Churn Prevention

---
name: churn-prevention
description: "When the user wants to reduce churn or build retention systems — 'cancel flow,' 'save offer,' 'dunning,' 'failed payment recovery,' 'win-back,' 'exit survey,' 'pause subscription,' 'involuntary churn,' 'customers are leaving.' For post-cancel win-back sequences, see email-sequence. For in-app upgrade paywalls, see paywall-upgrade-cro."
category: marketing
tier: on-demand
---

# Churn Prevention

Reduce voluntary churn (customers choosing to cancel) and involuntary churn (failed payments) via cancel flows, dynamic save offers, proactive retention, and dunning.

## Before Starting

**Product context:** If `.agents/product-marketing-context.md` exists (or `.claude/product-marketing-context.md` in older setups), read it first and tailor output to it; only ask for what it doesn't cover.

Gather this context (ask if not provided):

1. **Current churn situation** — Monthly churn rate (voluntary vs. involuntary if known)? Active subscribers? Average MRR per customer? Existing cancel flow, or instant cancel?
2. **Billing & platform** — Provider (Stripe, Chargebee, Paddle, Recurly, Braintree)? Monthly, annual, or both intervals? Pausing or downgrades supported? Retention tooling (Churnkey, ProsperStack, Raaft)?
3. **Product & usage data** — Feature usage tracked per user? Engagement drop-offs identifiable? Cancellation reason data from past churns? 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)? Offboarding brand tone (empathetic, direct, playful)?

---

## How This Skill Works

Two churn types, two 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 is typically 50-70% of total churn; involuntary is 30-50% but often easier to fix.

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

```
Trigger → Survey → Dynamic Offer → Confirmation → Post-Cancel
```

1. **Trigger** — Customer clicks "Cancel subscription" in account settings.
2. **Exit Survey** — Ask why; the reason determines which save offer to show.
3. **Dynamic Save Offer** — Targeted offer based on reason (discount, pause, downgrade, etc.)
4. **Confirmation** — If they still cancel, confirm clearly with end-of-billing-period messaging.
5. **Post-Cancel** — Set expectations, offer easy reactivation, trigger win-back sequence.

### Exit Survey Design

The 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)
- Most common reasons first (review data quarterly)
- No guilt trips — "Help us improve" framing beats "Why are you leaving?"

### Dynamic Save Offers

**Match the offer to the reason.** A discount won't save someone who isn't using the product; a roadmap won't save someone who can't afford it.

| 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%+ (trains customers to cancel for deals)
- Time-limit it ("This offer expires when you leave this page")
- Show dollar amount saved, not just the percentage

**Pause subscription**
- 1-3 month maximum (longer pauses rarely reactivate)
- 60-80% of pausers eventually return to active
- Auto-reactivation with advance notice email; keep data and settings intact

**Plan downgrade**
- Lower tier instead of full cancellation; show what they keep vs. lose
- Position as "right-size your plan," with an easy path back up

**Feature unlock / extension**
- Unlock an untried premium feature or extend a higher-tier trial; 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, or a personal founder email at 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 "continue cancelling" 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](references/cancel-flow-patterns.md).

---

## Churn Prediction & Proactive Retention

The best save happens before the customer ever clicks "Cancel."

### Risk Signals

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

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

| 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

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:**
- 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
- Plain text outperforms 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](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 |

**Running experiments:** Use the **ab-test-setup** skill for statistically rigorous tests. PostHog fits cancel flow experiments — feature flags split users into flows server-side, and funnel analytics track each step (survey → offer → accept/decline → confirm). See the [PostHog integration guide](../../tools/integrations/posthog.md) 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; some churned users will want to come back

---

## Tool Integrations

For implementation, see the [tools registry](../../tools/REGISTRY.md).

### 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 |

---

## 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