app-analytics▌
eronred/aso-skills · updated Apr 8, 2026
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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.
App Analytics
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.
Initial Assessment
- Check for
app-marketing-context.md— read it for context - Ask: What analytics tools do you currently use?
- Ask: What are your top 3 questions about your app's performance?
- Ask: What decisions do you need data to make?
- Ask: Do you run paid acquisition? (attribution matters)
Analytics Stack
Essential Tools
| 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 |
App Store Connect Analytics
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:
- App Store Search
- App Store Browse
- Web Referral
- App Referral
Key Metrics Framework
Acquisition Metrics
| 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 |
Engagement Metrics
| 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 |
Retention Metrics
| 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) |
Revenue Metrics
| 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 |
Event Tracking Plan
Core Events (track these minimum)
# 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)
Event Naming Conventions
- Use
snake_case - Format:
[object]_[action](e.g.,photo_saved,workout_completed) - Be specific but not too granular
- Include relevant properties (but not PII)
- Consistent across platforms
Dashboard Setup
Executive Dashboard (check weekly)
┌─────────────────────────────────────────────┐
│ Weekly Summary │
├──────────────┬──────────────┬───────────────┤
│ Downloads │ Revenue │ DAU │
│ [N] (+X%) │ $[N] (+X%) │ [N] (+X%) │
├──────────────┼──────────────┼───────────────┤
│ Conversion │ D1 Retention│ Rating │
│ [X]% (+X%) │ [X]% (+X%) │ [X.X] ★ │
└──────────────┴──────────────┴───────────────┘
Funnel Dashboard (check daily)
Impressions → Page Views → Downloads → Activation → Purchase
[N] [N] [N] [N] [N]
[X]% [X]% [X]% [X]%
Cohort Dashboard (check monthly)
Retention curves by:
- Install date cohort
- Acquisition source
- Country
- Subscription plan
Output Format
Analytics Audit
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]
Tracking Plan
Provide a complete event tracking plan with:
- Event name
- When it fires
- Properties to include
- Which tool tracks it
Metric Interpretation
When the user shares data, provide:
- How their metrics compare to benchmarks
- What the trends indicate
- Specific actions to take based on the data
Related Skills
ab-test-store-listing— Measure test resultsretention-optimization— Interpret retention datamonetization-strategy— Revenue metric optimizationua-campaign— Attribution and UA metrics
How to use app-analytics on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add app-analytics
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches app-analytics from GitHub repository eronred/aso-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate app-analytics. Access the skill through slash commands (e.g., /app-analytics) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★46 reviews- ★★★★★Ganesh Mohane· Dec 16, 2024
We added app-analytics from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Amina Haddad· Dec 16, 2024
app-analytics has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Maya Singh· Dec 8, 2024
app-analytics reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Maya Srinivasan· Dec 4, 2024
app-analytics fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Harper Rao· Dec 4, 2024
We added app-analytics from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Chinedu Iyer· Nov 23, 2024
We added app-analytics from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Ava Ramirez· Nov 15, 2024
I recommend app-analytics for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Sakshi Patil· Nov 7, 2024
app-analytics fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Harper Patel· Nov 7, 2024
Useful defaults in app-analytics — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Chaitanya Patil· Oct 26, 2024
Registry listing for app-analytics matched our evaluation — installs cleanly and behaves as described in the markdown.
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