# Retention Optimization

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

- Repository: https://github.com/appeeky/aso-skills (2243 stars)
- Category: Engineering
- License: MIT
- Last updated: 2026-10-06
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add appeeky/aso-skills --skill retention-optimization -g -a claude-code -y`
Codex: `npx skills add appeeky/aso-skills --skill retention-optimization -g -a codex -y`
Cursor: `npx skills add appeeky/aso-skills --skill retention-optimization -g -a cursor -y`
Gemini CLI: `npx skills add appeeky/aso-skills --skill retention-optimization -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add appeeky/aso-skills`

## 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.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# 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?

The rest: https://github.com/appeeky/aso-skills/blob/HEAD/skills/retention-optimization/SKILL.md