What is cohort analysis?

Cohort analysis is a method for tracking and analyzing groups of users, known as cohorts, who share a common characteristic over time. This could be anything from the month they signed up to a specific action they took within your app. By focusing on these groups, you can gain valuable insights into user behavior.

Cohort analysis helps businesses to:

• Identify patterns: Track how different user groups behave over time. Spot trends quickly and efficiently. This helps you understand user journeys better. Learn more about cohort metrics and reading retention graphs to get detailed insights.

• Improve retention: Discover why users leave and act to retain them. Analyze drop-off points and address issues promptly. This keeps users engaged longer. Investigate through scoping to specific cohorts and retention charts to understand where improvements can be made.

• Optimize features: Adjust features to meet specific cohort needs. Understand which features resonate with different groups. Tailor your product to enhance user satisfaction. Utilize tools like conversion rate optimization and lean hypothesis testing to refine and enhance your features.

Examples of cohort analysis in action

• Retention improvement: An education app groups users by acquisition source. It finds that users from a specific campaign have higher retention. The app then invests more in that campaign. Learn more about retention improvement and analyzing cohorts.

• Feature optimization: A music streaming service analyzes cohorts by behavior. It discovers that users who create playlists in the first week are more likely to stay. The service improves its onboarding to encourage playlist creation. Discover how behavioral targeting and cohort analysis can help in feature optimization.

• Reducing churn: An e-commerce site segments users by purchase behavior. It identifies that users who don't use a specific feature are more likely to churn. The site simplifies access to that feature to improve retention. Learn more about churn rate, conversion rate optimization, and reducing churn.