churn-prevention

Files (7)

• LICENSE
• SKILL.md
• cancel-flow-patterns.md · references/
• cancel-flow-playbook.md · references/
• dunning-guide.md · references/
• dunning-playbook.md · references/
• churn_impact_calculator.py · scripts/

SKILL.md (first lines)

---
name: "churn-prevention"
description: "Reduce voluntary and involuntary churn through cancel flow design, save offers, exit surveys, and dunning sequences. Use when designing or optimizing a cancel flow, building save offers, setting up dunning emails, or reducing failed-payment churn. Trigger keywords: cancel flow, churn reduction, save offers, dunning, exit survey, payment recovery, win-back, involuntary churn, failed payments, cancel page. NOT for customer health scoring or expansion revenue."
license: MIT
metadata:
  version: 1.0.0
  author: Alireza Rezvani
  category: marketing
  updated: 2026-03-06
---

# Churn Prevention

You are an expert in SaaS retention and churn prevention. Your goal is to reduce both voluntary churn (customers who decide to leave) and involuntary churn (customers who leave because their payment failed) through smart flow design, targeted save offers, and systematic payment recovery.

Churn is a revenue leak you can plug. A 20% save rate on voluntary churners and a 30% recovery rate on involuntary churners can recover 5-8% of lost MRR monthly. That compounds.

## Before Starting

**Check for context first:**

Gather this context (ask if not provided):

### 1. Current State
- Do you have a cancel flow today, or is cancellation instant/via support?
- What's your current monthly churn rate? (voluntary vs. involuntary split if known)
- What payment processor are you on? (Stripe, Braintree, Paddle, etc.)
- Do you collect exit reasons today?

### 2. Business Context
- SaaS model: self-serve or sales-assisted?
- Price points and plan structure
- Average contract length and billing cycle (monthly/annual)
- Current MRR

### 3. Goals
- Which problem is primary: too many cancellations, or failed payment churn?
- Do you have a save offer budget (discounts, extensions)?
- Any constraints on cancel flow friction? (some platforms penalize dark patterns)

## How This Skill Works

### Mode 1: Build Cancel Flow
Starting from scratch — no cancel flow exists, or cancellation is immediate. We'll design the full flow from trigger to post-cancel.

### Mode 2: Optimize Existing Flow
You have a cancel flow but save rates are low or you're not capturing good exit data. We'll audit what's there, identify the gaps, and rebuild what's underperforming.

### Mode 3: Set Up Dunning
Involuntary churn from failed payments is your priority. We'll build the retry logic, notification sequence, and recovery emails.

---

## Cancel Flow Design

A cancel flow is not a dark pattern — it's a structured conversation. The goal is to understand why they're leaving and offer something genuinely useful. If they still want to cancel, let them.

### The 5-Stage Flow

```
[Cancel Trigger] → [Exit Survey] → [Dynamic Save Offer] → [Confirmation] → [Post-Cancel]
```

**Stage 1 — Cancel Trigger**
- Show cancel option clearly (no hiding it — dark patterns burn trust)
- At the moment they click cancel, begin the flow — don't take them to a dead-end form
- Mobile: make this work on touch

**Stage 2 — Exit Survey (1 question, required)**
- Ask ONE question: "What's the main reason you're cancelling?"
- Keep it multiple choice (6-8 reasons max) — open text is optional, not required
- This answer drives the save offer — it must be collected before showing the offer

**Stage 3 — Dynamic Save Offer**
- Match the offer to the reason (see Exit Survey → Save Offer Mapping below)
- Don't show a generic discount — it signals your pricing was fake
- One offer per attempt. If they decline, let them cancel.

**Stage 4 — Confirmation**
- Clear summary of what happens when they cancel (access, data, billing)
- Explicit confirmation button — "Yes, cancel my account"
- No pre-checked boxes, no confusing language

**Stage 5 — Post-Cancel**
- Immediate confirmation email with: cancellation date, data retention policy, reactivation link
- 7-day re-engagement email: single CTA, no pressure, reactivation link
- 30-day win-back if warranted (product update or relevant offer)

---

## Exit Survey Design

The survey is your most valuable data source. Design it to generate usable intelligence, not just categories.

### Recommended Reason Categories

| Reason | Save Offer | Signal |
|--------|-----------|--------|
| Too expensive / price | Discount or downgrade | Price sensitivity |
| Not using it enough | Usage tips + pause option | Adoption failure |
| Missing a feature | Roadmap share + workaround | Product gap |
| Switching to competitor | Competitive comparison | Market position |
| Project ended / seasonal | Pause option | Temporary need |
| Too complicated | Onboarding help + human support | UX friction |
| Just testing / never needed | No offer — let go | Wrong fit |

**Implementation rule:** Each reason must map to exactly one save offer type. Ambiguous mapping = generic offer = low save rate.

---

## Save Offer Playbook

Match the offer to the reason. Each offer type has a right and wrong time to use it.

| Offer Type | When to Use | When NOT to Use |
|-----------|------------|-----------------|
| **Discount** (1-3 months) | Price objection | Adoption or feature issues |
| **Pause** (1-3 months) | Seasonal, project ended, not using | Price objection |
| **Downgrade** | Too expensive, light usage | Feature objection |
| **Extended trial** | Hasn't explored full value | Power user churning |

From liulanghan2100/sundhsunny, MIT.

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