Cohort Growth Estimator
Estimate how a user cohort retains over time with month-by-month retention percentages.
A retention curve that flattens over time is a strong signal of product-market fit. It means that users who survive the initial drop-off period tend to stick around indefinitely, forming a stable base of engaged customers. Conversely, a curve that continues to decline steadily suggests the product is not delivering enough ongoing value to retain users beyond their initial interest.
The key milestones in most cohort analyses are Month 1, Month 3, Month 6, and Month 12. The drop between signup and Month 1 captures the activation gap, where users who signed up but never fully engaged will disappear. The Month 1 to Month 3 window reflects early habit formation. Month 6 reveals medium-term stickiness, and Month 12 represents the long-term retention floor.
This estimator takes your initial cohort size and retention percentages at each milestone, then calculates the absolute number of active users remaining at each point. It also computes the average retention across all four milestones. Use these projections to model revenue forecasts, plan infrastructure needs, and evaluate the impact of product changes on long-term retention.
Estimator
Results
How to Use
- Enter the initial cohort size (total users who signed up in a given month)
- Enter the Month 1 retention rate as a percentage of the original cohort
- Enter the Month 3 retention rate as a percentage of the original cohort
- Enter the Month 6 retention rate as a percentage of the original cohort
- Enter the Month 12 retention rate as a percentage of the original cohort
- Click Calculate to see active user counts at each milestone and the average retention rate
FAQ
What is cohort analysis?
Cohort analysis groups users by the time period they were acquired and tracks their behavior over subsequent periods. For retention analysis, you take all users who signed up in a specific month and measure what percentage are still active at Month 1, Month 3, Month 6, and Month 12. This reveals the true retention pattern without it being distorted by new user acquisition.
What retention curve shape indicates product-market fit?
A retention curve that drops initially but then flattens out into a horizontal line indicates strong product-market fit. This shape means users who survive the first few months tend to remain active long-term. If the curve continues to slope downward without flattening, the product may not be delivering sufficient ongoing value.
How can I use cohort data to improve retention?
Compare retention curves across different cohorts to identify trends. If newer cohorts retain better than older ones, your product improvements are working. Look at the biggest drop-off points to determine where users disengage. If the biggest drop is between signup and Month 1, focus on onboarding. If it happens between Month 1 and Month 3, focus on engagement and habit formation.