Cohort Retention Matrix
The triangular table that doesn't lie about retention.
Put this metric to work: explore FlowMRR's MRR retention analytics to track revenue movements, retention and forecasts from your own account.
A grid where each row is a signup cohort (month customers joined) and each column shows the percentage still active N months later. The most honest representation of retention — averages hide everything that matters, cohorts reveal it.
Worked example
Jan-2025 cohort: 100% at M0 → 92% at M1 → 87% at M3 → 81% at M6 → 76% at M12. Compare to Feb-2025: same M0, but 71% at M6. Feb cohort is leaking faster — investigate what changed.
Illustrative comparisons
M12 retention (B2B SaaS)These unsourced ranges are illustrative scenarios, not measured industry benchmarks, percentiles or recommended targets. Their qualitative labels are editorial interpretations. Compare your own cohorts using the same segment, period, currency and measurement basis.
Why it matters
A single churn number averages over years of cohorts with completely different experiences. The cohort matrix lets you see whether product changes, onboarding tweaks, or pricing moves changed retention. If your matrix shows newer cohorts retaining better than older ones, you have product-market fit improving — the single most valuable signal in early SaaS.
Common mistakes
- Reading rows without comparing them — you need at least 2 cohorts to draw any conclusion.
- Mixing continuous survival with point-in-time retention — disclose whether returning customers count as retained, and keep their original acquisition cohort.
- Truncating short cohorts (e.g. comparing M6 retention of a 5-month-old cohort and a 24-month-old one).