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Aso-skills 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.

install
source · Clone the upstream repo
git clone https://github.com/Eronred/aso-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/Eronred/aso-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/asc-metrics" ~/.claude/skills/eronred-aso-skills-asc-metrics && rm -rf "$T"
manifest: skills/asc-metrics/SKILL.md
source content

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