Churn and risk monitoring

Write down what churn means for your model before counting. Subscription: the customer's recurring revenue goes to zero and does not come back in the next cycle. Contract: the current contract ends without renewal, and end of life is the earlier of end date and cancellation date. Rental: the contract no longer has any rent receipt scheduled. Repeat purchase without contract: inactive after N days without buying (for example, 365), with risk well before that.

Cancellation and dropout sources record when the information was entered, not when the customer stopped. Keep both dates. In a database cleanup, billing cancels at once subscriptions that stalled months ago: close the churn at the earlier of the cancellation date and the last payment plus one cycle. Lost revenue is the last recurring value known before cancellation, because the MRR field zeroes when the subscription is cancelled.

Monthly churn = customers in the base on the first day of the month who left during the month / base on the first day. New customers of the month stay out of the denominator. Compute it in customers and in revenue, always separately. For a quarter or year, recompute from the sums, never add monthly rates.

Involuntary is an exit caused by a failed payment that was not recovered. An overdue invoice is not churn yet: track the cohort of subscriptions with a failure each month and count as recovered those that paid successfully within one billing cycle (30 days monthly, 90 quarterly, 1 year annual). In a real base, the recovery rate of closed months was close to 45%, so half of involuntary churn is recoverable through collection.

These go straight into the queue: cancellation or downgrade request, subscription set not to renew, contract notice, confirmed overdue installment, and a long cycle (annual, semiannual) expiring within 60 days or expired up to 45 days ago without renewal. Usage and engagement signals only come in after being tested against real churns.

For renewals, an explainable score works better than arbitrary weights: risk = 100 x (1 - historical renewal rate of the profile), where the profile combines billing cycle, payment method (automatic or manual) and whether it is the customer's first long cycle. Compute the rate only with contracts that already expired and had time to renew.

A customer who buys without a contract is at risk after 1.5 times their own average purchase cycle, or after 270 to 365 days without buying when they bought more than once. A single purchase calls for contact 15 to 45 days later and becomes no repeat purchase between 90 and 365 days. Contact silence is also measured against the account's historical cadence, and a small base (fewer than 5 events) does not alert.

A cancellation shortly after the sale (for example, within 45 days, or 90 for large accounts) is a sales or onboarding problem, not a retention one. Flag those exits and analyze them apart. Classify the tenure of every churn in fixed bands: below 1 month, 1 to 3 months and 3 months or more.

An account enabled in the system is not an active customer: active means paid service in force. A delinquent customer who still has access stays in the base. Paused, frozen and onboarding are statuses of their own: the current book can be active plus onboarding plus paused, but the default answer to how many active customers uses active only. Before marking someone inactive, check the safeguards: recent purchase or billing, renewal in the next 30 days, an active-until date in the future.

If the routine writes status back to the CRM, it stops on its own when the source is stale (for example, no load for more than 30 days), when the record count dropped below expected, or when the run would deactivate more than 20% of the base. A late source makes it look like nobody bought anything.