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SKILL.md

retention-optimization

Agent skill fromappeeky/aso-skills

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.

How to install retention-optimization

install retention-optimization
# install the aso-skills pack with the skills CLI
npx skills add appeeky/aso-skills

# or add only this skill to Claude Code: copy the folder

skills/retention-optimization/

# into

~/.claude/skills/retention-optimization/ (all projects)

.claude/skills/retention-optimization/ (one project)

skills/retention-optimization/SKILL.md

MITFull file
1# Retention Optimization
2
3You 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.
4
5## Initial Assessment
6
71. Check for `app-marketing-context.md` — read it for context
82. Ask for **current retention metrics** (Day 1, Day 7, Day 30 if available)
93. Ask for **app category** (benchmarks vary dramatically)
104. Ask about **monetization model** (retention strategy differs for free vs subscription)
115. Ask about **current engagement features** (push notifications, streaks, etc.)
12
13## Retention Benchmarks
14
15### Industry Averages (Day 1 / Day 7 / Day 30)
16
17| Category | Day 1 | Day 7 | Day 30 | Good |
18|----------|-------|-------|--------|------|
19| Games | 25-30% | 10-15% | 3-5% | D1 >35%, D30 >8% |
20| Social | 30-35% | 15-20% | 8-12% | D1 >40%, D30 >15% |
21| Health & Fitness | 20-25% | 10-12% | 4-6% | D1 >30%, D30 >10% |
22| Productivity | 15-20% | 8-10% | 3-5% | D1 >25%, D30 >8% |
23| E-commerce | 15-20% | 5-8% | 2-3% | D1 >25%, D30 >5% |
24| Finance | 20-25% | 10-12% | 5-8% | D1 >30%, D30 >10% |
25| Education | 15-20% | 8-10% | 3-5% | D1 >25%, D30 >8% |
26
27## Retention Framework
28
29### 1. Activation (Day 0-1)
30
31The first session determines everything. Users who don't reach the "aha moment" in session 1 rarely return.
32
33**Diagnose:**
34- What % of users complete onboarding?
35- How long until the first value moment?
36- What's the drop-off point in the first session?
37
38**Optimize:**
39…

Excerpt shown under the repository's MIT license.

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