[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6EA4S9NT47FSXRC1GQRYRG8":3,"skill-same:01M6EA4S9NT47FSXRC1GQRYRG8":74},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":51,"commitSha":52,"skillDirectory":53,"forksCount":54,"repositoryHtmlUrl":55,"repositoryHomepageUrl":56,"ownerHtmlUrl":57,"ownerBlogUrl":6,"ownerDescription":58,"updatedAt":59,"install":60,"resources":73},"01M6EA4S9NT47FSXRC1GQRYRG8","asc-metrics",null,"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.","ComeOnOliver\u002Fskillshub","ComeOnOliver","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F43215937?v=4","01M6E5JNFECJAAVFE0W7SMWWD2","Haoran Shu","01M6E5JNNDQS7AJZDYFQ8TPZCK",67,"MIT","https:\u002F\u002Fgithub.com\u002FComeOnOliver\u002Fskillshub\u002Fblob\u002Fmain\u002Fskills\u002FEronred\u002Faso-skills\u002Fasc-metrics\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"asc metrics","metrics","asc","sales","trials","store","compare","revenue","via","app","use","performance","strategy","analyze","how","iap","data","downloads","connect","analytics","2026-11-10 10:12:30",false,"---\nname: asc-metrics\ndescription: 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.\nmetadata:\n  version: 1.0.0\n---\n\n# ASC Metrics\n\nYou 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.\n\n## Prerequisites\n\n- Appeeky account with ASC connected (Settings → Integrations → App Store Connect)\n- Indie plan or higher (2 credits per request)\n- Data syncs nightly; up to 90 days of history available\n\nIf ASC is not connected, prompt the user to connect it at [appeeky.com\u002Fsettings](https:\u002F\u002Fappeeky.com) and return.\n\n## Initial Assessment\n\n1. Check for `app-marketing-context.md` — read it for app context\n2. Ask: **What do you want to analyze?** (downloads, revenue, subscriptions, country breakdown, trend comparison)\n3. Ask: **Which time period?** (default: last 30 days)\n4. Ask: **Specific app or all apps?**\n\n## Fetching Data\n\n### Step 1 — List available apps\n\n```bash\nGET \u002Fv1\u002Fconnect\u002Fmetrics\u002Fapps\n```\n\nMatch the user's app to an `app_apple_id` if not already known.\n\n### Step 2 — Get overview (portfolio)\n\n```bash\nGET \u002Fv1\u002Fconnect\u002Fmetrics?from=YYYY-MM-DD&to=YYYY-MM-DD\n```\n\n### Step 3 — Get app detail (single app)\n\n```bash\nGET \u002Fv1\u002Fconnect\u002Fmetrics\u002Fapps\u002F:appId?from=YYYY-MM-DD&to=YYYY-MM-DD\n```\n\nResponse includes: `daily[]`, `countries[]`, `totals`.\n\nSee full API reference: [appeeky-connect.md](..\u002F..\u002Ftools\u002Fintegrations\u002Fappeeky-connect.md)\n\n## Analysis Frameworks\n\n### Period-over-Period Comparison\n\nFetch two equal-length windows and compare:\n\n| Metric | Prior Period | Current Period | Change |\n|--------|-------------|----------------|--------|\n| Downloads | [N] | [N] | [+\u002F-X%] |\n| Revenue | $[N] | $[N] | [+\u002F-X%] |\n| Subscriptions | [N] | [N] | [+\u002F-X%] |\n| Trials | [N] | [N] | [+\u002F-X%] |\n| Trial → Sub Rate | [X]% | [X]% | [+\u002F-X pp] |\n\n**What to look for:**\n- Downloads rising but revenue flat → pricing or paywall issue\n- Trials rising but conversions flat → paywall or onboarding issue\n- Revenue rising but downloads flat → good monetization improvement\n\n### Daily Trend Analysis\n\nFrom `daily[]`, identify:\n- **Spikes** — Did a feature, update, or press trigger them?\n- **Drops** — Correlate with app updates, seasonality, or algorithm changes\n- **Trend direction** — 7-day moving average vs prior 7 days\n\n### Country Breakdown\n\nSort `countries[]` by downloads and revenue:\n1. **Top 5 by downloads** — Are you investing in ASO for these markets?\n2. **Top 5 by revenue** — Higher ARPD (avg revenue per download) = prioritize ASO\n3. **High downloads, low revenue** — Markets with weak monetization\n4. **Low downloads, high revenue** — Under-tapped premium markets (localize)\n\n### Revenue Quality Check\n\nCompute from the data:\n\n| Metric | Formula | Benchmark |\n|--------|---------|-----------|\n| ARPD | Revenue \u002F Downloads | > $0.05 good; > $0.20 excellent |\n| Trial rate | Trials \u002F Downloads | > 20% means strong paywall reach |\n| Sub conversion | Subscriptions \u002F Trials | > 25% is strong |\n| Revenue per sub | Revenue \u002F Subscriptions | Depends on pricing |\n\n## Output Format\n\n### Performance Snapshot\n\n```\n? [App Name] — [Period]\n\nDownloads:     [N]  ([+\u002F-X%] vs prior period)\nRevenue:       $[N] ([+\u002F-X%])\nSubscriptions: [N]  ([+\u002F-X%])\nTrials:        [N]  ([+\u002F-X%])\nIAP Count:     [N]  ([+\u002F-X%])\nTrial→Sub:     [X]%\n\nTop Markets (downloads):\n  1. [Country] — [N] downloads, $[N]\n  2. [Country] — [N] downloads, $[N]\n  3. [Country] — [N] downloads, $[N]\n\nKey Observations:\n- [What the trend means]\n- [Any anomaly and likely cause]\n- [Opportunity identified]\n\nRecommended Actions:\n1. [Specific action based on data]\n2. [Specific action based on data]\n```\n\n### Trend Alert\n\nWhen a significant change (>20%) is detected, flag it:\n\n```\n⚠️  Downloads dropped [X]% this week\n    Possible causes: [list 2-3 hypotheses]\n    Next steps: [specific diagnostic actions]\n```\n\n## Common Questions\n\n**\"Why did my downloads drop?\"**\n1. Pull daily trend — when did it start?\n2. Check if an update shipped on that date\n3. Check keyword rankings (use `keyword-research` skill)\n4. Check competitor activity (use `competitor-analysis` skill)\n\n**\"Which countries should I localize for?\"**\nPull country breakdown → sort by downloads → flag high-download, non-English markets → use `localization` skill\n\n**\"Is my monetization improving?\"**\nCompare trial rate and trial→sub rate period over period → use `monetization-strategy` skill for paywall improvements\n\n## Related Skills\n\n- `app-analytics` — Full analytics stack setup and KPI framework\n- `monetization-strategy` — Improve subscription conversion and paywall\n- `retention-optimization` — Reduce churn using the metrics as input\n- `localization` — Expand top-performing markets seen in country data\n- `ua-campaign` — Validate whether paid installs show in downloads spike\n\n","# ASC Metrics\n\nYou 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.\n\n## Prerequisites\n\n- Appeeky account with ASC connected (Settings → Integrations → App Store Connect)\n- Indie plan or higher (2 credits per request)\n- Data syncs nightly; up to 90 days of history available\n\nIf ASC is not connected, prompt the user to connect it at [appeeky.com\u002Fsettings](https:\u002F\u002Fappeeky.com) and return.\n\n## Initial Assessment\n\n1. Check for `app-marketing-context.md` — read it for app context\n2. Ask: **What do you want to analyze?** (downloads, revenue, subscriptions, country breakdown, trend comparison)\n3. Ask: **Which time period?** (default: last 30 days)\n4. Ask: **Specific app or all apps?**\n\n## Fetching Data\n\n### Step 1 — List available apps\n\n```bash\nGET \u002Fv1\u002Fconnect\u002Fmetrics\u002Fapps\n```\n\nMatch the user's app to an `app_apple_id` if not already known.\n\n### Step 2 — Get overview (portfolio)\n\n```bash\nGET \u002Fv1\u002Fconnect\u002Fmetrics?from=YYYY-MM-DD&to=YYYY-MM-DD\n```\n\n### Step 3 — Get app detail (single app)\n\n```bash\nGET \u002Fv1\u002Fconnect\u002Fmetrics\u002Fapps\u002F:appId?from=YYYY-MM-DD&to=YYYY-MM-DD\n```\n\nResponse includes: `daily[]`, `countries[]`, `totals`.\n\nSee full API reference: [appeeky-connect.md](..\u002F..\u002Ftools\u002Fintegrations\u002Fappeeky-connect.md)\n\n## Analysis Frameworks\n\n### Period-over-Period Comparison\n\nFetch two equal-length windows and compare:\n\n| Metric | Prior Period | Current Period | Change |\n|--------|-------------|----------------|--------|\n| Downloads | [N] | [N] | [+\u002F-X%] |\n| Revenue | $[N] | $[N] | [+\u002F-X%] |\n| Subscriptions | [N] | [N] | [+\u002F-X%] |\n| Trials | [N] | [N] | [+\u002F-X%] |\n| Trial → Sub Rate | [X]% | [X]% | [+\u002F-X pp] |\n\n**What to look for:**\n- Downloads rising but revenue flat → pricing or paywall issue\n- Trials rising but conversions flat → paywall or onboarding issue\n- Revenue rising but downloads flat → good monetization improvement\n\n### Daily Trend Analysis\n\nFrom `daily[]`, identify:\n- **Spikes** — Did a feature, update, or press trigger them?\n- **Drops** — Correlate with app updates, seasonality, or algorithm changes\n- **Trend direction** — 7-day moving average vs prior 7 days\n\n### Country Breakdown\n\nSort `countries[]` by downloads and revenue:\n1. **Top 5 by downloads** — Are you investing in ASO for these markets?\n2. **Top 5 by revenue** — Higher ARPD (avg revenue per download) = prioritize ASO\n3. **High downloads, low revenue** — Markets with weak monetization\n4. **Low downloads, high revenue** — Under-tapped premium markets (localize)\n\n### Revenue Quality Check\n\nCompute from the data:\n\n| Metric | Formula | Benchmark |\n|--------|---------|-----------|\n| ARPD | Revenue \u002F Downloads | > $0.05 good; > $0.20 excellent |\n| Trial rate | Trials \u002F Downloads | > 20% means strong paywall reach |\n| Sub conversion | Subscriptions \u002F Trials | > 25% is strong |\n| Revenue per sub | Revenue \u002F Subscriptions | Depends on pricing |\n\n## Output Format\n\n### Performance Snapshot\n\n```\n? [App Name] — [Period]\n\nDownloads:     [N]  ([+\u002F-X%] vs prior period)\nRevenue:       $[N] ([+\u002F-X%])\nSubscriptions: [N]  ([+\u002F-X%])\nTrials:        [N]  ([+\u002F-X%])\nIAP Count:     [N]  ([+\u002F-X%])\nTrial→Sub:     [X]%\n\nTop Markets (downloads):\n  1. [Country] — [N] downloads, $[N]\n  2. [Country] — [N] downloads, $[N]\n  3. [Country] — [N] downloads, $[N]\n\nKey Observations:\n- [What the trend means]\n- [Any anomaly and likely cause]\n- [Opportunity identified]\n\nRecommended Actions:\n1. [Specific action based on data]\n2. [Specific action based on data]\n```\n\n### Trend Alert\n\nWhen a significant change (>20%) is detected, flag it:\n\n```\n⚠️  Downloads dropped [X]% this week\n    Possible causes: [list 2-3 hypotheses]\n    Next steps: [specific diagnostic actions]\n```\n\n## Common Questions\n\n**\"Why did my downloads drop?\"**\n1. Pull daily trend — when did it start?\n2. Check if an update shipped on that date\n3. Check keyword rankings (use `keyword-research` skill)\n4. Check competitor activity (use `competitor-analysis` skill)\n\n**\"Which countries should I localize for?\"**\nPull country breakdown → sort by downloads → flag high-download, non-English markets → use `localization` skill\n\n**\"Is my monetization improving?\"**\nCompare trial rate and trial→sub rate period over period → use `monetization-strategy` skill for paywall improvements\n\n## Related Skills\n\n- `app-analytics` — Full analytics stack setup and KPI framework\n- `monetization-strategy` — Improve subscription conversion and paywall\n- `retention-optimization` — Reduce churn using the metrics as input\n- `localization` — Expand top-performing markets seen in country data\n- `ua-campaign` — Validate whether paid installs show in downloads 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