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churn-prevention

skill · 434 lines · MIT · skills/churn-prevention/SKILL.md

The facts

Its 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.

The description the agent reads to decide when to use it.

From its settingsline 3

When it starts

This skill fires when someone is losing subscribers or worried about retention — high or rising churn, customers canceling or leaving, failed payments, or a wish to build a cancel flow, save offers, exit survey, pause option, dunning or win-back system. It is picked from the description alone, so any talk of churn, cancellation, offboarding or involuntary churn should trigger it.

Things a person might say (the model's guesses)

  • “Our churn rate jumped to 6% last month — how do we keep people from canceling?”
  • “Can you help me design a cancel flow with a save offer for people who say it's too expensive?”
  • “Payments keep failing and customers are losing access — how should our dunning emails work?”

A model's summary of when it is used.

A model's reading

Files it mentions

references/cancel-flow-patterns.md, references/dunning-playbook.md

Files the text names, such as ones to read or write. Found by matching words, so treat them as pointers.

Found by matching wordsline 204 line 334

What it leads to

Other skills this one hands off to, calls, requires or offers instead, as a model read them.

A model's reading

What leads to it

Other skills that hand off to this one, call it, require it or offer it instead, as a model read them.

A model's reading

Licence

MIT, from LICENSE

The terms its author shares it under, which let it be shown here.

From the repositorylicence text

Other settings

metadata: version: 2.0.3

More settings at the top of the file, shown as written.

From its settingsline 4
Other files in this skill (3) Close

The text

Open on GitHub

Most marks come from matching words in the file, so treat them as pointers.

1---
2name: churn-prevention
3description: "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."
4metadata:
5 version: 2.0.3
6---
7
8# Churn Prevention
9
10You 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.

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.

Raw lines 1 to 11
Boilerplate, lines 12 to 18. The same text appears in 6 other files here. Close
12## Before Starting
15If `.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.
17Gather this context (ask if not provided):
19### 1. Current Churn Situation
20- What's your monthly churn rate? (Voluntary vs. involuntary if known)
21- How many active subscribers?
22- What's the average MRR per customer?
23- Do you have a cancel flow today, or does cancel happen instantly?

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?
Raw lines 19 to 24
25### 2. Billing & Platform
26- What billing provider? (Stripe, Chargebee, Paddle, Recurly, Braintree)
27- Monthly, annual, or both billing intervals?
28- Do you support plan pausing or downgrades?
29- Any existing retention tooling? (Churnkey, ProsperStack, Raaft)

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)
Raw lines 25 to 30
31### 3. Product & Usage Data
32- Do you track feature usage per user?
33- Can you identify engagement drop-offs?
34- Do you have cancellation reason data from past churns?
35- What's your activation metric? (What do retained users do that churned users don't?)

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?)
Raw lines 31 to 36
37### 4. Constraints
38- B2B or B2C? (Affects flow design)
39- Self-serve cancellation required? (Some regulations mandate easy cancel)
40- Brand tone for offboarding? (Empathetic, direct, playful)
42---

4. Constraints

  • B2B or B2C? (Affects flow design)
  • Self-serve cancellation required? (Some regulations mandate easy cancel)
  • Brand tone for offboarding? (Empathetic, direct, playful)

Raw lines 37 to 43
44## How This Skill Works
46Churn has two types requiring different strategies:
48| Type | Cause | Solution |
49|------|-------|----------|
50| **Voluntary** | Customer chooses to cancel | Cancel flows, save offers, exit surveys |
51| **Involuntary** | Payment fails | Dunning emails, smart retries, card updaters |
53Voluntary churn is typically 50-70% of total churn. Involuntary churn is 30-50% but is often easier to fix.
55This skill supports three modes:
571. **Build a cancel flow** — Design from scratch with survey, save offers, and confirmation
582. **Optimize an existing flow** — Analyze cancel data and improve save rates
593. **Set up dunning** — Failed payment recovery with retries and email sequences
61---

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

Raw lines 44 to 62
63## Cancel Flow Design

Cancel Flow Design

Raw lines 63 to 64
65### The Cancel Flow Structure
67Every cancel flow follows this sequence:
69```
70Trigger → Survey → Dynamic Offer → Confirmation → Post-Cancel
71```
73**Step 1: Trigger**
74Customer clicks "Cancel subscription" in account settings.
76**Step 2: Exit Survey**
77Ask why they're cancelling. This determines which save offer to show.
79**Step 3: Dynamic Save Offer**
80Present a targeted offer based on their reason (discount, pause, downgrade, etc.)
82**Step 4: Confirmation**
83If they still want to cancel, confirm clearly with end-of-billing-period messaging.
85**Step 5: Post-Cancel**
86Set expectations, offer easy reactivation path, trigger win-back sequence.

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.

Raw lines 65 to 87
88### Exit Survey Design
90The exit survey is the foundation. Good reason categories:
92| Reason | What It Tells You |
93|--------|-------------------|
94| Too expensive | Price sensitivity, may respond to discount or downgrade |
95| Not using it enough | Low engagement, may respond to pause or onboarding help |
96| Missing a feature | Product gap, show roadmap or workaround |
97| Switching to competitor | Competitive pressure, understand what they offer |
98| Technical issues / bugs | Product quality, escalate to support |
99| Temporary / seasonal need | Usage pattern, offer pause |
100| Business closed / changed | Unavoidable, learn and let go gracefully |
101| Other | Catch-all, include free text field |
103**Survey best practices:**
104- 1 question, single-select with optional free text
105- 5-8 reason options max (avoid decision fatigue)
106- Put most common reasons first (review data quarterly)
107- Don't make it feel like a guilt trip
108- "Help us improve" framing works better than "Why are you leaving?"

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?"
Raw lines 88 to 109
110### Dynamic Save Offers
112The 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.
114**Offer-to-reason mapping:**
116| Cancel Reason | Primary Offer | Fallback Offer |
117|---------------|---------------|----------------|
118| Too expensive | Discount (20-30% for 2-3 months) | Downgrade to lower plan |
119| Not using it enough | Pause (1-3 months) | Free onboarding session |
120| Missing feature | Roadmap preview + timeline | Workaround guide |
121| Switching to competitor | Competitive comparison + discount | Feedback session |
122| Technical issues | Escalate to support immediately | Credit + priority fix |
123| Temporary / seasonal | Pause subscription | Downgrade temporarily |
124| Business closed | Skip offer (respect the situation) | — |

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)—
Raw lines 110 to 125
126### Save Offer Types
128**Discount**
129- 20-30% off for 2-3 months is the sweet spot
130- Avoid 50%+ discounts (trains customers to cancel for deals)
131- Time-limit the offer ("This offer expires when you leave this page")
132- Show the dollar amount saved, not just the percentage
134**Pause subscription**
135- 1-3 month pause maximum (longer pauses rarely reactivate)
136- 60-80% of pausers eventually return to active
137- Auto-reactivation with advance notice email
138- Keep their data and settings intact
140**Plan downgrade**
141- Offer a lower tier instead of full cancellation
142- Show what they keep vs. what they lose
143- Position as "right-size your plan" not "downgrade"
144- Easy path back up when ready
146**Feature unlock / extension**
147- Unlock a premium feature they haven't tried
148- Extend trial of a higher tier
149- Works best for "not getting enough value" reasons
151**Personal outreach**
152- For high-value accounts (top 10-20% by MRR)
153- Route to customer success for a call
154- Personal email from founder for smaller companies

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
Raw lines 126 to 155
156### Cancel Flow UI Patterns
158```
159┌─────────────────────────────────────┐
160│ We're sorry to see you go │
161│ │
162│ What's the main reason you're │
163│ cancelling? │
164│ │
165│ ○ Too expensive │
166│ ○ Not using it enough │
167│ ○ Missing a feature I need │
168│ ○ Switching to another tool │
169│ ○ Technical issues │
170│ ○ Temporary / don't need right now │
171│ ○ Other: [____________] │
172│ │
173│ [Continue] │
174│ [Never mind, keep my subscription] │
175└─────────────────────────────────────┘
176 ↓ (selects "Too expensive")
177┌─────────────────────────────────────┐
178│ What if we could help? │
179│ │
180│ We'd love to keep you. Here's a │
181│ special offer: │
182│ │
183│ ┌───────────────────────────────┐ │
184│ │ 25% off for the next 3 months│ │
185│ │ Save $XX/month │ │
186│ │ │ │
187│ │ [Accept Offer] │ │
188│ └───────────────────────────────┘ │
189│ │
190│ Or switch to [Basic Plan] at │
191│ $X/month → │
192│ │
193│ [No thanks, continue cancelling] │
194└─────────────────────────────────────┘
195```
197**UI principles:**
198- Keep the "continue cancelling" option visible (no dark patterns)
199- One primary offer + one fallback, not a wall of options
200- Show specific dollar savings, not abstract percentages
201- Use the customer's name and account data when possible
202- Mobile-friendly (many cancellations happen on mobile)
204For detailed cancel flow patterns by industry and billing provider, see [references/cancel-flow-patterns.md](references/cancel-flow-patterns.md).
206---

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.


Raw lines 156 to 207
208## Churn Prediction & Proactive Retention
210The best save happens before the customer ever clicks "Cancel."

Churn Prediction & Proactive Retention

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

Raw lines 208 to 211
212### Risk Signals
214Track these leading indicators of churn:
216| Signal | Risk Level | Timeframe |
217|--------|-----------|-----------|
218| Login frequency drops 50%+ | High | 2-4 weeks before cancel |
219| Key feature usage stops | High | 1-3 weeks before cancel |
220| Support tickets spike then stop | High | 1-2 weeks before cancel |
221| Email open rates decline | Medium | 2-6 weeks before cancel |
222| Billing page visits increase | High | Days before cancel |
223| Team seats removed | High | 1-2 weeks before cancel |
224| Data export initiated | Critical | Days before cancel |
225| Individual recommendation rating is 0–6 (detractor) | Medium | 1-3 months before 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
Individual recommendation rating is 0–6 (detractor)Medium1-3 months before cancel
Raw lines 212 to 226
227### Health Score Model
229Build a simple health score (0-100) from weighted signals. Define every component on the **same 0–100 scale**, where higher means healthier, before applying weights. Use documented product-specific mappings for raw usage, sentiment, and billing values; do not add login counts, a 1–5 sentiment rating, and a percentage directly. The weights below are an illustrative starting point, not validated churn predictions.
231Treat missing or stale signals as unavailable, rather than automatically healthy or zero. Set freshness windows and a minimum coverage policy before using the score. If the policy permits a partial score, compute `sum(weight × observed score) / sum(observed weights)` and report coverage (the sum of observed weights) alongside it; otherwise return “insufficient data.” All unavailable means no score. For example, only login (80) and feature usage (60) produce `(0.30×80 + 0.25×60)/0.55 = 70.91`, with 55% coverage. Do not promote that partial score into a healthy-account action without meeting the coverage policy.
233An individual rating of 0–6 is a detractor; aggregate NPS (−100 to 100) is a different measure.
235[Gainsight's measure-weight documentation](https://support.gainsight.com/gainsight_nxt/05Scorecards/02Admin_Guides/Measure_Weights_in_Scorecards) explains redistribution for unavailable measures.
237Illustrative complete-data model:
239```
240Health Score = (
241 Login frequency score × 0.30 +
242 Feature usage score × 0.25 +
243 Support sentiment × 0.15 +
244 Billing health × 0.15 +
245 Engagement score × 0.15
247```
249Validate score mappings and intervention thresholds against later observed renewal/churn outcomes before operational use; the following tiers are illustrative.
251| Score | Status | Action |
252|-------|--------|--------|
253| 80-100 | Healthy | Upsell opportunities |
254| 60-79 | Needs attention | Proactive check-in |
255| 40-59 | At risk | Intervention campaign |
256| 0-39 | Critical | Personal outreach |

Health Score Model

Build a simple health score (0-100) from weighted signals. Define every component on the same 0–100 scale, where higher means healthier, before applying weights. Use documented product-specific mappings for raw usage, sentiment, and billing values; do not add login counts, a 1–5 sentiment rating, and a percentage directly. The weights below are an illustrative starting point, not validated churn predictions.

Treat missing or stale signals as unavailable, rather than automatically healthy or zero. Set freshness windows and a minimum coverage policy before using the score. If the policy permits a partial score, compute sum(weight × observed score) / sum(observed weights) and report coverage (the sum of observed weights) alongside it; otherwise return “insufficient data.” All unavailable means no score. For example, only login (80) and feature usage (60) produce (0.30×80 + 0.25×60)/0.55 = 70.91, with 55% coverage. Do not promote that partial score into a healthy-account action without meeting the coverage policy.

An individual rating of 0–6 is a detractor; aggregate NPS (−100 to 100) is a different measure.

Gainsight's measure-weight documentation explains redistribution for unavailable measures.

Illustrative complete-data model:

Health Score = (
  Login frequency score × 0.30 +
  Feature usage score   × 0.25 +
  Support sentiment     × 0.15 +
  Billing health        × 0.15 +
  Engagement score      × 0.15
)

Validate score mappings and intervention thresholds against later observed renewal/churn outcomes before operational use; the following tiers are illustrative.

ScoreStatusAction
80-100HealthyUpsell opportunities
60-79Needs attentionProactive check-in
40-59At riskIntervention campaign
0-39CriticalPersonal outreach
Raw lines 227 to 257
258### Proactive Interventions
260**Before they think about cancelling:**
262| Trigger | Intervention |
263|---------|-------------|
264| Usage drop >50% for 2 weeks | "We noticed you haven't used [feature]. Need help?" email |
265| Approaching plan limit | Upgrade nudge (not a wall — paywalls handles this) |
266| No login for 14 days | Re-engagement email with recent product updates |
267| NPS detractor (0-6) | Personal follow-up within 24 hours |
268| Support ticket unresolved >48h | Escalation + proactive status update |
269| Annual renewal in 30 days | Value recap email + renewal confirmation |
271---

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

Raw lines 258 to 272
273## Involuntary Churn: Payment Recovery
275Failed payments cause 30-50% of all churn but are the most recoverable.

Involuntary Churn: Payment Recovery

Failed payments cause 30-50% of all churn but are the most recoverable.

Raw lines 273 to 276
277### The Dunning Stack
279```
280Pre-dunning → Smart retry → Dunning emails → Grace period → Hard cancel
281```

The Dunning Stack

Pre-dunning → Smart retry → Dunning emails → Grace period → Hard cancel
Raw lines 277 to 282
283### Pre-Dunning (Prevent Failures)
285- **Card expiry alerts**: Email 30, 15, and 7 days before card expires
286- **Backup payment method**: Prompt for a second payment method at signup
287- **Card updater services**: Visa/Mastercard auto-update programs (reduces hard declines 30-50%)
288- **Pre-billing notification**: Email 3-5 days before charge for annual plans

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
Raw lines 283 to 289
290### Smart Retry Logic
292Not all failures are the same. Retry strategy by decline type:
294| Decline Type | Examples | Retry Strategy |
295|-------------|----------|----------------|
296| Soft decline (temporary) | Insufficient funds, processor timeout | Retry 3-5 times over 7-10 days |
297| Hard decline (permanent) | Card stolen, account closed | Don't retry — ask for new card |
298| Authentication required | 3D Secure, SCA | Send customer to update payment |
300**Retry timing best practices:**
301- Retry 1: 24 hours after failure
302- Retry 2: 3 days after failure
303- Retry 3: 5 days after failure
304- Retry 4: 7 days after failure (with dunning email escalation)
305- After 4 retries: Hard cancel with reactivation path
307**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.

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.

Raw lines 290 to 308
309### Dunning Email Sequence
311| Email | Timing | Tone | Content |
312|-------|--------|------|---------|
313| 1 | Day 0 (failure) | Friendly alert | "Your payment didn't go through. Update your card." |
314| 2 | Day 3 | Helpful reminder | "Quick reminder — update your payment to keep access." |
315| 3 | Day 7 | Urgency | "Your account will be paused in 3 days. Update now." |
316| 4 | Day 10 | Final warning | "Last chance to keep your account active." |
318**Dunning email best practices:**
319- Direct link to payment update page (no login required if possible)
320- Show what they'll lose (their data, their team's access)
321- Don't blame ("your payment failed" not "you failed to pay")
322- Include support contact for help
323- Plain text performs better than designed emails for dunning

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
Raw lines 309 to 324
325### Recovery Benchmarks
327| Metric | Poor | Average | Good |
328|--------|------|---------|------|
329| Soft decline recovery | <40% | 50-60% | 70%+ |
330| Hard decline recovery | <10% | 20-30% | 40%+ |
331| Overall payment recovery | <30% | 40-50% | 60%+ |
332| Pre-dunning prevention | None | 10-15% | 20-30% |
334For the complete dunning playbook with provider-specific setup, see [references/dunning-playbook.md](references/dunning-playbook.md).
336---

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.


Raw lines 325 to 337
338## Metrics & Measurement

Metrics & Measurement

Raw lines 338 to 339
340### Key Churn Metrics
342| Metric | Formula | Target |
343|--------|---------|--------|
344| Monthly churn rate | Churned customers / Start-of-month customers | <5% B2C, <2% B2B |
345| Revenue churn (net) | (Lost MRR - Expansion MRR) / Start MRR | Negative (net expansion) |
346| Cancel flow save rate | Saved / Total cancel sessions | 25-35% |
347| Offer acceptance rate | Accepted offers / Shown offers | 15-25% |
348| Pause reactivation rate | Reactivated / Total paused | 60-80% |
349| Dunning recovery rate | Recovered / Total failed payments | 50-60% |
350| Time to cancel | Days from first churn signal to cancel | Track trend |

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
Raw lines 340 to 351
352### Cohort Analysis
354Segment churn by:
355- **Acquisition channel** — Which channels bring stickier customers?
356- **Plan type** — Which plans churn most?
357- **Tenure** — When do most cancellations happen? (30, 60, 90 days?)
358- **Cancel reason** — Which reasons are growing?
359- **Save offer type** — Which offers work best for which segments?

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?
Raw lines 352 to 360
361### Cancel Flow A/B Tests
363Test one variable at a time:
365| Test | Hypothesis | Metric |
366|------|-----------|--------|
367| Discount % (20% vs 30%) | Higher discount saves more | Save rate, LTV impact |
368| Pause duration (1 vs 3 months) | Longer pause increases return rate | Reactivation rate |
369| Survey placement (before vs after offer) | Survey-first personalizes offers | Save rate |
370| Offer presentation (modal vs full page) | Full page gets more attention | Save rate |
371| Copy tone (empathetic vs direct) | Empathetic reduces friction | Save rate |
373**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](https://github.com/coreyhaines31/marketingskills/blob/main/tools/integrations/posthog.md) for setup.
375---

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.


Raw lines 361 to 376
Names a skill ab-testing :373
377## Common Mistakes
379- **No cancel flow at all** — Instant cancel leaves money on the table. Even a simple survey + one offer saves 10-15%
380- **Making cancellation hard to find** — Hidden cancel buttons breed resentment and bad reviews. Many jurisdictions require easy cancellation (FTC Click-to-Cancel rule)
381- **Same offer for every reason** — A blanket discount doesn't address "missing feature" or "not using it"
382- **Discounts too deep** — 50%+ discounts train customers to cancel-and-return for deals
383- **Ignoring involuntary churn** — Often 30-50% of total churn and the easiest to fix
384- **No dunning emails** — Letting payment failures silently cancel accounts
385- **Guilt-trip copy** — "Are you sure you want to abandon us?" damages brand trust
386- **Not tracking save offer LTV** — A "saved" customer who churns 30 days later wasn't really saved
387- **Pausing too long** — Pauses beyond 3 months rarely reactivate. Set limits.
388- **No post-cancel path** — Make reactivation easy and trigger win-back emails, because some churned users will want to come back
390---

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

Raw lines 377 to 391
392## Tool Integrations
394For implementation, see the [tools registry](https://github.com/coreyhaines31/marketingskills/blob/main/tools/REGISTRY.md).

Tool Integrations

For implementation, see the tools registry.

Raw lines 392 to 395
396### Retention Platforms
398| Tool | Best For | Key Feature |
399|------|----------|-------------|
400| **Churnkey** | Full cancel flow + dunning | AI-powered adaptive offers, 34% avg save rate |
401| **ProsperStack** | Cancel flows with analytics | Advanced rules engine, Stripe/Chargebee integration |
402| **Raaft** | Simple cancel flow builder | Easy setup, good for early-stage |
403| **Chargebee Retention** | Chargebee customers | Native integration, was Brightback |

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
Raw lines 396 to 404
405### Billing Providers (Dunning)
407| Provider | Smart Retries | Dunning Emails | Card Updater |
408|----------|:------------:|:--------------:|:------------:|
409| **Stripe** | Built-in (Smart Retries) | Built-in | Automatic |
410| **Chargebee** | Built-in | Built-in | Via gateway |
411| **Paddle** | Built-in | Built-in | Managed |
412| **Recurly** | Built-in | Built-in | Built-in |
413| **Braintree** | Manual config | Manual | Via gateway |

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
Raw lines 405 to 414
415### Related CLI Tools
417| Tool | Use For |
418|------|---------|
419| `stripe` | Subscription management, dunning config, payment retries |
420| `customer-io` | Dunning email sequences, retention campaigns |
421| `posthog` | Cancel flow A/B tests via feature flags, funnel analytics |
422| `mixpanel` / `ga4` | Usage tracking, churn signal analysis |
423| `segment` | Event routing for health scoring |
425---

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

Raw lines 415 to 426
427## Related Skills
429- **emails**: For win-back email sequences after cancellation
430- **paywalls**: For in-app upgrade moments and trial expiration
431- **pricing**: For plan structure and annual discount strategy
432- **onboarding**: For activation to prevent early churn
433- **analytics**: For setting up churn signal events
434- **ab-testing**: For testing cancel flow variations with statistical rigor

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
Raw lines 427 to 434
Names a skill paywalls :430
Names a skill pricing :431
Names a skill onboarding :432
Names a skill analytics :433

From coreyhaines31/marketingskills at 88c79f6, 2026-10-30. Skills read by DeepSeek V4.1 Flash on 2026-11-04. Summary and techniques by Claude Opus 5.5 on 2026-11-06.