User Cohort Retention Calculator
Generate a cohort retention heatmap from a few simple assumptions. Compare newer cohorts, see the retention curve, and estimate retained users without entering every checkpoint manually.
View all free toolsCohort assumptions
Adjust the assumptions to update the matrix instantly.
Cohort retention KPIs
Month 11 retention
52.7%
Retention of the oldest, fully matured cohort.
Retained users
263
From 500 starting users in the oldest cohort.
Average month 1 retention
90.5%
Across cohorts mature enough to reach month one.
Ongoing monthly churn
5.0%
One minus ongoing monthly retention.
Cohort retention matrix
Darker cells indicate stronger retention. Blank cells are months newer cohorts have not reached yet.
| User cohort | Users | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Cohort 1 | 500 | 100% | 88% | 84% | 79% | 75% | 72% | 68% | 65% | 61% | 58% | 55% | 53% |
| Cohort 2 | 500 | 100% | 89% | 84% | 80% | 76% | 72% | 68% | 65% | 62% | 59% | 56% | — |
| Cohort 3 | 500 | 100% | 89% | 85% | 80% | 76% | 72% | 69% | 65% | 62% | 59% | — | — |
| Cohort 4 | 500 | 100% | 90% | 85% | 81% | 77% | 73% | 69% | 66% | 63% | — | — | — |
| Cohort 5 | 500 | 100% | 90% | 86% | 81% | 77% | 73% | 70% | 66% | — | — | — | — |
| Cohort 6 | 500 | 100% | 91% | 86% | 82% | 78% | 74% | 70% | — | — | — | — | — |
| Cohort 7 | 500 | 100% | 91% | 86% | 82% | 78% | 74% | — | — | — | — | — | — |
| Cohort 8 | 500 | 100% | 92% | 87% | 83% | 78% | — | — | — | — | — | — | — |
| Cohort 9 | 500 | 100% | 92% | 87% | 83% | — | — | — | — | — | — | — | — |
| Cohort 10 | 500 | 100% | 93% | 88% | — | — | — | — | — | — | — | — | — |
| Cohort 11 | 500 | 100% | 93% | — | — | — | — | — | — | — | — | — | — |
| Cohort 12 | 500 | 100% | — | — | — | — | — | — | — | — | — | — | — |
How the cohort model works
The heatmap applies one activation assumption and one steady-state retention assumption across acquisition cohorts. The improvement slider shows whether newer cohorts are getting stickier or weaker.
Month 1 retention = Base month 1 retention + cohort improvement
Retention at month t = Month 1 retention × Ongoing monthly retention^(t − 1)
Retained users = Starting cohort users × Retention
Watch the first drop
Month-one retention highlights activation and expectation mismatch.
Read across rows
Each row shows how one fixed acquisition cohort changes over time.
Read down columns
Each column compares cohorts at the same maturity point.
Alex Tapio
Founder of Finamodel • Professional Financial Modeller • Ex-Deloitte
Frequently asked
Every cohort starts at 100%. Month-one retention applies the initial drop, then ongoing monthly retention compounds from month two onward. The improvement control increases month-one retention for each newer cohort.
For a fixed cohort at a given checkpoint, cumulative churn equals 100% minus retention. Ongoing monthly churn equals 100% minus the ongoing monthly retention assumption.
Older cohorts have had more time to mature. Newer cohorts only show the months they have actually reached, which prevents incomplete cohorts from being compared at unavailable checkpoints.
Use an event tied to delivered value, such as completing a workflow, placing an order, or using a core feature. Apply the same definition and observation window to every cohort.
Aggregate users mix acquisition growth with customer behavior. Cohorts hold start time constant, making it easier to see whether onboarding or product changes improve long-term retention.
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