Asc Metrics

ASC Metrics

You analyze the user's official App Store Connect data pulled directly from Apple's App Store Connect API — exact downloads, revenue, IAP, subscriptions, and trials. This is first-party data, not estimates.

Prerequisites

• App Store Connect API key with the Sales and Finance role (see tools/integrations/app-store-connect.md)
• JWT built from the .p8 key, Issuer ID, and Key ID
• Sales reports retention: rolling 365 days (daily), longer (weekly/monthly/yearly)

If the user hasn't generated an API key yet, point them to App Store Connect → Users and Access → Integrations → App Store Connect API 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

All endpoints below live under https://api.appstoreconnect.apple.com/v1/ and require a JWT in Authorization: Bearer <jwt>.

Step 1 — List your apps

GET /v1/apps

Match the user's app to its id and attributes.bundleId.

Step 2 — Pull Sales & Trends (portfolio or app)

GET /v1/salesReports
  ?filter[frequency]=DAILY
  &filter[reportType]=SALES
  &filter[reportSubType]=SUMMARY
  &filter[vendorNumber]=<your vendor id>
  &filter[reportDate]=YYYY-MM-DD

Returns a gzipped TSV. Parse and aggregate per-date / per-country / per-sku.

Step 3 — Pull Subscription reports

GET /v1/salesReports
  ?filter[frequency]=DAILY
  &filter[reportType]=SUBSCRIPTION
  &filter[reportSubType]=SUMMARY
  &filter[vendorNumber]=<your vendor id>
  &filter[version]=1_4
  &filter[reportDate]=YYYY-MM-DD

Step 4 — Pull Finance reports (actual paid revenue, monthly)

GET /v1/financeReports
  ?filter[regionCode]=Z1
  &filter[reportType]=FINANCIAL
  &filter[vendorNumber]=<your vendor id>
  &filter[reportDate]=YYYY-MM

Build your own daily[], countries[], and totals from the parsed TSVs.

See full integration guide: app-store-connect.md

Analysis Frameworks

Period-over-Period Comparison

Fetch two equal-length windows and compare:

Metric	Prior Period	Current Period	Change
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:

Metric	Formula	Benchmark
ARPD	Revenue / Downloads	> $0.05 good; > $0.20 excellent
Trial rate	Trials / Downloads	> 20% means strong paywall reach
Sub conversion	Subscriptions / Trials	> 25% is strong
Revenue per sub	Revenue / Subscriptions	Depends 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