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asc-metrics

asc-metrics

github.com/appeekyData & databases2.2k2.5k installsUpdated 3w ago
Repository

About asc-metrics

A skill for analyzing official App Store Connect data synced to Appeeky, including downloads, revenue, in-app purchases, subscriptions, and trials. It is intended for app teams that need first-party performance analysis by period, app, or country rather than estimates.

Key features

  1. 01App Store Connect metrics retrieval
  2. 02Period-over-period comparisons
  3. 03Daily trend analysis
  4. 04Country-level breakdowns
  5. 05Revenue quality calculations
  6. 06Performance snapshot and alerts

Use cases

  1. 01Comparing downloads and revenue across periods
  2. 02Finding daily spikes or drops
  3. 03Identifying countries for localization
  4. 04Assessing trial and subscription conversion

Install

Copy the command and run it in a terminal.

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

After installing, type/asc-metricsin Claude Code to confirm it loaded.

Details

From the project README

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

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