Interview to Insights V3
Turn interviews into evidence-backed insights
Description
Recommended by
淡苍
Why we love this skill
Trace every insight to quotes, timestamps, and participants, while actively testing disconfirming evidence and separating behavior from stated opinion for clearer, decision-ready research.
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 and product teams: skip days of manual analysis and coding. Every claim is anchored to participant quotes with timestamps, making it auditable and traceable and reducing the risk of AI-fabricated insights. Opportunities are framed as "when [situation], [who] wants [outcome] because [reason]", ready to inform product roadmaps and market decisions. For researchers and academics: follow rigorous qualitative research practice rather than simple summarization—quote-first open coding, Behavior/Belief/Wish evidence tagging, falsifiable themes, and deliberate searches for disconfirming evidence. The method is rigorous enough for a research paper. Sample discipline is strict: do not report percentages with fewer than 12 participants, flag n=1 as a hypothesis rather than a finding, and measure conclusion strength by participant count. For product managers, UX and market researchers, journalists, consultants, founders, and anyone with hours of recordings but no research findings.
Related Skills
View all
ResearchSignal 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.
Dialogue Director Pro | Interview Design Engine
This isn't just a list of questions; it helps you design a memorable conversation. A 7-step process, from guest research to finalized materials: Guest Profile → Narrative Structure → Question Matrix → Process Layout → Interview Rehearsal → Material Conversion → Interview Debriefing 💡 Steps 1-3 form the core design process, delivering a complete interview plan independently; Steps 4-7 enhance the experience and can be used as needed. 🔍 Guest Profile | Online search of publicly available guest information generates a five-dimensional in-depth profile—factual skeleton, story vein, core conflict, communication style, and emotional entry point—telling you which direction to dig. Non-public figures automatically switch to interview-style information gathering. 🌿 Follow-up Question Branching Tree | When generating questions, the system pre-predicts the possible directions of the guest's answers for each key question and designs corresponding follow-up questions. You take this "decision tree" to the event, listen to the guest's answer, and then choose the corresponding branch to ask follow-up questions—no need for on-site AI, no need for real-time text transcription; all plans are designed during the preparation stage. It lets you be a chess player on-site, not an improvisational actor. No similar function exists on the market. 🎬 AI Rehearsal | Before the interview, AI plays the role of a guest, simulating three answering styles (in-depth/superficial/evasive), allowing you to practice follow-up questions and identify blind spots in the process. 📝 Five Outputs | Generates from a single interview: interview article/ podcast script/ oral history transcript/ social media content package/documentary script skeleton. 📊 Interview Debriefing | Plan vs. reality comparison, analysis of gold mines and regrets, five-dimensional capability radar chart, allowing you to grow with every interview. Suitable for: podcast interviews, interviews, student interviews, UX in-depth interviews, executive interviews.
Research Report Generator
📝 Value in one sentence: Enter a topic or upload materials, and AI handles the entire process from organizing sources to drafting. 🔍 Core features: Smart source integration: Upload multiple documents and AI automatically extracts key viewpoints, critical data, and representative cases, while removing duplicates and flagging conflicts. Automatic outline generation: Based on the topic or source content, it creates a logically clear and well-structured article outline. One-click draft writing: Generates content section by section according to the outline, with every data point and case study source-tagged and traceable. Five writing styles: Supports formal reports, WeChat articles, Xiaohongshu notes, academic papers, and business briefings. Transparent citations: Every figure and viewpoint is marked with its source—no fabrication or invention. Automated content workflow: Source parsing → viewpoint extraction → outline generation → writing in five styles. 🎯 Use cases: 📊 Industry research: Enter "Humanoid Robot Industry 2026" to generate a draft analysis report with data and case studies. 📝 Content creation: Upload 3 related articles to combine into an in-depth WeChat article. 📚 Academic writing: Upload multiple paper abstracts to create a literature review draft. 📋 Competitor analysis: Upload several competitor documents to instantly generate a comparative analysis report. 🧠 Personal learning: Enter a new-domain topic to quickly generate a knowledge overview. 💼 Business decisions: Input business data and background information to produce a decision brief for the CEO. 👩💼 Who it's for: Researchers, analysts, content creators, product managers, students, and consultants—anyone who needs to quickly produce high-quality first drafts.
Interview to Insights V3
Turn interviews into evidence-backed insights
Description
Recommended by
淡苍
Why we love this skill
Trace every insight to quotes, timestamps, and participants, while actively testing disconfirming evidence and separating behavior from stated opinion for clearer, decision-ready research.
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 and product teams: skip days of manual analysis and coding. Every claim is anchored to participant quotes with timestamps, making it auditable and traceable and reducing the risk of AI-fabricated insights. Opportunities are framed as "when [situation], [who] wants [outcome] because [reason]", ready to inform product roadmaps and market decisions. For researchers and academics: follow rigorous qualitative research practice rather than simple summarization—quote-first open coding, Behavior/Belief/Wish evidence tagging, falsifiable themes, and deliberate searches for disconfirming evidence. The method is rigorous enough for a research paper. Sample discipline is strict: do not report percentages with fewer than 12 participants, flag n=1 as a hypothesis rather than a finding, and measure conclusion strength by participant count. For product managers, UX and market researchers, journalists, consultants, founders, and anyone with hours of recordings but no research findings.
Related Skills
View allResearchSignal 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.
Dialogue Director Pro | Interview Design Engine
This isn't just a list of questions; it helps you design a memorable conversation. A 7-step process, from guest research to finalized materials: Guest Profile → Narrative Structure → Question Matrix → Process Layout → Interview Rehearsal → Material Conversion → Interview Debriefing 💡 Steps 1-3 form the core design process, delivering a complete interview plan independently; Steps 4-7 enhance the experience and can be used as needed. 🔍 Guest Profile | Online search of publicly available guest information generates a five-dimensional in-depth profile—factual skeleton, story vein, core conflict, communication style, and emotional entry point—telling you which direction to dig. Non-public figures automatically switch to interview-style information gathering. 🌿 Follow-up Question Branching Tree | When generating questions, the system pre-predicts the possible directions of the guest's answers for each key question and designs corresponding follow-up questions. You take this "decision tree" to the event, listen to the guest's answer, and then choose the corresponding branch to ask follow-up questions—no need for on-site AI, no need for real-time text transcription; all plans are designed during the preparation stage. It lets you be a chess player on-site, not an improvisational actor. No similar function exists on the market. 🎬 AI Rehearsal | Before the interview, AI plays the role of a guest, simulating three answering styles (in-depth/superficial/evasive), allowing you to practice follow-up questions and identify blind spots in the process. 📝 Five Outputs | Generates from a single interview: interview article/ podcast script/ oral history transcript/ social media content package/documentary script skeleton. 📊 Interview Debriefing | Plan vs. reality comparison, analysis of gold mines and regrets, five-dimensional capability radar chart, allowing you to grow with every interview. Suitable for: podcast interviews, interviews, student interviews, UX in-depth interviews, executive interviews.
Research Report Generator
📝 Value in one sentence: Enter a topic or upload materials, and AI handles the entire process from organizing sources to drafting. 🔍 Core features: Smart source integration: Upload multiple documents and AI automatically extracts key viewpoints, critical data, and representative cases, while removing duplicates and flagging conflicts. Automatic outline generation: Based on the topic or source content, it creates a logically clear and well-structured article outline. One-click draft writing: Generates content section by section according to the outline, with every data point and case study source-tagged and traceable. Five writing styles: Supports formal reports, WeChat articles, Xiaohongshu notes, academic papers, and business briefings. Transparent citations: Every figure and viewpoint is marked with its source—no fabrication or invention. Automated content workflow: Source parsing → viewpoint extraction → outline generation → writing in five styles. 🎯 Use cases: 📊 Industry research: Enter "Humanoid Robot Industry 2026" to generate a draft analysis report with data and case studies. 📝 Content creation: Upload 3 related articles to combine into an in-depth WeChat article. 📚 Academic writing: Upload multiple paper abstracts to create a literature review draft. 📋 Competitor analysis: Upload several competitor documents to instantly generate a comparative analysis report. 🧠 Personal learning: Enter a new-domain topic to quickly generate a knowledge overview. 💼 Business decisions: Input business data and background information to produce a decision brief for the CEO. 👩💼 Who it's for: Researchers, analysts, content creators, product managers, students, and consultants—anyone who needs to quickly produce high-quality first drafts.
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