Cohort retention analysis measures how [[User Retention Rate|User Retention]] varies across different groups (cohorts) over time. A cohort is a subset of users who share a common characteristic, such as sign-up date or first feature used. This analysis helps understand long-term engagement patterns, identify trends, and diagnose retention issues. ## Types of Cohorts 1. **Time-Based Cohorts:** Users grouped by sign-up date (e.g., January 2024 sign-ups). 2. **Behavioral Cohorts:** Users grouped by actions taken (e.g., first feature used, first purchase made). 3. **Acquisition Cohorts:** Users segmented by acquisition source (e.g., organic search vs. paid ads). 4. 1. **Geographical Cohorts:** Users grouped by location to analyze regional retention differences. 5. **Device-Based Cohorts:** Users segmented by device type (e.g., mobile vs. desktop) to assess platform-specific retention trends. 6. **Subscription-Based Cohorts:** Users classified by membership tier or payment model (e.g., free vs. premium users). ## Challenges in Cohort Retention Analysis - **Multiple Influencing Factors:** Internal changes (e.g., bug fixes, feature launches) and external factors (e.g., seasonality, market shifts) can impact retention. - **Data Noise:** Variability in user behavior can obscure meaningful trends. - **Attribution Complexity:** Identifying the exact reason for retention differences across cohorts is difficult.