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asc-metrics

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🇺🇸

Original

English
🇨🇳

Translation

Chinese

ASC Metrics

ASC指标

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.
你需要分析同步到Appeeky中的用户官方App Store Connect数据——精确的下载量、收入、IAP、订阅和试用数据。这是第一方数据，而非估算值。

Prerequisites

前提条件

  • 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.
  • 已连接ASC的Appeeky账户（设置 → 集成 → App Store Connect）
  • Indie套餐或更高版本（每次请求消耗2个积分）
  • 数据每日同步；最多可查看90天的历史数据
若未连接ASC，请提示用户前往appeeky.com/settings进行连接后再返回。

Initial Assessment

初始评估

  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?
  1. 查看
    app-marketing-context.md
    文件——了解应用背景信息
  2. 询问：你想要分析哪些内容？（下载量、收入、订阅、地区细分、趋势对比）
  3. 询问：时间范围是？（默认：过去30天）
  4. 询问：特定应用还是所有应用？

Fetching Data

获取数据

Step 1 — List available apps

步骤1 — 列出可用应用

bash
GET /v1/connect/metrics/apps
Match the user's app to an 
app_apple_id
if not already known.
bash
GET /v1/connect/metrics/apps
若尚未知晓用户的应用ID，需将用户的应用与
app_apple_id
进行匹配。

Step 2 — Get overview (portfolio)

步骤2 — 获取总览（应用组合）

bash
GET /v1/connect/metrics?from=YYYY-MM-DD&to=YYYY-MM-DD
bash
GET /v1/connect/metrics?from=YYYY-MM-DD&to=YYYY-MM-DD

Step 3 — Get app detail (single app)

步骤3 — 获取应用详情（单个应用）

bash
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
bash
GET /v1/connect/metrics/apps/:appId?from=YYYY-MM-DD&to=YYYY-MM-DD
响应内容包含：
daily[]
、
countries[]
、
totals
。
查看完整API参考：appeeky-connect.md

Analysis Frameworks

分析框架

Period-over-Period Comparison

同期对比分析

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
获取两个等长的时间窗口并进行对比：
指标上期本期变化
下载量[N][N][±X%]
收入$[N]$[N][±X%]
订阅数[N][N][±X%]
试用数[N][N][±X%]
试用转订阅率[X]%[X]%[±X个百分点]
关注要点：
  • 下载量上升但收入持平 → 定价或付费墙存在问题
  • 试用数上升但转化率持平 → 付费墙或新手引导存在问题
  • 收入上升但下载量持平 → 变现策略优化效果良好

Daily Trend Analysis

每日趋势分析

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
从
daily[]
数据中识别：
  • 峰值 — 是否由功能更新、版本迭代或媒体报道引发？
  • 下降 — 与应用更新、季节性因素或算法变化关联分析
  • 趋势方向 — 7日移动平均值与之前7天对比

Country Breakdown

地区细分分析

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)
按下载量和收入对
countries[]
进行排序：
  1. 下载量Top5地区 — 你是否在这些市场投入ASO优化？
  2. 收入Top5地区 — ARPD（每下载平均收入）越高，越应优先进行ASO优化
  3. 高下载量、低收入 — 变现能力较弱的市场
  4. 低下载量、高收入 — 未充分开发的高端市场（需本地化）

Revenue Quality Check

收入质量检查

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
从数据中计算以下指标：
指标计算公式基准值
ARPD收入 / 下载量>$0.05为良好；>$0.20为优秀
试用率试用数 / 下载量>20%意味着付费墙触达效果好
订阅转化率订阅数 / 试用数>25%表现强劲
每订阅收入收入 / 订阅数取决于定价策略

Output Format

输出格式

Performance Snapshot

性能快照

📊 [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]
📊 [应用名称] — [时间范围]

下载量:     [N] （较上期 [±X%]）
收入:       $[N]（较上期 [±X%]）
订阅数:     [N] （较上期 [±X%]）
试用数:     [N] （较上期 [±X%]）
IAP购买量:  [N] （较上期 [±X%]）
试用转订阅率:     [X]%

顶级市场（按下载量）:
  1. [国家] — [N] 次下载，$[N] 收入
  2. [国家] — [N] 次下载，$[N] 收入
  3. [国家] — [N] 次下载，$[N] 收入

关键发现:
- [趋势含义]
- [异常情况及可能原因]
- [识别到的机会]

建议行动:
1. [基于数据的具体行动]
2. [基于数据的具体行动]

Trend Alert

趋势警报

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]
当检测到显著变化（>20%）时，进行标记：
⚠️  本周下载量下降了 [X]%
    可能原因: [列出2-3个假设]
    下一步行动: [具体诊断措施]

Common Questions

常见问题

"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
“为什么我的下载量下降了？”
  1. 提取每日趋势——下降从何时开始？
  2. 检查是否在该日期发布了应用更新
  3. 检查关键词排名（使用
    keyword-research
    技能）
  4. 检查竞品动态（使用
    competitor-analysis
    技能）
“我应该为哪些国家进行本地化？” 提取地区细分数据 → 按下载量排序 → 标记高下载量的非英语市场 → 使用
localization
技能
“我的变现策略是否在优化？” 对比不同时间段的试用率和试用转订阅率 → 使用
monetization-strategy
技能优化付费墙

Related Skills

相关技能

  • 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
  • app-analytics
    — 完整分析栈搭建与KPI框架
  • monetization-strategy
    — 提升订阅转化率与付费墙效果
  • retention-optimization
    — 利用指标数据降低用户流失
  • localization
    — 拓展地区数据中表现优异的市场
  • ua-campaign
    — 验证付费安装是否体现在下载量峰值中