本文へ移動
cccskills
無料GitHub で公開

churn-prevention

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.

インストール方法を見る

含まれるファイル(4)

  • SKILL.md18.0 KB
  • evals/evals.json6.5 KB
  • references/cancel-flow-patterns.md10.4 KB
  • references/dunning-playbook.md12.4 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

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

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

ai-seo

無料

When the user wants to optimize content for AI search engines, get cited by LLMs, or appear in AI-generated answers. Also use when the user mentions '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,' 'optimize for Claude/Gemini,' 'llms.txt,' 'OKF,' 'Open Knowledge Format,' 'knowledge bundle,' or 'agent-readable site.' Use this whenever someone wants their content to be cited or surfaced by AI assistants and AI search engines. For traditional technical and on-page SEO audits, see seo-audit. For structured data implementation, see schema.

日本語の概要は準備中です。原文の説明を表示しています。

Nexus-JPF/note-companion8702026年10月12日 更新

analytics

無料

When the user wants to set up, improve, or audit analytics tracking and measurement. Also use when the user mentions "set up tracking," "GA4," "Google Analytics," "conversion tracking," "event tracking," "UTM parameters," "tag manager," "GTM," "analytics implementation," "tracking plan," "how do I measure this," "track conversions," "Mixpanel," "Segment," "are my events firing," or "analytics isn't working." Use this whenever someone asks how to know if something is working or wants to measure marketing results. For choosing attribution models, comparing multi-touch/MMM/incrementality, or reconciling conflicting numbers across tools, see attribution. For A/B test measurement, see ab-testing.

日本語の概要は準備中です。原文の説明を表示しています。

Nexus-JPF/note-companion8702026年10月12日 更新

When the user wants to figure out which marketing actually drives conversions and revenue, choose or interpret an attribution model, or reconcile conflicting numbers across tools. Also use when the user mentions "attribution," "attribution model," "first-touch vs last-touch," "multi-touch," "which channel drives revenue," "what's my real CAC," "my dashboards disagree," "Google/Meta says X but GA says Y," "media mix model," "MMM," "incrementality," "geo lift," "holdout test," "how did you hear about us," "self-reported attribution," "dark social," or wants to instrument attribution themselves — "stitch my bookings to their source," "SavvyCal/Calendly attribution," "close the identify gap," "track conversions on a third-party domain," "first-party / self-hosted attribution." For event tracking setup and UTMs, see analytics. For ad-platform pixels/CAPI, see ads. For pipeline and CRM revenue reporting, see revops. For the AI-search attribution blind spot, see ai-seo.

日本語の概要は準備中です。原文の説明を表示しています。

Nexus-JPF/note-companion8702026年10月12日 更新

When the user wants to find co-marketing partners, plan joint campaigns, or brainstorm partnership opportunities. Use when the user says 'co-marketing,' 'partner marketing,' 'joint campaign,' 'who should we partner with,' 'integration marketing,' 'cross-promotion,' 'collaborate with another company,' 'partnership ideas,' or 'co-brand.' For customer referral programs, see referrals. For launch-specific partnerships, see launch.

日本語の概要は準備中です。原文の説明を表示しています。

Nexus-JPF/note-companion8702026年10月12日 更新

Build and leverage online communities to drive product growth and brand loyalty. Use when the user wants to create a community strategy, grow a Discord or Slack community, manage a forum or subreddit, build brand advocates, increase word-of-mouth, drive community-led growth, engage users post-signup, or turn customers into evangelists. Trigger phrases: "build a community," "community strategy," "Discord community," "Slack community," "community-led growth," "brand advocates," "user community," "forum strategy," "community engagement," "grow our community," "ambassador program," "community flywheel."

日本語の概要は準備中です。原文の説明を表示しています。

Nexus-JPF/note-companion8702026年10月12日 更新

When the user wants to research, profile, or analyze competitors from their URLs. Also use when the user mentions 'competitor profile,' 'competitor research,' 'competitor analysis,' 'profile this competitor,' 'analyze competitor,' 'competitive intelligence,' 'competitor deep dive,' 'who are my competitors,' 'competitor landscape,' 'competitor dossier,' 'competitive audit,' or 'research these competitors.' Input is a list of competitor URLs. Output is structured competitor profile markdown files. For creating comparison/alternative pages from profiles, see competitors. For sales-specific battle cards, see sales-enablement.

日本語の概要は準備中です。原文の説明を表示しています。

Nexus-JPF/note-companion8702026年10月12日 更新

Nexus-JPF のスキルをすべて見る

このスキルの問題を報告する