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.
What this skill does
# 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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