Why customers leave

• churn
• cancel
• leaving
• retention
• not renewing
• lost customer

• Did they ever reach first value?
• When did usage or contact actually stop, relative to when they cancelled?
• Which segment and which channel did they come from?
• Was the reason given the reason, or the polite version?

• cancellations by segment and channel
• activity before cancellation
• time from purchase to cancellation
• stated reasons

• Wrong customers acquired
• Value never reached
• A product gap concentrated in one segment

• If
  Most leavers never reached first value
  Then
  This is an onboarding problem, not a product one.
• If
  Leavers cluster in one channel or segment
  Then
  It is an acquisition-quality problem; fix qualification.
• If
  Long-tenured customers leave
  Then
  Value decays over time — look at expansion and outcomes, not setup.

Classify the last ten departures into never-activated, wrong-fit, or value-decayed, using records rather than recollection.

Read after 21 days.

• At least seven of ten classify cleanly into one bucket
• One dominant cause is identifiable

• Departures spread evenly across all three — there is no single cause and no single fix

• Never-activated dominates → Run onboarding design.
• Wrong-fit dominates → Run customer profile discovery.
• Value-decay dominates → Run expansion logic and behaviour-led roadmap.

Aury can carry out: read company, prepare document, file memory, flag risk. Specialists involved: operations, product, research.

Your approval: Contacting departed customers is founder-approved.

Requires at least ten departures to classify. Below that, treat each as an anecdote.

Stated reasons are unreliable. Behaviour before cancellation is the stronger evidence.

• Sourced operator experience: Churn-classification practice in recurring-revenue businesses
• Aurygine synthesis: Aurygine synthesis across founder journeys

Confidence: high. Last reviewed 2026-08-25. Your company's own recorded results override this playbook whenever the two disagree.