analytics-interpretation
Interpret app metrics and make data-driven decisions. Covers DAU/MAU, retention, LTV, ARPU, App Store Connect analytics, AARRR funnel analysis, cohort analysis, and diagnostic decision trees. Use when user wants to understand their metrics, diagnose problems, or build a data-driven growth plan.
npx skills add rshankras/claude-code-apple-skills --skill analytics-interpretation --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
Interpret your app's metrics, diagnose problems, and make data-driven decisions. Works with App Store Connect data, third-party analytics, or raw numbers the user provides.
How it works
Step 1: Gather Context Ask the user questions about app type, monetization, available metrics, and what they want to learn. Also pull App Store Connect peer-group benchmarks before interpreting trends.
Step 2: Identify Key Metrics by App Type Categorize metrics based on monetization model (Free with Ads, Freemium, Subscription, Paid Upfront) and explain why each metric matters.
Step 3: App Store Connect Analytics Interpretation Explain the funnel from Impressions to Paying Users, define key terms, and segment metrics by source types and page type. Provide interpretation guidance for each funnel step (Impressions to TTR, TTR to Downloads, D1, D7, D30 retention, DAU/MAU).
Step 4: AARRR Funnel Analysis Diagnose acquisition, activation, retention, revenue, and referral with benchmarks and diagnostic questions.
Step 5: Cohort Analysis (Subscription Apps) Describe reading cohort retention tables, rules of thumb for interpreting changes, and how to compare cohorts before/after changes. Include App Store Connect subscription metrics and segment cohorts by acquisition source.
Step 6: Diagnostic Decision Trees If the user reports a bad metric, use decision trees to guide actions for low impressions, high impressions with low product page views, good downloads but poor retention, and good retention with low revenue, including concrete remediation steps.
Step 7: Invest, Iterate, Pivot, or Sunset? Provide guidance on paths to take based on the overall metrics picture.
# Analytics Interpretation Interpret your app's metrics, diagnose problems, and make data-driven decisions. Works with App Store Connect data, third-party analytics, or raw numbers the user provides. ## When This Skill Activates Use this skill when the user: - Wants to understand their app metrics or analytics - Asks about retention, LTV, ARPU, or churn - Wants to know if their metrics are good or bad - Needs help interpreting App Store Connect analytics - Wants a data-driven growth plan - Asks "what should I focus on to grow?" - Has metrics data and wants to know what it means ## Process ### Step 1: Gather Context Ask the user via AskUserQuestion: 1. **App type and monetization model** - Free with ads, freemium, subscription, paid upfront, or hybrid? 2. **Current metrics they have access to** - App Store Connect? Third-party analytics (Mixpanel, Firebase, Amplitude)? 3. **Specific numbers they can share** - Downloads, DAU/MAU, retention, revenue, conversion rates? 4. **What they want to know** - "Are my metrics good?" / "What should I fix?" / "Should I keep going?" Also pull App Store Connect **peer group benchmarks** (App Analytics → Benchmarks) before interpreting any trend — th
- When This Skill Activates
- Process
- Step 1: Gather Context
- Step 2: Identify Key Metrics by App Type
- Step 3: App Store Connect Analytics Interpretation
- Step 4: AARRR Funnel Analysis
- Step 5: Cohort Analysis (Subscription Apps)
- Step 6: Diagnostic Decision Trees
- Step 7: Invest, Iterate, Pivot, or Sunset?
- Reference Files
- Output Format
- References
What does the analytics-interpretation skill do?
Interpret app metrics and make data-driven decisions. Covers DAU/MAU, retention, LTV, ARPU, App Store Connect analytics, AARRR funnel analysis, cohort analysis, and diagnostic decision trees. Use when user wants to understand their metrics, diagnose problems, or build a data-driven growth plan.
How do I install it?
Run `npx skills add rshankras/claude-code-apple-skills --skill analytics-interpretation --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From rshankras/claude-code-apple-skills, a repository with 589 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.