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Glossary

Cohort Analysis

Cohort Analysis

Sergey Zubkov

Updated: July 27, 2023

5 min read

Content

What is cohort analysis

Cohort analysis is a method of analyzing data that involves grouping data sets by shared characteristics or experiences, typically within a specific time frame. The purpose of cohort analysis is to track changes or patterns in behavior over time and to gain insights into the factors that influence those changes.

Cohort analysis in marketing for mobile apps

User retention is a critical aspect of mobile app analytics, but it can be difficult to track changes in user behavior because of varying levels of engagement and user journey stages. This is where cohort analysis comes in. This methodology groups users based on specific shared criteria, allowing developers and marketers to compare the performance of these groups over time. This provides valuable insights into trends and movements that might otherwise go unnoticed.

Every mobile user has a lifespan, and their activity varies at different stages. Cohort analysis enables developers and marketers to remove interference and observe user behavior patterns based on specific criteria. For example, they can group users who downloaded an app in January and monitor how many of those users remain active after a certain period, such as 30 or 60 days. This data can then be used to identify trends and patterns in user behavior, enabling them to optimize their app and retention strategies to improve user engagement and increase revenue.

For instance, developers can divide their app users into groups based on the specific week they installed the app after its launch. They can then observe and analyze the behavior of each group as a cohort throughout their entire user journey.

Cohort analysis is also a useful tool for measuring the effectiveness of marketing campaigns and user acquisition efforts. By analyzing the retention rates of users acquired through various channels or campaigns, developers and marketers can identify which channels are most effective and adjust their marketing strategies accordingly. Cohort analysis helps developers and marketers gain valuable insights into their user base and make data-driven decisions that optimize their app and retention strategies.

Running a Cohort Analysis for mobile apps can provide a number of advantages, including:

  1. Identifying potential customers who are ready to make an in-app purchase
  2. Predicting future behavior such as retention or defection and identifying app users who can be retained
  3. Targeting specific customer groups for cross-selling or up-selling initiatives 
  4. Determining which activities, features, or changes are effective for customers
  5. Using present data as a benchmark for future improvement of mobile app growth strategy

How to do cohort analysis in Adapty

In order to effectively monetize your app, it’s crucial to have a clear understanding of your revenue metrics and how different groups of paying users are impacted by app growth. This is where Adapty comes in with the advanced real-time cohort analysis for mobile subscriptions.

Adapty’s Analytics dashboard provides a dedicated section for cohorts, allowing you to evaluate your monetization strategies, track your app’s churn rate, and analyze how key metrics evolve over time. The dashboard presents revenue, subscriber count, and average revenue per subscriber (ARPPU) for each month in a user-friendly table format.

By segmenting users into specific cohorts based on various criteria, you can observe how they renew or churn and determine the effectiveness of changes to your app, such as pricing modifications. Cohorts are typically grouped by month, but retention is tracked according to your product. Adapty’s platform enables you to analyze data at the renewal period and day level, which is particularly helpful for tracking non-subscription products like consumables or one-time purchases.

For example, if your app offers weekly subscriptions, you can display ARPPU, ARPAS, total revenue, or subscriptions and track the performance of each cohort on the 1st, 3rd, 7th, 14th, and other days. You can also use filters to analyze payment trends for specific countries, products, duration, paywalls, attribution, and store to assess performance changes over time compared to previous months. With Adapty’s Analytics dashboard, you can gain valuable insights into your app’s revenue metrics and optimize your monetization strategy.

To learn more about how mobile app companies can benefit from Adapty’s subscription analytics in cohort analysis, check out the case study of Union Apps