访谈转录 → 决策洞察V3
挖掘访谈材料，生成可信度极高的分析报告，既适合学者，也适合产品经理、UX/市场研究员、记者、顾问等人群
访谈转录 → 决策洞察V3
挖掘访谈材料，生成可信度极高的分析报告，既适合学者，也适合产品经理、UX/市场研究员、记者、顾问等人群
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描述
把访谈、用户调研或焦点小组的转录稿，变成一份每条结论都有据可查的证据化研究综合。从 1 份到 20 份转录，直接产出编码主题、张力地图、机会积压，以及对决策问题的直接回答——不再有"数小时录音、零结论"。 对企业与产品团队：省去分析师数天的整理与编码时间；每条判断锚定参与者原话与时间戳，可审计、可追溯，从源头杜绝"AI 编造洞察"的风险；机会清单按「when [situation], [who] wants [outcome] because [reason]」输出，可直接衔接产品路线与市场决策。 对研究者与学者：遵循真实定性研究实践而非摘要——quote-first 开放编码、Behaviour/Belief/Wish 证据分类、可证伪主题、主动反证猎取，方法严谨到可以写进论文；样本纪律严格：少于 12 名参与者不报告百分比，n=1 明示为假设而非发现，结论强度以参与者计数为准。 适合产品经理、UX/市场研究员、记者、顾问、创始人，以及任何手握录音素材却迟迟没有研究结论的人。 English: Turn interview, user research, or focus-group transcripts into an evidence-led research synthesis where every conclusion is traceable to a verbatim quote. Feed it one transcript or twenty, and get coded themes, a tension map, an opportunity backlog, and a direct answer to your decision question—no more hours of recordings with zero findings. For businesses & product teams: skip days of manual coding; every claim is anchored to participant quotes with timestamps, auditable and traceable, eliminating the risk of AI-fabricated insights; opportunities are framed as "when [situation], [who] wants [outcome] because [reason]", ready to feed product roadmaps and market decisions. For researchers & academics: real qualitative practice, not summarisation—quote-first open coding, Behaviour/Belief/Wish evidence tagging, falsifiable themes, deliberate disconfirming-evidence hunting, rigorous enough for a methods section; strict sample discipline: no percentages under 12 participants, n=1 flagged as hypothesis rather than finding, theme strength counted in participants. For product managers, UX & market researchers, journalists, consultants, founders doing customer discovery—and anyone sitting on hours of recordings with no findings.
為什麼我們推薦這個技能
以逐字引文、时间戳和参与者为锚点，从开放编码一路推进到主题、张力与决策建议。独特之处在于反证优先的双重审计机制，严格区分行为、信念与愿望，主动约束结论强度，显著降低定性研究中的过度推断。
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研究Signal Room: Interview Synthesis
YouMind already transcribes your calls, interviews and podcasts. Signal Room is what happens next. Drop in one transcript or twenty and get back a research synthesis an actual analyst would sign: coded themes, verbatim evidence with timestamps, the places people disagree, and a ranked answer to the decision you are trying to make. The method is real qualitative practice, not summarisation: • Open coding that works quote-first — no quote, no code — with codes named in the participant's own words rather than analyst jargon • Every code tagged Behaviour, Belief or Wish, because "I would definitely pay for that" is not the same class of evidence as "I paid for that last month" • Themes stated as falsifiable sentences, with strength counted in participants rather than quotes, and disconfirming evidence hunted for on purpose • A tension map showing where your participants genuinely split and what predicts which side they fall on • An opportunity backlog written as "when [situation], [who] wants [outcome] because [reason]", each rated Strong, Suggestive or Anecdotal • A direct answer to your decision question, with a stated confidence level and what would change it • The three questions this round could not answer, and who to interview next Guardrails that matter: it never invents or polishes a quote, it refuses to report percentages on fewer than twelve participants, it pseudonymises participants by default, and it will tell you to your face when n=1 means you have a hypothesis rather than a finding. For product managers, UX and market researchers, journalists, consultants, founders doing customer discovery, and anyone sitting on hours of recordings and no findings.
研究客声有据｜CUSTOMER SIGNAL
评论很多，真正值得解决的是什么？ 「客声有据」整理客户访谈、问卷、评论、工单与流失反馈，提取原话、痛点、触发事件和替代做法。合并重复材料，保留反例，把研究结论和待验证机会分开。 支持研究综合、VOC原话库、JTBD、暂定用户画像、竞品评价对照与研究缺口计划；也能设计公开社区研究、客户访谈和PMF问卷。在线采集取决于宿主现有工具，无联网时交付搜索与采样方案。 适合产品经理、独立开发者、运营和小团队。抱怨不等于愿意付钱，研究会标出证据边界及验证下一步。 发布品牌：leowang。基于MIT许可的customer-research v2.0.4改编，保留必要版权许可。
研究到底值不值？-循证决策引擎Pro
一次决策尽调，四件套交付。 「到底值不值？」不给你一句“建议做”或“不建议”，而是把一个人生决策当成一次投资尽调来做：先测你的个人权重（同样一件事，月薪 5000 和 5 万的人答案不同），再扫法律/健康/财务/关系四条红线，然后搜学术论文与官方数据，按成本-收益-证据等级建模算账，做十年总账与敏感性分析，最后用 Pre-mortem、基准率和偏见清单反向压测，并设计一个花小钱买信息的“最小可行实验”。 你会拿到： ① 一份交互式决策仪表盘（网页）：四口径雷达、性价比仪表、十年现金流、可拖动的敏感性滑块（看结论何时翻转）、证据金字塔、风险矩阵、90 天作战地图、可保存的复盘账本、3:4 分享卡。 ② 一份决策尽调报告（文档）：结论、账目、证据链、风险、行动，可存档可打印。 ③ 一套 90 天作战地图：第 1 周验证什么、止损线在哪、什么条件退出、何时复查。 ④ 一份决策复盘账本：记录预测与实际，训练自己的判断校准。 适合：考研 vs 工作、要不要跳槽、该不该买房、要不要创业、要不要读博、要不要结束一段关系、要不要接这个 offer、要不要做手术、要不要搬去另一个城市。 方法严谨：每条证据标 A/B/C 与原始出处，数字连置信区间一起抄；搜不到就直说搜不到；评级公式全部公开，可自己复算。 方法论致敬开源项目《高性价比人生指南》(github.com/eternity4719/HowToLiveBetter)，并做了个人化加权、十年总账、证伪压测与“买信息”四层升级。
