name icp-research version 4.2 author genesys-growth last_updated "2026-03-15T00:00:00.000Z" 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. Upstream: recommended company-context. Downstream: feeds positioning, product-messaging, landing-page-copy, content-strategy, and outreach-emails.
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 multiple dimensions. See references/dimension-schemas.md for complete field definitions.
TAM analysis
Market opportunity sizing with explicit methodology, assumptions, and targeting strategy.
Field Description TAM summary Rich paragraph explaining total addressable market with methodology TAM calculation table Metric, value, source/basis, and targeting strategy for each layer ICP row Below SOM: highest priority segment based on research findings Assumptions Documented assumptions underlying each estimate
TAM table structure:
Metric Value Source/Basis Targeting strategy TAM $XB [Methodology] Long-term market awareness and category leadership SAM $XM [Qualification] Segment-specific campaigns and channel strategy SOM $XM [Capture estimate] Direct sales and targeted ABM ICP $XM [Research findings] Highest-priority accounts for immediate focus
Firmographics
Company attributes that define ideal customers with segment deep-dives.
Field Description Geography summary Paragraph with regional patterns and evidence Geography table Regions sorted by concentration, with URL + date evidence Industry summary Paragraph explaining vertical patterns Industry table Industries sorted by presence, with URL + date evidence Company segments summary Paragraph describing size/stage patterns Segments table Enterprise → Mid-market → SMB → Startup Segment deep-dives For each segment: Priorities, ICP-fit, Budget & sales cycle, Unique approach, Proof points Technographics Required tools, integrations, and tech stack indicators Adjacent stack Common tools and integrations
Company segment deep-dive structure:
For each segment (Enterprise, Mid-market, SMB), include:
Priorities: Key priorities within today's market trends and dynamicsICP-fit: Why this segment is a good fit for our productBudget & sales cycle: Spending power and typical cycle lengthUnique approach: How we target this segment uniquelyProof points: Stats of impact from representatives with URLs and dates
Technographics
Required technology prerequisites and common stack patterns. This section identifies tools that indicate fit or readiness.
Category Purpose CRM Customer relationship management (Salesforce, HubSpot, Pipedrive) E-commerce Commerce platforms (Shopify, BigCommerce, WooCommerce) Marketing automation Email and automation (Klaviyo, Mailchimp, Braze, Marketo) CDP Customer data platforms (Segment, mParticle, Rudderstack) Analytics Product and web analytics (Amplitude, Mixpanel, Google Analytics, Posthog) Cloud Infrastructure providers (AWS, Azure, GCP, Vercel) Data warehouse Data storage (Snowflake, BigQuery, Redshift, Databricks) ERP Enterprise resource planning (SAP, NetSuite, Oracle) Communication Team communication (Slack, Microsoft Teams) Project management Work management (Jira, Asana, Monday, Linear)
Technographics table structure:
Category Required/Preferred Common tools Why it matters Evidence [Category] Required [Tool names] [Product dependency or integration] [Source] ([URL], [Date]) [Category] Preferred [Tool names] [Better fit or faster time-to-value] [Source] ([URL], [Date])
Personas
Who buys and uses the product, with explicit Champion and Economic Buyer deep-dives.
Field Description Persona overview Rich paragraph summarizing buying committee structure Personas table Sorted: Champion → Economic Buyer → User → Influencer Core use case Business process definition with steps, scenarios, alternatives, drivers, outcomes Champion deep-dive Explicit template for the person who drives evaluation Economic Buyer deep-dive Explicit template for the person who controls budget User deep-dive(s) Additional personas who use the product daily Use cases by role Champion first, then by seniority Alternatives mentioned Competitors and substitutes with URLs Buying journey Champion → Economic Buyer → User columns
Core use case structure:
Use case statement: 1-2 sentences defining the business processKey steps: Numbered steps in the processCore scenarios: 3-4 typical scenariosCurrent alternatives: Competitors, Manual, DIY approachesBusiness drivers: What drives the needDesired outcomes: What success looks like
Champion deep-dive structure (12 fields):
The Champion is the person who feels the pain daily, drives the evaluation, and advocates internally for the solution.
Titles: Title variations with context (e.g., "Manager of X, Senior Y, Lead Z")Department & team size: Where they sit and typical team structureResponsibilities: Key responsibilities in paragraph form (2-3 sentences)Jobs to be done: 3-5 product-agnostic jobs they're trying to accomplishSuccess metrics / KPIs: How they're measured and what success looks likeChallenges: Things that make their job harder (obstacles they struggle with)Pain points: Problems that hurt them directly (negative impact they feel)Current alternatives: How they currently achieve goals without this productProblems with alternatives: Specific issues with current approachBuying behavior: How they typically discover and evaluate solutionsChannels & influences: Communities, content, events, and influencers they trustTestimonial: Verbatim quote from case study with name, title, company, and description of product usage
Economic Buyer deep-dive structure (13 fields):
The Economic Buyer is the person who controls budget and makes the final purchasing decision.
Titles: Title variations with context (e.g., "VP of X, Director of Y, Head of Z")Department & team size: Where they sit, reporting structure, direct reportsResponsibilities: Key responsibilities in paragraph form (2-3 sentences)Jobs to be done: 3-5 business-level jobs they're trying to accomplishSuccess metrics / KPIs: Business metrics they're accountable forChallenges: Business-level obstacles they facePain points: Business impacts that create urgencyWhat they actually care about: Beyond stated concerns — what drives decisionsCommon objections: Typical pushback during sales processWhat a "no-brainer" looks like: Conditions that make approval easyBuying behavior: How they evaluate and approve purchasesChannels & influences: Where they get information and who they trustTestimonial: Verbatim quote from case study with name, title, company
Negative ICP
Identifying who is NOT a fit helps sales disqualify quickly and avoid bad-fit deals.
Field Description Disqualification criteria Table of attributes that indicate poor fit Red flags Warning signs from churned or unsuccessful customers Objection patterns Objections that signal poor fit vs. legitimate concerns
Intent signals and buying triggers
Observable events or behaviors indicating a company or persona is more likely to buy now.
Field Description Overview Paragraph explaining signal detection strategy Company-level signals Events at the organization level Persona-level signals Behaviors from individual buyers Signal sources Where to detect each signal
Sorting rules
Apply consistent sorting 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
Rich description requirements
Every section must include contextual paragraphs, not just tables. All evidence must include URL and access date.
Minimum requirements
Section Required prose Each macro section (1-12) Opening paragraph (3-5 sentences) summarizing findings Each industry vertical 2-3 sentences explaining why this industry fits and evidence Each company segment Deep-dive with Priorities, ICP-fit, Budget & sales cycle, Unique approach, Proof points Champion persona Full deep-dive with all 12 fields including Channels & influences Economic Buyer persona Full deep-dive with all 13 fields including Channels & influences Core use case Full definition with steps, scenarios, alternatives, drivers, outcomes Each ICP segment Deep-dive with Priorities, ICP-fit, Budget & sales cycle, Unique approach, Proof points Negative ICP Disqualification criteria, red flags, and objection patterns Intent signals Company-level and persona-level signals with detection sources Data gaps Paragraph explaining impact of missing data and mitigation
Paragraph quality checklist
Workflow
Phase 1: Data extraction
Discover key pages
Fetch: [domain]/customers OR /case-studies OR /success-stories
Fetch: [domain]/solutions OR /use-cases OR /industries
Fetch: [domain]/pricing
Fetch: [domain]/integrations OR /partners
Search: site:[domain] case study testimonial
Search: site:g2.com "[company]" reviews
Search: site:linkedin.com "[company]" hiring [relevant role]
Extract raw data per source (record URL and date for each):
Customer names and logos
Job titles and roles mentioned
Industry and company size indicators
Quantified outcomes and stats
Verbatim quotes and pain point language
Use case descriptions and workflows
Tech stack and integrations
Community and content references
Normalize attributes
Attribute Normalization rules Geography Map to: US, North America, EMEA, APAC, LATAM, Global Industry Use standard verticals: SaaS, E-commerce, Finance, Healthcare, etc. Company size Revenue bands: <$1M, $1-10M, $10-50M, $50-100M, $100M+ Team size Employee bands: 1-10, 11-50, 51-200, 201-500, 501-1000, 1000+ Tech stack Category + tool name: CRM (Salesforce), CDP (Segment)
Phase 2: Analysis and synthesis
For each segment (by industry x company size):
Identify patterns across extracted dataDefine core use case with steps, scenarios, alternatives, drivers, outcomesBuild Champion deep-dive with all 12 fields including Channels & influencesBuild Economic Buyer deep-dive with all 13 fields including Channels & influencesMap use cases to segment-specific needsIdentify negative ICP criteria and red flagsIdentify intent signals at company and persona levelCollect proof points with testimonials for personas and segmentsDocument technographics with required and preferred toolsCalculate TAM estimate with targeting strategy per layerIdentify ICP as highest-priority segment below SOM
Phase 3: Structured output
Generate numbered sections following the report structure above.
Apply sorting rules to all tables (Champion first for personas).
Include rich descriptions with URLs and dates for all evidence.
Include deep-dives for company segments, personas (Champion and Economic Buyer explicitly), and ICP segments.
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
Reference files
File Purpose references/dimension-schemas.mdComplete field definitions for all dimensions references/icp-output-template.mdFull report template with numbered sections references/search-patterns.mdDetailed search queries per data type references/examples/example-strapi.mdWorked example: Strapi (headless CMS)
Quality checklist
