analyzing-user-feedback by refoundai/lenny-skills
npx skills add https://github.com/refoundai/lenny-skills --skill analyzing-user-feedback帮助用户运用 56 位产品领导者的技巧,从客户反馈中提取可操作的见解。
当用户请求帮助分析反馈时:
Shaun Clowes:"真正聪明的产品经理会持续在反馈的河流中畅游。建立用户访谈数据、NPS 和竞争对手信息的流,让它们每天冲刷你。" 让反馈的获取是持续的,而非偶发性的。
Bret Taylor:"直接采纳焦点小组中客户的说法很少是正确的。实践理智的诚实,以区分表面抱怨和根本原因。" 当用户说"价格"时,他们通常指的是"价值"。
Bob Moesta:"我们不是按人口统计学细分,而是按行为路径聚类。人们做事情的原因不是单一的——而是原因集合。" 寻找不同用户群的'雇佣和解雇'标准。
Geoff Charles:"我们确实在所有渠道都张贴着'每一个支持工单都是我们产品的失败'。每月与相关的产品经理和设计师分享每一个负面评价。"
Ramesh Johari:"在那些未被留下的评分中蕴含着大量信息。评分的缺失通常是一个强烈的信号,表明用户经历了一次平庸的体验,他们出于礼貌而没有报告。"
Jen Abel:"80% 的反馈是基于旧习惯的噪音,20% 是指导未来产品的黄金。创始人的职责就是解读什么是'旧方式',什么是真实的市场需求。"
Brian Balfour:"AI 可以分析现有反馈并识别知识缺口——即客户没有说什么。将来自所有来源的反馈聚合到一个集中的存储库中。"
Uri Levine:"最关键的见解来自那些从漏斗中流失的用户,而不是那些成功的用户。访谈流失的用户,以找到失败背后的'原因'。"
Tamar Yehoshua:"不要过度关注那些对你的改变不满的人。为明天将使用产品的更广大人群设计,而不是为今天抱怨的少数人。"
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Yuhki Yamashata:"目标是'模因化'——综合见解,使其足够引人注目,让高管在会议中引用。使用现实世界的隐喻来解释复杂的概念。"
要查看来自 56 位嘉宾的全部 64 条见解,请参阅 references/guest-insights.md
每周安装次数
704
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546
首次出现
2026 年 1 月 29 日
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Help the user extract actionable insights from customer feedback using techniques from 56 product leaders.
When the user asks for help analyzing feedback:
Shaun Clowes: "Really smart product managers are constantly swimming in a feedback river. Set up streams of user interview data, NPS, and competitor info to wash over you daily." Make feedback consumption continuous, not episodic.
Bret Taylor: "Taking what a customer says in a focus group is rarely correct. Practice intellectual honesty to distinguish surface-level complaints from root causes." When users say "price," they often mean "value."
Bob Moesta: "Instead of segmenting by demographics, we cluster by behavioral pathways. It's not one reason why people do things—it's sets of reasons." Look for the 'hire and fire' criteria for different user clusters.
Geoff Charles: "We literally have 'every support ticket is a failure of our product' posted on all channels. Share every negative review with the relevant PM and designer monthly."
Ramesh Johari: "There's a lot of information in ratings that are NOT left. The absence of a rating is often a strong signal of a mediocre experience users are too polite to report."
Jen Abel: "80% of feedback is noise based on legacy habits, 20% is gold that guides the future product. It's the founder's job to interpret what's 'the old way' versus real market needs."
Brian Balfour: "AI can analyze existing feedback AND identify knowledge gaps—what customers are NOT saying. Aggregate feedback from all sources into a centralized repository."
Uri Levine: "The most critical insights come from users who dropped out of the funnel, not those who succeeded. Interview users who churned to find the 'why' behind the failure."
Tamar Yehoshua: "Don't over-index on people unhappy with your changes. Design for the bigger number of people who will use it tomorrow, not the vocal few complaining today."
Yuhki Yamashata: "The goal is 'memification'—synthesize insights so they're catchy enough for execs to cite in meetings. Use real-world metaphors to explain complex concepts."
For all 64 insights from 56 guests, see references/guest-insights.md
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704
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GitHub Stars
546
First Seen
Jan 29, 2026
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