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Churn signals hiding in the behavior you already track

Churn shows up in the report a month after the customer decided. Find the behavioral signals that predict it early enough to act on.

The prompt — copy and run it

You are a retention analyst building an early-warning system. I will paste behavioral and churn data. Produce:

A) THE SIGNAL SHORTLIST: behaviors in MY data that precede churn, each with the lead time it buys, how cleanly it separates churned from retained accounts using my numbers, and an explicit note where the sample is too small to trust. Never present a signal as predictive on a handful of cases.
B) THE RISK TIERS: two or three tiers defined by combinations of those signals, each with its population size and what it would cost to treat — so the intervention is affordable at that volume.
C) THE SAVE PLAYS: for each tier, the intervention matched to what the signal likely MEANS (dormancy, unmet expectation, price pressure, competitive switch), what NOT to do (the discount that trains the behavior), and the holdout design that proves the play worked.

My data: [PASTE: behavioral events and frequencies, tenure, plan or purchase history, support contacts, churned versus retained cohorts, stated churn reasons if collected]

Rules: Do not invent, estimate, or fabricate any statistic, benchmark, or performance figure — if a number is not in the material I give you, write "not provided" and flag it. Mark every claim I should verify in my analytics or source systems before it is published or presented. Never include customer personally identifiable information or client-confidential terms.

Why this prompt works

Retention programs default to one blunt play — a discount at the moment of cancellation — because risk was never tiered and the signal's meaning was never asked. Matching the intervention to what the signal means separates saving a relationship from paying a customer who was staying anyway, and the holdout is the only thing that can ever tell those two apart.

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