Retention Optimization
- 2.4k installs
- 1.7k repo stars
- Updated July 27, 2026
- eronred/aso-skills
retention-optimization is an ASO skill for diagnosing churn and planning mobile retention improvements.
About
The retention-optimization skill diagnoses mobile app churn and engagement problems using category benchmarks for Day 1, Day 7, and Day 30 retention across games, social, health, productivity, e-commerce, finance, and education. Initial assessment reads app-marketing-context.md when present, then collects current retention metrics, app category, monetization model, and existing engagement features. The framework covers activation in the first session, habit formation Days 1 to 7 with push and streak tactics, engagement deepening Days 7 to 30, and long-term retention beyond Day 30. It details push notification timing tables, win-back campaigns, and subscription cancellation flows that offer alternatives without forced retention. Output includes a retention diagnostic comparing metrics to benchmarks, estimated impact, and week-one quick wins plus month and quarter strategic actions. Related skills include app-analytics for tracking, monetization-strategy for revenue impact, review-management, and app-launch for onboarding.
- Category retention benchmarks for Day 1, 7, and 30 by app type.
- Four-phase framework: activation, habit, deepening, long-term.
- Push notification schedule with value-driven copy rules.
- Win-back and cancellation flows with reason-based alternatives.
- Diagnostic output with benchmark gaps and prioritized action plan.
Retention Optimization by the numbers
- 2,443 all-time installs (skills.sh)
- +75 installs in the week ending Aug 5, 2026 (Skillselion tracking)
- Ranked #239 of 1,879 Marketing & SEO skills by installs in the Skillselion catalog
- Security screen: LOW risk (skills.sh audit)
- Data as of Aug 5, 2026 (Skillselion catalog sync)
retention-optimization capabilities & compatibility
- Capabilities
- category benchmark comparison for d1/d7/d30 · activation and habit formation playbooks · push notification and win back campaign tables · cancellation flow alternatives by churn reason · structured diagnostic and phased action plan out
- Use cases
- marketing · seo
What retention-optimization says it does
The first session determines everything.
Max 3-5 notifications per week
Make it easy to cancel (forced retention backfires)
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| Installs | 2.4k |
|---|---|
| repo stars | ★ 1.7k |
| Security audit | 3 / 3 scanners passed |
| Last updated | July 27, 2026 |
| Repository | eronred/aso-skills ↗ |
Users are leaving my app; how do I improve Day 1, Day 7, and Day 30 retention?
Diagnose mobile app retention issues and deliver a prioritized plan across activation, habit formation, engagement, and churn prevention.
Who is it for?
Mobile apps with retention or engagement problems across onboarding and push strategy.
Skip if: Skip for first-launch onboarding-only issues; see app-launch. For monetization, see monetization-strategy.
When should I use this skill?
User mentions retention, churn, DAU/MAU, engagement, or users uninstalling.
What you get
Benchmarked diagnostic plus prioritized quick wins and strategic retention tactics.
- prioritized retention plan
- benchmark comparison report
By the numbers
- Benchmarks retention at Day 1, Day 7, and Day 30 checkpoints
- Ships as version 1.0.0 in eronred/aso-skills
Files
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 usersAction 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 trackingmonetization-strategy— Retention's impact on revenuereview-management— Retention issues surface in reviewsapp-launch— First-time user experience
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Pick retention-optimization over generic ASO or keyword skills when the problem is user return rates and churn, not store visibility or rankings.
FAQ
What inputs does it need first?
Retention metrics, app category, monetization model, and current engagement features.
How are push notifications constrained?
Max 3 to 5 per week, always value-driven, personalized, and A/B tested timing and copy.
What does the output include?
Diagnostic versus benchmarks, biggest drop-off, impact estimate, and week/month/quarter action plans.
Is Retention Optimization safe to install?
skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.