Churn and retention calculator
Churn, retention, net growth and average customer lifetime for a period.
Fill in the fields and the result will appear here automatically.
Churn measures losses from the opening customer cohort: divide customers lost from that cohort by customers present at the start. New customers do not enter that denominator. To reconcile the ending count, enter new customers still present at the end, after any early departures. Lifetime 1/c is a separate geometric estimate under constant churn probability c, including the first active period; one observation does not establish a customer lifespan.
How it works
Formula and logic
With opening cohort S, its losses L and retained newcomers G: churn = L/S × 100%, retention = (S−L)/S × 100%, ending count = S−L+G, net growth = (G−L)/S × 100%. Counts are whole and nonnegative, S > 0 and L ≤ S. For c=L/S > 0, model lifetime = 1 + (1−c) + (1−c)² + … = 1/c periods; c=0 has no finite estimate.
Example
Of 1,000 customers 50 left and 80 arrived: churn 5.00%, retention 95.00%, ending with 1,030 customers. With 100 opening customers,100 lost and 0 retained newcomers, retention is 0%, ending count 0 and model lifetime 1 period.
Fields and units
- Customers at the start — unitless
- Lost from the opening cohort — unitless
- New customers retained at the end — unitless
How to use
- — Enter how many customers you had at the start of the period.
- — Enter how many were lost during the period.
- — Enter how many were gained during the period.
- — Those gained do not enter the churn denominator.
- — For newcomers, count only those still present at period end; do not mix their departures into the opening-cohort churn.
Method and limitations
- Calculation method
- Formula and logic
- Data or methodology source
- Stripe Atlas: geometric customer lifetime under constant churn
- Limitation
- Opening cohort and retained newcomers. Lifetime 1/c assumes constant churn and does not guarantee lifespan or payments.
FAQ
Why the customers at the start rather than at the end?
To measure departures within the same opening cohort. New customers can leave in the same period too, but they form a different cohort: do not mix their departures into L; subtract them from retained newcomers G.
How does churn relate to customer lifetime?
Only under constant churn probability and equal period lengths. Monthly churn of 5% gives 20 model active months; 100% still includes the first active month. Cohort-age changes and future payment guarantees are outside this estimate.
Why is lifetime hidden at zero churn?
Formally it is infinite, and infinity on screen would promise an everlasting customer. Zero churn in a single period is ordinary enough, but immortality does not follow from it.
Can net growth be negative?
Yes, and it is an important signal: more customers left than arrived, so the base is shrinking even with decent retention.
Should churn be measured in customers or in revenue?
Here it is customers. Revenue churn is a separate figure and can differ several times over: losing one large account barely moves the headcount number.