app-analytics

eronred/aso-skills · updated Apr 8, 2026

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$npx skills add https://github.com/eronred/aso-skills --skill app-analytics
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summary

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.

skill.md

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

  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)

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 results
  • retention-optimization — Interpret retention data
  • monetization-strategy — Revenue metric optimization
  • ua-campaign — Attribution and UA metrics
how to use app-analytics

How to use app-analytics on Cursor

AI-first code editor with Composer

1

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
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/eronred/aso-skills --skill app-analytics

The skills CLI fetches app-analytics from GitHub repository eronred/aso-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/app-analytics

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

GET_STARTED →

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. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 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

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.746 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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