Customer churn, revenue churn, compounded annual churn and average lifetime. The formula is simple — the interpretation is where founders go wrong.
Enter one month. Customer churn is the headline number; revenue churn tells you whether you are losing your bigger accounts.
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Churn rate is the share of customers who cancel in a given period. The formula is simple and the interpretation is not, which is where most founders go wrong.
Monthly customer churn = customers lost ÷ customers at the start of the month.
Customers acquired during the month are excluded from the denominator. Including them flatters the number, because new signups have had almost no opportunity to cancel yet. A fast-growing product using the wrong denominator can report half its actual churn rate.
The second common error is annualising by multiplying by twelve. Churn compounds — at 5% monthly you retain 0.95 to the twelfth power, so you lose roughly 46% over a year rather than 60%. The calculator does this correctly.
Both matter and they answer different questions. Customer churn tells you how many relationships you are losing. Revenue churn tells you whether the ones leaving were your larger accounts.
| Pattern | Means |
|---|---|
| Revenue churn lower than customer churn | You are losing smaller accounts. Usually fine. |
| Revenue churn higher than customer churn | Your bigger customers are leaving. Investigate first. |
| Roughly equal | Churn is spread evenly across account sizes |
If you have expansion revenue, net revenue churn can go negative — existing customers growing faster than others leave. That is a strong position and it depends entirely on your pricing structure, which the value metric framework covers.
The arithmetic is exact and the result is noisy. With forty customers, one cancellation is 2.5% and two is 5% — a doubling driven by one person's circumstances.
Two adjustments help. Use a three-month rolling average rather than a single month, and look at the shape rather than the level: whether cancellations cluster in the first sixty days or spread evenly across cohorts tells you far more than the percentage does.
For what the number should be at your stage, the churn benchmark check interprets a rate you already have against solo-scale bands.
The rate tells you there is a problem. It does not tell you which one, and the five types need opposite fixes — a discount solves one of them and worsens another.
Sort your last twenty cancellations by two data points you already have: how long after signup they cancelled, and whether they were active in the fortnight before. The churn reduction framework covers the sorting, and the churn guide covers the fixes.
If a large share of your cancellations turn out to be failed card payments, that is the cheapest thing on the list to fix — see SaaS business automation.
Divide customers lost during the month by customers at the start of the month. Exclude customers acquired during the month from the denominator — including them flatters the figure, because new signups have had almost no opportunity to cancel.
Churn compounds, so it is not monthly multiplied by twelve. Use one minus (one minus the monthly rate) to the twelfth power. At 5% monthly you lose roughly 46% of customers over a year rather than 60%.
Customer churn counts relationships lost; revenue churn counts money lost. If revenue churn is higher than customer churn, your larger accounts are the ones leaving, which is more urgent than the headline number suggests.
No. At forty customers one cancellation is 2.5% and two is 5%, so the monthly figure swings on individual circumstances. Use a three-month rolling average and look at whether cancellations cluster early rather than at the level itself.
It is the inverse of your monthly churn rate — at 5% monthly the average customer stays about 20 months. Treat it as directional rather than precise, especially if your product is younger than the lifetime the formula implies.
Bring your rate and your last twenty cancellations. Marcus names which of the five churn types you have and the one fix worth making.
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