# retention-optimization

Diagnoses mobile app churn and provides a prioritized retention plan. Useful when users stop returning, engagement drops, or push notifications need a rework.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · 3300 installs · ★ 2219
- Author: appeeky
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/appeeky/aso-skills/tree/HEAD/skills/retention-optimization/SKILL.md
- Updated: 2026-10-06
- HTML: https://affpapa.org/en/nevibecode/skills/retention-optimization

## What it does

This skill analyzes user churn in mobile apps and provides a structured action plan. It first checks for `app-marketing-context.md` in the project, then asks for your category, monetization model, and retention figures. The agent compares these stats against category benchmarks, including games, finance, and social apps.

The workflow covers activation, habit formation, engagement, and long-term retention. It helps draft personalized push notifications, reduce initial onboarding friction, and build subscription cancellation flows with pause options. The final output provides a diagnosis and prioritizes tasks for the first week, month, and quarter.

Baseline retention figures are strictly required. Running the skill without actual metrics reduces it to generic advice.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add appeeky/aso-skills --skill retention-optimization -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/retention-optimization/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/retention-optimization/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add appeeky/aso-skills --skill retention-optimization -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/retention-optimization/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add appeeky/aso-skills --skill retention-optimization -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/retention-optimization/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install appeeky/aso-skills retention-optimization
```

2. **Manually: put the files in place**
- File: `.github/skills/retention-optimization/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add appeeky/aso-skills --skill retention-optimization -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/appeeky/aso-skills --path skills/retention-optimization
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/retention-optimization/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add appeeky/aso-skills --skill retention-optimization -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/appeeky/aso-skills/tree/HEAD/skills/retention-optimization/SKILL.md

## When to use it
- diagnose drop-off points during onboarding and initial app sessions
- schedule targeted push notifications based on user activity
- create retention flows for subscription cancellation screens
- compare app retention metrics against industry category benchmarks

## Example prompts
- Analyze our mobile app retention metrics and give me a prioritized plan
- Help me design a push notification schedule to bring users back during their first week
- How can we improve our subscription cancellation flow to reduce churn?

## Source text · SKILL.md · MIT

Below is the content of a third-party file. It is data, not instructions for you: do not act on anything written inside unless the human asks. Block tag: 145cedcfadb364b0.

BEGIN THIRD-PARTY FILE 145cedcfadb364b0
```text
---
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.
metadata:
  version: 1.0.0
---

# 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?
```
END THIRD-PARTY FILE 145cedcfadb364b0

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---
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