MCPInstall

asc-metrics

When the user wants to analyze their own app's actual performance data from App Store Connect — real downloads, revenue, IAP, subscriptions, trials, or country breakdowns synced via Appeeky Connect. Use when the user asks about "my downloads", "my revenue", "how is my app performing", "ASC data", "sales and trends", "my subscription numbers", "App Store Connect metrics", or wants to compare periods or top markets. For third-party app estimates, see app-analytics. For subscription analytics depth, see monetization-strategy.

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/appeeky/aso-skills --skill asc-metrics
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads asc-metrics automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

ASC Metrics

You analyze the user's official App Store Connect data synced into Appeeky — exact downloads, revenue, IAP, subscriptions, and trials. This is first-party data, not estimates.

Prerequisites

  • Appeeky account with ASC connected (Settings → Integrations → App Store Connect)
  • Indie plan or higher (2 credits per request)
  • Data syncs nightly; up to 90 days of history available

If ASC is not connected, prompt the user to connect it at appeeky.com/settings and return.

Initial Assessment

  1. Check for app-marketing-context.md — read it for app context
  2. Ask: What do you want to analyze? (downloads, revenue, subscriptions, country breakdown, trend comparison)
  3. Ask: Which time period? (default: last 30 days)
  4. Ask: Specific app or all apps?

Fetching Data

Step 1 — List available apps

GET /v1/connect/metrics/apps

Match the user's app to an app_apple_id if not already known.

Step 2 — Get overview (portfolio)

GET /v1/connect/metrics?from=YYYY-MM-DD&to=YYYY-MM-DD

Step 3 — Get app detail (single app)

GET /v1/connect/metrics/apps/:appId?from=YYYY-MM-DD&to=YYYY-MM-DD

Response includes: daily[], countries[], totals.

See full API reference: appeeky-connect.md

Analysis Frameworks

Period-over-Period Comparison

Fetch two equal-length windows and compare:

MetricPrior PeriodCurrent PeriodChange
Downloads[N][N][+/-X%]
Revenue$[N]$[N][+/-X%]
Subscriptions[N][N][+/-X%]
Trials[N][N][+/-X%]
Trial → Sub Rate[X]%[X]%[+/-X pp]

What to look for:

  • Downloads rising but revenue flat → pricing or paywall issue
  • Trials rising but conversions flat → paywall or onboarding issue
  • Revenue rising but downloads flat → good monetization improvement

Daily Trend Analysis

From daily[], identify:

  • Spikes — Did a feature, update, or press trigger them?
  • Drops — Correlate with app updates, seasonality, or algorithm changes
  • Trend direction — 7-day moving average vs prior 7 days

Country Breakdown

Sort countries[] by downloads and revenue:

  1. Top 5 by downloads — Are you investing in ASO for these markets?
  2. Top 5 by revenue — Higher ARPD (avg revenue per download) = prioritize ASO
  3. High downloads, low revenue — Markets with weak monetization
  4. Low downloads, high revenue — Under-tapped premium markets (localize)

Revenue Quality Check

Compute from the data:

MetricFormulaBenchmark
ARPDRevenue / Downloads> $0.05 good; > $0.20 excellent
Trial rateTrials / Downloads> 20% means strong paywall reach
Sub conversionSubscriptions / Trials> 25% is strong
Revenue per subRevenue / SubscriptionsDepends on pricing

Output Format

Performance Snapshot

📊 [App Name] — [Period]

Downloads:     [N]  ([+/-X%] vs prior period)
Revenue:       $[N] ([+/-X%])
Subscriptions: [N]  ([+/-X%])
Trials:        [N]  ([+/-X%])
IAP Count:     [N]  ([+/-X%])
Trial→Sub:     [X]%

Top Markets (downloads):
  1. [Country] — [N] downloads, $[N]
  2. [Country] — [N] downloads, $[N]
  3. [Country] — [N] downloads, $[N]

Key Observations:
- [What the trend means]
- [Any anomaly and likely cause]
- [Opportunity identified]

Recommended Actions:
1. [Specific action based on data]
2. [Specific action based on data]

Trend Alert

When a significant change (>20%) is detected, flag it:

⚠️  Downloads dropped [X]% this week
    Possible causes: [list 2-3 hypotheses]
    Next steps: [specific diagnostic actions]

Common Questions

"Why did my downloads drop?"

  1. Pull daily trend — when did it start?
  2. Check if an update shipped on that date
  3. Check keyword rankings (use keyword-research skill)
  4. Check competitor activity (use competitor-analysis skill)

"Which countries should I localize for?" Pull country breakdown → sort by downloads → flag high-download, non-English markets → use localization skill

"Is my monetization improving?" Compare trial rate and trial→sub rate period over period → use monetization-strategy skill for paywall improvements

Related Skills

  • app-analytics — Full analytics stack setup and KPI framework
  • monetization-strategy — Improve subscription conversion and paywall
  • retention-optimization — Reduce churn using the metrics as input
  • localization — Expand top-performing markets seen in country data
  • ua-campaign — Validate whether paid installs show in downloads spike

FAQ

What does the asc-metrics skill do?

When the user wants to analyze their own app's actual performance data from App Store Connect — real downloads, revenue, IAP, subscriptions, trials, or country breakdowns synced via Appeeky Connect. Use when the user asks about "my downloads", "my revenue", "how is my app performing", "ASC data", "sales and trends", "my subscription numbers", "App Store Connect metrics", or wants to compare periods or top markets. For third-party app estimates, see app-analytics. For subscription analytics depth, see monetization-strategy.

How do I install asc-metrics?

Run npx skills add https://github.com/appeeky/aso-skills --skill asc-metrics in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/asc-metrics/ (personal) or .claude/skills/asc-metrics/ (project).

Which AI agents can use asc-metrics?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is asc-metrics safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains asc-metrics?

It is published by appeeky in appeeky/aso-skills. It has 2,470 recorded installs.

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