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Churn Precursor Monitor

Tests named behavioral patterns, champion contact going silent, engagement declining, distinct-contact count contracting, against a client's own past churned accounts, validates only the patterns that actually recurred often enough to trust, then applies just those to flag which currently-active accounts are showing the same shape right now.

Any CRM

The problem

A churn postmortem explains what happened to one account after it's already gone. The more useful question is which behavioral patterns keep showing up before churn, so they become a warning on accounts that haven't churned yet, not a footnote in a retro.

How it works

01Phase 1: tests whether the champion contact going silent, overall engagement declining, or the number of active contacts contracting actually preceded past churns for this specific book of business
02Only validates a pattern once it recurred in at least half of the churned accounts with enough history to judge, and there were at least 3 to judge it against
03Phase 2: applies only the validated patterns to currently-active accounts, never an unvalidated rule
04Requires at least two validated patterns to fire at once before calling an account at-risk, one firing pattern gets watched, not flagged

Verified on real test data

Churn Precursor Monitor

5 synthetic churned accounts used to calibrate three precursor patterns, plus a deliberately clean churned account to keep the hit rate honest, then applied forward to 4 active accounts covering a full cluster, a single signal, a genuinely healthy account, and a thin-history account.

3/3

Precursors validated

1/1

At-risk account correctly flagged

1/1

Single-signal account correctly held at "watching"

→Correctly validated all three precursor patterns at an 80% hit rate across 5 judgeable churned accounts, and correctly left one deliberately clean churned account out of the "fired" count instead of forcing a match.
→Correctly flagged one active account at-risk with all three validated precursors firing at once (champion silent 90 days, engagement down, distinct contacts contracted), naming each one individually.
→Correctly held a second active account at "watching" despite a real engagement decline, because only one of the three validated precursors fired, and correctly cleared two other active accounts showing no validated precursor at all.

The same three patterns that preceded four out of five past churns are now being tracked live on accounts that have not churned yet, and only one of four active accounts actually matches the full pattern.

See the full test run →

Questions about Churn Precursor Monitor

What happens if none of the three patterns validate?

Phase 2 is skipped entirely and the report says so plainly, rather than applying a generic industry rule that was never actually tested against this client's own churn history.

Is this a predictive machine-learning model?

No. It's three specific, named, rule-based checks, not a trained classifier. The calibration step is what makes it more than a generic checklist: a pattern only gets applied forward once it's proven true for this book of business, not assumed true in general.

Runs against your CRM using your own credentials, through your own AI instance. We don't copy, store, or retain your data.

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