product-market-fit-analysis by manojbajaj95/claude-gtm-plugin
npx skills add https://github.com/manojbajaj95/claude-gtm-plugin --skill product-market-fit-analysis用于评估、实现和扩展产品市场契合度的综合框架。
| 情境 | 使用此技能用于 |
|---|---|
| 衡量 PMF | Sean Ellis 调查 |
| 留存分析 | 留存曲线 |
| PMF 验证 | 领先指标 |
| 特定细分市场的 PMF | 细分市场分析 |
| 扩展决策 | PMF 后策略 |
产品市场契合度是指产品满足强烈市场需求的状态。它不是非黑即白的——而是一个连续体。
当你拥有 PMF 时,它是显而易见的。
Matt MacInnis:"产品市场契合度是你看到它时绝对能认出来的东西。因此,如果你不能绝对确定,那么你就没有它。"
| 级别 | 客户数量 | 关注点 |
|---|
广告位招租
在这里展示您的产品或服务
触达数万 AI 开发者,精准高效
| 萌芽期 | 3-5 | 满意度 |
| 发展期 | 5-25 | 需求 |
| 强健期 | 25-100 | 效率 |
| 极致期 | 100+ | 扩展 |
问题:
"如果你不能再使用这个产品,你会有什么感觉?"
- 非常失望
- 有点失望
- 不失望
基准:
40% 的人选择"非常失望" = 方向正确
将选择"非常失望"的群体作为核心价值指标来关注。
Uri Levine 的定义:
"产品市场契合度只有一个指标。留存率。如果你创造了价值,他们会回来。如果他们不回来,你就没有创造价值。"
需要关注的点:
关键留存点:
Christian Idiodi:
"圣杯其实是参考客户——一个足够喜欢它并愿意告诉别人的人。"
| 市场 | 目标参考客户数量 |
|---|---|
| B2B | 6-8 个参考客户 |
| B2C | 15-25 个参考客户 |
| 指标 | 含义 |
|---|---|
| "非常失望" > 40% | 强大的核心价值 |
| 留存曲线趋于平缓 | 产品创造持续价值 |
| 客户"拉动" | 市场在拉动产品 |
| 宕机时的愤怒反应 | 产品是关键任务 |
| 客户推动下一步 | 真实意图,而非礼貌性兴趣 |
Raaz Herzberg:
"我们感觉到问题变了——'你们如何定价?我们什么时候可以开始概念验证?' 这才是真正的意图。"
真正的拉动特征包括:
Jeff Weinstein:
"在那 20 分钟里,我们的客户并没有愤怒。这就是我们没有达到产品市场契合度的信号。"
如果你的产品宕机了,却没人注意到或抱怨,那么你还没有解决一个关键任务问题。
Karri Saarinen:"我们的思考方式是,'我们在特定细分市场中是否达到了契合度?'以及这种契合度有多强。"
PMF 存在于细分市场中,而非普遍存在。
从窄处开始,然后扩展:
Casey Winters:"如果你有一个留存良好的产品,却找不到更多用户,我不认为那是产品市场契合度。"
真正的 PMF 需要:
两者缺一不可,否则就没有真正的 PMF。
Casey Winters:"一旦你建立了规模,保护你所构建的东西就变得越来越重要。如果你不持续改进产品,你可能在一年或五年内失去产品市场契合度。"
市场变化,竞争对手改进,用户期望提高。持续监控并保护 PMF。
| 错误 | 现实 |
|---|---|
| 将发布高峰与 PMF 混淆 | 持续的有机增长才重要 |
| 忽视留存数据 | 如果他们不回来,就没有 PMF |
| 过早扩展 | 在 PMF 前进行付费增长会烧钱 |
| 将 TAM 与 PMF 混为一谈 | 大市场 ≠ 在其中达到契合度 |
| 听取"有点失望"的反馈 | 关注"非常失望"的反馈 |
| 信号 | 行动 |
|---|---|
| 40%+ "非常失望" + 留存曲线平缓 | 准备扩展 |
| < 40% "非常失望" | 继续迭代 |
| 没有参考客户 | 先建立参考客户 |
| 没有分发机制 | 先寻找渠道 |
| 因素 | 扩展 | 继续迭代 |
|---|---|---|
| PMF 调查 | > 40% 非常失望 | < 40% |
| 留存 | 曲线趋于平缓 | 衰减至零 |
| 参考客户 | 达到目标 | 尚未达到 |
| 分发 | 渠道已确定 | 未知 |
每周安装量
96
代码仓库
GitHub 星标数
20
首次出现
2026年3月11日
安全审计
安装于
opencode96
gemini-cli22
github-copilot22
codex22
kimi-cli22
amp22
Comprehensive framework for assessing, achieving, and scaling product-market fit.
| Situation | Use This Skill For |
|---|---|
| Measuring PMF | Sean Ellis Survey |
| Retention analysis | Retention Curves |
| PMF validation | Leading Indicators |
| Segment-specific PMF | Segment Analysis |
| Scaling decisions | Post-PMF Strategy |
Product-market fit is the condition where a product satisfies a strong market demand. It's not binary — it's a spectrum.
PMF is obvious when you have it.
Matt MacInnis: "Product market fit is something where you absolutely know it when you see it. Therefore if you don't absolutely know it, you don't have it."
| Level | Customers | Focus |
|---|---|---|
| Nascent | 3-5 | Satisfaction |
| Developing | 5-25 | Demand |
| Strong | 25-100 | Efficiency |
| Extreme | 100+ | Scaling |
The Question:
"How would you feel if you could no longer use this product?"
- Very disappointed
- Somewhat disappointed
- Not disappointed
The Benchmark:
40% "very disappointed" = on the right track
Focus on the "very disappointed" segment as the core value indicator.
Uri Levine's Definition:
"Product market fit has one metric. Retention. If you create value, they will come back. If they're not coming back, you're not creating value."
What to look for:
Key retention points:
Christian Idiodi:
"The holy grail is really a reference customer - somebody who loves it enough to tell people about it."
| Market | Target References |
|---|---|
| B2B | 6-8 reference customers |
| B2C | 15-25 reference customers |
| Indicator | What It Means |
|---|---|
| "Very disappointed" > 40% | Strong core value |
| Retention curve flattening | Product creates ongoing value |
| Customer "pull" | Market is pulling product |
| Outrage during outages | Product is mission-critical |
| Customer driving next steps | Intent, not polite interest |
Raaz Herzberg:
"We felt the questions change — 'How are you pricing this? When can we start a POV?' That's real intent."
True pull is characterized by:
Jeff Weinstein:
"During those 20 minutes our customers weren't furious. That was the signal we did not have product market fit."
If your product goes down and nobody notices or complains, you haven't solved a mission-critical problem.
Karri Saarinen: "The way we think about it is, 'Do we have the fit in specific segments?' and how strong that fit is."
PMF exists in segments, not universally.
Start narrow, then expand:
Casey Winters: "If you have a product that retains well and you can't find more users for it, I don't think that's product market fit."
True PMF requires:
Without both, you don't have true PMF.
Casey Winters: "Protecting what you've built is increasingly important once you build scale. You might fall out of product market fit in a year or five years if you're not continually making your product better."
Markets shift, competitors improve, user expectations rise. Continuously monitor and protect PMF.
| Mistake | Reality |
|---|---|
| Confusing launch spikes with PMF | Sustained organic growth matters |
| Ignoring retention data | If they don't come back, no PMF |
| Scaling too early | Paid growth before PMF burns cash |
| Conflating TAM with PMF | Large market ≠ fit within it |
| Listening to "somewhat disappointed" | Focus on "very disappointed" |
| Signal | Action |
|---|---|
| 40%+ "very disappointed" + flattening retention | Ready to scale |
| < 40% "very disappointed" | Keep iterating |
| No reference customers | Build them first |
| No distribution mechanism | Find channels first |
| Factor | Scale | Keep Iterating |
|---|---|---|
| PMF survey | > 40% very disappointed | < 40% |
| Retention | Curve flattening | Decaying to zero |
| References | Target achieved | Not yet |
| Distribution | Channels identified | Unknown |
Weekly Installs
96
Repository
GitHub Stars
20
First Seen
Mar 11, 2026
Security Audits
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Installed on
opencode96
gemini-cli22
github-copilot22
codex22
kimi-cli22
amp22
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