retention-optimization
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.
Best use case
retention-optimization is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using retention-optimization should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/retention-optimization/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How retention-optimization Compares
| Feature / Agent | retention-optimization | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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 - "Missing feature" → Share roadmap, offer to notify - "Found alternative" → Highlight unique value 3. Offer pause instead of cancel 4. Make it easy to cancel (forced retention backfires) ## Output Format ### Retention Diagnostic ``` Current State: - Day 1: [X]% (benchmark: [Y]%) [above/below] - Day 7: [X]% (benchmark: [Y]%) [above/below] - Day 30: [X]% (benchmark: [Y]%) [above/below] Biggest Drop-off: Day [N] to Day [N] Estimated Impact: [X]% improvement = [Y] additional monthly users ``` ### Action Plan **Week 1 (Quick Wins):** 1. [specific tactic with expected impact] 2. [specific tactic with expected impact] **Month 1 (High Impact):** 1. [specific tactic with expected impact] 2. [specific tactic with expected impact] **Quarter 1 (Strategic):** 1. [specific tactic with expected impact] 2. [specific tactic with expected impact] ## Related Skills - `app-analytics` — Set up retention tracking - `monetization-strategy` — Retention's impact on revenue - `review-management` — Retention issues surface in reviews - `app-launch` — First-time user experience
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