Definition
Cohort maturity describes whether a cohort has reached stable, longer-term retention behavior (often after early churn decays).
Example
A cohort becomes mature when monthly retention stabilizes after early churn drops.
How to use it
- Do not forecast long-term LTV from immature cohorts without a decay model.
- Use two-stage retention curves when early churn differs from steady-state churn.
- Compare mature cohorts to see true product-market fit improvements.
Common mistakes
- Projecting long-term LTV from only the first few months of data.
- Comparing cohorts at different maturity levels as if they are equal.
Why this matters
This term matters because small changes compound in SaaS metrics. Use consistent definitions by cohort and segment so you can diagnose retention, payback, and growth quality.
Practical checklist
- Write a 1-line definition for "Cohort Maturity" that your team will use consistently.
- Keep the time window consistent (weekly/monthly/quarterly) when comparing trends.
- Segment results (channel/plan/cohort) before drawing big conclusions from blended averages.
- Sanity-check with a related calculator from the same category on MetricKit.
- Read the related guide (e.g., Two-stage churn: modeling early drop-off vs steady-state retention) for context and common pitfalls.
Where to use this on MetricKit
Calculators
- Revenue Retention Curve Calculator: Model GRR and NRR over time from monthly expansion, contraction, and churn assumptions (existing cohort only).
- Unit Economics Dashboard Calculator: Compute a unit economics snapshot: gross profit LTV, CAC payback, LTV:CAC, and break-even targets from a few inputs.
- Cohort Payback Curve Calculator: Estimate when a cohort pays back CAC using a simple retention curve (two-stage churn) and optional expansion.
- Retention Targets Planner (NRR/GRR): Compute required expansion (for a target NRR) and allowable churn+contraction (for a target GRR) using monthly rates.
- Quota Attainment Calculator: Calculate quota attainment and pacing from booked revenue to date, quota, and days elapsed in the period.
Guides
- Two-stage churn: modeling early drop-off vs steady-state retention: A practical guide to two-stage churn models: why early churn matters, how to model it, and how to connect retention improvements to LTV.
- Cohort analysis playbook: retention curves, LTV forecasting, and payback: A practical cohort analysis workflow: build retention curves, forecast LTV, and translate retention quality into payback and growth decisions.