All case studies

A pet health subscription brand · Pet · Subscription

$30M+ GMVAnomaly DetectionFor: Head of Retention

Telling real churn apart from broken billing

Monthly cohort reporting showed rising cancellations. The team planned a retention campaign for a problem that was operational.

Same day
Detection of the failure spike, down from a monthly cycle
1,200
Subscribers recovered once billing was fixed
$85K
Revenue saved from a mis-targeted retention push
0
Retention campaigns launched for the wrong cause

Their unseen challenge

Churn that was not churn

Issue
  • Cancellations rose sharply but only surfaced in the monthly cohort report.
  • Nothing separated voluntary churn from failed payments and retries.
Effect
  • Weeks of subscribers lost to a fixable operational fault.
  • A retention budget nearly spent on the wrong problem.
Result
  • Avoidable subscriber loss.
  • Misdirected retention spend.
Impact
1,200 subscribers recovered and $85K in mis-targeted retention spend avoided

The solution

Anomaly detection on subscription signals

Consequential watches payment, retry, and cancellation events together, so an operational fault never reads as customer behaviour.

Payment signal monitoring

Failure and retry rates are tracked as revenue metrics.

Cause separation

Voluntary churn is reported separately from involuntary churn.

Same-day alerts

A spike surfaces in Slack the day it starts.

The results

What changed with Consequential

Monthly to same day

Detection moved from a monthly cycle to the day of the spike.

Subscribers recovered

Involuntary cancellations were reversed once billing was corrected.

Right diagnosis

The team stopped treating an operational fault as a retention problem.

Ongoing coverage

The same check runs continuously.

We were about to launch a win-back campaign for customers who never meant to leave.Head of Retention, pet subscription brand

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