asc-metrics

name	asc-metrics
description	When the user wants to analyze their own app's actual performance data from App Store Connect — downloads, revenue, IAP, subscriptions, trials, country breakdowns, analytics, or sales reports via the App Store Connect CLI. 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 ASO keyword/ranking evidence, use Astro MCP. For third-party app estimates, see app-analytics. For subscription analytics depth, see monetization-strategy.
metadata	{"version":"1.0.0"}

ASC Metrics

You analyze the user's official App Store Connect data through the asc CLI — downloads, revenue, IAP, subscriptions, trials, and reports. This is first-party data, not estimates.

Prerequisites

• App Store Connect CLI installed: asc version
• Authenticated API profile: asc auth status --validate
• Access to analytics/sales/finance endpoints depends on the App Store Connect API key role.

If auth is missing, ask the user to run asc auth login with their App Store Connect API key details, then validate with asc auth doctor.

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

Use explicit JSON output for analysis.

Step 1 — Validate auth and list apps

asc auth status --validate
asc apps list --output json

Match the user's app to the numeric App Store Connect app ID if not already known.

Step 2 — Discover available report commands

asc analytics --help
asc insights --help
asc finance --help
asc performance --help

Step 3 — Pull the relevant official data

asc analytics get --help
asc analytics get --date YYYY-MM-DD --output json --paginate
asc insights --help
asc finance --help

Use --paginate on list/report commands when available. If a metric is not exposed by the API or the key lacks permission, say so and ask for an App Store Connect export instead.

ASO Context

Use Astro MCP for ranking/rating context alongside official metrics:

• search_rankings with includeHistory: true
• get_app_ratings with includeHistory: true
• get_app_keywords

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