asc-metrics▌
eronred/aso-skills · updated Apr 8, 2026
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.
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
- Check for
app-marketing-context.md— read it for app context - Ask: What do you want to analyze? (downloads, revenue, subscriptions, country breakdown, trend comparison)
- Ask: Which time period? (default: last 30 days)
- 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:
| 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:
- Top 5 by downloads — Are you investing in ASO for these markets?
- Top 5 by revenue — Higher ARPD (avg revenue per download) = prioritize ASO
- High downloads, low revenue — Markets with weak monetization
- 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?"
- Pull daily trend — when did it start?
- Check if an update shipped on that date
- Check keyword rankings (use
keyword-researchskill) - Check competitor activity (use
competitor-analysisskill)
"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 frameworkmonetization-strategy— Improve subscription conversion and paywallretention-optimization— Reduce churn using the metrics as inputlocalization— Expand top-performing markets seen in country dataua-campaign— Validate whether paid installs show in downloads spike
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★75 reviews- ★★★★★Pratham Ware· Dec 28, 2024
Solid pick for teams standardizing on skills: asc-metrics is focused, and the summary matches what you get after install.
- ★★★★★Alexander Jackson· Dec 28, 2024
Registry listing for asc-metrics matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Amelia Smith· Dec 16, 2024
asc-metrics reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Sofia Harris· Dec 8, 2024
I recommend asc-metrics for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Sofia Sanchez· Dec 4, 2024
We added asc-metrics from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Sofia Huang· Nov 27, 2024
Keeps context tight: asc-metrics is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Sofia Brown· Nov 23, 2024
asc-metrics reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Sofia Liu· Nov 19, 2024
asc-metrics fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Amelia Anderson· Nov 7, 2024
We added asc-metrics from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Naina Haddad· Oct 26, 2024
asc-metrics fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
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