Reduce voluntary and involuntary churn through cancel flows, dynamic save offers, and payment recovery.
Works with
Design exit surveys and targeted save offers (discounts, pauses, downgrades) matched to cancellation reasons, typically recovering 25-35% of at-risk customers
Implement proactive retention by tracking health signals (login frequency, feature usage, support sentiment) and intervening before customers reach the cancel page
Set up dunning sequences with smart payment retries, escalati
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionchurn-preventionExecute the skills CLI command in your project's root directory to begin installation:
Fetches churn-prevention from coreyhaines31/marketingskills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate churn-prevention. Access via /churn-prevention in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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You 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.
Check for product marketing context first:
If .agents/product-marketing-context.md exists (or .claude/product-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.
Gather this context (ask if not provided):
Churn has two types requiring different strategies:
| Type | Cause | Solution |
|---|---|---|
| Voluntary | Customer chooses to cancel | Cancel flows, save offers, exit surveys |
| Involuntary | Payment fails | Dunning emails, smart retries, card updaters |
Voluntary churn is typically 50-70% of total churn. Involuntary churn is 30-50% but is often easier to fix.
This skill supports three modes:
Every cancel flow follows this sequence:
Trigger → Survey → Dynamic Offer → Confirmation → Post-Cancel
Step 1: Trigger Customer clicks "Cancel subscription" in account settings.
Step 2: Exit Survey Ask why they're cancelling. This determines which save offer to show.
Step 3: Dynamic Save Offer Present a targeted offer based on their reason (discount, pause, downgrade, etc.)
Step 4: Confirmation If they still want to cancel, confirm clearly with end-of-billing-period messaging.
Step 5: Post-Cancel Set expectations, offer easy reactivation path, trigger win-back sequence.
The exit survey is the foundation. Good reason categories:
| Reason | What It Tells You |
|---|---|
| Too expensive | Price sensitivity, may respond to discount or downgrade |
| Not using it enough | Low engagement, may respond to pause or onboarding help |
| Missing a feature | Product gap, show roadmap or workaround |
| Switching to competitor | Competitive pressure, understand what they offer |
| Technical issues / bugs | Product quality, escalate to support |
| Temporary / seasonal need | Usage pattern, offer pause |
| Business closed / changed | Unavoidable, learn and let go gracefully |
| Other | Catch-all, include free text field |
Survey best practices:
The 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.
Offer-to-reason mapping:
| Cancel Reason | Primary Offer | Fallback Offer |
|---|---|---|
| Too expensive | Discount (20-30% for 2-3 months) | Downgrade to lower plan |
| Not using it enough | Pause (1-3 months) | Free onboarding session |
| Missing feature | Roadmap preview + timeline | Workaround guide |
| Switching to competitor | Competitive comparison + discount | Feedback session |
| Technical issues | Escalate to support immediately | Credit + priority fix |
| Temporary / seasonal | Pause subscription | Downgrade temporarily |
| Business closed | Skip offer (respect the situation) | — |
Discount
Pause subscription
Plan downgrade
Feature unlock / extension
Personal outreach
┌─────────────────────────────────────┐
│ We're sorry to see you go │
│ │
│ What's the main reason you're │
│ cancelling? │
│ │
│ ○ Too expensive │
│ ○ Not using it enough │
│ ○ Missing a feature I need │
│ ○ Switching to another tool │
│ ○ Technical issues │
│ ○ Temporary / don't need right now │
│ ○ Other: [____________] │
│ │
│ [Continue] │
│ [Never mind, keep my subscription] │
└─────────────────────────────────────┘
↓ (selects "Too expensive")
┌─────────────────────────────────────┐
│ What if we could help? │
│ │
│ We'd love to keep you. Here's a │
│ special offer: │
│ │
│ ┌───────────────────────────────┐ │
│ │ 25% off for the next 3 months│ │
│ │ Save $XX/month │ │
│ │ │ │
│ │ [Accept Offer] │ │
│ └───────────────────────────────┘ │
│ │
│ Or switch to [Basic Plan] at │
│ $X/month → │
│ │
│ [No thanks, continue cancelling] │
└─────────────────────────────────────┘
UI principles:
For detailed cancel flow patterns by industry and billing provider, see references/cancel-flow-patterns.md.
The best save happens before the customer ever clicks "Cancel."
Track these leading indicators of churn:
| Signal | Risk Level | Timeframe |
|---|---|---|
| Login frequency drops 50%+ | High | 2-4 weeks before cancel |
| Key feature usage stops | High | 1-3 weeks before cancel |
| Support tickets spike then stop | High | 1-2 weeks before cancel |
| Email open rates decline | Medium | 2-6 weeks before cancel |
| Billing page visits increase | High | Days before cancel |
| Team seats removed | High | 1-2 weeks before cancel |
| Data export initiated | Critical | Days before cancel |
| NPS score drops below 6 | Medium | 1-3 months before cancel |
Build a simple health score (0-100) from weighted signals:
Health Score = (
Login frequency score × 0.30 +
Feature usage score × 0.25 +
Support sentiment × 0.15 +
Billing health × 0.15 +
Engagement score × 0.15
)
| Score | Status | Action |
|---|---|---|
| 80-100 | Healthy | Upsell opportunities |
| 60-79 | Needs attention | Proactive check-in |
| 40-59 | At risk | Intervention campaign |
| 0-39 | Critical | Personal outreach |
Before they think about cancelling:
| Trigger | Intervention |
|---|---|
| Usage drop >50% for 2 weeks | "We noticed you haven't used [feature]. Need help?" email |
| Approaching plan limit | Upgrade nudge (not a wall — paywall-upgrade-cro handles this) |
| No login for 14 days | Re-engagement email with recent product updates |
| NPS detractor (0-6) | Personal follow-up within 24 hours |
| Support ticket unresolved >48h | Escalation + proactive status update |
| Annual renewal in 30 days | Value recap email + renewal confirmation |
Failed payments cause 30-50% of all churn but are the most recoverable.
Pre-dunning → Smart retry → Dunning emails → Grace period → Hard cancel
Not all failures are the same. Retry strategy by decline type:
| Decline Type | Examples | Retry Strategy |
|---|---|---|
| Soft decline (temporary) | Insufficient funds, processor timeout | Retry 3-5 times over 7-10 days |
| Hard decline (permanent) | Card stolen, account closed | Don't retry — ask for new card |
| Authentication required | 3D Secure, SCA | Send customer to update payment |
Retry timing best practices:
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.
| Timing | Tone | Content | |
|---|---|---|---|
| 1 | Day 0 (failure) | Friendly alert | "Your payment didn't go through. Update your card." |
| 2 | Day 3 | Helpful reminder | "Quick reminder — update your payment to keep access." |
| 3 | Day 7 | Urgency | "Your account will be paused in 3 days. Update now." |
| 4 | Day 10 | Final warning | "Last chance to keep your account active." |
Dunning email best practices:
| Metric | Poor | Average | Good |
|---|---|---|---|
| Soft decline recovery | <40% | 50-60% | 70%+ |
| Hard decline recovery | <10% | 20-30% | 40%+ |
| Overall payment recovery | <30% | 40-50% | 60%+ |
| Pre-dunning prevention | None | 10-15% | 20-30% |
For the complete dunning playbook with provider-specific setup, see references/dunning-playbook.md.
| Metric | Formula | Target |
|---|---|---|
| Monthly churn rate | Churned customers / Start-of-month customers | <5% B2C, <2% B2B |
| Revenue churn (net) | (Lost MRR - Expansion MRR) / Start MRR | Negative (net expansion) |
| Cancel flow save rate | Saved / Total cancel sessions | 25-35% |
| Offer acceptance rate | Accepted offers / Shown offers | 15-25% |
| Pause reactivation rate | Reactivated / Total paused | 60-80% |
| Dunning recovery rate | Recovered / Total failed payments | 50-60% |
| Time to cancel | Days from first churn signal to cancel | Track trend |
Segment churn by:
Test one variable at a time:
| Test | Hypothesis | Metric |
|---|---|---|
| Discount % (20% vs 30%) | Higher discount saves more | Save rate, LTV impact |
| Pause duration (1 vs 3 months) | Longer pause increases return rate | Reactivation rate |
| Survey placement (before vs after offer) | Survey-first personalizes offers | Save rate |
| Offer presentation (modal vs full page) | Full page gets more attention | Save rate |
| Copy tone (empathetic vs direct) | Empathetic reduces friction | Save rate |
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/decline → confirm). See the PostHog integration guide for setup.
For implementation, see the tools registry.
| Tool | Best For | Key Feature |
|---|---|---|
| Churnkey | Full cancel flow + dunning | AI-powered adaptive offers, 34% avg save rate |
| ProsperStack | Cancel flows with analytics | Advanced rules engine, Stripe/Chargebee integration |
| Raaft | Simple cancel flow builder | Easy setup, good for early-stage |
| Chargebee Retention | Chargebee customers | Native integration, was Brightback |
| Provider | Smart Retries | Dunning Emails | Card Updater |
|---|---|---|---|
| Stripe | Built-in (Smart Retries) | Built-in | Automatic |
| Chargebee | Built-in | Built-in | Via gateway |
| Paddle | Built-in | Built-in | Managed |
| Recurly | Built-in | Built-in | Built-in |
| Braintree | Manual config | Manual | Via gateway |
| Tool | Use For |
|---|---|
stripe |
Subscription management, dunning config, payment retries |
customer-io |
Dunning email sequences, retention campaigns |
posthog |
Cancel flow A/B tests via feature flags, funnel analytics |
mixpanel / ga4 |
Usage tracking, churn signal analysis |
segment |
Event routing for health scoring |
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
churn-prevention has been reliable in day-to-day use. Documentation quality is above average for community skills.
churn-prevention is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in churn-prevention — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Keeps context tight: churn-prevention is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend churn-prevention for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Keeps context tight: churn-prevention is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for churn-prevention matched our evaluation — installs cleanly and behaves as described in the markdown.
churn-prevention fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Useful defaults in churn-prevention — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
churn-prevention is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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