What is Cohort Retention Value?
This projects the total revenue a customer cohort will generate over a chosen window, accounting for the fact that the group shrinks every month as people leave. The naive version — cohort size times monthly revenue times months — assumes nobody ever churns, and overstates the answer badly enough to justify acquisition spend the business cannot support. The geometric decay used here is the same reasoning behind serious LTV modelling. It still simplifies in one important way: it applies a single retention rate to every month, when real cohorts lose people fastest at the start.
Why it matters
- It gives a realistic, compounding revenue projection instead of naively multiplying cohort size by monthly revenue.
- It shows how much retention rate — even small differences — changes total cohort value.
- It's the underlying math behind most serious LTV and cohort-based revenue forecasting.
The formula
Cohort Revenue = Cohort Size × Monthly Revenue × [r × (1 − r^months) ÷ (1 − r)], where r = Retention Rate
- Cohort Size
- — number of customers who joined in the same period
- Monthly Revenue
- — average revenue per active customer per month
- r (Retention Rate)
- — share of the cohort still active each month, compounding
- months
- — the projection window
How to use this calculator
- 01Pull cohort size and average monthly retention rate from your cohort analysis.
- 02Enter average monthly revenue per retained customer.
- 03Set a projection window — 12 months is a common starting point.
- 04The result accounts for natural cohort shrinkage, unlike a simple flat multiplication.
Worked example
A cohort of 1,000 customers retains at 90% monthly, generating $20/month per retained customer, projected over 12 months.
- r = 0.90
- Sum factor = 0.90 × (1 − 0.90¹²) ÷ (1 − 0.90) ≈ 6.46
- Projected revenue = 1,000 × $20 × 6.46 ≈ $129,163
This cohort is projected to generate about $129,000 over 12 months — meaningfully less than a naive flat calculation (1,000 × $20 × 12 = $240,000) would suggest, because of natural monthly attrition.
Industry benchmarks
Compiled August 2026
High-retention cohort (95%+ monthly)
Value close to naive full-cohort estimate
Minimal shrinkage over the projection window.
Moderate retention (85% – 92%)
Meaningfully below naive estimate
Typical for many subscription businesses.
Low retention (below 80%)
Sharply below naive estimate
Most cohort value concentrated in the first few months.
Month-one retention specifically
Usually the steepest drop
A single flat rate understates early loss and overstates later loss.
Common mistakes
- Assuming flat cohort size over the projection window instead of accounting for compounding attrition.
- Using a single average retention rate across the whole projection when early-month retention is often lower than later-month retention.
- Not revisiting this projection as actual cohort behavior data comes in.
- Projecting further out than the business can see — a 36-month window on a two-year-old product is extrapolating past any cohort that has actually lived that long.
How to improve your cohort retention value
Compare against churn's dollar cost directly
This projection and the Churn Revenue Impact calculator answer related questions — use both for a fuller picture.
Calculate churn revenue impact →Use real monthly cohort data, not one flat rate, when available
Retention often varies by month since signup — plugging in actual month-by-month rates gives a more accurate projection than one averaged rate.
Compare cohorts by acquisition channel
Cohorts acquired through different channels retain very differently. Splitting the projection by source usually shows that a cheaper channel is producing materially less valuable customers.
Compare CAC by channel →Frequently asked questions
Why is this different from just multiplying cohort size × revenue × months?+
Because that naive calculation assumes no one ever churns — this formula accounts for the cohort shrinking a little each month, which is much closer to reality.
What if retention rate isn't constant every month?+
This formula assumes a constant rate for simplicity — for more precision, apply actual month-by-month retention rates from your cohort table instead.
How long a projection window should I use?+
Twelve months is the usual default, and it has the advantage of matching how budgets are planned. Going longer compounds the flat-rate assumption, so if you do project further out, treat the later months as increasingly speculative rather than forecast.
Should this be revenue or gross profit?+
Gross profit, if the output will be compared against acquisition cost. Revenue-based cohort value overstates what the cohort is worth by your entire cost of serving it, which is exactly the comparison that decides how much you can afford to spend winning them.
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