Retention & Churn Prevention

Analyze churn, predict at-risk customers, and design retention strategies.

Install

git clone https://github.com/thatrebeccarae/claude-marketing.git && cp -r claude-marketing/skills/retention-churn-prevention ~/.claude/skills/

Churn Analysis Framework

Churn Types

Churn Rate Calculation

Monthly churn rate = Customers lost / Customers at start of month
Annual churn rate = 1 - (1 - monthly rate)^12
Net revenue retention = (Start MRR + Expansion - Contraction - Churn) / Start MRR

Benchmarks

Customer Health Scoring

Early Warning Signals

Win-Back Campaigns

Timing

Win-Back Sequence

Email 1 (Day 1): Address exit reason, offer to help
Email 2 (Day 7): New features since they left
Email 3 (Day 14): Comeback incentive (discount or extended trial)
Email 4 (Day 30): Final offer with urgency

Retention Levers

1. Onboarding — Time to first value predicts retention more than any other factor
2. Engagement loops — Regular touchpoints (weekly reports, digests)
3. Feature adoption — Users who adopt 3+ features churn 50% less
4. Community — Community members have 2-3x higher retention
5. Switching costs — Integrations and data create healthy lock-in
6. Proactive support — Reach out before problems become cancellations

CLV Calculation

Simple CLV = ARPU / Monthly Churn Rate
Full CLV = ARPU * Gross Margin % * (1 / Churn Rate)
CLV:CAC ratio target: >3:1

Integration with Other Skills

• klaviyo-analyst — Design retention email flows and win-back sequences
• customer-journey-mapping — Map retention and advocacy stages
• google-analytics — Cohort analysis and engagement metrics
• cro-auditor — Optimize cancellation flow to save more customers