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retention-churn-prevention

Customer retention analysis, churn prediction, cohort analysis, win-back campaigns, and loyalty program design. Use when the user asks about churn, retention, customer lifetime value, cohort analysis, or win-back strategies.

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thatrebeccarae/claude-marketing

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  • SKILL.md3.9 KB
  • EXAMPLES.md1.8 KB
  • LICENSE1.0 KB
  • REFERENCE.md235 B

SKILL.md (original)

Review the instructions the agent will receive before you install.

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

TypeDefinitionSignal
VoluntaryCustomer actively cancelsCancellation request, downgrade
InvoluntaryPayment failure, card expiryFailed charge, dunning
SilentStops using but does not cancelUsage decline, no logins

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

MetricExcellentGoodConcerning
Monthly churn (SaaS)<1%1-2%>3%
Annual churn (SaaS)<5%5-10%>15%
Net revenue retention>120%100-120%<100%

Customer Health Scoring

SignalWeightHealthyAt Risk
Product usage25%Daily/weeklyMonthly or less
Feature adoption20%5+ features1-2 features
Support sentiment15%Positive/noneNegative
Billing health15%On time, expandingLate, downgrading
Engagement15%Opens, clicksIgnores
NPS/CSAT10%Promoter (9-10)Detractor (0-6)

Early Warning Signals

TimeframeSignalAction
7 daysLogin frequency drops 50%+In-app nudge, value reminder
14 daysKey feature usage stopsCS outreach, usage tips
30 daysNo logins for 2+ weeksPersonal CS email, re-engagement
60 daysNPS detractor, unresolved ticketExecutive escalation, save offer
90 daysCancellation signalsRetention call, custom offer

Win-Back Campaigns

Timing

Post-Churn PeriodResponse RateApproach
0-7 days15-25%Immediate save, address exit reason
7-30 days8-15%New feature announcement, incentive
30-90 days3-8%Major update, significant discount
90+ days<3%Annual check-in

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

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