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Cohort analysis helps marketers track customer behavior by grouping users with shared characteristics. This blog highlights its benefits, offers a straightforward guide to get started, and shares relatable examples to enhance retention and drive growth.
Cohort analysis examines groups of users over time—often defined by their acquisition date or behavior—to reveal how their actions evolve. By tracking these cohorts, businesses can pinpoint trends, optimize marketing strategies, and uncover ways to improve user retention.
For instance, an e-commerce platform might compare purchasing behaviors of users acquired through different marketing channels, while a subscription service might identify factors influencing churn. However, to be meaningful, cohorts must be well-defined. Cohort analysis can yield misleading insights if groups are too broad, too small, or not representative of key user actions.
Unlike RFM analysis (Recency, Frequency, Monetary value), which groups users by purchase behavior and value, cohort analysis highlights time-based trends. It’s most effective when combined with other segmentation methods, such as behavioral segmentation or psychographic segmentation, to form a more holistic view of user engagement.
A typical example is sending an email campaign to 1,000 users and observing how many of them purchase on Day 1, Day 2, and so on. If you send a new email to a fresh cohort a few weeks later, you can compare purchase patterns to assess the impact of timing. Another scenario is an app tracking the percentage of new users returning each day for 10 days—helping you see how retention changes over time.
To illustrate the concept, here’s an example of cohort analysis. With this cohort chart, let’s track a daily cohort of users who launched an app for the first time and revisited it over the next 10 days.
From this data, we observe that by the 7th day, only 1 in 8 users who launched the app on January 26 were still active. Only 27% remained on Day 1, out of 13,487 new users in this timeframe, whereas it decreased to 12.5% on Day 7, and 12.1% on Day 10.
Grouping users into different types of cohorts for further analysis can unlock valuable insights that can help you tailor your engagement and retention strategies effectively. Broadly speaking, users can be segregated into the following cohorts:
These cohorts are based on when users first interacted with your product, such as by day, week, or month of sign-up. Acquisition cohorts allow you to track user retention over time. This highlights when users are leaving your app.
The retention curve plotted based on the chart above shows a sharp drop-off of around 75% after the first day. Moreover, a secondary decline occurs after Day 5, with retention falling to under 12%. By Day 10, only about 11% of the original users remain active.
This pattern suggests that users are not quickly reaching the app’s core value. So, this leads to significant drop-offs. To help users discover the app’s value faster which could help boost retention, focus on improving the onboarding experience. Acquisition cohort analysis is excellent for identifying when churn occurs. However, to understand the reasons behind the drop-offs, you need to look at behavioral cohorts.
Cohorts are formed based on specific user actions within a defined timeframe—like app installs, launches, or transactions. By grouping users according to these actions, behavioral cohorts reveal why users leave and how different behaviors influence long-term engagement and retention. Let’s examine two behavioral cohorts: users who completed a transaction and those who abandoned a cart.
Compare the two behavioral cohorts to identify critical moments for engagement. Then, develop strategies to reduce the churn rate, which may include timely retargeting campaigns and personalized incentives.
Cohort analysis uncovers actionable insights into user behavior, helping you optimize marketing and product strategies. By identifying why certain cohorts churn, you can develop more targeted retention efforts. Analyzing the most engaged cohorts highlights where to focus your time and budget, ultimately enhancing the customer experience and driving sustainable growth.
Conducting a cohort analysis involves a series of critical steps— from setting clear goals to analyzing results— each essential for gaining meaningful insights. Follow them systematically to make data-driven decisions and enhance your business strategies.
Begin by defining clear objectives for your cohort analysis. Define what you aim to achieve with your cohort analysis. Are you looking to boost retention, reduce churn, or understand user behavior better? Clear goals will guide your analysis and help you measure success. Setting specific goals will guide your analysis and help you focus on relevant metrics.
Identify the key metrics that align with your goals. Common metrics include retention rates, engagement levels, and conversion rates. Choose the right metrics to ensure that your analysis provides meaningful insights.
Group users based on relevant criteria, such as acquisition date or specific behaviors. Ensure that the cohorts are meaningful and representative of different user segments. Accurate cohort definitions are crucial for obtaining reliable insights.
Visualizing cohort data can reveal trends and patterns more effectively than raw data. Use charts and graphs, such as retention curves, to illustrate how different cohorts perform over time. This makes it easier to identify significant changes and trends.
Regularly analyze the data to track changes and assess the impact of your strategies. Refine your cohorts and analysis methods continuously based on your findings to improve accuracy and relevance.
Choosing the right tool for cohort analysis is crucial for gaining actionable insights. Look for a platform that offers flexibility, intuitive data visualization, and advanced analytics. Here’s what to keep in mind when evaluating your options:
CleverTap is one such tool that offers these functionalities, helping you create and analyze cohorts, visualize data, and derive actionable insights.
When it comes to effective cohort analysis, selecting the right tool is crucial. CleverTap stands out as a comprehensive platform that provides all the necessary features to conduct insightful cohort analysis and enhance user engagement.
Here are the key capabilities that set CleverTap apart from other platforms:
By leveraging these features, CleverTap empowers you to conduct detailed cohort analysis, uncover valuable insights, and drive strategies that boost user engagement and business growth. For a deeper dive into CleverTap’s customer data analytics capabilities, visit our Customer Data Analytics page.
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BukuKas was launched in December 2019 by Krishnan M Menon. It is an SME digitization startup offering a digital ledger app for Indonesian small businesses. The company serves nearly 2 million monthly users by helping them manage cash, inventory, and analytics. BukuKas is expanding its services to include digital payments and social commerce. Here’s how CleverTap helped BukaKas hit outstanding goals:
CleverTap’s cohort analysis offers powerful insights into user behavior, helping businesses track and compare engagement across different groups. This enables tailored strategies that improve user retention and drive growth.