Retention Curve Calculator

Model a simple cohort retention curve (logo retention) and translate it into expected revenue and gross profit over time.

Retention curves show how customer survival changes over time. They are often more informative than a single churn rate because they reveal where drop-offs happen (activation and early lifecycle).

This calculator uses a simple constant monthly churn assumption to generate retention at key checkpoints and estimate expected revenue and gross profit per original customer.

Prefer an explanation- Read the guide.
 
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Tip: you can type commas (e.g., 10,000).

Example

Using the default inputs, the result is:
78.5%
Monthly logo churn
2%
ARPA (monthly)
$800
Gross margin
80%
Months to model
36

How to calculate

  1. Enter ARPA and gross margin to translate retained customers into gross profit.
  2. Enter monthly logo churn (constant churn assumption).
  3. Choose a horizon and review retention at 3/6/12/24 months plus expected value.

Formula

Retention after m months = (1 - monthly churn)^m
  • Uses constant monthly logo churn (simplification).
  • ARPA and gross margin are constant over the horizon.
  • Outputs are per original customer/account in the cohort (expected value).

FAQ

Why use a retention curve instead of a single churn rate-
Retention curves show where churn happens (early vs late). Two products can have the same average churn but very different early drop-off, which affects activation work and payback.
How do I make this more realistic-
Use observed cohorts segmented by plan/channel and model churn that decays over time. If you have expansion, model revenue retention (NRR/GRR) alongside logo retention.

Common mistakes

  • Using blended churn across segments (plan/channel) and hiding weak cohorts.
  • Confusing revenue retention (NRR/GRR) with logo retention (customer count).
  • Assuming constant churn when churn decays over time (use real cohorts when possible).

Quick checks

  • Keep time units consistent (monthly vs annual) across inputs and outputs.
  • Segment by cohort/channel/plan before trusting a blended average.
  • Use the related guide to avoid common definition and denominator mismatches.