cohort-analysis

You can track weekly user retention by grouping users into cohorts based on their signup date, calculating return rates over subsequent weeks, and comparing segment breakdowns to identify engagement trends.

Cohort analysis is a technique that compares user retention, engagement, and revenue metrics across specific groups over time. You need it when aggregate metrics fail to reveal how different user segments behave long-term.

Yes, you can compare retention and revenue trends by segmenting users into cohorts based on plan type. This allows you to measure week-over-week return rates and engagement differences between free and paid users.

To segment user behavior by acquisition channel, you group users into cohorts based on their source channel, then calculate their return rates and engagement metrics over time to evaluate which channels drive the strongest retention.

Yes, this approach works with PostgreSQL data. You can use your PostgreSQL database to group users by signup date or acquisition channel, calculate return rates, and extract actionable retention insights.

The best way to extract actionable insights from cohort retention data is to compare week-over-week return rates across segmented cohorts, identifying the specific acquisition channels and plan types that drive long-term engagement.