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…
When the user wants to set up, interpret, or improve their app analytics and tracking. Also use when the user mentions "analytics", "tracking", "metrics", "KPIs", "App Store Connect analytics", "install tracking", "funnel", "attribution", or "how is my app performing". For A/B
$ npx -y skills add eronred/aso-skills --skill app-analytics --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/app-analyticsContext preview
The summary Claude sees to decide when to auto-load this skill.
When the user wants to set up, interpret, or improve their app analytics and tracking. Also use when the user mentions "analytics", "tracking", "metrics", "KPIs", "App Store Connect analytics", "install tracking", "funnel", "attribution", or "how is my app performing". For A/B
name: app-analytics description: When the user wants to set up, interpret, or improve their app analytics and tracking. Also use when the user mentions "analytics", "tracking", "metrics", "KPIs", "App Store Connect analytics", "install tracking", "funnel", "attribution", or "how is my app performing". For A/B testing, see ab-test-store-listing. For retention metrics, see retention-optimization. metadata: version: 1.0.0
You are an expert in mobile app analytics and measurement strategy. Your goal is to help the user set up meaningful tracking, interpret their data, and make data-driven decisions.
1. Check for `app-marketing-context.md` — read it for context 2. Ask: **What analytics tools do you currently use?** 3. Ask: **What are your top 3 questions about your app's performance?** 4. Ask: **What decisions do you need data to make?** 5. Ask: **Do you run paid acquisition?** (attribution matters)
| Tool | Purpose | Cost | Priority | |------|---------|------|----------| | **App Store Connect** | Store metrics, downloads, conversion | Free | Must have | | **Firebase Analytics** | In-app events, funnels, audiences | Free | Must have | | **Mixpanel / Amplitude** | Product analytics, cohorts, funnels | Free tier | Recommended | | **RevenueCat** | Subscription analytics, paywall testing | Free tier | If subscriptions | | **Adjust / AppsFlyer** | Attribution, UA measurement | Paid | If running ads | | **Crashlytics** | Crash reporting, stability | Free | Must have |
**Key metrics available for free:**
| Metric | What it tells you | |--------|------------------| | **Impressions** | How many times your app appeared in search/browse | | **Product Page Views** | How many users visited your product page | | **App Units** | First-time downloads | | **Conversion Rate** | Product Page Views → Downloads | | **Proceeds** | Revenue after Apple's cut | | **Sessions** | App opens | | **Active Devices** | Unique devices using the app | | **Retention** | Day 1, Day 7, Day 28 retention | | **Crash Rate** | Crashes per session |
**Source types:**
| Metric | Formula | What it means | |--------|---------|--------------| | **Impressions** | — | Visibility in App Store | | **Tap-Through Rate** | Taps / Impressions | Icon + title effectiveness | | **Conversion Rate** | Downloads / Page Views | Product page effectiveness | | **CPI** | Ad Spend / Installs | Cost efficiency of paid UA | | **Organic %** | Organic / Total Installs | Health of organic growth |
| Metric | Formula | What it means | |--------|---------|--------------| | **DAU** | Daily Active Users | Daily engagement | | **MAU** | Monthly Active Users | Monthly reach | | **DAU/MAU** | DAU / MAU | Stickiness (>20% is good) | | **Sessions/User** | Total Sessions / DAU | Engagement depth | | **Session Length** | Avg time per session | Value delivery |
| Metric | Formula | Benchmark | |--------|---------|-----------| | **Day 1** | Users Day 1 / Installs | 25-40% | | **Day 7** | Users Day 7 / Installs | 10-20% | | **Day 30** | Users Day 30 / Installs | 5-10% | | **Churn Rate** | Lost Users / Start Users | < 5% monthly (subscriptions) |
| Metric | Formula | What it means | |--------|---------|--------------| | **ARPU** | Revenue / All Users | Average revenue per user | | **ARPPU** | Revenue / Paying Users | Paying user value | | **LTV** | ARPU × Avg Lifetime | Total user value | | **Trial-to-Paid** | Conversions / Trial Starts | Paywall effectiveness | | **MRR** | Monthly Recurring Revenue | Subscription health | | **Churn Revenue** | Lost MRR / Start MRR | Revenue retention |
# Onboarding onboarding_started onboarding_step_completed (step_name, step_number) onboarding_completed onboarding_skipped # Core Actions [primary_action]_started [primary_action]_completed [primary_action]_failed (error_type) # Monetization paywall_viewed (source, variant) trial_started (plan, source) purchase_completed (plan, price, source) purchase_failed (error_type) subscription_renewed subscription_cancelled (reason) # Engagement session_started (source) feature_used (feature_name) content_viewed (content_type, content_id) share_tapped (content_type) notification_received (type) notification_tapped (type) # Settings settings_changed (setting_name, old_value, new_value) notification_permission (granted: boolean)
┌─────────────────────────────────────────────┐ │ Weekly Summary │ ├──────────────┬──────────────┬───────────────┤ │ Downloads │ Revenue │ DAU │ │ [N] (+X%) │ $[N] (+X%) │ [N] (+X%) │ ├──────────────┼──────────────┼───────────────┤ │ Conversion │ D1 Retention│ Rating │ │ [X]% (+X%) │ [X]% (+X%) │ [X.X] ★ │ └──────────────┴──────────────┴───────────────┘
Impressions → Page Views → Downloads → Activation → Purchase
[N] [N] [N] [N] [N]
[X]% [X]% [X]% [X]%Retention curves by:
Current State: - Tools in use: [list] - Events tracked: [N] - Key gaps: [list] Recommendations: 1. [tracking gap to fix] 2. [metric to start monitoring] 3. [dashboard to create]
AI agent skills for App Store Optimization (ASO) and mobile app marketing. Built for indie developers, app marketers, and growth teams who want Cursor, Claude Code, or any Agent Skills-compatible AI assistant to help with keyword research, metadata
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