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Use when users are cancelling, failed payments are rising, or subscription retention needs improvement.","YYC-Cube\u002FYYC3-Knowledge-Base","YYC-Cube","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F235006543?v=4","01M79J2PH4SWD2X0825X6PN748","yyc3","01M79J2PHVK3F6ZBYT8K2SCZCW",1,"MIT","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-antigravity-awesome-skills\u002Fplugins\u002Fantigravity-awesome-skills-claude\u002Fskills\u002Fchurn-prevention\u002FSKILL.md",[],[],"2026-11-15 14:19:17",false,"---\nname: churn-prevention\ndescription: \"Reduce voluntary and involuntary churn with cancel flows, save offers, dunning, win-back tactics, and retention strategy. Use when users are cancelling, failed payments are rising, or subscription retention needs improvement.\"\nrisk: unknown\nsource: \"https:\u002F\u002Fgithub.com\u002Fcoreyhaines31\u002Fmarketingskills\"\ndate_added: \"2026-03-21\"\nmetadata:\n  version: 1.1.0\n---\n\n# Churn Prevention\n\nYou are an expert in SaaS retention and churn prevention. Your goal is to help reduce both voluntary churn (customers choosing to cancel) and involuntary churn (failed payments) through well-designed cancel flows, dynamic save offers, proactive retention, and dunning strategies.\n\n## When to Use\n- Use when churn is rising or cancellation behavior needs intervention.\n- Use when designing cancel flows, save offers, dunning, or retention programs.\n- Use when the user wants to reduce either voluntary or involuntary churn.\n\n## Before Starting\n\n**Check for product marketing context first:**\nIf `.agents\u002Fproduct-marketing-context.md` exists (or `.claude\u002Fproduct-marketing-context.md` in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.\n\nGather this context (ask if not provided):\n\n### 1. Current Churn Situation\n- What's your monthly churn rate? (Voluntary vs. involuntary if known)\n- How many active subscribers?\n- What's the average MRR per customer?\n- Do you have a cancel flow today, or does cancel happen instantly?\n\n### 2. Billing & Platform\n- What billing provider? (Stripe, Chargebee, Paddle, Recurly, Braintree)\n- Monthly, annual, or both billing intervals?\n- Do you support plan pausing or downgrades?\n- Any existing retention tooling? (Churnkey, ProsperStack, Raaft)\n\n### 3. Product & Usage Data\n- Do you track feature usage per user?\n- Can you identify engagement drop-offs?\n- Do you have cancellation reason data from past churns?\n- What's your activation metric? (What do retained users do that churned users don't?)\n\n### 4. Constraints\n- B2B or B2C? (Affects flow design)\n- Self-serve cancellation required? (Some regulations mandate easy cancel)\n- Brand tone for offboarding? (Empathetic, direct, playful)\n\n---\n\n## How This Skill Works\n\nChurn has two types requiring different strategies:\n\n| Type | Cause | Solution |\n|------|-------|----------|\n| **Voluntary** | Customer chooses to cancel | Cancel flows, save offers, exit surveys |\n| **Involuntary** | Payment fails | Dunning emails, smart retries, card updaters |\n\nVoluntary churn is typically 50-70% of total churn. Involuntary churn is 30-50% but is often easier to fix.\n\nThis skill supports three modes:\n\n1. **Build a cancel flow** — Design from scratch with survey, save offers, and confirmation\n2. **Optimize an existing flow** — Analyze cancel data and improve save rates\n3. **Set up dunning** — Failed payment recovery with retries and email sequences\n\n---\n\n## Cancel Flow Design\n\n### The Cancel Flow Structure\n\nEvery cancel flow follows this sequence:\n\n```\nTrigger → Survey → Dynamic Offer → Confirmation → Post-Cancel\n```\n\n**Step 1: Trigger**\nCustomer clicks \"Cancel subscription\" in account settings.\n\n**Step 2: Exit Survey**\nAsk why they're cancelling. This determines which save offer to show.\n\n**Step 3: Dynamic Save Offer**\nPresent a targeted offer based on their reason (discount, pause, downgrade, etc.)\n\n**Step 4: Confirmation**\nIf they still want to cancel, confirm clearly with end-of-billing-period messaging.\n\n**Step 5: Post-Cancel**\nSet expectations, offer easy reactivation path, trigger win-back sequence.\n\n### Exit Survey Design\n\nThe exit survey is the foundation. Good reason categories:\n\n| Reason | What It Tells You |\n|--------|-------------------|\n| Too expensive | Price sensitivity, may respond to discount or downgrade |\n| Not using it enough | Low engagement, may respond to pause or onboarding help |\n| Missing a feature | Product gap, show roadmap or workaround |\n| Switching to competitor | Competitive pressure, understand what they offer |\n| Technical issues \u002F bugs | Product quality, escalate to support |\n| Temporary \u002F seasonal need | Usage pattern, offer pause |\n| Business closed \u002F changed | Unavoidable, learn and let go gracefully |\n| Other | Catch-all, include free text field |\n\n**Survey best practices:**\n- 1 question, single-select with optional free text\n- 5-8 reason options max (avoid decision fatigue)\n- Put most common reasons first (review data quarterly)\n- Don't make it feel like a guilt trip\n- \"Help us improve\" framing works better than \"Why are you leaving?\"\n\n### Dynamic Save Offers\n\nThe key insight: **match the offer to the reason.** A discount won't save someone who isn't using the product. A feature roadmap won't save someone who can't afford it.\n\n**Offer-to-reason mapping:**\n\n| Cancel Reason | Primary Offer | Fallback Offer |\n|---------------|---------------|----------------|\n| Too expensive | Discount (20-30% for 2-3 months) | Downgrade to lower plan |\n| Not using it enough | Pause (1-3 months) | Free onboarding session |\n| Missing feature | Roadmap preview + timeline | Workaround guide |\n| Switching to competitor | Competitive comparison + discount | Feedback session |\n| Technical issues | Escalate to support immediately | Credit + priority fix |\n| Temporary \u002F seasonal | Pause subscription | Downgrade temporarily |\n| Business closed | Skip offer (respect the situation) | — |\n\n### Save Offer Types\n\n**Discount**\n- 20-30% off for 2-3 months is the sweet spot\n- Avoid 50%+ discounts (trains customers to cancel for deals)\n- Time-limit the offer (\"This offer expires when you leave this page\")\n- Show the dollar amount saved, not just the percentage\n\n**Pause subscription**\n- 1-3 month pause maximum (longer pauses rarely reactivate)\n- 60-80% of pausers eventually return to active\n- Auto-reactivation with advance notice email\n- Keep their data and settings intact\n\n**Plan downgrade**\n- Offer a lower tier instead of full cancellation\n- Show what they keep vs. what they lose\n- Position as \"right-size your plan\" not \"downgrade\"\n- Easy path back up when ready\n\n**Feature unlock \u002F extension**\n- Unlock a premium feature they haven't tried\n- Extend trial of a higher tier\n- Works best for \"not getting enough value\" reasons\n\n**Personal outreach**\n- For high-value accounts (top 10-20% by MRR)\n- Route to customer success for a call\n- Personal email from founder for smaller companies\n\n### Cancel Flow UI Patterns\n\n```\n┌─────────────────────────────────────┐\n│  We're sorry to see you go          │\n│                                     │\n│  What's the main reason you're      │\n│  cancelling?                        │\n│                                     │\n│  ○ Too expensive                    │\n│  ○ Not using it enough              │\n│  ○ Missing a feature I need         │\n│  ○ Switching to another tool        │\n│  ○ Technical issues                 │\n│  ○ Temporary \u002F don't need right now │\n│  ○ Other: [____________]            │\n│                                     │\n│  [Continue]                         │\n│  [Never mind, keep my subscription] │\n└─────────────────────────────────────┘\n         ↓ (selects \"Too expensive\")\n┌─────────────────────────────────────┐\n│  What if we could help?             │\n│                                     │\n│  We'd love to keep you. Here's a    │\n│  special offer:                     │\n│                                     │\n│  ┌───────────────────────────────┐  │\n│  │  25% off for the next 3 months│  │\n│  │  Save $XX\u002Fmonth               │  │\n│  │                               │  │\n│  │  [Accept Offer]               │  │\n│  └───────────────────────────────┘  │\n│                                     │\n│  Or switch to [Basic Plan] at       │\n│  $X\u002Fmonth →                         │\n│                                     │\n│  [No thanks, continue cancelling]   │\n└─────────────────────────────────────┘\n```\n\n**UI principles:**\n- Keep the \"continue cancelling\" option visible (no dark patterns)\n- One primary offer + one fallback, not a wall of options\n- Show specific dollar savings, not abstract percentages\n- Use the customer's name and account data when possible\n- Mobile-friendly (many cancellations happen on mobile)\n\nFor detailed cancel flow patterns by industry and billing provider, see [references\u002Fcancel-flow-patterns.md](references\u002Fcancel-flow-patterns.md).\n\n---\n\n## Churn Prediction & Proactive Retention\n\nThe best save happens before the customer ever clicks \"Cancel.\"\n\n### Risk Signals\n\nTrack these leading indicators of churn:\n\n| Signal | Risk Level | Timeframe |\n|--------|-----------|-----------|\n| Login frequency drops 50%+ | High | 2-4 weeks before cancel |\n| Key feature usage stops | High | 1-3 weeks before cancel |\n| Support tickets spike then stop | High | 1-2 weeks before cancel |\n| Email open rates decline | Medium | 2-6 weeks before cancel |\n| Billing page visits increase | High | Days before cancel |\n| Team seats removed | High | 1-2 weeks before cancel |\n| Data export initiated | Critical | Days before cancel |\n| NPS score drops below 6 | Medium | 1-3 months before cancel |\n\n### Health Score Model\n\nBuild a simple health score (0-100) from weighted signals:\n\n```\nHealth Score = (\n  Login frequency score × 0.30 +\n  Feature usage score   × 0.25 +\n  Support sentiment     × 0.15 +\n  Billing health        × 0.15 +\n  Engagement score      × 0.15\n)\n```\n\n| Score | Status | Action |\n|-------|--------|--------|\n| 80-100 | Healthy | Upsell opportunities |\n| 60-79 | Needs attention | Proactive check-in |\n| 40-59 | At risk | Intervention campaign |\n| 0-39 | Critical | Personal outreach |\n\n### Proactive Interventions\n\n**Before they think about cancelling:**\n\n| Trigger | Intervention |\n|---------|-------------|\n| Usage drop >50% for 2 weeks | \"We noticed you haven't used [feature]. Need help?\" email |\n| Approaching plan limit | Upgrade nudge (not a wall — paywall-upgrade-cro handles this) |\n| No login for 14 days | Re-engagement email with recent product updates |\n| NPS detractor (0-6) | Personal follow-up within 24 hours |\n| Support ticket unresolved >48h | Escalation + proactive status update |\n| Annual renewal in 30 days | Value recap email + renewal confirmation |\n\n---\n\n## Involuntary Churn: Payment Recovery\n\nFailed payments cause 30-50% of all churn but are the most recoverable.\n\n### The Dunning Stack\n\n```\nPre-dunning → Smart retry → Dunning emails → Grace period → Hard cancel\n```\n\n### Pre-Dunning (Prevent Failures)\n\n- **Card expiry alerts**: Email 30, 15, and 7 days before card expires\n- **Backup payment method**: Prompt for a second payment method at signup\n- **Card updater services**: Visa\u002FMastercard auto-update programs (reduces hard declines 30-50%)\n- **Pre-billing notification**: Email 3-5 days before charge for annual plans\n\n### Smart Retry Logic\n\nNot all failures are the same. Retry strategy by decline type:\n\n| Decline Type | Examples | Retry Strategy |\n|-------------|----------|----------------|\n| Soft decline (temporary) | Insufficient funds, processor timeout | Retry 3-5 times over 7-10 days |\n| Hard decline (permanent) | Card stolen, account closed | Don't retry — ask for new card |\n| Authentication required | 3D Secure, SCA | Send customer to update payment |\n\n**Retry timing best practices:**\n- Retry 1: 24 hours after failure\n- Retry 2: 3 days after failure\n- Retry 3: 5 days after failure\n- Retry 4: 7 days after failure (with dunning email escalation)\n- After 4 retries: Hard cancel with reactivation path\n\n**Smart retry tip:** Retry on the day of the month the payment originally succeeded (if Day 1 worked before, retry on Day 1). Stripe Smart Retries handles this automatically.\n\n### Dunning Email Sequence\n\n| Email | Timing | Tone | Content |\n|-------|--------|------|---------|\n| 1 | Day 0 (failure) | Friendly alert | \"Your payment didn't go through. Update your card.\" |\n| 2 | Day 3 | Helpful reminder | \"Quick reminder — update your payment to keep access.\" |\n| 3 | Day 7 | Urgency | \"Your account will be paused in 3 days. Update now.\" |\n| 4 | Day 10 | Final warning | \"Last chance to keep your account active.\" |\n\n**Dunning email best practices:**\n- Direct link to payment update page (no login required if possible)\n- Show what they'll lose (their data, their team's access)\n- Don't blame (\"your payment failed\" not \"you failed to pay\")\n- Include support contact for help\n- Plain text performs better than designed emails for dunning\n\n### Recovery Benchmarks\n\n| Metric | Poor | Average | Good |\n|--------|------|---------|------|\n| Soft decline recovery | \u003C40% | 50-60% | 70%+ |\n| Hard decline recovery | \u003C10% | 20-30% | 40%+ |\n| Overall payment recovery | \u003C30% | 40-50% | 60%+ |\n| Pre-dunning prevention | None | 10-15% | 20-30% |\n\nFor the complete dunning playbook with provider-specific setup, see [references\u002Fdunning-playbook.md](references\u002Fdunning-playbook.md).\n\n---\n\n## Metrics & Measurement\n\n### Key Churn Metrics\n\n| Metric | Formula | Target |\n|--------|---------|--------|\n| Monthly churn rate | Churned customers \u002F Start-of-month customers | \u003C5% B2C, \u003C2% B2B |\n| Revenue churn (net) | (Lost MRR - Expansion MRR) \u002F Start MRR | Negative (net expansion) |\n| Cancel flow save rate | Saved \u002F Total cancel sessions | 25-35% |\n| Offer acceptance rate | Accepted offers \u002F Shown offers | 15-25% |\n| Pause reactivation rate | Reactivated \u002F Total paused | 60-80% |\n| Dunning recovery rate | Recovered \u002F Total failed payments | 50-60% |\n| Time to cancel | Days from first churn signal to cancel | Track trend |\n\n### Cohort Analysis\n\nSegment churn by:\n- **Acquisition channel** — Which channels bring stickier customers?\n- **Plan type** — Which plans churn most?\n- **Tenure** — When do most cancellations happen? (30, 60, 90 days?)\n- **Cancel reason** — Which reasons are growing?\n- **Save offer type** — Which offers work best for which segments?\n\n### Cancel Flow A\u002FB Tests\n\nTest one variable at a time:\n\n| Test | Hypothesis | Metric |\n|------|-----------|--------|\n| Discount % (20% vs 30%) | Higher discount saves more | Save rate, LTV impact |\n| Pause duration (1 vs 3 months) | Longer pause increases return rate | Reactivation rate |\n| Survey placement (before vs after offer) | Survey-first personalizes offers | Save rate |\n| Offer presentation (modal vs full page) | Full page gets more attention | Save rate |\n| Copy tone (empathetic vs direct) | Empathetic reduces friction | Save rate |\n\n**How to run cancel flow experiments:** Use the **ab-test-setup** skill to design statistically rigorous tests. PostHog is a good fit for cancel flow experiments — its feature flags can split users into different flows server-side, and its funnel analytics track each step of the cancel flow (survey → offer → accept\u002Fdecline → confirm).\n\n---\n\n## Common Mistakes\n\n- **No cancel flow at all** — Instant cancel leaves money on the table. Even a simple survey + one offer saves 10-15%\n- **Making cancellation hard to find** — Hidden cancel buttons breed resentment and bad reviews. Many jurisdictions require easy cancellation (FTC Click-to-Cancel rule)\n- **Same offer for every reason** — A blanket discount doesn't address \"missing feature\" or \"not using it\"\n- **Discounts too deep** — 50%+ discounts train customers to cancel-and-return for deals\n- **Ignoring involuntary churn** — Often 30-50% of total churn and the easiest to fix\n- **No dunning emails** — Letting payment failures silently cancel accounts\n- **Guilt-trip copy** — \"Are you sure you want to abandon us?\" damages brand trust\n- **Not tracking save offer LTV** — A \"saved\" customer who churns 30 days later wasn't really saved\n- **Pausing too long** — Pauses beyond 3 months rarely reactivate. Set limits.\n- **No post-cancel path** — Make reactivation easy and trigger win-back emails, because some churned users will want to come back\n\n---\n\n## Tool Integrations\n\nFor implementation, use the billing, analytics, and experimentation tools available in the current environment.\n\n### Retention Platforms\n\n| Tool | Best For | Key Feature |\n|------|----------|-------------|\n| **Churnkey** | Full cancel flow + dunning | AI-powered adaptive offers, 34% avg save rate |\n| **ProsperStack** | Cancel flows with analytics | Advanced rules engine, Stripe\u002FChargebee integration |\n| **Raaft** | Simple cancel flow builder | Easy setup, good for early-stage |\n| **Chargebee Retention** | Chargebee customers | Native integration, was Brightback |\n\n### Billing Providers (Dunning)\n\n| Provider | Smart Retries | Dunning Emails | Card Updater |\n|----------|:------------:|:--------------:|:------------:|\n| **Stripe** | Built-in (Smart Retries) | Built-in | Automatic |\n| **Chargebee** | Built-in | Built-in | Via gateway |\n| **Paddle** | Built-in | Built-in | Managed |\n| **Recurly** | Built-in | Built-in | Built-in |\n| **Braintree** | Manual config | Manual | Via gateway |\n\n### Related CLI Tools\n\n| Tool | Use For |\n|------|---------|\n| `stripe` | Subscription management, dunning config, payment retries |\n| `customer-io` | Dunning email sequences, retention campaigns |\n| `posthog` | Cancel flow A\u002FB tests via feature flags, funnel analytics |\n| `mixpanel` \u002F `ga4` | Usage tracking, churn signal analysis |\n| `segment` | Event routing for health scoring |\n\n---\n\n## Related Skills\n\n- **email-sequence**: For win-back email sequences after cancellation\n- **paywall-upgrade-cro**: For in-app upgrade moments and trial expiration\n- **pricing-strategy**: For plan structure and annual discount strategy\n- **onboarding-cro**: For activation to prevent early churn\n- **analytics-tracking**: For setting up churn signal events\n- **ab-test-setup**: For testing cancel flow variations with statistical rigor\n\n## Limitations\n- Use this skill only when the task clearly matches the scope described above.\n- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.\n- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.\n","# Churn Prevention\n\nYou are an expert in SaaS retention and churn prevention. Your goal is to help reduce both voluntary churn (customers choosing to cancel) and involuntary churn (failed payments) through well-designed cancel flows, dynamic save offers, proactive retention, and dunning strategies.\n\n## When to Use\n- Use when churn is rising or cancellation behavior needs intervention.\n- Use when designing cancel flows, save offers, dunning, or retention programs.\n- Use when the user wants to reduce either voluntary or involuntary churn.\n\n## Before Starting\n\n**Check for product marketing context first:**\nIf `.agents\u002Fproduct-marketing-context.md` exists (or `.claude\u002Fproduct-marketing-context.md` in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.\n\nGather this context (ask if not provided):\n\n### 1. Current Churn Situation\n- What's your monthly churn rate? (Voluntary vs. involuntary if known)\n- How many active subscribers?\n- What's the average MRR per customer?\n- Do you have a cancel flow today, or does cancel happen instantly?\n\n### 2. Billing & Platform\n- What billing provider? (Stripe, Chargebee, Paddle, Recurly, Braintree)\n- Monthly, annual, or both billing intervals?\n- Do you support plan pausing or downgrades?\n- Any existing retention tooling? (Churnkey, ProsperStack, Raaft)\n\n### 3. Product & Usage Data\n- Do you track feature usage per user?\n- Can you identify engagement drop-offs?\n- Do you have cancellation reason data from past churns?\n- What's your activation metric? (What do retained users do that churned users don't?)\n\n### 4. Constraints\n- B2B or B2C? (Affects flow design)\n- Self-serve cancellation required? (Some regulations mandate easy cancel)\n- Brand tone for offboarding? (Empathetic, direct, playful)\n\n---\n\n## How This Skill Works\n\nChurn has two types requiring different strategies:\n\n| Type | Cause | Solution |\n|------|-------|----------|\n| **Voluntary** | Customer chooses to cancel | Cancel flows, save offers, exit surveys |\n| **Involuntary** | Payment fails | Dunning emails, smart retries, card updaters |\n\nVoluntary churn is typically 50-70% of total churn. Involuntary churn is 30-50% but is often easier to fix.\n\nThis skill supports three modes:\n\n1. **Build a cancel flow** — Design from scratch with survey, save offers, and confirmation\n2. **Optimize an existing flow** — Analyze cancel data and improve save rates\n3. **Set up dunning** — Failed payment recovery with retries and email sequences\n\n---\n\n## Cancel Flow Design\n\n### The Cancel Flow Structure\n\nEvery cancel flow follows this sequence:\n\n```\nTrigger → Survey → Dynamic Offer → Confirmation → Post-Cancel\n```\n\n**Step 1: Trigger**\nCustomer clicks \"Cancel subscription\" in account settings.\n\n**Step 2: Exit Survey**\nAsk why they're cancelling. This determines which save offer to show.\n\n**Step 3: Dynamic Save Offer**\nPresent a targeted offer based on their reason (discount, pause, downgrade, etc.)\n\n**Step 4: Confirmation**\nIf they still want to cancel, confirm clearly with end-of-billing-period messaging.\n\n**Step 5: Post-Cancel**\nSet expectations, offer easy reactivation path, trigger win-back sequence.\n\n### Exit Survey Design\n\nThe exit survey is the foundation. Good reason categories:\n\n| Reason | What It Tells You |\n|--------|-------------------|\n| Too expensive | Price sensitivity, may respond to discount or downgrade |\n| Not using it enough | Low engagement, may respond to pause or onboarding help |\n| Missing a feature | Product gap, show roadmap or workaround |\n| Switching to competitor | Competitive pressure, understand what they offer |\n| Technical issues \u002F bugs | Product quality, escalate to support |\n| Temporary \u002F seasonal need | Usage pattern, offer pause |\n| Business closed \u002F changed | Unavoidable, learn and let go gracefully |\n| Other | Catch-all, include free text field |\n\n**Survey best practices:**\n- 1 question, single-select with optional free text\n- 5-8 reason options max (avoid decision fatigue)\n- Put most common reasons first (review data quarterly)\n- Don't make it feel like a guilt trip\n- \"Help us improve\" framing works better than \"Why are you leaving?\"\n\n### Dynamic Save Offers\n\nThe key insight: **match the offer to the reason.** A discount won't save someone who isn't using the product. A feature roadmap won't save someone who can't afford it.\n\n**Offer-to-reason mapping:**\n\n| Cancel Reason | Primary Offer | Fallback Offer |\n|---------------|---------------|----------------|\n| Too expensive | Discount (20-30% for 2-3 months) | Downgrade to lower plan |\n| Not using it enough | Pause (1-3 months) | Free onboarding session |\n| Missing feature | Roadmap preview + timeline | Workaround guide |\n| Switching to competitor | Competitive comparison + discount | Feedback session |\n| Technical issues | Escalate to support immediately | Credit + priority fix |\n| Temporary \u002F seasonal | Pause subscription | Downgrade temporarily |\n| Business closed | Skip offer (respect the situation) | — |\n\n### Save Offer Types\n\n**Discount**\n- 20-30% off for 2-3 months is the sweet spot\n- Avoid 50%+ discounts (trains customers to cancel for deals)\n- Time-limit the offer (\"This offer expires when you leave this page\")\n- Show the dollar amount saved, not just the percentage\n\n**Pause subscription**\n- 1-3 month pause maximum (longer pauses rarely reactivate)\n- 60-80% of pausers eventually return to active\n- Auto-reactivation with advance notice email\n- Keep their data and settings intact\n\n**Plan downgrade**\n- Offer a lower tier instead of full cancellation\n- Show what they keep vs. what they lose\n- Position as \"right-size your plan\" not \"downgrade\"\n- Easy path back up when ready\n\n**Feature unlock \u002F extension**\n- Unlock a premium feature they haven't tried\n- Extend trial of a higher tier\n- Works best for \"not getting enough value\" reasons\n\n**Personal outreach**\n- For high-value accounts (top 10-20% by MRR)\n- Route to customer success for a call\n- Personal email from founder for smaller companies\n\n### Cancel Flow UI Patterns\n\n```\n┌─────────────────────────────────────┐\n│  We're sorry to see you go          │\n│                                     │\n│  What's the main reason you're      │\n│  cancelling?                        │\n│                                     │\n│  ○ Too expensive                    │\n│  ○ Not using it enough              │\n│  ○ Missing a feature I need         │\n│  ○ Switching to another tool        │\n│  ○ Technical issues                 │\n│  ○ Temporary \u002F don't need right now │\n│  ○ Other: [____________]            │\n│                                     │\n│  [Continue]                         │\n│  [Never mind, keep my subscription] │\n└─────────────────────────────────────┘\n         ↓ (selects \"Too expensive\")\n┌─────────────────────────────────────┐\n│  What if we could help?             │\n│                                     │\n│  We'd love to keep you. Here's a    │\n│  special offer:                     │\n│                                     │\n│  ┌───────────────────────────────┐  │\n│  │  25% off for the next 3 months│  │\n│  │  Save $XX\u002Fmonth               │  │\n│  │                               │  │\n│  │  [Accept Offer]               │  │\n│  └───────────────────────────────┘  │\n│                                     │\n│  Or switch to [Basic Plan] at       │\n│  $X\u002Fmonth →                         │\n│                                     │\n│  [No thanks, continue cancelling]   │\n└─────────────────────────────────────┘\n```\n\n**UI principles:**\n- Keep the \"continue cancelling\" option visible (no dark patterns)\n- One primary offer + one fallback, not a wall of options\n- Show specific dollar savings, not abstract percentages\n- Use the customer's name and account data when possible\n- Mobile-friendly (many cancellations happen on mobile)\n\nFor detailed cancel flow patterns by industry and billing provider, see [references\u002Fcancel-flow-patterns.md](references\u002Fcancel-flow-patterns.md).\n\n---\n\n## Churn Prediction & Proactive Retention\n\nThe best save happens before the customer ever clicks \"Cancel.\"\n\n### Risk Signals\n\nTrack these leading indicators of churn:\n\n| Signal | Risk Level | Timeframe |\n|--------|-----------|-----------|\n| Login frequency drops 50%+ | High | 2-4 weeks before cancel |\n| Key feature usage stops | High | 1-3 weeks before cancel |\n| Support tickets spike then stop | High | 1-2 weeks before cancel |\n| Email open rates decline | Medium | 2-6 weeks before cancel |\n| Billing page visits increase | High | Days before cancel |\n| Team seats removed | High | 1-2 weeks before cancel |\n| Data export initiated | Critical | Days before cancel |\n| NPS score drops below 6 | Medium | 1-3 months before cancel |\n\n### Health Score Model\n\nBuild a simple health score (0-100) from weighted signals:\n\n```\nHealth Score = (\n  Login frequency score × 0.30 +\n  Feature usage score   × 0.25 +\n  Support sentiment     × 0.15 +\n  Billing health        × 0.15 +\n  Engagement score      × 0.15\n)\n```\n\n| Score | Status | Action |\n|-------|--------|--------|\n| 80-100 | Healthy | Upsell opportunities |\n| 60-79 | Needs attention | Proactive check-in |\n| 40-59 | At risk | Intervention campaign |\n| 0-39 | Critical | Personal outreach |\n\n### Proactive Interventions\n\n**Before they think about cancelling:**\n\n| Trigger | Intervention |\n|---------|-------------|\n| Usage drop >50% for 2 weeks | \"We noticed you haven't used [feature]. Need help?\" email |\n| Approaching plan limit | Upgrade nudge (not a wall — paywall-upgrade-cro handles this) |\n| No login for 14 days | Re-engagement email with recent product updates |\n| NPS detractor (0-6) | Personal follow-up within 24 hours |\n| Support ticket unresolved >48h | Escalation + proactive status update |\n| Annual renewal in 30 days | Value recap email + renewal confirmation |\n\n---\n\n## Involuntary Churn: Payment Recovery\n\nFailed payments cause 30-50% of all churn but are the most recoverable.\n\n### The Dunning Stack\n\n```\nPre-dunning → Smart retry → Dunning emails → Grace period → Hard cancel\n```\n\n### Pre-Dunning (Prevent Failures)\n\n- **Card expiry alerts**: Email 30, 15, and 7 days before card expires\n- **Backup payment method**: Prompt for a second payment method at signup\n- **Card updater services**: Visa\u002FMastercard auto-update programs (reduces hard declines 30-50%)\n- **Pre-billing notification**: Email 3-5 days before charge for annual plans\n\n### Smart Retry Logic\n\nNot all failures are the same. Retry strategy by decline type:\n\n| Decline Type | Examples | Retry Strategy |\n|-------------|----------|----------------|\n| Soft decline (temporary) | Insufficient funds, processor timeout | Retry 3-5 times over 7-10 days |\n| Hard decline (permanent) | Card stolen, account closed | Don't retry — ask for new card |\n| Authentication required | 3D Secure, SCA | Send customer to update payment |\n\n**Retry timing best practices:**\n- Retry 1: 24 hours after failure\n- Retry 2: 3 days after failure\n- Retry 3: 5 days after failure\n- Retry 4: 7 days after failure (with dunning email escalation)\n- After 4 retries: Hard cancel with reactivation path\n\n**Smart retry tip:** Retry on the day of the month the payment originally succeeded (if Day 1 worked before, retry on Day 1). Stripe Smart Retries handles this automatically.\n\n### Dunning Email Sequence\n\n| Email | Timing | Tone | Content |\n|-------|--------|------|---------|\n| 1 | Day 0 (failure) | Friendly alert | \"Your payment didn't go through. Update your card.\" |\n| 2 | Day 3 | Helpful reminder | \"Quick reminder — update your payment to keep access.\" |\n| 3 | Day 7 | Urgency | \"Your account will be paused in 3 days. Update now.\" |\n| 4 | Day 10 | Final warning | \"Last chance to keep your account active.\" |\n\n**Dunning email best practices:**\n- Direct link to payment update page (no login required if possible)\n- Show what they'll lose (their data, their team's access)\n- Don't blame (\"your payment failed\" not \"you failed to pay\")\n- Include support contact for help\n- Plain text performs better than designed emails for dunning\n\n### Recovery Benchmarks\n\n| Metric | Poor | Average | Good |\n|--------|------|---------|------|\n| Soft decline recovery | \u003C40% | 50-60% | 70%+ |\n| Hard decline recovery | \u003C10% | 20-30% | 40%+ |\n| Overall payment recovery | \u003C30% | 40-50% | 60%+ |\n| Pre-dunning prevention | None | 10-15% | 20-30% |\n\nFor the complete dunning playbook with provider-specific setup, see [references\u002Fdunning-playbook.md](references\u002Fdunning-playbook.md).\n\n---\n\n## Metrics & Measurement\n\n### Key Churn Metrics\n\n| Metric | Formula | Target |\n|--------|---------|--------|\n| Monthly churn rate | Churned customers \u002F Start-of-month customers | \u003C5% B2C, \u003C2% B2B |\n| Revenue churn (net) | (Lost MRR - Expansion MRR) \u002F Start MRR | Negative (net expansion) |\n| Cancel flow save rate | Saved \u002F Total cancel sessions | 25-35% |\n| Offer acceptance rate | Accepted offers \u002F Shown offers | 15-25% |\n| Pause reactivation rate | Reactivated \u002F Total paused | 60-80% |\n| Dunning recovery rate | Recovered \u002F Total failed payments | 50-60% |\n| Time to cancel | Days from first churn signal to cancel | Track trend |\n\n### Cohort Analysis\n\nSegment churn by:\n- **Acquisition channel** — Which channels bring stickier customers?\n- **Plan type** — Which plans churn most?\n- **Tenure** — When do most cancellations happen? (30, 60, 90 days?)\n- **Cancel reason** — Which reasons are growing?\n- **Save offer type** — Which offers work best for which segments?\n\n### Cancel Flow A\u002FB Tests\n\nTest one variable at a time:\n\n| Test | Hypothesis | Metric |\n|------|-----------|--------|\n| Discount % (20% vs 30%) | Higher discount saves more | Save rate, LTV impact |\n| Pause duration (1 vs 3 months) | Longer pause increases return rate | Reactivation rate |\n| Survey placement (before vs after offer) | Survey-first personalizes offers | Save rate |\n| Offer presentation (modal vs full page) | Full page gets more attention | Save rate |\n| Copy tone (empathetic vs direct) | Empathetic reduces friction | Save rate |\n\n**How to run cancel flow experiments:** Use the **ab-test-setup** skill to design statistically rigorous tests. PostHog is a good fit for cancel flow experiments — its feature flags can split users into different flows server-side, and its funnel analytics track each step of the cancel flow (survey → offer → accept\u002Fdecline → confirm).\n\n---\n\n## Common Mistakes\n\n- **No cancel flow at all** — Instant cancel leaves money on the table. Even a simple survey + one offer saves 10-15%\n- **Making cancellation hard to find** — Hidden cancel buttons breed resentment and bad reviews. Many jurisdictions require easy cancellation (FTC Click-to-Cancel rule)\n- **Same offer for every reason** — A blanket discount doesn't address \"missing feature\" or \"not using it\"\n- **Discounts too deep** — 50%+ discounts train customers to cancel-and-return for deals\n- **Ignoring involuntary churn** — Often 30-50% of total churn and the easiest to fix\n- **No dunning emails** — Letting payment failures silently cancel accounts\n- **Guilt-trip copy** — \"Are you sure you want to abandon us?\" damages brand trust\n- **Not tracking save offer LTV** — A \"saved\" customer who churns 30 days later wasn't really saved\n- **Pausing too long** — Pauses beyond 3 months rarely reactivate. Set limits.\n- **No post-cancel path** — Make reactivation easy and trigger win-back emails, because some churned users will want to come back\n\n---\n\n## Tool Integrations\n\nFor implementation, use the billing, analytics, and experimentation tools available in the current environment.\n\n### Retention Platforms\n\n| Tool | Best For | Key Feature |\n|------|----------|-------------|\n| **Churnkey** | Full cancel flow + dunning | AI-powered adaptive offers, 34% avg save rate |\n| **ProsperStack** | Cancel flows with analytics | Advanced rules engine, Stripe\u002FChargebee integration |\n| **Raaft** | Simple cancel flow builder | Easy setup, good for early-stage |\n| **Chargebee Retention** | Chargebee customers | Native integration, was Brightback |\n\n### Billing Providers (Dunning)\n\n| Provider | Smart Retries | Dunning Emails | Card Updater |\n|----------|:------------:|:--------------:|:------------:|\n| **Stripe** | Built-in (Smart Retries) | Built-in | Automatic |\n| **Chargebee** | Built-in | Built-in | Via gateway |\n| **Paddle** | Built-in | Built-in | Managed |\n| **Recurly** | Built-in | Built-in | Built-in |\n| **Braintree** | Manual config | Manual | Via gateway |\n\n### Related CLI Tools\n\n| Tool | Use For |\n|------|---------|\n| `stripe` | Subscription management, dunning config, payment retries |\n| `customer-io` | Dunning email sequences, retention campaigns |\n| `posthog` | Cancel flow A\u002FB tests via feature flags, funnel analytics |\n| `mixpanel` \u002F `ga4` | Usage tracking, churn signal analysis |\n| `segment` | Event routing for health scoring |\n\n---\n\n## Related Skills\n\n- **email-sequence**: For win-back email sequences after cancellation\n- **paywall-upgrade-cro**: For in-app upgrade moments and trial expiration\n- **pricing-strategy**: For plan structure and annual discount strategy\n- **onboarding-cro**: For activation to prevent early churn\n- **analytics-tracking**: For setting up churn signal events\n- **ab-test-setup**: For testing cancel flow variations with statistical rigor\n\n## Limitations\n- Use this skill only when the task clearly matches the scope described above.\n- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.\n- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.\n",{"name":5,"risk":24,"source":25,"metadata":26,"date_added":28,"description":7},"unknown","https:\u002F\u002Fgithub.com\u002Fcoreyhaines31\u002Fmarketingskills",{"version":27},"1.1.0","2026-03-21","main","87afe6ce96220accf50a345dea46784c8c9f210e","YYC3-Skills-技能包\u002FYYC3-Skills-技能包-antigravity-awesome-skills\u002Fplugins\u002Fantigravity-awesome-skills-claude\u002Fskills\u002Fchurn-prevention",0,"https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base","https:\u002F\u002Fkb.yyc3.top\u002F","https:\u002F\u002Fgithub.com\u002FYYC-Cube","万象归元于云枢 | 深栈智启新纪元","2026-11-10 10:37:32",{"source":8,"skillName":5,"commands":39,"prompt":49,"zipAvailable":50},[40,43,46],{"tool":41,"command":42},"npx","npx skills add YYC-Cube\u002FYYC3-Knowledge-Base --skill churn-prevention",{"tool":44,"command":45},"bunx","bunx skills add YYC-Cube\u002FYYC3-Knowledge-Base --skill churn-prevention",{"tool":47,"command":48},"pnpm","pnpm dlx skills add YYC-Cube\u002FYYC3-Knowledge-Base --skill churn-prevention","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-antigravity-awesome-skills\u002Fplugins\u002Fantigravity-awesome-skills-claude\u002Fskills\u002Fchurn-prevention\u002FSKILL.md",true,[52,58,62],{"path":53,"resourceType":54,"resourceTypeDesc":55,"sizeBytes":56,"sourceHtmlUrl":57},"evals\u002Fevals.json","REFERENCE","参考文档",6702,"https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-antigravity-awesome-skills\u002Fplugins\u002Fantigravity-awesome-skills-claude\u002Fskills\u002Fchurn-prevention\u002Fevals\u002Fevals.json",{"path":59,"resourceType":54,"resourceTypeDesc":55,"sizeBytes":60,"sourceHtmlUrl":61},"references\u002Fcancel-flow-patterns.md",10678,"https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-antigravity-awesome-skills\u002Fplugins\u002Fantigravity-awesome-skills-claude\u002Fskills\u002Fchurn-prevention\u002Freferences\u002Fcancel-flow-patterns.md",{"path":63,"resourceType":54,"resourceTypeDesc":55,"sizeBytes":64,"sourceHtmlUrl":65},"references\u002Fdunning-playbook.md",12688,"https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-Skills-技能包\u002FYYC3-Skills-技能包-antigravity-awesome-skills\u002Fplugins\u002Fantigravity-awesome-skills-claude\u002Fskills\u002Fchurn-prevention\u002Freferences\u002Fdunning-playbook.md",[67,74,81,88,95,102],{"skillNo":68,"name":69,"nameZh":6,"description":70,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":71,"categories":72,"keywords":73,"publishedAt":19},"01M7CTDWHERCXPQCP0K03A86AS","vercel-sandbox","Run agent-browser + Chrome inside Vercel Sandbox microVMs for browser automation from any Vercel-deployed app. Use when the user needs browser automation in a Vercel app (Next.js, SvelteKit, Nuxt, Remix, Astro, etc.), wants to run headless Chrome without binary size limits, needs persistent browser sessions across commands, or wants ephemeral isolated browser environments. Triggers include \"Vercel Sandbox browser\", \"microVM Chrome\", \"agent-browser in sandbox\", \"browser automation on Vercel\", or any task requiring Chrome in a Vercel Sandbox.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Fvercel-sandbox\u002FSKILL.md",[],[],{"skillNo":75,"name":76,"nameZh":6,"description":77,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":78,"categories":79,"keywords":80,"publishedAt":19},"01M7CTD8D2BNJY54S65M47HEJA","slack","Interact with Slack workspaces using browser automation. Use when the user needs to check unread channels, navigate Slack, send messages, extract data, find information, search conversations, or automate any Slack task. Triggers include \"check my Slack\", \"what channels have unreads\", \"send a message to\", \"search Slack for\", \"extract from Slack\", \"find who said\", or any task requiring programmatic Slack interaction.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Fslack\u002FSKILL.md",[],[],{"skillNo":82,"name":83,"nameZh":6,"description":84,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":85,"categories":86,"keywords":87,"publishedAt":19},"01M7CTCSSB8ZP3Q58C3YZDZK1W","electron","Automate Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify, etc.) using agent-browser via Chrome DevTools Protocol. Use when the user needs to interact with an Electron app, automate a desktop app, connect to a running app, control a native app, or test an Electron application. Triggers include \"automate Slack app\", \"control VS Code\", \"interact with Discord app\", \"test this Electron app\", \"connect to desktop app\", or any task requiring automation of a native Electron application.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Felectron\u002FSKILL.md",[],[],{"skillNo":89,"name":90,"nameZh":6,"description":91,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":92,"categories":93,"keywords":94,"publishedAt":19},"01M7CTCBJY76688V4DCZGWFHGQ","dogfood","Systematically explore and test a web application to find bugs, UX issues, and other problems. Use when asked to \"dogfood\", \"QA\", \"exploratory test\", \"find issues\", \"bug hunt\", \"test this app\u002Fsite\u002Fplatform\", or review the quality of a web application. Produces a structured report with full reproduction evidence -- step-by-step screenshots, repro videos, and detailed repro steps for every issue -- so findings can be handed directly to the responsible teams.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Fdogfood\u002FSKILL.md",[],[],{"skillNo":96,"name":97,"nameZh":6,"description":98,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":99,"categories":100,"keywords":101,"publishedAt":19},"01M7CTC4H0FFGVEAQR9PA4GA1A","agent-browser","Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to \"open a website\", \"fill out a form\", \"click a button\", \"take a screenshot\", \"scrape data from a page\", \"test this web app\", \"login to a site\", \"automate browser actions\", or any task requiring programmatic web interaction.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-WebSpec-Web标准\u002FYYC3-WebSpec-Web标准-standards\u002Fbrowser-agent\u002Fskills\u002Fagent-browser\u002FSKILL.md",[],[],{"skillNo":103,"name":104,"nameZh":6,"description":105,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":106,"categories":107,"keywords":108,"publishedAt":19},"01M7CTBKVFYBG78FDSABSDJTTQ","shadcn","Manages shadcn components and projects — adding, searching, fixing, debugging, styling, and composing UI, including chat interfaces. Provides project context, component docs, and usage examples. Applies when working with shadcn\u002Fui, component registries, presets, --preset codes, or any project with a components.json file. Also triggers for \"shadcn init\", \"create an app with --preset\", \"switch to --preset\", and for building a design system or applying a DESIGN.md or brand spec to shadcn\u002Fui.","https:\u002F\u002Fgithub.com\u002FYYC-Cube\u002FYYC3-Knowledge-Base\u002Fblob\u002Fmain\u002FYYC3-UI-界面组件\u002FYYC3-UI-界面组件-ui\u002Fskills\u002Fshadcn\u002FSKILL.md",[],[]]