| name | icp-research |
| version | 4.2 |
| last_updated | "2026-04-30T00:00:00.000Z" |
| author | marketing-team |
| description | Scrapes case studies, testimonials, and solutions pages from a target website to build structured ICP documentation. Produces TAM analysis, firmographic segments, champion and economic buyer personas, use case mapping, customer proof points, and voice-of-customer synthesis with normalized attributes. Requires website URL as primary input. Triggers: "ICP research", "ideal customer profile", "customer segment analysis", "persona research", "use case analysis", "who are their customers", or any URL provided for customer research. Upstream: recommended company-context. Downstream: feeds icp-behavioural, positioning, content-strategy, product-messaging, landing-page-copy, and outreach-emails. NOT for behavioural simulation (use /icp-behavioural) or interview prep (use /customer-interviews). |
| goal | Scrapes case studies, testimonials, and solutions pages from a target website to build structured ICP documentation. |
| outcome | Scrapes case studies, testimonials, and solutions pages from a target website to build structured ICP documentation. Produces TAM analysis, firmographic segments, champion and economic buyer personas, use case mapping, customer proof points, and voice-of-customer synthesis with normalized... |
| primitive | research |
| ontology_type | icp-profile |
| review_gate | 1 |
| inputs | {"required":[],"recommended":["company-context"]} |
| outputs | [{"type":"icp-profile","feeds_into":["positioning","product-messaging","website-copy","aeo-content","outreach-emails","sales-enablement","competitor-research"]}] |
| depends_on | [] |
| feeds_into | ["aeo-content","competitor-research","website-copy","outreach-emails","positioning","product-messaging","sales-enablement"] |
| owned_by_agent | researcher |
| mcps_used | [] |
| push_targets | ["gdrive","notion"] |
| triggers | {"slash_commands":["/icp-research"],"natural_language":[]} |
| status | draft |
| locked_by | null |
| locked_date | null |
| lock_version | null |
| sources_count | 0 |
| context | fork |
| effort | max |
ICP research skill
Generate ideal customer profiles for B2B SaaS clients through systematic research and structured output.
Report structure
The final ICP report follows this numbered section order:
| Section | Purpose |
|---|
| Header | Research date, website, category, confidence score (1-5) |
| 1. Executive summary | High-level synthesis of findings and strategic recommendations |
| 2. TAM analysis | Market sizing with targeting strategy per layer (TAM/SAM/SOM/ICP) |
| 3. Firmographics analysis | Geographic, industry, company segment patterns, and technographics |
| 4. Roles and personas | Core use case, Champion deep-dive, Economic Buyer deep-dive, buying journey |
| 5. Negative ICP | Who is NOT a fit, disqualification criteria, and red flags |
| 6. Customer proof points | Named customers, outcomes, and evidence with URLs |
| 7. Voice of customer synthesis | Language patterns, pain points, and outcome terminology |
| 8. ICP segment definitions | Scoring matrix, in-market signals, segment deep-dives |
| 9. Intent signals and buying triggers | Observable signals indicating purchase readiness |
| 10. Recommendations | Prioritization and messaging by segment |
| 11. Data gaps | Missing information and follow-up suggestions |
| 12. Source appendix | All sources with access dates, URLs, and confidence levels |
Confidence score calculation: Count High/Medium/Low data points. Score 5 if >70% High, Score 4 if >50% High, Score 3 if mixed, Score 2 if >50% Low, Score 1 if >70% Low.
Output dimensions
Research produces structured outputs across these dimensions. Full field schemas + table structures + persona deep-dive templates: references/dimensions.md.
| Dimension | What it covers |
|---|
| TAM analysis | TAM/SAM/SOM/ICP table with targeting strategy per layer + assumptions |
| Firmographics | Geography, industry, company segments + segment deep-dives + technographics + adjacent stack |
| Technographics | Required vs preferred tools by category (CRM, CDP, Analytics, etc.) with evidence |
| Personas | Champion (12 fields) + Economic Buyer (13 fields) + Users + buying journey + core use case |
| Negative ICP | Disqualification criteria + red flags from churn + objections that signal poor fit |
| Customer proof points | Named customers + outcome patterns with URL + date |
| Voice of customer | Terminology / pain / outcome / objection patterns with verbatim quotes |
| Segments | Scoring matrix (TAM × Ease of win × Strategic fit) + per-segment deep-dive + positioning |
| Beachhead selection (optional) | Pick ONE segment to dominate first using weighted scoring rubric |
| Intent signals | Company-level + persona-level signals with detection sources |
Each persona deep-dive includes a verbatim Channels & Influences map (communities, content, events, influencers) and a sourced testimonial. Each segment deep-dive includes Priorities, ICP-fit, Budget & sales cycle, Unique approach, and Proof points.
Sorting rules
Apply consistently across all tables:
| Dimension | Sort order |
|---|
| Decision role | Champion → Economic Buyer → User → Influencer |
| Company size | Enterprise → Mid-market → SMB → Startup |
| Frequency | Very high → High → Medium → Low |
| Confidence | High → Medium → Low |
| Customer concentration | High → Medium → Low |
| Priority | 1 → 2 → 3 → 4 |
| Industry presence | Strong → Moderate → Emerging |
Workflow
The research runs in 3 phases. Read references/workflow.md for the full step-by-step.
Phase summary:
- Data extraction — discover key pages (customers, case studies, solutions, pricing, integrations, G2, LinkedIn) → extract raw data with URL+date per source → normalize attributes (geography, industry, company size, team size, tech stack)
- Analysis and synthesis — identify patterns per segment → build Champion + Economic Buyer deep-dives → identify negative ICP + intent signals → collect proof points → document technographics → calculate TAM with targeting strategy → identify ICP as highest-priority segment below SOM
- Structured output — generate the 12 numbered sections, apply sorting rules, include rich descriptions with URLs and dates
Input requirements
Required
- Website URL — primary company website
Optional (improves quality)
| Input | Purpose |
|---|
| Case studies URL | Direct link to case studies page |
| Testimonials URL | Direct link to testimonials |
| Market context | Category, competitors, GTM approach |
| Sales call notes | Win/loss context, objections |
| Existing ICP docs | Validate or expand current understanding |
Anti-hallucination guardrails
- Never invent customer names. Only cite publicly referenced customers.
- Quote verbatim. Use exact customer language in quotes.
- Mark confidence levels. Tag data as High/Medium/Low confidence.
- Cite sources with URLs and dates. Include URL and access date for every claim.
- Acknowledge gaps. Explicit "Not available" for missing data.
| Confidence | Definition |
|---|
| High | Direct from official source, verifiable |
| Medium | Third-party source, multiple signals |
| Low | Single indirect source, inferred |
Quality
Pre-delivery checklist (coverage / personas / segments / evidence): references/quality.md.
Reference files
Related context
Built from:
MMYY-company-context.md (company profile)MMYY-competitor-*.md (competitor profiles for market context)- Win/loss analysis if available
Feeds into:
/icp-behavioural (synthetic personas built on ICP foundation)/positioning (positioning targets ICP pain points)/product-messaging (messaging speaks to ICP personas)/content-strategy (content targets ICP channels and topics)
