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.
MCP get_skill({ skillId: "retention-optimization-fd9179df" })Use this skill with your agent
Create a free account and connect via MCP
# 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
Related Skills
More skills in Business, Marketing & Sales
Ab Testing
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program," or "experiment playbook." Use this whenever someone is comparing two approaches and wants to measure which performs better, or when they want to build a systematic experimentation practice. For tracking implementation, see analytics. For page-level conversion optimization, see cro.
Ab Test Setup
When the user wants to plan, design, or implement an A/B test or experiment. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "conversion experiment," "statistical significance," or "test this." For tracking implementation, see analytics-tracking.
Ab Test Setup
Ab Test Setup linked from Corey Haines marketing skills, with the upstream skill instructions available on GitHub.
Ab Test Store Listing
When the user wants to A/B test App Store product page elements to improve conversion rate. Also use when the user mentions "A/B test", "product page optimization", "test my screenshots", "test my icon", "conversion rate optimization", "CPP", or "custom product pages". For screenshot design, see screenshot-optimization. For metadata optimization, see metadata-optimization.
Account Research
Research a company or person and get actionable sales intel. Works standalone with web search, supercharged when you connect enrichment tools or your CRM. Trigger with "research [company]", "look up [person]", "intel on [prospect]", "who is [name] at [company]", or "tell me about [company]".
Account Research
Research a company using Common Room data. Triggers on 'research [company]', 'tell me about [domain]', 'pull up signals for [account]', 'what's going on with [company]', or any account-level question.
Explore Other Categories
Skills from other categories with shared topics
App Rejection Recovery
When the user's app or update was rejected by Apple App Review or Google Play Review and they need to diagnose why, fix it, and resubmit fast. Use when the user mentions "app rejected", "App Review rejection", "guideline violation", "Apple rejected my app", "Google Play rejected", "Play policy violation", "Resolution Center", "metadata rejection", "binary rejection", "guideline 2.1", "guideline 4.3", "guideline 5.1.1", "Sign in with Apple required", "Apple ID rejection", "Play Store suspension", "appeal", "I need to respond to App Review", or "expedited review". For pre-submission listing health, see aso-audit. For metadata-only fixes, see metadata-optimization.
Crash Analytics
When the user wants to monitor, triage, or reduce their app's crash rate — including setting up Crashlytics, prioritizing which crashes to fix first, interpreting crash data, and understanding how crashes affect App Store ranking. Use when the user mentions "crash", "crashlytics", "crash rate", "ANR", "app not responding", "crash-free sessions", "crash-free users", "symbolication", "stability", "firebase crashes", "app crashing", or "crash report". For overall analytics setup, see app-analytics.
Agent Protocol
Inter-agent communication protocol for C-suite agent teams. Defines invocation syntax, loop prevention, isolation rules, and response formats. Use when C-suite agents need to query each other, coordinate cross-functional analysis, or run board meetings with multiple agent roles.