Retention curves: how to read them and why they matter

A practical guide to retention curves: what they show, how to interpret churn vs retention, and how to connect retention to LTV and payback.

Updated 2026-01-28

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What a retention curve shows

A retention curve shows the fraction of a cohort that remains active over time. Instead of a single churn number, the curve reveals where drop-off happens (activation period vs later months) and whether retention is improving across cohorts.

Logo vs revenue retention

  • Logo retention tracks customer count survival (accounts).
  • Revenue retention (GRR/NRR) tracks dollars retained and can be high even if logo retention is weak (when expansion offsets churn).

How to use retention curves

  • Identify the biggest drop (month 1-3 often indicates activation/onboarding issues).
  • Segment by plan, channel, and cohort start month to avoid blended averages.
  • Connect to unit economics: retention drives LTV and payback feasibility.

Common mistakes

  • Using blended churn to forecast LTV when segments differ materially.
  • Assuming constant churn forever (churn often decays over time).
  • Looking at NRR alone and missing logo churn problems.

FAQ

Do I need cohort curves if I already track churn-
Yes if you want better forecasting and diagnosis. The shape of the curve matters: two businesses can have the same average churn but very different early retention, which changes payback and growth quality.
What's a good retention curve-
It depends on product and segment. The key is improvement over time and strong early retention. Track benchmarks within your own history first, then compare to peers cautiously.

More in saas metrics

Retention & churn hub: cohorts, GRR/NRR, and retention curves
Retention rate: how to measure retention correctly