churn-prevention

name	churn-prevention
description	ALWAYS use this when the request matches Churn Prevention: Reduce voluntary and involuntary churn with cancel flows, save offers, dunning, win-back tactics, and retention strategy.

Churn Prevention

Selective Reading Rule

Start with:

• references/usage-routing.md
• references/quality-checklist.md

Then load only the inherited docs, scripts, assets, or examples that match the user's actual task.

Selective Reading Rule

Start with:

• references/senior-master-standard.md

Then load only the references, scripts, assets, or examples needed for the user's actual task.

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.

When to Use

• Use when churn is rising or cancellation behavior needs intervention.
• Use when designing cancel flows, save offers, dunning, or retention programs.
• Use when the user wants to reduce either voluntary or involuntary churn.

Before Starting

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):

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:

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:

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 — 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

---

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.

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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-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).

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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

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Tool Integrations

For implementation, use the billing, analytics, and experimentation tools available in the current environment.

Retention Platforms

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

Billing Providers (Dunning)

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

Related CLI Tools

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

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Related Skills

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

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.