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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.
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
SOC 職業分類に基づく
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Klaviyo API and developer integration expertise. Event tracking, SDKs, webhooks, rate limits, OAuth, catalog sync, and code patterns. Use when the user asks about Klaviyo API, integrating with Klaviyo, tracking events, building custom integrations, webhook handling, or developer implementation. For marketing strategy, flow optimization, and campaign auditing, see the klaviyo-analyst skill.
Pre-push hygiene check for GitHub repositories. Scans for PII, secrets, and sensitive data before pushing. Audits commit messages, enforces repo-specific blocklists, and rate-limits pushes to avoid GitHub abuse detection. Use before any git push, especially to public repos.
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Comprehensive content marketing toolkit with brand voice analysis, SEO optimization scripts, content frameworks, social media strategy, and content calendar planning. Use when writing blog posts, creating social media content, analyzing brand voice, optimizing SEO, planning content calendars, or developing content strategy. For deep SEO writing optimization, see the seo-content-writer skill.
| name | retention-churn-prevention |
| description | 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. |
| license | MIT |
| origin | custom |
| author | Rebecca Rae Barton |
| author_url | https://github.com/thatrebeccarae |
| metadata | {"version":"1.0.0","category":"growth","domain":"retention","updated":"2026-03-18T00:00:00.000Z","tested":"2026-03-18T00:00:00.000Z","tested_with":"Claude Code v2.1"} |
Analyze churn, predict at-risk customers, and design retention strategies.
git clone https://github.com/thatrebeccarae/claude-marketing.git && cp -r claude-marketing/skills/retention-churn-prevention ~/.claude/skills/
| Type | Definition | Signal |
|---|---|---|
| Voluntary | Customer actively cancels | Cancellation request, downgrade |
| Involuntary | Payment failure, card expiry | Failed charge, dunning |
| Silent | Stops using but does not cancel | Usage decline, no logins |
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
| Metric | Excellent | Good | Concerning |
|---|---|---|---|
| Monthly churn (SaaS) | <1% | 1-2% | >3% |
| Annual churn (SaaS) | <5% | 5-10% | >15% |
| Net revenue retention | >120% | 100-120% | <100% |
| Signal | Weight | Healthy | At Risk |
|---|---|---|---|
| Product usage | 25% | Daily/weekly | Monthly or less |
| Feature adoption | 20% | 5+ features | 1-2 features |
| Support sentiment | 15% | Positive/none | Negative |
| Billing health | 15% | On time, expanding | Late, downgrading |
| Engagement | 15% | Opens, clicks | Ignores |
| NPS/CSAT | 10% | Promoter (9-10) | Detractor (0-6) |
| Timeframe | Signal | Action |
|---|---|---|
| 7 days | Login frequency drops 50%+ | In-app nudge, value reminder |
| 14 days | Key feature usage stops | CS outreach, usage tips |
| 30 days | No logins for 2+ weeks | Personal CS email, re-engagement |
| 60 days | NPS detractor, unresolved ticket | Executive escalation, save offer |
| 90 days | Cancellation signals | Retention call, custom offer |
| Post-Churn Period | Response Rate | Approach |
|---|---|---|
| 0-7 days | 15-25% | Immediate save, address exit reason |
| 7-30 days | 8-15% | New feature announcement, incentive |
| 30-90 days | 3-8% | Major update, significant discount |
| 90+ days | <3% | Annual check-in |
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
Simple CLV = ARPU / Monthly Churn Rate
Full CLV = ARPU * Gross Margin % * (1 / Churn Rate)
CLV:CAC ratio target: >3:1