onewave-ai Churn Autopsy
Dissect a client departure with forensic rigor and produce churn-autopsy.md: a historical record and retention playbook that turns a loss into organizational learning.
Contents
references/inputs.md-- required and optional data to gather before analysisreferences/analysis-framework.md-- the six-phase forensic methodreferences/root-cause-taxonomy.md-- root cause categories and subcategoriesreferences/output-template.md-- fullchurn-autopsy.mdreport structurereferences/standards.md-- objectivity, rigor, sensitivity, incomplete-data, and operating rules
Workflow
- Collect. Gather all available inputs per
references/inputs.md. Read provided files directly; query connected CRM and analytics MCP tools for account, usage, and support data. Note any gaps. - Organize. Build the full chronological timeline from first touch to cancellation before attempting analysis.
- Analyze. Apply the six phases in
references/analysis-framework.mdsystematically, without skipping: baseline, timeline of decline, root cause classification, missed warning signs, counterfactual analysis, lessons learned. - Classify. Assign one primary root cause and any contributing causes using
references/root-cause-taxonomy.md. - Draft. Write the report in the structure defined in
references/output-template.md. - Challenge. Review every conclusion against
references/standards.md; attempt to disprove each finding before keeping it. - Finalize. Produce
churn-autopsy.mdwith all sections complete in the current working directory or a user-specified location.