Rapid Industry Understanding
Systematic 8-dimension industry report
Description
Recommended by
淡苍
Why we love this skill
This skill embodies the essence of McKinsey-style industry research. Through a 'search-then-judge' approach and an eight-dimension analysis framework, it ensures each report is based on the latest data, providing deep insights and decision-making advice, not just generalities.
📋 Usage Guide This Skill is an industry research engine based on McKinsey methodology, using the eight-dimension framework from Xiao Jing's "How to Quickly Understand an Industry". Tell it an industry name, and it produces a systematic research report. —————————————————————————————— 🚀 Basic Usage Just tell me the industry you want to research—the more specific, the better: a. "Analyze the solid-state battery industry" b. "Look at the humanoid robot supply chain from an entrepreneurial perspective" c. "Is the solar industry still investable now?" You can optionally provide three details (if missing, I'll use defaults): 1. Industry name: be specific, e.g., "perovskite solar" instead of "new energy"—required; 2. Goal: investment / career / entrepreneurship / competitive analysis / education, default: investment; 3. Region: China market / global / US / Southeast Asia..., default: China market; —————————————————————————————— ⚙️ What it does automatically? The entire process has 4 stages: 1. Multi-round web searches for market size/growth/penetration rate, supply chain, competitive landscape, moat evidence, policy, valuation—every conclusion has a source and timestamp, never fabricated; 2. Lifecycle positioning: use penetration rate to determine if the industry is in introduction/growth/maturity/decline—different stages have completely different research focuses; 3. Eight-dimension deep dive: business model → market size → moat (forced deep dive into dynamic trends) → competitive landscape (forced scoring on each of Porter's Five Forces) → valuation → PEST → business cycle; 4. Contrarian check: distinguish market priced-in consensus from overlooked real issues, and provide decision recommendations; —————————————————————————————— 📊 What it outputs? A professional research report in Markdown format, structured as: 1. ⚡ 30-second verdict — stage / core profit logic / biggest opportunity / biggest risk / one-sentence conclusion; 2. Research object and boundary definition; 3. Lifecycle positioning (with penetration rate data); 4. Eight-dimension analysis (moat includes dynamic trend table, Porter's Five Forces scoring table); 5. Contrarian check; 6. Conclusion and decision recommendations; 7. Key risk list; 8. Data sources and time notes; —————————————————————————————— 🔑 Two Core Highlights 1. Forced deep dive on moat: not just the type of barrier, but must answer "has it widened or narrowed in the past 2-3 years?" using market share/gross margin/pricing power data; 2. Porter's Five Forces scored individually: all five forces scored to avoid shortcuts, determining who has the strongest bargaining power now and whether the landscape is favorable or deteriorating for leaders; —————————————————————————————— ⏱️ Time Approximately 2-4 minutes, due to multiple rounds of search + dimension-by-dimension analysis + report writing —————————————————————————————— 🧩 Subsequent Extensions After the report is generated, you can continue with two specialized analyses (requires manual confirmation, won't run automatically): 1. "Unchain to find bottlenecks": identify physical bottlenecks in the supply chain that can't be bypassed when trends scale, locking in true beneficiary targets; 2. "DCF valuation": run a full discounted cash flow model for a specific company within the industry; —————————————————————————————— ▶️ Want to try? Just tell me an industry name, e.g., "Take a look at the AI agent industry from an entrepreneurial perspective" or "What's the situation with the hydrogen energy supply chain?"
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ResearchSlow Teacher's Keyword Method
Use the keyword learning method to quickly get started in any field: output a table of 20 core keywords (with one-sentence explanations, application scenarios, and best practices), hand-drawn comic-style SVG logic relationship diagrams, simulate a domain expert answering 5 key questions, recommend 3–5 professional books, and assemble them into a well-formatted report; enter 'Interpret [Book Title]' to switch to the seven-part in-depth book interpretation mode.
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.
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Helps product managers, founders, and app developers understand AI papers through historical causal links, turning those insights into product judgments, technical boundaries, engineering intuition, and opportunity analysis.
Rapid Industry Understanding
Systematic 8-dimension industry report
Description
Recommended by
淡苍
Why we love this skill
This skill embodies the essence of McKinsey-style industry research. Through a 'search-then-judge' approach and an eight-dimension analysis framework, it ensures each report is based on the latest data, providing deep insights and decision-making advice, not just generalities.
📋 Usage Guide This Skill is an industry research engine based on McKinsey methodology, using the eight-dimension framework from Xiao Jing's "How to Quickly Understand an Industry". Tell it an industry name, and it produces a systematic research report. —————————————————————————————— 🚀 Basic Usage Just tell me the industry you want to research—the more specific, the better: a. "Analyze the solid-state battery industry" b. "Look at the humanoid robot supply chain from an entrepreneurial perspective" c. "Is the solar industry still investable now?" You can optionally provide three details (if missing, I'll use defaults): 1. Industry name: be specific, e.g., "perovskite solar" instead of "new energy"—required; 2. Goal: investment / career / entrepreneurship / competitive analysis / education, default: investment; 3. Region: China market / global / US / Southeast Asia..., default: China market; —————————————————————————————— ⚙️ What it does automatically? The entire process has 4 stages: 1. Multi-round web searches for market size/growth/penetration rate, supply chain, competitive landscape, moat evidence, policy, valuation—every conclusion has a source and timestamp, never fabricated; 2. Lifecycle positioning: use penetration rate to determine if the industry is in introduction/growth/maturity/decline—different stages have completely different research focuses; 3. Eight-dimension deep dive: business model → market size → moat (forced deep dive into dynamic trends) → competitive landscape (forced scoring on each of Porter's Five Forces) → valuation → PEST → business cycle; 4. Contrarian check: distinguish market priced-in consensus from overlooked real issues, and provide decision recommendations; —————————————————————————————— 📊 What it outputs? A professional research report in Markdown format, structured as: 1. ⚡ 30-second verdict — stage / core profit logic / biggest opportunity / biggest risk / one-sentence conclusion; 2. Research object and boundary definition; 3. Lifecycle positioning (with penetration rate data); 4. Eight-dimension analysis (moat includes dynamic trend table, Porter's Five Forces scoring table); 5. Contrarian check; 6. Conclusion and decision recommendations; 7. Key risk list; 8. Data sources and time notes; —————————————————————————————— 🔑 Two Core Highlights 1. Forced deep dive on moat: not just the type of barrier, but must answer "has it widened or narrowed in the past 2-3 years?" using market share/gross margin/pricing power data; 2. Porter's Five Forces scored individually: all five forces scored to avoid shortcuts, determining who has the strongest bargaining power now and whether the landscape is favorable or deteriorating for leaders; —————————————————————————————— ⏱️ Time Approximately 2-4 minutes, due to multiple rounds of search + dimension-by-dimension analysis + report writing —————————————————————————————— 🧩 Subsequent Extensions After the report is generated, you can continue with two specialized analyses (requires manual confirmation, won't run automatically): 1. "Unchain to find bottlenecks": identify physical bottlenecks in the supply chain that can't be bypassed when trends scale, locking in true beneficiary targets; 2. "DCF valuation": run a full discounted cash flow model for a specific company within the industry; —————————————————————————————— ▶️ Want to try? Just tell me an industry name, e.g., "Take a look at the AI agent industry from an entrepreneurial perspective" or "What's the situation with the hydrogen energy supply chain?"
Related Skills
View all
ResearchSlow Teacher's Keyword Method
Use the keyword learning method to quickly get started in any field: output a table of 20 core keywords (with one-sentence explanations, application scenarios, and best practices), hand-drawn comic-style SVG logic relationship diagrams, simulate a domain expert answering 5 key questions, recommend 3–5 professional books, and assemble them into a well-formatted report; enter 'Interpret [Book Title]' to switch to the seven-part in-depth book interpretation mode.
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.
ResearchAI Paper Master
Helps product managers, founders, and app developers understand AI papers through historical causal links, turning those insights into product judgments, technical boundaries, engineering intuition, and opportunity analysis.
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