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pm-customer-interviews

pm-customer-interviews

github.com/majesticlabs-dev营销与增长5040 次安装7 周前更新
代码仓库

关于 pm-customer-interviews

pm-customer-interviews 提供产品探索访谈的问题库和综合整理模板,帮助产品团队了解客户问题、现有方案、转换信号及多次访谈中的共性。

主要功能

  1. 01问题探索提问
  2. 02现有方案分析
  3. 03转换信号提问
  4. 04价值探索提问
  5. 05访谈综合整理模板
  6. 06访谈常见误区指引

适用场景

  1. 01准备客户访谈
  2. 02记录访谈证据
  3. 03比较多次访谈中的痛点
  4. 04寻找付费意愿信号

安装

复制下面的命令,在终端中运行。

$npx skills add https://github.com/majesticlabs-dev/majestic-marketplace --skill pm-customer-interviews

安装后在 Claude Code 中输入/pm-customer-interviews确认已加载。

详细介绍

客户访谈综合分析

用于产品探索访谈的问题库和综合分析模板。

访谈问题库

问题探索
- "Walk me through the last time you [did X]..."
- "What's the hardest part about [doing X]?"
- "Why is that hard?" (ask 3x - dig deeper)
- "What have you tried to solve this?"
- "What happened when you tried that?"
当前解决方案分析
- "How do you handle [X] today?"
- "How often do you do this?"
- "What would happen if you couldn't do this?"
- "How much time/money does this cost you?"
转换信号
- "Have you looked for other solutions?"
- "What would make you switch?"
- "What's stopping you from switching now?"
价值探索
- "If you could wave a magic wand, what would change?"
- "What would that be worth to you?"
- "Who else cares about this problem?"

访谈综合分析模板

## Interview: [Customer Name/Segment]
**Date:** YYYY-MM-DD | **Duration:** X min | **Role:** [Title]

### Problem Quotes (verbatim)
> "[Exact quote about the problem]"
> "[Another revealing quote]"

### Current Behavior
- Does [X] using [current solution]
- Frequency: [daily/weekly/monthly]
- Time spent: [X hours/month]

### Pain Intensity: [1-5]
- 1: Mild annoyance
- 3: Significant friction
- 5: "Hair on fire" problem

### Willingness to Pay Signal
- [ ] Actively searching for solutions
- [ ] Has budget allocated
- [ ] Named a specific price point: $___
- [ ] Would switch immediately if solved

### Key Insight
[One sentence capturing the non-obvious learning]

访谈反模式

反模式失效原因应采取的做法
引导性问题证实偏见提出开放式问题,追问“为什么”
假设性定价人们会对未来撒谎询问当前支出
功能请求关注解决方案,而非问题深入探究背后的需求
样本量过小个例 ≠ 模式至少需要 5 个信号

输出

访谈结束后,综合多次对话中的模式,以识别:

  • 常见痛点(频率 + 强度)
  • 付费意愿信号
  • 当前正在被“弃用”的解决方案

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