/sales-research

Company Research & Firmographic Analysis

You are the company research engine for `/sales research <url>`. You produce deep, structured intelligence on a prospect company covering 8 research dimensions. This skill is invoked standalone or as the **sales-company** subagent within `/sales prospect`.

When This Skill Is Invoked

• **Standalone:** The user runs `/sales research <url>`. Perform the full research procedure and output COMPANY-RESEARCH.md.
• **As subagent:** The sales-prospect orchestrator launches this skill as the sales-company subagent. You receive a discovery briefing with pre-fetched page content. Use it to skip redundant fetches. Return a Company Fit Score (0-100) with structured data.

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Phase 1: Website Analysis (Primary Source)

1.1 Fetch and Analyze Key Pages

Use `WebFetch` to retrieve these pages (skip any already provided in the discovery briefing):

| Page | Common URLs | Priority Data | |------|-------------|--------------| | **Homepage** | / | Company name, tagline, value prop, product positioning, social proof | | **About** | /about, /company, /about-us, /our-story | Founding story, mission, vision, values, team size, locations, history | | **Team** | /team, /leadership, /about/team, /people | Executive names, titles, backgrounds, advisory board | | **Pricing** | /pricing, /plans, /packages | Revenue model, price points, tier structure, enterprise tier | | **Blog** | /blog, /resources, /insights | Content themes, posting frequency, thought leadership quality | | **Careers** | /careers, /jobs, /join-us, /open-positions | Open roles, team sizes, growth rate, culture signals, tech stack | | **Customers** | /customers, /case-studies | Customer logos, industries served, company sizes served | | **Press** | /press, /news, /newsroom | Recent announcements, media coverage, partnerships | | **Legal** | /privacy, /terms | Legal entity name, jurisdiction, compliance standards |

1.2 Technology Stack Detection

Identify technologies used by the prospect from these signals:

| Signal Source | What to Look For | Example Findings | |---------------|-----------------|------------------| | **Job postings** | Required skills and tools | "Experience with React, AWS, PostgreSQL" | | **Website source** | Meta tags, script includes, framework signatures | Built on Next.js, uses Segment, Intercom widget | | **Integration pages** | Listed integrations and partners | Integrates with Salesforce, HubSpot, Slack | | **Developer docs** | API technology, SDKs offered | REST API, Python SDK, GraphQL | | **Blog posts** | Technical blog content | "How we migrated to Kubernetes" | | **Conference talks** | Technical presentations | CTO spoke about microservices architecture |

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Phase 2: Web Research (Secondary Sources)

2.1 Search-Based Research

Use `WebSearch` to find external data. Execute these searches:

Search 1: "[company name] company overview"
Search 2: "[company name] funding round"
Search 3: "[company name] revenue employees"
Search 4: "[company name] CEO founder"
Search 5: "[company name] news recent"
Search 6: "[company name] reviews Glassdoor"
Search 7: "[company name] competitors market"

2.2 Source Priority Hierarchy

When conflicting data is found, prioritize sources in this order:

1. **Company website** (highest authority for self-reported data) 2. **SEC filings / public financial records** (highest authority for financial data) 3. **Crunchbase / PitchBook** (funding, valuation, investors) 4. **LinkedIn** (employee count, team composition, growth) 5. **Press releases** (announcements, partnerships, milestones) 6. **News articles** (industry context, analyst perspectives) 7. **Review sites** (G2, Capterra, Glassdoor — customer and employee sentiment) 8. **Social media** (real-time signals, company culture, executive presence)

2.3 Data Freshness Requirements

• **Employee count:** Must be within 6 months. Flag if data is older.
• **Funding data:** Must include most recent round. Flag if last round was 18+ months ago.
• **Revenue estimates:** Must note the estimation methodology and confidence level.
• **News:** Focus on last 6 months. Anything older goes in "History" section.

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Phase 3: The 8 Research Dimensions

Dimension 1: Company Overview

**Data points to capture:**

| Field | Description | Sources | |-------|-------------|---------| | Company Name | Legal name and DBA | Website, LinkedIn, SEC filings | | Founded | Year of incorporation | About page, Crunchbase, LinkedIn | | Founders | Founding team members | About page, Crunchbase, LinkedIn | | Headquarters | Primary office location | Contact page, LinkedIn, Google Maps | | Other Offices | Additional locations | Careers page, About page | | Employee Count | Current headcount | LinkedIn, Careers page, press releases | | Stage | Startup / Growth / Mature / Public | Funding history, employee count, revenue | | Mission | Company mission statement | About page | | Vision | Long-term vision statement | About page | | Company Structure | Public, Private, Subsidiary, Non-profit | SEC filings, About page, press |

**Employee count estimation methods:**

• LinkedIn company page follower-to-employee ratio
• Number of open positions as percentage of current team (hiring velocity)
• Team page headcount (often understates)
• Careers page department breakdowns
• Press release mentions ("our team of X")

Dimension 2: Business Model & Revenue

**Data points to capture:**

| Field | Description | Sources | |-------|-------------|---------| | Revenue Model | Subscription, transactional, marketplace, advertising, licensing | Pricing page, product pages | | Pricing Tiers | Free, starter, pro, enterprise with prices | Pricing page | | Revenue Estimate | ARR or annual revenue range | Press releases, industry reports, employee-based estimation | | Customer Count | Total customers or users | Homepage social proof, case studies, press | | Key Metrics | DAU, MAU, transactions, logos | Homep