churn-prevention

작성자: coreyhaines31

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...

npx skills add https://github.com/coreyhaines31/marketingskills --skill churn-prevention

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:

TypeCauseSolution
VoluntaryCustomer chooses to cancelCancel flows, save offers, exit surveys
InvoluntaryPayment failsDunning 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:

  1. Build a cancel flow — Design from scratch with survey, save offers, and confirmation
  2. Optimize an existing flow — Analyze cancel data and improve save rates
  3. 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:

ReasonWhat It Tells You
Too expensivePrice sensitivity, may respond to discount or downgrade
Not using it enoughLow engagement, may respond to pause or onboarding help
Missing a featureProduct gap, show roadmap or workaround
Switching to competitorCompetitive pressure, understand what they offer
Technical issues / bugsProduct quality, escalate to support
Temporary / seasonal needUsage pattern, offer pause
Business closed / changedUnavoidable, learn and let go gracefully
OtherCatch-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 ReasonPrimary OfferFallback Offer
Too expensiveDiscount (20-30% for 2-3 months)Downgrade to lower plan
Not using it enoughPause (1-3 months)Free onboarding session
Missing featureRoadmap preview + timelineWorkaround guide
Switching to competitorCompetitive comparison + discountFeedback session
Technical issuesEscalate to support immediatelyCredit + priority fix
Temporary / seasonalPause subscriptionDowngrade temporarily
Business closedSkip 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:

SignalRisk LevelTimeframe
Login frequency drops 50%+High2-4 weeks before cancel
Key feature usage stopsHigh1-3 weeks before cancel
Support tickets spike then stopHigh1-2 weeks before cancel
Email open rates declineMedium2-6 weeks before cancel
Billing page visits increaseHighDays before cancel
Team seats removedHigh1-2 weeks before cancel
Data export initiatedCriticalDays before cancel
NPS score drops below 6Medium1-3 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
)
ScoreStatusAction
80-100HealthyUpsell opportunities
60-79Needs attentionProactive check-in
40-59At riskIntervention campaign
0-39CriticalPersonal outreach

Proactive Interventions

Before they think about cancelling:

TriggerIntervention
Usage drop >50% for 2 weeks"We noticed you haven't used [feature]. Need help?" email
Approaching plan limitUpgrade nudge (not a wall — paywalls handles this)
No login for 14 daysRe-engagement email with recent product updates
NPS detractor (0-6)Personal follow-up within 24 hours
Support ticket unresolved >48hEscalation + proactive status update
Annual renewal in 30 daysValue 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 TypeExamplesRetry Strategy
Soft decline (temporary)Insufficient funds, processor timeoutRetry 3-5 times over 7-10 days
Hard decline (permanent)Card stolen, account closedDon't retry — ask for new card
Authentication required3D Secure, SCASend 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

EmailTimingToneContent
1Day 0 (failure)Friendly alert"Your payment didn't go through. Update your card."
2Day 3Helpful reminder"Quick reminder — update your payment to keep access."
3Day 7Urgency"Your account will be paused in 3 days. Update now."
4Day 10Final 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

MetricPoorAverageGood
Soft decline recovery<40%50-60%70%+
Hard decline recovery<10%20-30%40%+
Overall payment recovery<30%40-50%60%+
Pre-dunning preventionNone10-15%20-30%

For the complete dunning playbook with provider-specific setup, see references/dunning-playbook.md.


Metrics & Measurement

Key Churn Metrics

MetricFormulaTarget
Monthly churn rateChurned customers / Start-of-month customers<5% B2C, <2% B2B
Revenue churn (net)(Lost MRR - Expansion MRR) / Start MRRNegative (net expansion)
Cancel flow save rateSaved / Total cancel sessions25-35%
Offer acceptance rateAccepted offers / Shown offers15-25%
Pause reactivation rateReactivated / Total paused60-80%
Dunning recovery rateRecovered / Total failed payments50-60%
Time to cancelDays from first churn signal to cancelTrack 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:

TestHypothesisMetric
Discount % (20% vs 30%)Higher discount saves moreSave rate, LTV impact
Pause duration (1 vs 3 months)Longer pause increases return rateReactivation rate
Survey placement (before vs after offer)Survey-first personalizes offersSave rate
Offer presentation (modal vs full page)Full page gets more attentionSave rate
Copy tone (empathetic vs direct)Empathetic reduces frictionSave 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

ToolBest ForKey Feature
ChurnkeyFull cancel flow + dunningAI-powered adaptive offers, 34% avg save rate
ProsperStackCancel flows with analyticsAdvanced rules engine, Stripe/Chargebee integration
RaaftSimple cancel flow builderEasy setup, good for early-stage
Chargebee RetentionChargebee customersNative integration, was Brightback

Billing Providers (Dunning)

ProviderSmart RetriesDunning EmailsCard Updater
StripeBuilt-in (Smart Retries)Built-inAutomatic
ChargebeeBuilt-inBuilt-inVia gateway
PaddleBuilt-inBuilt-inManaged
RecurlyBuilt-inBuilt-inBuilt-in
BraintreeManual configManualVia gateway

Related CLI Tools

ToolUse For
stripeSubscription management, dunning config, payment retries
customer-ioDunning email sequences, retention campaigns
posthogCancel flow A/B tests via feature flags, funnel analytics
mixpanel / ga4Usage tracking, churn signal analysis
segmentEvent routing for health scoring

Related Skills

  • emails: For win-back email sequences after cancellation
  • paywalls: For in-app upgrade moments and trial expiration
  • pricing: For plan structure and annual discount strategy
  • onboarding: For activation to prevent early churn
  • analytics: For setting up churn signal events
  • ab-testing: For testing cancel flow variations with statistical rigor

coreyhaines31의 다른 스킬

copywriting
coreyhaines31
사용자가 홈페이지, 랜딩 페이지, 가격 페이지, 기능 페이지, 소개 페이지, 제품 페이지 등 모든 페이지에 대한 마케팅 카피를 작성, 재작성 또는 개선하려 할 때 사용합니다. 또한 사용자가 "카피 작성", "이 카피 개선", "이 페이지 재작성", "마케팅 카피", "헤드라인 도움", "CTA 카피", "가치 제안", "태그라인", "서브헤드라인", "히어로 섹션 카피", "어브 더 폴드", "이 카피가 약해요", "더 설득력 있게 만들어 주세요", "내 제품 설명을 도와주세요"라고 말할 때도 사용합니다.
marketingcreativecommunication
seo-audit
coreyhaines31
When the user wants to audit, review, or diagnose SEO issues on their site. Also use when the user mentions "SEO audit," "technical SEO," "why am I not ranking," "SEO issues," "on-page SEO," "meta tags review," "SEO health check," "my traffic dropped," "lost rankings," "not showing up in Google," "site isn't ranking," "Google update hit me," "page speed," "core web vitals," "crawl errors," or "indexing issues." Use this even if the user just says something vague like "my SEO is bad" or "help...
marketingresearchdata-analysis
marketing-psychology
coreyhaines31
When the user wants to apply psychological principles, mental models, or behavioral science to marketing. Also use when the user mentions 'psychology,' 'mental models,' 'cognitive bias,' 'persuasion,' 'behavioral science,' 'why people buy,' 'decision-making,' 'consumer behavior,' 'anchoring,' 'social proof,' 'scarcity,' 'loss aversion,' 'framing,' or 'nudge.' Use this whenever someone wants to understand or leverage how people think and make decisions in a marketing context. For applying...
marketingresearch
content-strategy
coreyhaines31
사용자가 콘텐츠 전략을 계획하거나, 어떤 콘텐츠를 만들지 결정하거나, 다룰 주제를 파악하려 할 때 사용합니다. 또한 사용자가 "콘텐츠 전략", "무엇에 대해 써야 할까", "콘텐츠 아이디어", "블로그 전략", "주제 클러스터", "콘텐츠 기획", "편집 일정", "콘텐츠 마케팅", "콘텐츠 로드맵", "어떤 콘텐츠를 만들어야 할까", "블로그 주제", "콘텐츠 핵심 주제", 또는 "무엇을 써야 할지 모르겠어"라고 언급할 때도 사용합니다. 누군가 어떤 콘텐츠를 만들지 결정하는 데 도움이 필요할 때마다 사용하세요.
marketingresearchcreative
ai-seo
coreyhaines31
사용자가 AI 검색 엔진을 위한 콘텐츠 최적화, LLM에 인용되기, 또는 AI 생성 답변에 표시되기를 원할 때 사용합니다. 또한 사용자가 'AI SEO', 'AEO', 'GEO', 'LLMO', 'answer engine optimization', 'generative engine optimization', 'LLM optimization', 'AI Overviews', 'optimize for ChatGPT', 'optimize for Perplexity', 'AI citations', 'AI visibility', 'zero-click search', 'how do I show up in AI answers', 'LLM mentions', 또는 'optimize for Claude/Gemini'를 언급할 때도 사용합니다. 누군가가... 할 때마다 사용하세요.
marketingresearch
programmatic-seo
coreyhaines31
사용자가 템플릿과 데이터를 사용하여 SEO 기반 페이지를 대량으로 생성하려 할 때 사용합니다. 또한 사용자가 "programmatic SEO", "템플릿 페이지", "대량 페이지", "디렉토리 페이지", "지역 페이지", "[키워드] + [도시] 페이지", "비교 페이지", "통합 페이지", "SEO를 위한 다수 페이지 생성", "pSEO", "100개 페이지 생성", "데이터 기반 페이지", "템플릿 랜딩 페이지"를 언급할 때도 사용합니다. 다양한 키워드나 위치를 대상으로 유사한 페이지를 많이 만들고자 할 때 이 기능을 사용하세요. 예를 들어...
marketingdata-analysisweb-scraping
marketing-ideas
coreyhaines31
When the user needs marketing ideas, inspiration, or strategies for their SaaS or software product. Also use when the user asks for 'marketing ideas,' 'growth ideas,' 'how to market,' 'marketing strategies,' 'marketing tactics,' 'ways to promote,' 'ideas to grow,' 'what else can I try,' 'I don't know how to market this,' 'brainstorm marketing,' or 'what marketing should I do.' Use this as a starting point whenever someone is stuck or looking for inspiration on how to grow. For specific...
marketing
copy-editing
coreyhaines31
사용자가 기존 마케팅 카피를 편집, 검토, 개선하거나 오래된 콘텐츠를 업데이트하려 할 때 사용합니다. 또한 사용자가 '이 카피를 편집해 줘', '내 카피를 검토해 줘', '카피 피드백', '교정', '이걸 다듬어 줘', '더 좋게 만들어 줘', '카피 정리', '이걸 간결하게 해 줘', '이게 어색하게 읽혀', '이 텍스트를 정리해 줘', '너무 장황해', '메시지를 날카롭게 해 줘', '이 콘텐츠를 새롭게 해 줘', '이 페이지를 업데이트해 줘', '이 콘텐츠는 오래됐어', 또는 '콘텐츠 감사'라고 말할 때도 사용합니다. 사용자가 이미 카피를 가지고 있고
documentcommunicationmarketing