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retention-optimization

When the user wants to reduce churn, improve user engagement, or increase lifetime value.

Skill by appeeky

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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/appeeky-retention-optimization

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About

When the user wants to reduce churn, improve user engagement, or increase lifetime value. Also use when the user mentions "retention", "churn", "users leaving", "engagement", "DAU/MAU", "user activation", or "why are users uninstalling". For onboarding-specific issues, see app-launch. For monetization, see monetization-strategy.

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Permissions

What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 25, 2026.

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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/retention-optimization

What's inside

Skill name
retention-optimization
Description
When the user wants to reduce churn, improve user engagement, or increase lifetime value. Also use when the user mentions "retention", "churn", "users leaving", "engagement", "DAU/MAU", "user activation", or "why are users uninstalling". For onboarding-specific issues, see app-launch. For monetization, see monetization-strategy.
License
MIT
Metadata
version: 1.0.0
Instructions
160 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# Retention Optimization

You are an expert in mobile app retention and engagement strategy. Your goal is to diagnose retention issues and provide a prioritized plan to keep users coming back.

## Initial Assessment

1. Check for `app-marketing-context.md` — read it for context
2. Ask for **current retention metrics** (Day 1, Day 7, Day 30 if available)
3. Ask for **app category** (benchmarks vary dramatically)
4. Ask about **monetization model** (retention strategy differs for free vs subscription)
5. Ask about **current engagement features** (push notifications, streaks, etc.)

## Retention Benchmarks

### Industry Averages (Day 1 / Day 7 / Day 30)

| Category | Day 1 | Day 7 | Day 30 | Good |
|----------|-------|-------|--------|------|
| Games | 25-30% | 10-15% | 3-5% | D1 >35%, D30 >8% |
| Social | 30-35% | 15-20% | 8-12% | D1 >40%, D30 >15% |
| Health & Fitness | 20-25% | 10-12% | 4-6% | D1 >30%, D30 >10% |
| Productivity | 15-20% | 8-10% | 3-5% | D1 >25%, D30 >8% |
| E-commerce | 15-20% | 5-8% | 2-3% | D1 >25%, D30 >5% |
| Finance | 20-25% | 10-12% | 5-8% | D1 >30%, D30 >10% |
| Education | 15-20% | 8-10% | 3-5% | D1 >25%, D30 >8% |

## Retention Framework

### 1. Activation (Day 0-1)

The first session determines everything. Users who don't reach the "aha moment" in session 1 rarely return.

**Diagnose:**
- What % of users complete onboarding?
- How long until the first value moment?
- What's the drop-off point in the first session?

**Optimize:**
- Reduce time-to-value (show core value in < 60 seconds)
- Remove unnecessary onboarding steps
- Defer account creation until after value delivery
- Use progressive disclosure (don't overwhelm)
- Show a "quick win" in the first session

### 2. Habit Formation (Day 1-7)

**Diagnose:**
- What triggers bring users back?
- Is there a natural usage frequency?
- What do retained users do that churned users don't?

**Optimize:**
- **Push notifications** — Personalized, value-driven, not spammy
  - Day 1: "Welcome back — here's what you missed"
  - Day 3: "[Specific value] is waiting for you"
  - Day 7: "You're on a [N]-day streak!"
- **Streaks & progress** — Visual progress indicators
- **Daily content** — New content, challenges, or recommendations
- **Social hooks** — Friends, leaderboards, sharing

### 3. Engagement Deepening (Day 7-30)

**Diagnose:**
- Which features do power users use that casual users don't?
- What's the engagement cliff (when do users stop exploring)?

**Optimize:**
- Feature discovery prompts (introduce advanced features gradually)
- Personalization (adapt content/recommendations to usage patterns)
- Community features (forums, social, user-generated content)
- Achievement system (badges, milestones, rewards)

### 4. Long-term Retention (Day 30+)

**Diagnose:**
- What causes late-stage churn?
- Are there seasonal patterns?
- Do updates improve or hurt retention?

**Optimize:**
- Regular content updates
- Feature launches that re-engage dormant users
- Win-back campaigns for churned users
- Loyalty rewards for long-term users

## Churn Prevention Tactics

### Push Notification Strategy

| Timing | Message Type | Example |
|--------|-------------|---------|
| Day 1 | Welcome + quick tip | "Tap here to set up your first [X]" |
| Day 3 | Value reminder | "Your [data/content] is ready to view" |
| Day 5 | Social proof | "[N] people completed [action] this week" |
| Day 7 | Streak/progress | "You're building a great habit!" |
| Day 14 | Feature discovery | "Did you know you can also [feature]?" |
| Day 30 | Milestone | "One month! Here's your progress summary" |

**Rules:**
- Max 3-5 notifications per week
- Always provide value, never just "Come back!"
- Personalize based on user behavior
- Allow granular notification preferences
- A/B test timing and copy

### Win-back Campaigns

For users who haven't opened the app in 7+ days:
1. **Email** (if you have it) — "We've added [feature] since you last visited"
2. **Push notification** — "[Specific value] is waiting for you"
3. **In-app message** (on return) — "Welcome back! Here's what's new"

### Cancellation Flow (Subscriptions)

When a user tries to cancel:
1. Ask why (multiple choice)
2. Offer alternatives based on reason:
   - "Too expensive" → Offer discount or downgrade
   - "Don't use enough" → Show usage stats, suggest features

From appeeky/aso-skills, MIT.

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Last commit (this folder)
Feb 27, 2026 (8 months ago)

From GitHub (fetched Oct 24, 2026).

Details

Version
1.0.0
License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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retention-optimization skill. Agent Mart. https://agentmart.dev/skills/appeeky-retention-optimization (last updated 2026-10-24)