churn-prevention

name churn-prevention description When the user wants to reduce churn, build cancellation flows, set up save offers, recover failed payments, or implement retention strategies. Also use when the user mentions 'churn,' 'cancel flow,' 'offboarding,' 'save offer,' 'dunning,' 'failed payment recovery,' 'win-back,' 'retention,' 'exit survey,' 'pause subscription,' 'involuntary churn,' 'people keep canceling,' 'churn rate is too high,' 'how do I keep users,' or 'customers are leaving.' Use this whenever someone is losing subscribers or wants to build systems to prevent it. For post-cancel win-back email sequences, see emails. For in-app upgrade paywalls, see paywalls. metadata {"version":"2.0.0"} Churn Prevention 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. Before Starting Check for product marketing context first: If .agents/product-marketing.md exists (or .claude/product-marketing.md , or the legacy product-marketing-context.md filename, 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): 1. Current Churn Situation What's your monthly churn rate? (Voluntary vs. involuntary if known) How many active subscribers? What's the average MRR per customer? Do you have a cancel flow today, or does cancel happen instantly? 2. Billing & Platform What billing provider? (Stripe, Chargebee, Paddle, Recurly, Braintree) Monthly, annual, or both billing intervals? Do you support plan pausing or downgrades? Any existing retention tooling? (Churnkey, ProsperStack, Raaft) 3. Product & Usage Data Do you track feature usage per user? Can you identify engagement drop-offs? Do you have cancellation reason data from past churns? What's your activation metric? (What do retained users do that churned users don't?) 4. Constraints B2B or B2C? (Affects flow design) Self-serve cancellation required? (Some regulations mandate easy cancel) Brand tone for offboarding? (Empathetic, direct, playful) How This Skill Works 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: Build a cancel flow — Design from scratch with survey, save offers, and confirmation Optimize an existing flow — Analyze cancel data and improve save rates Set up dunning — Failed payment recovery with retries and email sequences Cancel Flow Design The Cancel Flow Structure 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. Exit Survey Design 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: 1 question, single-select with optional free text 5-8 reason options max (avoid decision fatigue) Put most common reasons first (review data quarterly) Don't make it feel like a guilt trip "Help us improve" framing works better than "Why are you leaving?" Dynamic Save Offers 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) — Save Offer Types Discount 20-30% off for 2-3 months is the sweet spot Avoid 50%+ discounts (trains customers to cancel for deals) Time-limit the offer ("This offer expires when you leave this page") Show the dollar amount saved, not just the percentage Pause subscription 1-3 month pause maximum (longer pauses rarely reactivate) 60-80% of pausers eventually return to active Auto-reactivation with advance notice email Keep their data and settings intact Plan downgrade Offer a lower tier instead of full cancellation Show what they keep vs. what they lose Position as "right-size your plan" not "downgrade" Easy path back up when ready Feature unlock / extension Unlock a premium feature they haven't tried Extend trial of a higher tier Works best for "not getting enough value" reasons Personal outreach For high-value accounts (top 10-20% by MRR) Route to customer success for a call Personal email from founder for smaller companies Cancel Flow UI Patterns ┌─────────────────────────────────────┐ │ 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: Keep the "continue cancelling" option visible (no dark patterns) One primary offer + one fallback, not a wall of options Show specific dollar savings, not abstract percentages Use the customer's name and account data when possible Mobile-friendly (many cancellations happen on mobile) For detailed cancel flow patterns by industry and billing provider, see references/cancel-flow-patterns.md . Churn Prediction & Proactive Retention The best save happens before the customer ever clicks "Cancel." Risk Signals 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 Health Score Model 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 Proactive Interventions 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 — paywalls 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 Involuntary Churn: Payment Recovery Failed payments cause 30-50% of all churn but are the most recoverable. The Dunning Stack Pre-dunning → Smart retry → Dunning emails → Grace period → Hard cancel Pre-Dunning (Prevent Failures) Card expiry alerts : Email 30, 15, and 7 days before card expires Backup payment method : Prompt for a second payment method at signup Card updater services : Visa/Mastercard auto-update programs (reduces hard declines 30-50%) Pre-billing notification : Email 3-5 days before charge for annual plans Smart Retry Logic 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: Retry 1: 24 hours after failure Retry 2: 3 days after failure Retry 3: 5 days after failure Retry 4: 7 days after failure (with dunning email escalation) After 4 retries: Hard cancel with reactivation path 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. Dunning Email Sequence Email 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: Direct link to payment update page (no login required if possible) Show what they'll lose (their data, their team's access) Don't blame ("your payment failed" not "you failed to pay") Include support contact for help Plain text performs better than designed emails for dunning Recovery Benchmarks 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 . Metrics & Measurement Key Churn Metrics 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 Cohort Analysis Segment churn by: Acquisition channel — Which channels bring stickier customers? Plan type — Which plans churn most? Tenure — When do most cancellations happen? (30, 60, 90 days?) Cancel reason — Which reasons are growing? Save offer type — Which offers work best for which segments? Cancel Flow A/B Tests 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-testing 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. Common Mistakes No cancel flow at all — Instant cancel leaves money on the table. Even a simple survey + one offer saves 10-15% Making cancellation hard to find — Hidden cancel buttons breed resentment and bad reviews. Many jurisdictions require easy cancellation (FTC Click-to-Cancel rule) Same offer for every reason — A blanket discount doesn't address "missing feature" or "not using it" Discounts too deep — 50%+ discounts train customers to cancel-and-return for deals Ignoring involuntary churn — Often 30-50% of total churn and the easiest to fix No dunning emails — Letting payment failures silently cancel accounts Guilt-trip copy — "Are you sure you want to abandon us?" damages brand trust Not tracking save offer LTV — A "saved" customer who churns 30 days later wasn't really saved Pausing too long — Pauses beyond 3 months rarely reactivate. Set limits. No post-cancel path — Make reactivation easy and trigger win-back emails, because some churned users will want to come back Tool Integrations For implementation, see the tools registry . Retention Platforms | Tool | Best For | Key Feature |