icp-research · diff

v4.2 to v1.0

71 added, 471 removed. Audit A to A.

---

name: icp-research

- version: "4.2"

+ version: '1.0'

+ last_updated: 2026-05-19

author: genesys-growth

- last_updated: 2026-03-15

- description: |

- Generate comprehensive ideal customer profile and segment research for B2B SaaS clients.

- Triggers on phrases like 'ICP research for', 'customer segment analysis', 'ideal customer profile for',

- 'who are [company]s customers', 'segment research for [URL]', 'persona research', 'use case analysis',

- or requests involving customer identification, buyer persona development, use case mapping, or testimonial extraction.

- Requires website URL as primary input. Scrapes case studies, testimonials, solutions pages to extract

- structured ICP documentation with normalized attributes across TAM analysis, firmographics, personas,

- customer proof points, use cases, segments, and voice of customer synthesis.

- # Agentic Layer Fields

- dependencies:

+ description: Build structured ICP documentation by scraping case studies, testimonials, and solutions pages from your website. Produces firmographics, champion + economic buyer personas, pain points, decision criteria, anti-ICP, customer proof points, and voice-of-customer synthesis. Writes to marketing/icp/ICP.md as the canonical ICP every downstream skill reads. Triggers - "icp research", "ideal customer profile", "persona research", "customer segments", "who are our customers", "build ICP"

+ goal: Build a structured ICP from website signals + win-loss data so every downstream skill works from the same definition of the customer.

+ outcome: marketing/icp/ICP.md with firmographics, champion + economic buyer personas, pain points, anti-ICP, voice-of-customer.

+ primitive: research

+ ontology_type: icp-profile

+ review_gate: 2

+ inputs:

required: []

recommended:

- - company-context

+ - competitor-research

outputs:

- type: icp-profile

feeds_into:

- positioning

- product-messaging

- - landing-page-copy

- - aeo-content

- - outreach-emails

- - sales-enablement

- - competitor-research

+ - funnel-strategy

+ - content-strategy

+ owned_by_agent: researcher

+ mcps_used:

+ - exa

triggers:

- auto_suggest_when:

- - "user mentions 'ICP research' OR 'ideal customer profile' OR 'customer segment analysis'"

- - "user provides a website URL for ICP research"

- - "user mentions 'persona research' OR 'use case analysis' OR 'buyer persona'"

- - "user asks 'who are [company]s customers'"

- auto_run_when: null # Always require confirmation

- review_gate: 1 # Quick review (research output)

- output_path: "context/"

- ---

- # 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:**

- |--------|-------|--------------|-------------------|

- | 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 dynamics

- - **ICP-fit:** Why this segment is a good fit for our product

- - **Budget & sales cycle:** Spending power and typical cycle length

- - **Unique approach:** How we target this segment uniquely

- - **Proof 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:**

- |----------|-------------------|--------------|----------------|----------|

- ### 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 process

- - **Key steps:** Numbered steps in the process

- - **Core scenarios:** 3-4 typical scenarios

- - **Current alternatives:** Competitors, Manual, DIY approaches

- - **Business drivers:** What drives the need

- - **Desired outcomes:** What success looks like

- **Champion deep-dive structure (explicit template):**

- The Champion is the person who feels the pain daily, drives the evaluation, and advocates internally for the solution.

- 1. **Titles:** Title variations with context (e.g., "Manager of X, Senior Y, Lead Z")

- 2. **Department & team size:** Where they sit and typical team structure

- 3. **Responsibilities:** Key responsibilities in paragraph form (2-3 sentences)

- 4. **Jobs to be done:** 3-5 product-agnostic jobs they're trying to accomplish

- 5. **Success metrics / KPIs:** How they're measured and what success looks like

- 6. **Challenges:** Things that make their job harder (obstacles they struggle with)

- 7. **Pain points:** Problems that hurt them directly (negative impact they feel)

- 8. **Current alternatives:** How they currently achieve goals without this product

- 9. **Problems with alternatives:** Specific issues with current approach

- 10. **Buying behavior:** How they typically discover and evaluate solutions

- 11. **Channels & influences:** Communities, content, events, and influencers they trust

- 12. **Testimonial:** Verbatim quote from case study with name, title, company, and description of product usage

- **Channels & influences format:**

- - **Communities:** LinkedIn groups, Slack communities, forums (e.g., RevGenius, Pavilion, specific subreddits)

- - **Content sources:** Newsletters, podcasts, YouTube channels, blogs they follow

- - **Events:** Conferences, webinars, meetups they attend

- - **Influencers:** People they follow and trust on LinkedIn, Twitter, etc.

- **Economic Buyer deep-dive structure (explicit template):**

- The Economic Buyer is the person who controls budget and makes the final purchasing decision.

- 1. **Titles:** Title variations with context (e.g., "VP of X, Director of Y, Head of Z")

- 2. **Department & team size:** Where they sit, reporting structure, direct reports

- 3. **Responsibilities:** Key responsibilities in paragraph form (2-3 sentences)

- 4. **Jobs to be done:** 3-5 business-level jobs they're trying to accomplish

- 5. **Success metrics / KPIs:** Business metrics they're accountable for

- 6. **Challenges:** Business-level obstacles they face

- 7. **Pain points:** Business impacts that create urgency

- 8. **What they actually care about:** Beyond stated concerns — what drives decisions

- 9. **Common objections:** Typical pushback during sales process

- 10. **What a "no-brainer" looks like:** Conditions that make approval easy

- 11. **Buying behavior:** How they evaluate and approve purchases

- 12. **Channels & influences:** Where they get information and who they trust

- 13. **Testimonial:** Verbatim quote from case study with name, title, company

- **Channels & influences format (for Economic Buyer):**

- - **Communities:** Executive networks, industry associations, peer groups

- - **Content sources:** Industry reports, analyst briefings, executive newsletters

- - **Events:** Leadership summits, board meetings, industry conferences

- - **Influencers:** Analysts, advisors, peer executives they respect

- ### 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 |

- **Disqualification criteria table:**

- |-----------|-----------|----------------|----------|

- ### Customer proof points

- Evidence from specific customers with URLs and dates.

- | Field | Description |

- |-------|-------------|

- | Proof points overview | Paragraph synthesizing evidence quality |

- | Named customers table | With URL and date for each source |

- | Outcome patterns | Quantified results with URL and date |

- ### Voice of customer

- Language patterns from customer communications with source attribution.

- | Field | Description |

- |-------|-------------|

- | VOC overview | Paragraph explaining terminology patterns |

- | Terminology patterns | With URL and date |

- | Pain point language | With URL and date |

- | Outcome language | With URL and date |

- | Objection patterns | With URL and date |

- ### Segments

- Distinct customer segments with comprehensive targeting guidance.

- | Field | Description |

- |-------|-------------|

- | Segment overview | Paragraph explaining segmentation logic |

- | Scoring matrix | TAM × Ease of win × Strategic fit = Score |

- | In-market signals | Observable signals by segment |

- | Per-segment definition | Full attribute table with URL + date evidence |

- | **Segment deep-dives** | Priorities, ICP-fit, Budget & sales cycle, Unique approach, Proof points |

- | Positioning recommendation | Lead message for segment |

- **Segment deep-dive structure:**

- For each ICP segment, include:

- - **Priorities:** Key priorities within today's market trends

- - **ICP-fit:** Why this segment is a particularly good fit

- - **Budget & sales cycle:** Spending power and cycle length

- - **Unique approach:** How we target uniquely vs other segments

- - **Proof points:** Stats with customer name, title, description, URL, date

- ### Beachhead selection (optional)

- When segments are defined, optionally apply beachhead selection to pick ONE segment to dominate first.

- **Scoring rubric:**

- | Criterion | Weight | Description |

- |-----------|--------|-------------|

- | TAM opportunity | 30% | Revenue potential in this segment |

- | Ease of win | 30% | How quickly can we close deals? (short sales cycle, clear pain, few competitors) |

- | Strategic fit | 20% | Does winning here create leverage for adjacent segments? |

- | Reference-ability | 20% | Will wins here produce case studies that unlock other segments? |

- **Decision:** Score each segment 1-5 on each criterion. Multiply by weight. Highest composite score = recommended beachhead.

- ### 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 |

- **Intent signals table structure:**

- |--------|------|---------------|----------------|------------------|

- **Common company-level signals:**

- - New executive hire (VP/Head/Director of relevant function)

- - Open job postings in relevant department (scaling team)

- - Funding announcement (budget available)

- - Tech stack change (implementation moment)

- - Competitor displacement signals

- - Regulatory/compliance trigger

- - M&A activity

- **Common persona-level signals:**

- - Recent role change or promotion

- - LinkedIn posts about relevant challenges

- - Engagement with competitor content

- - Event attendance or speaking

- - Community participation

- - Content consumption patterns

- ---

- ## 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 |

+ slash_commands:

+ - /icp-research

+ status: draft

---

- ## 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

+ # icp-research — Stage 1 + 2 research skill

- - [ ] Opens with the key insight, not setup

- - [ ] Includes specific evidence (names, numbers, sources)

- - [ ] Includes URL and date for all evidence

- - [ ] Explains the "so what" — why this matters

- - [ ] Avoids generic language that could apply to any company

+ The article's Example 1 Day 5 skill. Reads your website + win-loss patterns (if available) + competitor outputs (if locked) and writes a structured ICP to `marketing/icp/ICP.md`. This file is canonical from creation — every downstream skill reads it.

---

- ## Workflow

- ### Phase 1: Data extraction

- 1. **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]

- ```

- 2. **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

- 3. **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 × company size):

- 1. **Identify patterns** across extracted data

- 2. **Define core use case** with steps, scenarios, alternatives, drivers, outcomes

- 3. **Build Champion deep-dive** with all 12 fields including Channels & influences

- 4. **Build Economic Buyer deep-dive** with all 13 fields including Channels & influences

- 5. **Map use cases** to segment-specific needs

- 6. **Identify negative ICP** criteria and red flags

- 7. **Identify intent signals** at company and persona level

- 8. **Collect proof points** with testimonials for personas and segments

- 9. **Document technographics** with required and preferred tools

- 10. **Calculate TAM estimate** with targeting strategy per layer

- 11. **Identify ICP** as highest-priority segment below SOM

- ### Phase 3: Structured output

- Generate numbered sections following the report structure above.

+ ## When to use

- Apply sorting rules to all tables (Champion first for personas).

+ - Day 5 of Example 1: after competitor research + win-loss data exist, build the ICP synthesis

+ - Quarterly refresh of ICP (markets shift)

+ - New segment exploration ("we're adding a healthcare vertical — re-run ICP for that segment")

+ - After major win-loss shift (5+ recent losses in a segment → re-run ICP)

- Include rich descriptions with URLs and dates for all evidence.

+ ## When NOT to use

- Include deep-dives for company segments, personas (Champion and Economic Buyer explicitly), and ICP segments.

+ - For behavioural simulation of an ICP buyer (use `/icp-behavioural` — not in V2 quickstart)

+ - For interview prep against a single account (use `/customer-interviews` — not in V2 quickstart)

+ - For competitor research (use `/competitor-research`)

+ - For positioning strategy (use `/positioning` after ICP locks)

- ---

+ ## How it works

- ## Input requirements

+ 1. Inputs: your website URL (required). Optional: list of representative customer URLs, win-loss patterns from prior cycle, competitor aggregate.

+ 2. Reads (Exa MCP for fresh data): website case studies, customer pages, testimonials, blog posts, About / Solutions pages.

+ 3. Optionally reads: `marketing/competitors/aggregate.md` (if locked) to inform "anti-ICP" framing; recent win-loss data from `marketing/icp/win-loss.md` (if `/win-loss-analysis` has run).

+ 4. Produces a structured ICP with these sections (matches the PulseAnalytics example at `marketing/icp/ICP.md`):

+ - **Firmographics** — company type, revenue stage, team size, funding, geography, industry

+ - **Champion persona** — title, tenure, reporting, owns, their week, JTBD, job-context triggers, pain points (priority order), decision criteria

+ - **Economic buyer persona** — title, motivation, decision criteria

+ - **Anti-ICP** — who NOT to sell to + why

+ - **Where they hang out** — acquisition channels with rationale

+ - **Customer proof points** — populate as real customers ship (start empty with `[UNAVAILABLE]` notation)

+ - **Voice of customer** — verbatim quotes by theme (populate from `/win-loss-analysis` over time)

+ 5. Every claim tagged with confidence per `.claude/rules/ontology.md`. Invented metrics forbidden — use `[UNAVAILABLE]` instead.

+ 6. Writes to `marketing/icp/ICP.md` (overwrites prior canonical; git history preserves prior versions).

- ### Required

- - **Website URL**: Primary company website

+ ## Invoke

- ### Optional (improves quality)

+ ```

+ /icp-research https://yourdomain.com

+ ```

- | 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 |

+ Or with optional inputs:

+ ```

+ /icp-research https://yourdomain.com + read these 3 case studies: [URLs]

+ ```

- ---

+ ## Example output

- ## Anti-hallucination guardrails

+ See [`marketing/icp/ICP.md`](../../../marketing/icp/ICP.md) for the PulseAnalytics example seed. Notice the structure repeats per persona (champion + economic buyer); pain points are priority-ordered; anti-ICP is explicit; VoC + proof points start `[UNAVAILABLE]` and fill as data lands.

- 1. **Never invent customer names.** Only cite publicly referenced customers.

- 2. **Quote verbatim.** Use exact customer language in quotes.

- 3. **Mark confidence levels.** Tag data as High/Medium/Low confidence.

- 4. **Cite sources with URLs and dates.** Include URL and access date for every claim.

- 5. **Acknowledge gaps.** Explicit "Not available" for missing data.

+ ## Dependencies

- | Confidence | Definition |

- |------------|------------|

- | High | Direct from official source, verifiable |

- | Medium | Third-party source, multiple signals |

- | Low | Single indirect source, inferred |

+ - **Reads from:** your website URL (required); `marketing/competitors/aggregate.md` (optional, recommended); `marketing/icp/win-loss.md` (optional, when `/win-loss-analysis` is wired)

+ - **Reads via Exa MCP (optional):** website + recent customer-facing pages

+ - **Writes to:** `marketing/icp/ICP.md` (canonical, every downstream skill reads here)

- ---

+ ## Customization

- ## Quality checklist

+ Add a custom segment (e.g., "Enterprise tier") by extending the firmographics section with a segment-table — different revenue/team-size cuts get different champion personas. The Genesys-internal version supports segment-by-segment ICPs; the quickstart simplifies to one ICP and one champion.

- - [ ] All 12 numbered sections present

- - [ ] Every section has opening synthesis paragraph

- - [ ] All tables sorted per sorting rules (Champion first for personas)

- - [ ] TAM table includes ICP row with targeting strategy

- - [ ] Technographics section included with Required/Preferred tools

- - [ ] Core use case defined with steps, scenarios, alternatives, drivers, outcomes

- - [ ] Champion deep-dive includes all 12 fields with Channels & influences

- - [ ] Economic Buyer deep-dive includes all 13 fields with Channels & influences

- - [ ] Persona deep-dives include testimonials with quotes

- - [ ] Company segment deep-dives include Priorities, ICP-fit, Budget & sales cycle, Unique approach, Proof points

- - [ ] Negative ICP documented with disqualification criteria and red flags

- - [ ] Intent signals documented with company-level and persona-level signals

- - [ ] ICP segment deep-dives include Priorities, ICP-fit, Budget & sales cycle, Unique approach, Proof points

- - [ ] Customer names sourced from public references only

- - [ ] Firmographics normalized to standard attributes

- - [ ] VOC quotes are verbatim with source URLs and dates

- - [ ] All evidence includes URL and access date

- - [ ] Confidence levels assigned to all key data

- - [ ] Data gaps documented with follow-up suggestions

+ Edit pain-point priority order based on real customer conversations as they happen. Pain priority drives messaging hierarchy downstream.

- ---

+ ## Where this fits in the Example 1 chain

- ## Related context

+ ```

+ Day 1-3: /competitor-research × N → per-competitor files

+ Day 3: /competitor-aggregate → competitor canonical

+ Day 4: /win-loss-analysis (excluded from V2 default) → win-loss data

+ Day 5: /icp-research (THIS SKILL) → canonical ICP

+ Week 2: /positioning reads ICP.md + competitor aggregate

+ ```

- **Built from:**

- - `context/MMYY-company-context.md` (company profile)

- - `context/MMYY-competitor-*.md` (market context)

+ ## Refresh cadence

- **Feeds into:**

- - `marketing/product-marketing/MMYY-positioning.md` (targeting)

- - `marketing/product-marketing/MMYY-product-messaging.md` (persona-specific messaging)

- - `marketing/content/MMYY-content-strategy.md` (audience-aligned content)

+ Quarterly. Trigger sooner on major win-loss shift, new segment entry, or major change in champion-persona vocabulary.