churn-prevention

Design cancel flows, save offers, and dunning schedules for subscription churn prevention.

Updated Mar 30, 2026
One-click install
npx skills add https://github.com/omeragaakbas/zoyare --skill churn-prevention-omeragaakbas
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: churn-prevention
Source: https://github.com/omeragaakbas/zoyare/tree/main/.claude/skills/churn-prevention
Command: npx skills add https://github.com/omeragaakbas/zoyare --skill churn-prevention-omeragaakbas

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps subscription businesses reduce both voluntary churn (users choosing to cancel) and involuntary churn (failed payments) by designing cancel flows, targeted save offers, exit surveys, proactive retention triggers, and robust dunning strategies to recover revenue and preserve customer relationships.

Core Features & Use Cases

  • Cancel flow design: Step-by-step frameworks for trigger → exit survey → dynamic save offer → confirmation → post-cancel experience that respect regulatory and UX constraints.
  • Exit survey & offer mapping: Pair common cancellation reasons with tailored saves (discounts, pauses, downgrades, feature trials, or personal outreach) and A/B test recommendations.
  • Involuntary churn recovery (dunning): Pre-dunning card-expiry notices, smart retry schedules, escalating dunning email templates, grace period handling, and provider-specific setup (Stripe, Chargebee, Paddle).
  • Proactive retention & health scoring: Signals (login, feature usage, support activity), a 0–100 health score model, risk tiers, and recommended interventions per tier.
  • Measurement & experiments: Key metrics, cohort analysis, and cancel-flow A/B test designs to evaluate save rates and long-term LTV impact.
  • Use case: A mid-market SaaS with 2,000 customers implements an exit survey + dynamic offer and Stripe smart retries to recover involuntary churn and improve save rates while retaining regulatory-compliant cancellation behavior.

Quick Start

Design a cancel flow that asks one exit question, shows a targeted save offer, and configures a 4-step dunning email plus smart retry logic for your Stripe subscriptions.

Frequently Asked Questions about churn-prevention

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I design a cancel flow that reduces SaaS subscriber churn?

Design a SaaS cancel flow by mapping exit survey questions to targeted save offers like discounts, pauses, or downgrades, then configure the trigger and confirmation stages to reduce voluntary churn while respecting UX constraints.

What is the best way to set up dunning schedules to recover failed subscription payments?

The best way to set up dunning for failed subscription payments is configuring pre-dunning card-expiry notices, smart retry schedules, and escalating email templates with grace period handling to recover involuntary churn.

Does this churn prevention approach work with Stripe and Chargebee billing providers?

Yes, this churn prevention approach provides specific integration guidance and dunning setup configurations for billing providers like Stripe, Chargebee, and Paddle to manage subscription retries and save offers.

How does health scoring identify at-risk subscription customers for proactive retention?

Health scoring identifies at-risk subscription customers by analyzing signals like login frequency, feature usage, and support activity to generate a 0-100 score, segmenting users into risk tiers for targeted retention interventions.

Can I A/B test save offers within a subscription cancel flow?

Yes, you can A/B test save offers within a cancel flow by applying the provided measurement frameworks to evaluate save rates, cohort analysis, and long-term LTV impact for different retention interventions.

What save offers should I map to specific cancellation reasons in an exit survey?

Map save offers to cancellation reasons by pairing issues like price sensitivity with discounts or pauses, feature gaps with trials, and complex needs with personal outreach to maximize retention.