菜单
Use when analyzing retention, cohort behavior, repeat purchase, active user return, lifecycle changes, or user stickiness over time. Builds cohort definitions, retention matrices, segment comparisons, and business interpretations.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Use when writing a concise daily report, daily worklog, standup update, shift handoff, or end-of-day summary for data analysis, data development, BI, governance, or operations work.
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Use when planning integration with databases, BI tools, data platforms, APIs, workflow systems, storage services, or third-party tools, including connection requirements, API availability, auth strategy, configuration questions, and validation steps.
Use when planning or writing market research for a specific industry, product category, competitor set, business opportunity, user segment, or go-to-market question with structured evidence and clear assumptions.
Use when diagnosing business metric changes or anomalies such as GMV decline, conversion drop, retention loss, churn increase, revenue change, lead decline, or active user fluctuation with a structured root cause analysis plan.
| name | retention-cohort-analysis |
| description | Use when analyzing retention, cohort behavior, repeat purchase, active user return, lifecycle changes, or user stickiness over time. Builds cohort definitions, retention matrices, segment comparisons, and business interpretations. |
分析用户、客户或业务对象在一段时间后的回访、复购、活跃或留存情况，并通过 Cohort 找出不同批次之间的差异。
这个 Skill 关注留存和 Cohort 分析，不负责完整增长策略，也不直接替代指标口径审查。
使用这个 Skill，当用户需要分析：
典型输入：
帮我看不同渠道新用户的 7 日和 30 日留存表现。
不要用这个 Skill 直接完成：
funnel-analysisab-test-analysismetric-definition-reviewerdata-analysis-report-writer如果没有明确“首日行为”和“回访行为”，先定义 Cohort 口径。
最少输入：
可选输入：
推荐使用 数据分析上下文模板。
最有价值的上下文是：Cohort 起点、回访行为、用户 ID、时间字段、留存窗口和分群维度。缺少时间窗口定义时，必须区分自然日、滚动窗口和自然周，不能混用。
## 留存 / Cohort 分析结果
### 1. 结论摘要
### 2. Cohort 定义
| 项目 | 口径 |
| --- | --- |
| Cohort 起点 | |
| 回访/留存行为 | |
| 统计对象 | |
| 时间窗口 | |
| 分群维度 | |
### 3. 留存矩阵
| Cohort | D1 | D7 | D14 | D30 |
| --- | --- | --- | --- | --- |
### 4. 关键发现
### 5. 分群差异
### 6. 异常批次
### 7. 可能原因
### 8. 建议动作
### 9. 口径风险与待确认问题
输出必须：
请用 retention-cohort-analysis 分析新用户留存：
Cohort 起点：注册日期
留存行为：任意一次打开 App
窗口：D1、D7、D30
维度：渠道、设备、首日是否完成关键行为