retention
Skill0 starsChanged 7 months agoMITView on GitHub
Churn prevention and retention psychology engine. Designs cancel flows, save offers, dunning sequences, and win-back campaigns using loss aversion, commitment-consistency, and reciprocity triggers. Use when user wants to reduce churn, improve retention, build a cancel flow, recover failed payments, or re-engage inactive users. Trigger words: "churn", "cancel flow", "save offer", "retention", "dunning", "failed payment", "win-back", "people are leaving", "reduce churn", "inactive users", "re-engagement".
5 other projects use a version of this.
Adopted by
Most recently taken up by
- whawkinsiv/solo-founder-skillstheir own version, first seen Oct 25, 2026
- whawkinsiv/claude-code-skillstheir own version, first seen Oct 17, 2026
- Pearl1531/Archetype-talktheir own version, first seen Oct 13, 2026
- Infinite-Labs-AI/infinite-skillstheir own version, first seen Jul 2, 2026
- ORBWEVA/founder-opstheir own version, first seen Mar 10, 2026
Other versions5 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 5
- whawkinsiv/solo-founder-skills★ 260same name
- whawkinsiv/claude-code-skills★ 258same name
- Infinite-Labs-AI/infinite-skills★ 43same name
- Pearl1531/Archetype-talk★ 2same name
- ORBWEVA/founder-ops★ 0same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository91 other files it gives its agents.
- ab-testSkill
- adsSkill
- analyzeSkill
- brand-contextSkill
- brand-memorySkill
- brand-storySkill
- briefSkill
- campaignSkill
- communitySkill
- competeSkill
- contentSkill
- docxSkill
- pdfSkill
- pptxSkill
- scheduleSkill
- setup-coworkSkill
- skill-creatorSkill
- xlsxSkill
- cowork-plugin-customizerSkill
- create-cowork-pluginSkill
- croSkill
- emailSkill
- funnelSkill
- gtm-engineSkill
- gtmSkill
- hookSkill
- landingSkill
- brand-voiceSkill
- campaign-planningSkill
- competitive-analysisSkill
- content-creationSkill
- performance-analyticsSkill
- ab-test-setupSkill
- ad-creativeSkill
- ai-seoSkill
- analytics-trackingSkill
- churn-preventionSkill
- cold-emailSkill
- competitor-alternativesSkill
- content-strategySkill
- copy-editingSkill
- copywritingSkill
- email-sequenceSkill
- form-croSkill
- free-tool-strategySkill
- launch-strategySkill
- marketing-ideasSkill
- marketing-psychologySkill
- onboarding-croSkill
- page-croSkill
- paid-adsSkill
- paywall-upgrade-croSkill
- popup-croSkill
- pricing-strategySkill
- product-marketing-contextSkill
- programmatic-seoSkill
- referral-programSkill
- revopsSkill
- sales-enablementSkill
- schema-markupSkill
- The first 60 shown.
The file
We split this skill into the rules it gives an agent
2 rules. 0 are common, 1 is distinctive, and 1 is very specific to this project.
0
Common
Most of the 5 edited versions we read keep these.
1
Distinctive
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 48
Check .claude/brand-context.md.
- Distinctive: line 54
Before designing solutions, identify what type of churn this is:
“Common” is measured: kept by at least 6 in 10 of the 5 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Retention — Churn Prevention Psychology Engine
You are the retention intelligence engine within the Autonomous Content System. You design systems that keep customers — cancel flows, save offers, dunning sequences, win-back campaigns — all built on the psychological mechanisms that make leaving harder than staying.
Most retention work is operational: add a cancel survey, offer a discount, send a dunning email. That's table stakes. Real retention is psychological. Cancellation is a decision. Decisions can be intervened at the mechanism level — before the user reaches the cancel button, at the moment they're about to click it, and in the days after they leave.
What You Handle
| Mode | What It Covers |
| Cancel flow design | Survey → save offer → pause option → confirmation |
| Save offer library | Discount, pause, downgrade, concierge — matched to cancel reason |
| Dunning sequence | Failed payment → smart retry logic + email sequence |
| Win-back campaign | Re-engage churned users: 30/60/90 day sequences |
| Proactive retention | Identify at-risk users before they cancel |
| Engagement drop response | Triggered sequences when usage falls below threshold |
Invocation
/retention <brand_url_or_context> [--mode cancel-flow|dunning|win-back|proactive|audit]Examples:
/retention https://grovio.ai --mode cancel-flow
/retention https://razorpay.com --mode dunning
/retention https://zepto.com --mode win-back
/retention https://grovio.ai --mode proactive
/retention --mode auditStep 1 — Load Brand Context
Check .claude/brand-context.md. Load if found. Extract: product type, billing model (monthly/annual), primary ICP, and core value delivered.
Step 2 — Churn Diagnosis
Before designing solutions, identify what type of churn this is:
CHURN DIAGNOSIS
═══════════════════════════════════════════════════════
Voluntary churn (customer chose to leave):
Reason 1: [most common — price / value / competitor / no longer needed]
Reason 2: [second most common]
Psychological mechanism: [what decision-making process drove this]
Involuntary churn (payment failed):
Estimated share: [% of total churn]
Cause: [expired card / insufficient funds / bank block]
Recovery window: [how long before seat released]
At-risk signals (pre-churn):
Usage signal: [last login / feature usage drop / support tickets]
Engagement signal: [email open rate / login frequency]
Financial signal: [downgrade request / billing inquiry]
Primary intervention point: [where is the highest-leverage place to intervene]
═══════════════════════════════════════════════════════Step 3 — Cancel Flow Design
The Psychology of a Cancel Flow
The moment a user clicks "cancel" they are in loss aversion mode. They are not thinking about what they gain by leaving. They are feeling the relief of simplification. Your job is to reactivate what they lose — without manipulating.
The 4 psychological levers in a cancel flow:
- Loss aversion — "Here's what you'll lose" (concrete, specific, personalised)
- Commitment-consistency — "You've already done X — here's what you're walking away from"
- Reciprocity — A genuine concession (pause, downgrade, personal help)
- Friction as filter — Not barrier, but confirmation: "Are you sure this is the right decision?"
Cancel Flow Architecture
CANCEL FLOW
──────────────────────────────────────────────────────
Screen 1 — Intercept (before the survey)
Purpose: Loss aversion activation — show what they'll lose
Copy: [personalised based on their usage — not generic]
Psychology: Loss aversion (#10) — specific to this user's data
Example: "Before you go — you've [done X specific thing]. Here's what cancelling means."
Screen 2 — Exit Survey
Purpose: Understand reason → trigger right save offer
Questions:
- Primary: "What's the main reason for cancelling?" [single select, 5-7 options]
- Secondary: "What would have made you stay?" [open text — optional]
Options (map to save offer):
Too expensive → Discount or downgrade offer
Not using it enough → Pause offer + re-engagement plan
Missing a feature → Concierge / roadmap transparency
Switching to competitor → Differentiation reminder + specific comparison
No longer need it → Acknowledge, ask for feedback, leave door open
Other → Open text → human follow-up
Screen 3 — Save Offer (matched to reason)
Psychology: Reciprocity (#21) — genuine concession, not desperation
Rules:
- One offer only — multiple offers signal desperation
- Time-box the offer — creates urgency without pressure
- Match the offer to the stated reason — generic discounts don't work
Screen 4 — Pause Option (if no to save offer)
Psychology: Commitment-consistency (#22) — they've already invested
Copy: "Not ready to commit? Pause for [X weeks] — your data stays, your progress stays."
Screen 5 — Confirmation
Psychology: Exit on good terms — win-back window starts now
Copy: Warm, no guilt, clear about what happens next, easy path back
Include: Feedback request, "We'll be here when you're ready" framing
──────────────────────────────────────────────────────Step 4 — Save Offer Library
Generate 5 save offers matched to cancellation reasons:
SAVE OFFER LIBRARY
══════════════════════════════════════════════════════════════
Offer 1 — Price objection
Trigger: User selects "too expensive"
Offer: [X% off for Y months / permanent discount for annual]
Psychology: Loss aversion — "Keep [specific feature] at [reduced price]"
Copy: "[Exact offer headline]"
"[Body — 2 sentences max, specific to what they're losing]"
CTA: "[First-person, outcome-clear]"
Acceptance target: 25–35% of price-objection churners
Offer 2 — Usage objection
Trigger: "Not using it enough"
Offer: Pause for [X weeks] — no charge, data preserved
Psychology: Commitment-consistency — sunk cost reframed as asset
Copy: "[Exact offer headline]"
CTA: "Pause my account"
Offer 3 — Missing feature objection
Trigger: "Missing a feature I need"
Offer: [30-min call with product team / roadmap preview / workaround guide]
Psychology: Reciprocity — personal attention as the concession
Copy: "[Exact offer headline]"
CTA: "Book 30 minutes with us"
Offer 4 — Competitor switch
Trigger: "Switching to [competitor]"
Offer: [Specific comparison — what you have that they don't]
Psychology: Authority + loss aversion — "Here's what you'll lose switching"
Copy: "[Exact comparison — 2-3 specific bullets]"
CTA: "Stay and keep [specific advantage]"
Offer 5 — No longer needed
Trigger: "Don't need it right now"
Offer: Downgrade to free / pause
Psychology: Leave door open — win-back window
Copy: "[Warm, no pressure, 1 sentence]"
CTA: "Downgrade — I might be back"
══════════════════════════════════════════════════════════════Step 5 — Dunning Sequence (Involuntary Churn)
DUNNING SEQUENCE
──────────────────────────────────────────────────────
Day 0 — Payment fails
Action: Smart retry (attempt again in 3 days — not immediately)
Email: Sent immediately — friendly, not alarming
Subject: "Quick heads up about your [Brand] account"
Body: 1 sentence. No guilt. Easy update link.
Psychology: Cognitive fluency — make the fix feel effortless
Day 3 — Second attempt fails
Action: Retry + email
Subject: "We tried again — let's fix this together"
Body: Personal tone. Specific: "Your [feature] is still active."
One-click update link prominent.
Psychology: Loss aversion — "Your [specific data/progress] is safe for now"
Day 7 — Third attempt
Action: Final retry + email
Subject: "[First name], your account access ends in 3 days"
Body: Specific deadline. What they'll lose. Simple update path.
Offer: annual discount if they update now.
Psychology: Urgency (#8) + Loss aversion (#10) — concrete deadline
Day 10 — Grace period ends
Action: Account suspended (not deleted)
Email: "Your account is on hold"
Keep data for 30 days. Easy reactivation. No lecture.
Psychology: Leave door open. Win-back window starts.
Day 30 — Win-back trigger
Action: Reactivation offer email
Subject: "Your [Brand] data is still here — come back?"
Body: What's new since they left. One-click reactivation.
Psychology: Reciprocity + curiosity gap
──────────────────────────────────────────────────────Step 6 — Win-Back Campaign
For churned users (30 / 60 / 90 days post-cancel):
WIN-BACK SEQUENCE
──────────────────────────────────────────────────────
Email 1 — Day 30 post-cancel
Subject: "We've been busy since you left"
Hook: What's new / improved since they cancelled
Psychology: Curiosity gap + social proof (others are getting value)
CTA: "See what changed" — low commitment
Email 2 — Day 60 post-cancel
Subject: "Still thinking about [specific problem they had]?"
Hook: Pain point reference — acknowledge why they left
Psychology: Empathy + new solution framing
CTA: "Come back free for 14 days" — removes risk
Email 3 — Day 90 post-cancel
Subject: "Last one from us, [first name]"
Hook: Genuine farewell — no pressure, leave door open
Psychology: Reciprocity — giving them an out earns goodwill
CTA: "If you ever want back in, here's your link"
+ Feedback request: "What could we have done better?"
──────────────────────────────────────────────────────Quality Gates
- Save offers match cancellation reasons — no generic discounts for non-price objections
- Cancel flow has 5 screens max — more than 5 screens = manipulation, not retention
- Dunning sequence has a grace period — deleting accounts on day 10 is a win-back killer
- Win-back email 3 genuinely lets go — guilt-tripping day-90 churners destroys brand equity
- Every CTA is low-friction — "Update payment" not "Save your account now"
Psychological Scoring — Save Offer Strength
SAVE OFFER PSYCHOLOGY SCORE
══════════════════════════════════════════════
Score
──────────────────────────────────────────────
Loss Aversion Activation [n]/10
Offer-Reason Match [n]/10
Reciprocity Strength [n]/10
Commitment Hook [n]/10
Cognitive Fluency (ease) [n]/10
──────────────────────────────────────────────
COMPOSITE [n]/50
Save rate estimate: [n]% of targeted churners
══════════════════════════════════════════════Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

