forget to share this post!

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What Is a Case Study and Why You Should Use Them

Case studies can provide more insights into your business while helping you conduct further research with robust qualitative data analysis to learn more.

If you're in charge of running a company, then you're likely always looking for new ways to run your business more efficiently and increase your customer base while streamlining as many processes as possible.

Unfortunately, it can sometimes be difficult to determine how to go about implementing the proper program in order to be successful. This is why many business owners opt to conduct a case study, which can help significantly. Whether you've been struggling with brand consistency or some other problem, the right case study can identify why your problem exists as well as provide a way to rectify it.

A case study is a great tool that many businesses aren't even aware exists, and there are marketing experts like Mailchimp who can provide you with step-by-step assistance with implementing a plan with a case study. Many companies discover that not only do they need to start a blog in order to improve business, but they also need to create specific and relevant blog titles.

If your company already has a blog, then optimizing your blog posts may be helpful. Regardless of the obstacles that are preventing you from achieving all your professional goals, a case study can work wonders in helping you reverse this issue.

What is a case study?

A case study is a comprehensive report of the results of theory testing or examining emerging themes of a business in real life context. Case studies are also often used in the healthcare industry, conducting health services research with primary research interest around routinely collected healthcare data.

However, for businesses, the purpose of a case study is to help small business owners or company leaders identify the issues and conduct further research into what may be preventing success through information collection, client or customer interviews, and in-depth data analysis.

Knowing the case study definition is crucial for any business owner. By identifying the issues that are hindering a company from achieving all its goals, it's easier to make the necessary corrections to promote success through influenced data collection.

Why are case studies important?

Now that we've answered the questions, "what is a case study?" Why are case studies important? Some of the top reasons why case studies are important include:

• Understand complex issues: Even after you conduct a significant amount of market research , you might have a difficult time understanding exactly what it means. While you might have the basics down, conducting a case study can help you see how that information is applied. Then, when you see how the information can make a difference in business decisions, it could make it easier to understand complex issues.
• Collect data: A case study can also help with data tracking . A case study is a data collection method that can help you describe the information that you have available to you. Then, you can present that information in a way the reader can understand.
• Conduct evaluations: As you learn more about how to write a case study, remember that you can also use a case study to conduct evaluations of a specific situation. A case study is a great way to learn more about complex situations, and you can evaluate how various people responded in that situation. By conducting a case study evaluation, you can learn more about what has worked well, what has not, and what you might want to change in the future.
• Identify potential solutions: A case study can also help you identify solutions to potential problems. If you have an issue in your business that you are trying to solve, you may be able to take a look at a case study where someone has dealt with a similar situation in the past. For example, you may uncover data bias in a specific solution that you would like to address when you tackle the issue on your own. If you need help solving a difficult problem, a case study may be able to help you.

Remember that you can also use case studies to target your audience . If you want to show your audience that you have a significant level of expertise in a field, you may want to publish some case studies that you have handled in the past. Then, when your audience sees that you have had success in a specific area, they may be more likely to provide you with their business. In essence, case studies can be looked at as the original method of social proof, showcasing exactly how you can help someone solve their problems.

What are the benefits of writing a business case study?

Although writing a case study can seem like a tedious task, there are many benefits to conducting one through an in depth qualitative research process.

• Industry understanding: First of all, a case study can give you an in-depth understanding of your industry through a particular conceptual framework and help you identify hidden problems that are preventing you from transcending into the business world.
• Develop theories: If you decide to write a business case study, it provides you with an opportunity to develop new theories. You might have a theory about how to solve a specific problem, but you need to write a business case study to see exactly how that theory has unfolded in the past. Then, you can figure out if you want to apply your theory to a similar issue in the future.
• Evaluate interventions: When you write a business case study that focuses on a specific situation you have been through in the past, you can uncover whether that intervention was truly helpful. This can make it easier to figure out whether you want to use the same intervention in a similar situation in the future.
• Identify best practices: If you want to stay on top of the best practices in your field, conducting case studies can help by allowing you to identify patterns and trends and develop a new list of best practices that you can follow in the future.
• Versatility: Writing a case study also provides you with more versatility. If you want to expand your business applications, you need to figure out how you respond to various problems. When you run a business case study, you open the door to new opportunities, new applications, and new techniques that could help you make a difference in your business down the road.
• Solve problems: Writing a great case study can dramatically improve your chances of reversing your problem and improving your business.
• These are just a few of the biggest benefits you might experience if you decide to publish your case studies. They can be an effective tool for learning, showcasing your talents, and teaching some of your other employees. If you want to grow your audience , you may want to consider publishing some case studies.

What are the limitations of case studies?

Case studies can be a wonderful tool for any business of any size to use to gain an in-depth understanding of their clients, products, customers, or services, but there are limitations.

One limitation of case studies is the fact that, unless there are other recently published examples, there is nothing to compare them to since, most of the time, you are conducting a single, not multiple, case studies.

Another limitation is the fact that most case studies can lack scientific evidence.

Types of case studies

There are specific types of case studies to choose from, and each specific type will yield different results. Some case study types even overlap, which is sometimes more favorable, as they provide even more pertinent data.

Here are overviews of the different types of case studies, each with its own theoretical framework, so you can determine which type would be most effective for helping you meet your goals.

Explanatory case studies

Explanatory case studies are pretty straightforward, as they're not difficult to interpret. This type of case study is best if there aren't many variables involved because explanatory case studies can easily answer questions like "how" and "why" through theory development.

Exploratory case studies

An exploratory case study does exactly what its name implies: it goes into specific detail about the topic at hand in a natural, real-life context with qualitative research.

The benefits of exploratory case studies are limitless, with the main one being that it offers a great deal of flexibility. Having flexibility when writing a case study is important because you can't always predict what obstacles might arise during the qualitative research process.

Collective case studies

Collective case studies require you to study many different individuals in order to obtain usable data.

Case studies that involve an investigation of people will involve many different variables, all of which can't be predicted. Despite this fact, there are many benefits of collective case studies, including the fact that it allows an ongoing analysis of the data collected.

Intrinsic case studies

This type of study differs from the others as it focuses on the inquiry of one specific instance among many possibilities.

Many people prefer these types of case studies because it allows them to learn about the particular instance that they wish to investigate further.

Instrumental case studies

An instrumental case study is similar to an intrinsic one, as it focuses on a particular instance, whether it's a person, organization, or something different.

One thing that differentiates instrumental case studies from intrinsic ones is the fact that instrumental case studies aren't chosen merely because a person is interested in learning about a specific instance.

Tips for writing a case study

If you have decided to write case studies for your company, then you may be unsure of where to start or which type to conduct.

However, it doesn't have to be difficult or confusing to begin conducting a case study that will help you identify ways to improve your business.

Here are some helpful tips for writing your case studies:

1. Your case study must be written in the proper format

When writing a case study, the format that you should be similar to this:

Administrative summary

The executive summary is an overview of what your report will contain, written in a concise manner while providing real-life context.

Despite the fact that the executive summary should appear at the beginning of your case studies, it shouldn't be written until you've completed the entire report because if you write it before you finish the report, this summary may not be completely accurate.

Key problem statement

In this section of your case study, you will briefly describe the problem that you hope to solve by conducting the study. You will have the opportunity to elaborate on the problem that you're focusing on as you get into the breadth of the report.

Problem exploration

This part of the case study isn't as brief as the other two, and it goes into more detail about the problem at hand. Your problem exploration must include why the identified problem needs to be solved as well as the urgency of solving it.

Additionally, it must include justification for conducting the problem-solving, as the benefits must outweigh the efforts and costs.

Proposed resolution

This case study section will also be lengthier than the first two. It must include how you propose going about rectifying the problem. The "recommended solution" section must also include potential obstacles that you might experience, as well as how these will be managed.

Furthermore, you will need to list alternative solutions and explain the reason the chosen solution is best. Charts can enhance your report and make it easier to read, and provide as much proof to substantiate your claim as possible.

Overview of monetary consideration

An overview of monetary consideration is essential for all case studies, as it will be used to convince all involved parties why your project should be funded. You must successfully convince them that the cost is worth the investment it will require. It's important that you stress the necessity for this particular case study and explain the expected outcome.

Execution timeline

In the execution times of case studies, you explain how long you predict it will take to implement your study. The shorter the time it will take to implement your plan, the more apt it is to be approved. However, be sure to provide a reasonable timeline, taking into consideration any additional time that might be needed due to obstacles.

Always include a conclusion in your case study. This is where you will briefly wrap up your entire proposal, stressing the benefits of completing the data collection and data analysis in order to rectify your problem.

2. Make it clear and comprehensive

You want to write your case studies with as much clarity as possible so that every aspect of the report is understood. Be sure to double-check your grammar, spelling, punctuation, and more, as you don't want to submit a poorly-written document.

Not only would a poorly-written case study fail to prove that what you are trying to achieve is important, but it would also increase the chances that your report will be tossed aside and not taken seriously.

3. Don't rush through the process

Writing the perfect case study takes time and patience. Rushing could result in your forgetting to include information that is crucial to your entire study. Don't waste your time creating a study that simply isn't ready. Take the necessary time to perform all the research necessary to write the best case study possible.

Depending on the case study, conducting case study research could mean using qualitative methods, quantitative methods, or both. Qualitative research questions focus on non-numerical data, such as how people feel, their beliefs, their experiences, and so on.

Meanwhile, quantitative research questions focus on numerical or statistical data collection to explain causal links or get an in-depth picture.

It is also important to collect insightful and constructive feedback. This will help you better understand the outcome as well as any changes you need to make to future case studies. Consider using formal and informal ways to collect feedback to ensure that you get a range of opinions and perspectives.

4. Be confident in your theory development

While writing your case study or conducting your formal experimental investigation, you should have confidence in yourself and what you're proposing in your report. If you took the time to gather all the pertinent data collected to complete the report, don't second-guess yourself or doubt your abilities. If you believe your report will be amazing, then it likely will be.

5. Case studies and all qualitative research are long

It's expected that multiple case studies are going to be incredibly boring, and there is no way around this. However, it doesn't mean you can choose your language carefully in order to keep your audience as engaged as possible.

If your audience loses interest in your case study at the beginning, for whatever reason, then this increases the likelihood that your case study will not be funded.

Case study examples

If you want to learn more about how to write a case study, it might be beneficial to take a look at a few case study examples. Below are a few interesting case study examples you may want to take a closer look at.

• Phineas Gage by John Martin Marlow : One of the most famous case studies comes from the medical field, and it is about the story of Phineas Gage, a man who had a railroad spike driven through his head in 1848. As he was working on a railroad, an explosive charge went off prematurely, sending a railroad rod through his head. Even though he survived this incident, he lost his left eye. However, Phineas Gage was studied extensively over the years because his experiences had a significant, lasting impact on his personality. This served as a case study because his injury showed different parts of the brain have different functions.
• Kitty Genovese and the bystander effect : This is a tragic case study that discusses the murder of Kitty Genovese, a woman attacked and murdered in Queens, New York City. Shockingly, while numerous neighbors watched the scene, nobody called for help because they assumed someone else would. This case study helped to define the bystander effect, which is when a person fails to intervene during an emergency because other people are around.
• Henry Molaison and the study of memory : Henry Molaison lost his memory and suffered from debilitating amnesia. He suffered from childhood epilepsy, and medical professionals attempted to remove the part of his brain that was causing his seizures. He had a portion of his brain removed, but it completely took away his ability to hold memories. Even though he went on to live until the age of 82, he was always forced to live in the present moment, as he was completely unable to form new memories.

Case study FAQs

When should you do a case study.

There are several scenarios when conducting a case study can be beneficial. Case studies are often used when there's a "why" or "how" question that needs to be answered. Case studies are also beneficial when trying to understand a complex phenomenon, there's limited research on a topic, or when you're looking for practical solutions to a problem.

How can case study results be used to make business decisions?

You can use the results from a case study to make future business decisions if you find yourself in a similar situation. As you assess the results of a case study, you can identify best practices, evaluate the effectiveness of an intervention, generate new and creative ideas, or get a better understanding of customer needs.

How are case studies different from other research methodologies?

When compared to other research methodologies, such as experimental or qualitative research methodology, a case study does not require a representative sample. For example, if you are performing quantitative research, you have a lot of subjects that expand your sample size. If you are performing experimental research, you may have a random sample in front of you. A case study is usually designed to deliberately focus on unusual situations, which allows it to shed new light on a specific business research problem.

Writing multiple case studies for your business

If you're feeling overwhelmed by the idea of writing a case study and it seems completely foreign, then you aren't alone. Writing a case study for a business is a very big deal, but fortunately, there is help available because an example of a case study doesn't always help.

Mailchimp, a well-known marketing company that provides comprehensive marketing support for all sorts of businesses, can assist you with your case study, or you can review one of their own recently published examples.

Mailchimp can assist you with developing the most effective content strategy to increase your chances of being as successful as possible. Mailchimp's content studio is a great tool that can help your business immensely.

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By Team Multiverse

• Arrow Right Streamline Icon: https://streamlinehq.com Real-world applications of business data analytics
• Arrow Right Streamline Icon: https://streamlinehq.com The role of a Business Data Analyst
• Arrow Right Streamline Icon: https://streamlinehq.com Essential skills for Business Data Analysts
• Arrow Right Streamline Icon: https://streamlinehq.com Steps to becoming a Business Data Analyst
• Arrow Right Streamline Icon: https://streamlinehq.com Take the next step in your data analytics journey with Multiverse

Business data analytics is a cornerstone of modern decision making and innovation.

Companies use the insights they gain from business analytics to create data-driven strategies. These approaches can improve customer satisfaction, operational efficiency, and profitability. Retailers, for example, can use data analytics to predict which products will sell fastest and optimize its supply chain management.

What is business data analytics?

Business data analytics uses software and statistical techniques to interpret data and gain meaningful insights. This process allows organizations to understand their operations better and improve performance. Business analytics also assists with strategic planning and risk management.

Say, for example, a national restaurant brand wants to update its menu. Data analytics allows the company to interpret customer reviews and sales trends to determine which meals and ingredients perform best. Based on these insights, the restaurant can tailor its menu to satisfy customers and boost sales.

Understanding business data analysis

You may have already started to master some of the components of business data analytics. This process involves a few basic steps:

• Ask a question - Start with a specific question or concern you want to address with data. For instance, you could explore customer trends to discover why your business's sales have declined.
• Data collection - Identify relevant data sources and gather information. You could survey customers or use data mining techniques to harvest social media posts.
• Data cleaning and processing - Organize the raw data into a usable format. This often involves transforming data by loading it into an environment optimized for analysis. You’ll also fill in missing data, remove inconsistencies, and correct errors.
• Data analysis - Apply statistical techniques and software to reveal patterns and correlations in the data set.
• Data visualization - Use software to transform the data into easy-to-understand graphics. These visualizations may include charts, graphs, and maps.
• Data interpretation - Study the results to extract meaningful insights. For instance, you might determine your target audience’s interests have changed, leading to a sales dip.
• Communicate findings - Share your results with decision makers and recommend the next steps. In this scenario, you might advise developing new services that better align with your consumer base.

Real-world applications of business data analytics

Business data analytics has many practical applications across industries. Here are three case studies that illustrate the value and versatility of this approach.

Tracking Machine Health in Manufacturing

The company installs advanced telematics software in its construction machinery. The software collects data about different aspects of machine behavior, including fault codes, fuel consumption, and idle time. This data gets streamed through the cloud to John Deere’s Machine Health Center in Iowa.

Local dealers use this data to diagnose machine problems remotely instead of traveling to construction sites or farms. They can select the necessary parts and repair tools to bring to the service appointment, saving time and reducing trips. Additionally, John Deere uses this information to identify and fix potential manufacturing errors.

These applications allow John Deere to improve its performance over time and provide more efficient service.

Improving patient care in healthcare

Data analytics allows Stanford Medicine Children’s Health (opens new window) to understand and improve the patient experience.

The organization uses evaluation forms to collect data about patients’ experiences during their hospital stays. Analysts use AI tools to synthesize the information and reveal patterns, such as complaints about staff responsiveness and wait times.

According to Chief Analytics Officer Brendan Watkins, the organization places these insights “directly into the hands of the folks who can make a difference [and], make systemic change with this data.” These stakeholders include healthcare providers who can use the information to deliver better patient care.

Boosting productivity in retail

The grocery chain Kroger (opens new window) has developed two data-driven applications to improve employee productivity.

First, the company created a task management application for Night Crew Managers. This application displays each store’s inventory and merchandise deliveries in real time. It also uses data analytics to optimize employee to-do lists to help them restock stores efficiently.

Additionally, Kroger uses a store management application to streamline store audits. This tool also automatically recommends tasks for employees as they prepare for audits.

Both applications help Kroger associates adapt to changing store conditions and improve the customer experience.

The role of a Business Data Analyst

A Business Data Analyst uses data to solve business problems and identify growth opportunities. They also support decision makers by offering recommendations based on their findings.

The day-to-day responsibilities of these professionals vary by role but typically include these tasks:

• Collect data from a wide range of sources, such as customer feedback forms, financial records, or in-product data from a software application
• Develop databases to organize information
• Process raw data to prepare it for analysis
• Build and train machine learning (ML) models to analyze enormous data sets
• Design predictive models to forecast potential outcomes
• Create data visualizations
• Deliver presentations about their findings
• Collaborate with colleagues in marketing, sales, and other departments
• Learn about the latest advancements and trends in business data analytics

Business Data Analysts wield significant influence in their organizations. Leaders rely on their expertise for a broad range of business decisions, such as:

• Choosing marketing and sales tactics
• Deciding whether to invest in a new venture
• Managing financial resources
• Selecting prototypes to develop into new products
• Scheduling manufacturing equipment for maintenance and replacement

Because Business Data Analysts deliver considerable value, they often earn lucrative salaries . According to Glassdoor, the pay range for this career is $97,000 to $153,000, with an average salary of $121,000.

Essential skills for Business Data Analysts

You’ll need the right technical and soft skills to thrive in a business data analytics role. If you’re interested in this career path, focus on developing these foundational abilities.

Technical skills

Business Data Analysts rely heavily on technology to interpret data. After all, you wouldn’t get very far if you had to analyze a spreadsheet with thousands of data points by hand. These technical skills will help you manage and process data effectively:

• Structured Query Language (SQL) - This language allows you to organize, manipulate, and search structured databases.
• Programming languages - Use R for exploratory data analysis and data visualization. Python enables you to automate tasks, clean data, and build Machine Learning (ML)ML algorithms.
• Statistical analysis - Understand how to use statistical methods to interpret data. For example, descriptive analytics evaluates historical data to understand events and patterns. Prescriptive analytics uses past and present data to recommend future actions.
• Artificial intelligence (AI) and ML - Companies increasingly rely on AI and ML to analyze data and predict future trends. Study foundational ML concepts like clustering algorithms, decision trees, and linear regression. You should also know how to use ML frameworks and libraries like PyTorch and TensorFlow.
• Data visualization - Transform data into accessible and visually appealing graphics. Popular data visualization platforms include Microsoft Power BI, Tableau, and Zoho Analytics.
• Reporting - Use business intelligence tools like Qlikview and Sisense to create interactive dashboards and reports for stakeholders.

Soft skills

Data Analysts need strong interpersonal skills to excel in the workplace, including:

• Adaptability - Business analytics evolves quickly, so prepare to embrace new approaches and tools.
• Collaboration - Share ideas and responsibilities with team members from different backgrounds and departments.
• Communication - Express your ideas clearly in conversations, presentations, and written reports. You should also learn to translate complex technical concepts for lay audiences.
• Critical thinking - Evaluate the accuracy of data, identify potential biases in the results, and assess potential recommendations for feasibility.
• Negotiation - Collaborate with multiple stakeholders to develop solutions that meet everyone’s needs.
• Problem-solving - Learn how to approach problems from different angles and devise novel solutions.

Steps to becoming a Business Data Analyst

There’s no universal blueprint to becoming a Business Data Analyst. You can use many resources and strategies to gain the knowledge and skills required for this career. Here are a few common pathways.

Earn a college degree

A college education is a traditional — but not required — educational pathway for Business Analysts. Many colleges and universities offer degrees in business analysis, data science, mathematics, and other relevant fields. 

Enrolling in a business data analytics program offers several benefits. A structured curriculum gives you a solid foundation in data management, statistical analysis, and other necessary skills. You’ll also receive feedback and guidance from faculty.

But a college education has a few drawbacks. First, a four-year degree requires a significant investment of time and money. Undergraduate students pay an average of $36,436 per year (opens new window) for tuition, books, and other expenses. You’ll also need to dedicate extensive time to studying and attending classes. People with full-time jobs, families, and other obligations may struggle to balance their responsibilities with a college education.

Many colleges also provide limited hands-on experience. A business data analytics major may learn foundational theories but not be able to apply these concepts in the real world. As a result, they may lack the experience and portfolio needed to land a position.

Obtain relevant certifications

Certifications enable you to develop your skills and showcase your abilities to potential employers. Here are a few relevant credentials that could help you prepare for data analytics roles:

• Entry Certificate in Business Analytics (ECBA) - The International Institute of Business Analysis (opens new window) offers this certificate for aspiring and entry-level data professionals. The certification demonstrates foundational competencies in business analysis planning, elicitation and collaboration, and other areas.
• Professional in Business Analysis (PMI-PBA) - The Project Management Institute (opens new window) designed this certification for Business Analysts who use data to support projects.
• Certified Foundation Level Business Analyst - The International Qualification Board for Business Analysis (opens new window) offers this foundational certification. It demonstrates proficiency in business modeling and creating business solutions.

Certifications cost much less than the average four-year degree and typically take less than a year to earn. They can accelerate your professional development and prove your commitment to the field to potential employers.

If you’re an established professional, you may already have many skills needed to succeed in business analytics. But everyone has areas for improvement. Thankfully, upskilling can fill any gaps in your knowledge — making you more productive at work and better prepared to advance in your career.

In fact, according to Gartner, 75% of employees who participate in upskilling programs agree it contributes to career progression.

Multiverse’s Applied Analytics Accelerator is one of the most effective ways to level up your skills. This cost-free six-month program allows you to immerse yourself in the field of business analytics while working for your current employer.

The apprenticeship includes six modules that teach you how to make data driven decisions and improve business processes. You’ll also learn data analysis and visualization skills you can immediately apply in your role. This fusion of structured learning and hands-on experience will help you kickstart or grow your career in business analysis.

Gain hands-on experience

Developing practical experience strengthens your skills and gives you a competitive advantage in the job market. Look for opportunities to apply your skills with real data sets.

For example, you could volunteer to analyze customer data for your current employer and recommend ways to improve marketing initiatives. You could also help clients solve business problems as a freelancer or consultant.

As you create projects, assemble them into a digital portfolio. Include a detailed description of each project and highlight their measurable outcomes. Potential employers can review your portfolio to gauge your experience level and skills.

If you’re looking for hand-on projects, Multiverse’s Applied Analytics Accelerator equips you to upskill your data chops while staying in your current role.

Take the next step in your data analytics journey with Multiverse

As a Business Analyst, you play a critical role in business decision making and strategic planning. Your insights can help companies develop cutting-edge innovations, improve customer experiences, reduce costs, and more.

Prepare for a career in this in-demand field with a Multiverse apprenticeship. Apprentices get paid to upskill and gain hands-on experience with real business analytics projects. They also receive one-on-one coaching tailored to their personal and professional goals.

Tell us about yourself by completing our quick application (opens new window) , and the Multiverse team will get in touch with the next steps.

Team Multiverse

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The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Save time and money responding to Freedom of Information Act (FOIA) requests

Avoid duplicative internal research, discover complementary datasets held by other agencies, empower employees to make better-informed, data-driven decisions, positive attention from the public, media, and other agencies, generate revenue and create new jobs in the private sector, business case for open data.

Six reasons why making your agency’s data open and accessible is a good business decision.

Case studies & examples

Making data open and accessible in a standard, machine-readable format by default can have significant productivity and cost savings for agencies. When conducting a cost-benefit analysis to determine whether and to what extent to modify existing datasets and systems in accordance with the recommendations of this memo, consider the following potential benefits.

When data is open by default, the public can access the information it seeks directly, freeing your agency from the time and cost expenditures related to responding to FOIAs.

Transparency into the total universe of data held by your agency helps prevent the possibility of wasting funds re-collecting data simply because a particular program or department is unaware of that data’s existence. Further, it may be possible to reduce the scope and cost of new collections based on the ability to re-use and/or pair with existing data. Maintaining a central data catalog for your agency makes it easier to understand what information is currently available, and reviewing this catalog prior to the start of any new data collection is a recommended best practice.

The benefits of transparency into your agency’s own datasets are amplified when every agency maintains its own standardized data catalog. Programs may realize that some or all of the data they need are already held by one or more other agencies, or that more powerful conclusions can be drawn from combining existing agency-held datasets with additional data across other agencies.

The new requirement to publish details about each dataset owned by your agency in a specific format will power a central search engine at Data.gov that every single Federal employee (and member of the public) can use to easily locate data held, owned, and/or created by the Federal Government. Making it easier to find existing data is key to being able to then incorporate that data into your agency’s everyday decision-making processes.

In recent years, entire events celebrating the release and use of open government data – many hosted by the White House – have taken place, with corresponding media coverage and international attention. The more data your agency makes available in easy-to-consume formats, the more opportunities for positive coverage of the availability and impact of those data and your agency’s efforts.

McKinsey estimates that open health data alone adds over $300 billion to the economy each year. Entrepreneurs and non-profits integrate existing open government datasets in ways ranging from web apps that connect you with the nearest hospital in case of an emergency, with information from Health and Human Services, to matching prospective college students with the most appropriate schools, based on IPEDS data maintained by the Department of Education. Making more of your agency data publicly available in standards-compliant, machine-readable formats makes it easier for private sector companies and entrepreneurs to create new innovations fueled by your agency’s data.

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An official website of the Office of Management and Budget, the General Services Administration, and the Office of Government Information Services.

This section contains explanations of common terms referenced on resources.data.gov.

More From Forbes

How enterprise analytics can help future-proof health systems.

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President and CEO of the Clinical Effectiveness business at Wolters Kluwer , leading customer-led innovation and a transformed workforce.

For years, the healthcare community has been focused on unlocking value from patient data stored in electronic medical records (EMRs). With EMRs embedded across more than 80% of physician offices and almost all hospitals (registration required), it is logical to place so much emphasis on EMR data. But collecting this wealth of patient data requires extensive documentation, adding to clinicians’ administrative burden and contributing to ongoing clinician burnout and healthcare workforce challenges.

As such, healthcare organizations and technology providers are turning their attention to ways to streamline and find new value in EMR use. For instance, could EMR data help improve quality and health equity initiatives? A recent study on secure messaging drew interesting comments from the physician community, including speculation as to whether analysis of EMR-integrated messages could " help facilitate at-scale identification of areas for improved team functioning [and] delivery of clinical care ."

In my view, these physicians are onto something: while the healthcare community has been hyper-focused on analyzing and activating patient data, there is a missed opportunity to look more closely at clinician data for complementary insights to help drive improvements in healthcare. EMR data may provide limited insights into clinician workflows, but the real opportunity comes from activating clinician insights outside of the EMR with unified enterprise analytics.

Gaining Point-Of-Care Insights From Clinical Decision Support Solutions

Clinical decision support (CDS) solutions provide clinicians with evidence-based content to help inform crucial care decisions. As my company recently highlighted, research has shown use of CDS is associated with improved patient outcomes and hospital processes.

Best High-Yield Savings Accounts Of 2024

Best 5% interest savings accounts of 2024.

My company is one provider of CDS solutions, and we have been investing in scaling that technology so enterprises can harness data from their own care teams to improve patient and population health outcomes. The millions of CDS searches clinicians across the globe make every single day during their workflow are a treasure trove of data waiting to be tapped.

What kind of insights could we expect to find in clinician search data? Let’s look at one hypothetical example.

Analytics In Action: A Case Study On Using Data To Improve Outcomes

For our hypothetical case study, let’s look at a health system that discovers a surprising trend: an uptick in searches for an antibiotic commonly used to treat urinary tract infections (UTIs). Now, what could the organization do with this information? To start, they might look at other organizations to see if other systems are experiencing this trend. In this case, let's say that benchmarking data shows this health system’s users are looking at and using antibiotics more than people at peer organizations.

But that’s not all the data can show. By drilling down further, the health system is able to quickly uncover that their nurse practitioner (NP) group has more searches than any other users for this drug. This insight raises a red flag among health system administrators. Not only are patients at risk of experiencing side effects when they are unnecessarily exposed to antibiotics, antibiotics overuse can lead to increased antimicrobial resistance . The health system implements an education campaign as part of their ongoing antimicrobial stewardship program. Starting with the NP group, the campaign focuses on educating care teams on proper care plans and guidelines for appropriate UTI treatment to avoid antibiotics overuse.

And here’s the real beauty of harnessing clinician data: our sample health system not only identifies an opportunity to improve quality metrics and patient care; they are also able to make meaningful changes and measure their success. At the end of the education campaign, the health system is able to confirm that antibiotic searches have declined and are now in line with benchmarks.

Future-Proofing Health Systems As They Face Unprecedented Challenges

In the face of emerging healthcare challenges, modern health systems need a more integrated, data-driven approach to help address staff shortages and care team inefficiencies, improve patient satisfaction and outcomes and scale for the future. By harnessing real-time behavior insights from clinician data, we can help health systems and hospitals inform decision making, connect care teams and streamline clinician workflows at the enterprise level.

There is unrealized potential in harnessing CDS data to understand where clinicians are spending their time and what type of information they are searching for. Armed with this information, healthcare organizations can identify opportunities for improvements, such as launching dedicated education and clinical quality initiatives to address gaps in care and proactively manage emerging community health trends.

In the years ahead, I believe we will see an increased use of unified enterprise analytics to connect care team decisions from point-of-care across the health ecosystem and, in turn, measurable improvements in operational effectiveness, safety, patient satisfaction and care equity.

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The state of EV charging in America: Harvard research shows chargers 78% reliable and pricing like the ‘Wild West’

Featuring Omar Asensio . By Barbara DeLollis and Glen Justice on June 26, 2024 .

BiGS Actionable Intelligence:

BOSTON — New data-driven research led by a Harvard Business School fellow reveals a significant obstacle to increasing electric vehicle (EV) sales and decreasing carbon emissions in the United States: owners’ deep frustration with the state of charging infrastructure, including unreliability, erratic pricing, and lack of charging locations.

The research proves that frustration extends beyond “range anxiety,” the common fear that EV batteries won't maintain enough charge to reach a destination. Current EV drivers don’t see that as a dominant issue. Instead, many have "charge anxiety," a fear about keeping an EV powered and moving, according to scholar Omar Asensio, the climate fellow at HBS’s Institute for the Study of Business in Global Society (BiGS) who led the study.

Asensio’s research is based on a first-ever examination of more than 1 million charging station reviews by EV drivers across North America, Europe, and Asia written over 10 years. In their reviews, these drivers described how they regularly encounter broken and malfunctioning chargers, erratic and secretive pricing, and even “charging deserts” — entire counties in states such as Washington and Virginia that don’t have a single public charger and that have even lost previously available chargers. EV drivers also routinely watch gas-engine vehicle drivers steal parking spots reserved for EV charging.

Asensio said that listening to the current drivers — owners rather than potential buyers — provides a new window on the state of America’s charging system because drivers are incredibly candid about their experiences.

“It’s different than what any one company or network would want you to believe,” said Asensio, who is also an associate professor at the Georgia Institute of Technology . He added that most charging providers don’t share their data and have few regulatory incentives to do so.

Research: EV chargers less reliable than gas pumps

One of the study’s main findings, discovered using customized artificial intelligence (AI) models trained on EV review data, is that charging stations in the U.S. have an average reliability score of only 78%, meaning that about one in five don’t work. They are, on average, less reliable than regular gas stations, Asensio said. “Imagine if you go to a traditional gas station and two out of 10 times the pumps are out of order,” he said. “Consumers would revolt.”

Elizabeth Bruce, director, Microsoft Innovation and Society, said, "This project is a great example of how increasing access to emerging AI technologies enables researchers to better understand how we can build a more sustainable and equitable society.”

Asensio’s research is timely as U.S. policymakers, entrepreneurs, automakers such as General Motors and Tesla , and others grapple with how to develop the nation’s charging network, who should finance it, and who should maintain it. Because charging influences vehicle sales and the ability to meet emissions targets, it’s a serious question. EV sales have climbed, topping 1 million in 2023, but concerns over batteries and charging could slow that growth.

Today, there are more than 64,000 public EV charging stations in the U.S., according to the U.S. Department of Energy's Alternative Fuels Data Center. Experts say that the nation needs many times more to make a smooth, sustainable, and equitable transition away from gas-powered vehicles — and to minimize the anxiety surrounding EVs.

“I couldn’t even convince my mother to buy an EV recently,” Asensio said. “Her decision wasn’t about the price. She said charging isn’t convenient enough yet to justify learning an entirely new way of driving.”

Reviews give voice to 1 million drivers

An economist and engineer by training, Asensio has been studying EV infrastructure since its infancy in 2010. At that time, the consensus among experts was that the private sector would finance a flourishing charging network, Asensio said. But that didn’t happen at the scale expected, which sparked his curiosity about how the charging market would emerge at points of interest rather than only near highways.

To get answers, Asensio focused on consumer reviews “because they offer objective, unsolicited evidence of peoples’ experience,” he said.

The smartphone apps that EV drivers use to pay for charging sessions allow them to review each station for factors such as functionality and pricing in real-time, much like consumers do on Yelp or Amazon. Asensio and his team, supported by Microsoft and National Science Foundation awards, spent years building models and training AI tools to extract insights and make predictions from drivers leaving these reviews in more than 72 languages.

Until now, this type of data hasn’t existed anywhere, leaving consumers, policymakers, and business leaders — including auto industry executives — in the dark.

Research reveals five facts about EV life

Here are some of the top findings from Asensio’s research about public EV charging stations:

Reliability problems. EV drivers often find broken equipment, making charging unreliable at best and simply not as easy as the old way of topping off a tank of gas. The reason? “No one’s maintaining these stations,” Asensio said. Entrepreneurs are already stepping in with a solution. For example, at Harvard Business School’s climate conference in April 2023, ChargerHelp! Co-founder Evette Ellis explained that her Los Angeles-based technology startup trains people to operate and maintain public charging stations. But until quality control improves nationwide, drivers will likely continue to encounter problems.

Driver clashes. One consumer complaint that surprised Asensio was a mysterious gripe from drivers about “getting ICE’d.” The researchers didn’t know what it meant, so they did some digging and discovered that ICE stands for “internal combustion engine.” EV drivers adopted the term to grouse about gas-fueled car drivers stealing their public EV charger spots for parking.

Price confusion. Drivers are vexed by the pricing they encounter at public charging stations, which are owned by a mix of providers, follow different pricing models, and do not regularly disclose pricing information. The result is often surprises on the road. As one reviewer wrote, “$21.65 to charge!!!!!!! Holy moly!!!! Don’t come here unless you are desperate!!”

Equity questions. Public charging stations are not equally distributed across the U.S., concentrated more heavily in large population centers and wealthy communities and less so in rural areas and smaller cities. The result is that drivers have disparate experiences, well-served in some areas and starved in others. Some parts of the country have become “charging deserts,” with no station at all.

Commercial questions. Commercial drivers in many areas can’t find enough public EV charging stations to reliably charge their cars. Here too, drivers are having very different experiences, well-supplied in some areas and not in others.

‘Wild West’ pricing is a major pain point

The research shows that EV drivers are dissatisfied with EV charging station pricing models, likening the situation to the “Wild West.” Indeed, vehicle charging is both unregulated and non-transparent.

Pricing can vary substantially by facility, level of demand, time of day, and other factors, including the type of charger available. A 45-minute fast charger may have one price, while a traditional charger that takes 3 to 5 hours may have another. Pricing can also change by the hour, based on market conditions.

Unlike traditional gas stations, which often display fuel prices on lighted signs, EV stations rarely advertise what charging will cost. Drivers often arrive without any information on what to expect or how to make comparisons, because there’s no reliable way for consumers to find the most cost-effective places to charge. “The government has a source that lists all locations, but not in real-time,” Asensio said. “You might need five different apps to figure it out.”

The driver reviews in Asensio’s data reflect the irritation caused by the current system. “People are getting frustrated because they don’t feel like they’re getting their money’s worth,” he said.

Why is the charging network so opaque? Research conducted by Asensio and his colleagues in 2021 found that charging station hosts, in the absence of regulation, have no incentive to share data — and they don’t. Station hosts are typically privately owned, highly decentralized, not well-monitored, and have highly varied patterns of demand and pricing.

The lack of transparency prevents researchers — and journalists — from investigating trends. In stark contrast to headlines trumpeting the ups and downs of gas prices, news organizations are not reporting on differential pricing among EV charging stations.

‘Charging deserts’ emerge

With municipal, state, and federal governments all pushing to increase the number of electric vehicles on the road and decrease carbon emissions, experts agree that America will need more charging stations — a lot more.

Looking only at Level 2 chargers, which top off an EV battery in 3 to 5 hours and are the most common type, S&P Global Mobility estimates a need for 1.2 million nationwide by 2027 and almost twice that by 2030. That’s in addition to in-home chargers.

Of course, that assumes robust growth in EV sales. “The transition to a vehicle market dominated by electric vehicles (EVs) will take years to fully develop, but it has begun,” said Ian McIlravey, an analyst at S&P. “With the transition comes a need to evolve the public vehicle charging network, and today's charging infrastructure is insufficient to support a drastic increase in the number of EVs in operation.”

Making matters more difficult, the chargers that do exist are not evenly distributed. Predictably, the places with the most public chargers installed are those with the highest number of registered electric vehicles, including states like California, Florida, and Texas. Yet, even as the federal government invests billions in new charging stations, many of them along major transportation corridors, places are left behind.

Asensio’s research shows that small urban centers and rural areas attract fewer public charging stations, and in some cases, there are “charging deserts” with no facilities at all — and they may not be where you think.

For example, electric vehicles are popular in Washington state, which ranked fourth in number of EV registrations and sixth in number of public charging stations in 2023. Yet Ferry County , an area outside Spokane with about 7,500 residents, where the average commute is 25 minutes and the median income is about $46,000, had only one charging station for several years. And now there are none.

Similarly, Virginia ranked 11th in EV registrations and 13th in public chargers in 2023. There, researchers found Wise County, an area outside Roanoke and Knoxville, Tennessee, with about 3,500 residents and a median income of almost $45,000. The county has an average commute time of 22 minutes, but there are no public charging stations available.

EV charging presents a classic “chicken and egg” situation, begging the question of whether cars or charging facilities must come first. However, a lack of public charging in areas like Ferry County and Wise County makes electric vehicle adoption difficult.

As American drivers debate whether to swap their gas-powered vehicles for EVs and lower emissions, Asensio said research should play a larger role. Policymakers, auto manufacturers, entrepreneurs, and investors need more and better data to build infrastructure where it’s needed, provide reliable charging, and facilitate EV sales.

“How [else] can we make effective decisions about the economics of EVs?” Asensio said.

General Motors: ‘Anxiety around EV charging’

Omar Vargas, head of public policy at General Motors, emphasized the importance of public EV charging infrastructure to driving EV adoption during an interview with The BiGS Fix at one of BiGS’ business leadership roundtables in Northern Virginia.

“We're looking at what are the best places to install an EV charging station for a community,” Vargas said. “The anxiety around EV charging is an inhibitor to EV adoption.”

Beyond the public investment in rolling out charging infrastructure, GM (whose brands include Chevrolet and Cadillac) has committed $750 million in private capital to the development of EV charging stations. It is partnering with car dealerships and other companies. For instance, GM is testing charging stations at Flying J rest stops.

GM, which reported full-year revenue of $171.8 billion for 2023 , also is joining community partnership efforts that are being formed to secure federal dollars through state and local governments. “We're helping that kind of planning, and we're pretty confident that in the next couple of years, we're going to have a vigorous EV charging network in the United States,” Vargas said.

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Research: Using AI at Work Makes Us Lonelier and Less Healthy

• David De Cremer
• Joel Koopman

Employees who use AI as a core part of their jobs report feeling more isolated, drinking more, and sleeping less than employees who don’t.

The promise of AI is alluring — optimized productivity, lightning-fast data analysis, and freedom from mundane tasks — and both companies and workers alike are fascinated (and more than a little dumbfounded) by how these tools allow them to do more and better work faster than ever before. Yet in fervor to keep pace with competitors and reap the efficiency gains associated with deploying AI, many organizations have lost sight of their most important asset: the humans whose jobs are being fragmented into tasks that are increasingly becoming automated. Across four studies, employees who use it as a core part of their jobs reported feeling lonelier, drinking more, and suffering from insomnia more than employees who don’t.

Imagine this: Jia, a marketing analyst, arrives at work, logs into her computer, and is greeted by an AI assistant that has already sorted through her emails, prioritized her tasks for the day, and generated first drafts of reports that used to take hours to write. Jia (like everyone who has spent time working with these tools) marvels at how much time she can save by using AI. Inspired by the efficiency-enhancing effects of AI, Jia feels that she can be so much more productive than before. As a result, she gets focused on completing as many tasks as possible in conjunction with her AI assistant.

• David De Cremer is a professor of management and technology at Northeastern University and the Dunton Family Dean of its D’Amore-McKim School of Business. His website is daviddecremer.com .
• JK Joel Koopman is the TJ Barlow Professor of Business Administration at the Mays Business School of Texas A&M University. His research interests include prosocial behavior, organizational justice, motivational processes, and research methodology. He has won multiple awards from Academy of Management’s HR Division (Early Career Achievement Award and David P. Lepak Service Award) along with the 2022 SIOP Distinguished Early Career Contributions award, and currently serves on the Leadership Committee for the HR Division of the Academy of Management .

Partner Center

Markets for Diversifying Agriculture: Case Studies of the U.S Midwest

Agricultural diversification stands out as a critical strategy for addressing challenges and seizing opportunities within the agricultural landscape, especially in regions like the Midwest of the U.S. This research delves into the dynamics, opportunities, challenges, and key success drivers associated with agricultural diversification in the Midwest, focusing on three primary crops: oats, peas, and wheat. Employing a case study methodology grounded in empirical and contextual inquiry principles, the research aims to grasp the nuances of diversified agriculture. Data collection integrates primary and secondary sources, including semi-structured interviews and participation in field days. The data collection period spanned from October 2022 to February 2024. Interviews with 29 stakeholders, including farmers, industry representatives, agricultural cooperatives, and non-profits, provided insights into diversified agriculture practices.

Each case study provides in-depth insights into the opportunities, challenges, and key drivers of success associated with promoting diversified agriculture initiatives. These case studies underscore the significance of innovation, market access, sustainability, and collaboration in driving success within the industry. The cross-case analysis offers a comprehensive examination of the potential for agricultural diversification in the US Midwest. Through a comparative analysis of the three case studies, commonalities and key themes emerge, shedding light on stakeholder dynamics, business strategies, operational aspects, and scalability factors.

In summary, this research significantly contributes to the body of knowledge on agricultural diversification, offering insights that can guide future decisions, agricultural practices, and research endeavors aimed at promoting sustainability and resilience in the agricultural sector in the US Midwest.

Degree Type

• Master of Science
• Horticulture

Campus location

• West Lafayette

Advisor/Supervisor/Committee Chair

Additional committee member 2, additional committee member 3, usage metrics.

• Sustainable agricultural development
• Agricultural land planning