Subscription churn rate:
formula and worked example

The leak that a growing subscriber count can hide

Subscription churn rate is the fraction of your existing subscribers who leave during a period. It is the counterweight to growth: every month you must win enough new subscribers just to replace those who left before the total can rise. A business adding 100 subscribers a month and losing 90 is growing by only ten.

Churn matters beyond the headcount because it sets how long a subscriber stays, and therefore what each one is worth. Two businesses with identical sign-up numbers and prices can have very different futures if one loses 2% a month and the other 6%.

The measure also exposes the true cost of acquisition. If a subscriber is expected to stay about 33 months at 3% monthly churn, you can spend more to win one than if the expected stay were 12 months. Churn therefore feeds directly into how much marketing you can afford, which is why investors and lenders ask for it before almost any other subscription figure.

Formula and how to count each input

• Lost subscribers: customers from the starting group who cancelled or lapsed during the period.
• Starting subscribers: everyone active on the first day of the period. Do not add people who joined mid-period.

The restriction in the denominator is what keeps the measure honest. Someone who joined on the 10th and left on the 20th does not belong in either input if you follow the starting-cohort method, though you may track them separately.

Worked example: 45 of 1,500 subscribers leave

A meal-kit service begins the month with 1,500 active subscribers. By month end, 45 of those have cancelled.

1. 1Count active subscribers on day one: 1,500.
2. 2Count how many of those left within the month: 45.
3. 3Divide: 45 ÷ 1,500 = 0.03.
4. 4Multiply by 100: monthly churn is 3%.

Over twelve months, if the same rate held, the share of today's subscribers still remaining would be 0.97 raised to the twelfth power, about 69%. That means roughly 31% lost within a year.

What a 3% monthly rate implies

Judge churn against your pricing model and customer type, as conventions differ a great deal.

• Consumer subscriptions with monthly billing and low switching costs tend to see higher churn than business subscriptions with annual contracts.
• Average lifetime in months is approximately 1 ÷ monthly churn, so 3% suggests about 33 months, a rough guide that assumes the rate is steady.
• Churn is usually highest in the first months after sign-up, so a base full of new subscribers will look worse than a mature one.
• Improving churn from 3% to 2% lengthens expected lifetime from about 33 to 50 months, which often does more for value than a price increase.

Check whether the loss is voluntary or involuntary. Cancellations by choice point to product, price or fit problems. Failed card payments and expired details are involuntary losses, and they are often recoverable with reminders and retry schedules. Splitting the two shows how much of your churn you can fix without changing the product at all.

How sensitive the rate is to lost subscribers

Since the base is fixed, churn rises in direct proportion to cancellations: 49.5 lost subscribers instead of 45 takes the rate to 3.3%. A change of 0.3 points looks trivial but compounds, because the annual loss rises from about 31% to about 33%. Small monthly shifts deserve more attention than they seem to.

Errors that muddy churn reporting

• Including subscribers who joined during the period in the denominator, which lowers the rate artificially for fast-growing businesses.
• Multiplying monthly churn by twelve to get annual churn, which overstates the loss because the base shrinks each month.
• Mixing subscriber churn with revenue churn, where a customer downgrading counts as partial loss.
• Treating paused subscriptions as active, or as lost, inconsistently from one period to the next.

Keep revenue in view alongside headcount. If the subscribers who leave are mostly on the cheapest plan, logo churn can look alarming while revenue churn is mild; if the biggest accounts leave, the reverse is true. Reporting both figures, together with the split between voluntary and involuntary exits, gives a far clearer picture than one percentage that treats every subscriber as equal.

Turning the number into a decision

Say your average subscriber pays 500 a month with a 60% margin, so each is worth 300 monthly. At 3% churn, expected lifetime of 33 months implies about 10,000 in contribution per subscriber. If a retention offer reduces churn to 2.5%, lifetime becomes 40 months, adding about 2,000. That is the budget ceiling for any retention programme aimed at moving from 3% to 2.5%.

Cohorts add a clearer picture still. Group subscribers by the month they joined and track what share remain after one, three and six months. If newer cohorts lose subscribers faster than older ones did at the same age, something changed in acquisition quality or onboarding, even if the blended monthly rate looks unchanged.