product-analytics
Use product analytics to understand user behavior, measure feature adoption, and inform product decisions with data. Use when defining events, analyzing funnels and retention, diagnosing drops, or evaluating the impact of changes.
- License 许可
- MIT
- 最近更新
- 2026-07-22
- Stars
- ★ 7
- Forks
- 1
01 前言 Front Matter
- name
- product-analytics
- description
- Use product analytics to understand user behavior, measure feature adoption, and inform product decisions with data. Use when defining events, analyzing funnels and retention, diagnosing drops, or evaluating the impact of changes.
03 SKILL.md 正文
Product Analytics
Overview
Product analytics turns usage into insight. Done well, it answers what users do, where they struggle, and whether changes improved outcomes.
When to Use
- Defining instrumentation for new features
- Analyzing activation, retention, and engagement
- Measuring impact after launches
- Exploring user behavior to generate hypotheses
Core Practices
- Define a clear analytics tracking plan (events, properties, ownership)
- Focus on a small set of meaningful funnels and retention views
- Segment by cohort, persona proxy, or acquisition source when relevant
- Combine quantitative patterns with qualitative research
- Establish baselines before judging experiments or launches
Principles
- Instrument for decisions, not for collecting everything possible
- Protect data quality — bad events create false confidence
- Look at trends and cohorts, not only snapshots
- Privacy and compliance constraints are part of the design
Verification
- [ ] Key product questions can be answered with available data
- [ ] Event definitions are documented and trusted
- [ ] Insights regularly appear in product decisions
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