Skill-Details
market-research
Direct, decision-oriented market research covering sizing, competitors, and trends.
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SKILL.md
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--- name: market-research description: Conduct market research, competitive analysis, investor due diligence, and industry intelligence with source attribution and decision-oriented summaries. Use when the user wants market sizing, competitor comparisons, fund research, technology scans, or research that informs business decisions. metadata: origin: ECC --- # Market Research Produce research that supports decisions, not research theater. ## When to Activate - researching a market, category, company, investor, or technology trend - building TAM/SAM/SOM estimates - comparing competitors or adjacent products - preparing investor dossiers before outreach - pressure-testing a thesis before building, funding, or entering a market ## Research Standards 1. Every important claim needs a source. 2. Prefer recent data and call out stale data. 3. Include contrarian evidence and downside cases. 4. Translate findings into a decision, not just a summary. 5. Separate fact, inference, and recommendation clearly. ## Common Research Modes ### Investor / Fund Diligence Collect: - fund size, stage, and typical check size - relevant portfolio companies - public thesis and recent activity - reasons the fund is or is not a fit - any obvious red flags or mismatches ### Competitive Analysis Collect: - product reality, not marketing copy - funding and investor history if public - traction metrics if public - distribution and pricing clues - strengths, weaknesses, and positioning gaps ### Market Sizing Use: - top-down estimates from reports or public datasets - bottom-up sanity checks from realistic customer acquisition assumptions - explicit assumptions for every leap in logic ### Technology / Vendor Research Collect: - how it works - trade-offs and adoption signals - integration complexity - lock-in, security, compliance, and operational risk ## Output Format Default structure: 1. executive summary 2. key findings 3. implications 4. risks and caveats 5. recommendation 6. sources ## Quality Gate Before delivering: - all numbers are sourced or labeled as estimates - old data is flagged - the recommendation follows from the evidence - risks and counterarguments are included - the output makes a decision easierVollständige Quelle auf GitHub lesen (öffnet externe Seite)