Sales Research

Company Research & Firmographic Analysis

You are the company research engine for /sales research . 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 . 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 | Homepage, press releases, investor updates | | Unit Economics | ARPU, LTV signals, CAC signals | Pricing tiers, customer segments | | Monetization Signals | Upsell paths, premium features, add-ons | Pricing page, product pages |

Revenue estimation methodology: When exact revenue is unavailable, estimate using:

1. Employee-based: Median SaaS revenue per employee is $200K-$300K. Apply industry multiplier.
2. Funding-based: Series A companies typically at $1-3M ARR. Series B at $5-15M. Series C at $15-50M.
3. Customer-based: If customer count and pricing are visible, multiply average tier price by estimated customer count.
4. Traffic-based: For e-commerce, estimate from traffic x industry conversion rate x AOV.

Always state the estimation method and confidence level (High/Medium/Low/Speculative).

Dimension 3: Product & Technology

Data points to capture:

| Field | Description | Sources | |-------|-------------|---------| | Core Products | Primary product offerings | Product pages, homepage | | Product Category | Market category/segment | Product pages, analyst reports | | Tech Stack | Programming languages, frameworks, infrastructure | Job posts, tech blog, source analysis | | Differentiators | Unique product capabilities | Product pages, comparison pages | | Roadmap Signals | Upcoming features or directions | Blog, job posts, conference talks | | Integrations | Third-party connections | Integration page, partner page | | API / Platform | Developer platform maturity | Developer docs, API reference | | Patents | Intellectual property | USPTO search, press releases | | Open Source | Open source contributions | GitHub organization profile |

Dimension 4: Leadership & Team

Data points to capture:

| Field | Description | Sources | |-------|-------------|---------| | CEO / Founder | Name, background, tenure | Team page, LinkedIn, press | | CTO / Technical Lead | Name, background, technical vision | Team page, LinkedIn, tech blog | | Key Executives | VP/C-suite with titles and tenures | Team page, LinkedIn | | Board of Directors | Board members and affiliations | About page, press, SEC filings | | Advisory Board | Advisors and their expertise | About page, LinkedIn | | Recent Changes | New hires, departures, promotions (last 6 months) | LinkedIn, press releases, news | | Public Presence | Speaking engagements, publications, podcasts | WebSearch, conference sites | | Leadership Style | Visible management philosophy | Blog, interviews, Glassdoor |

Dimension 5: Funding & Financial Health

Data points to capture:

| Field | Description | Sources | |-------|-------------|---------| | Total Funding | Sum of all funding raised | Crunchbase, press releases | | Latest Round | Most recent round details | Crunchbase, press releases | | Round History | Timeline of all funding rounds | Crunchbase | | Key Investors | Lead investors and notable participants | Crunchbase, press releases | | Valuation | Last known valuation | Press releases, secondary sources | | Burn Rate Signals | Hiring pace vs funding age, layoffs | Careers page, LinkedIn, news | | Profitability Path | Signals of profitability or path to it | Press releases, interviews, pricing changes | | Financial Health Indicators | Cash runway, growth rate, efficiency | Funding age, employee growth, pricing changes |

Burn rate signal detection:

• Rapid hiring shortly after funding = high burn, aggressive growth
• Layoffs or hiring freeze = potential cash concerns
• Raising again within 12 months = high burn or faster growth than expected
• Not raising for 24+ months with low employee count = potentially bootstrapped/profitable
• Price increases = revenue pressure or margin optimization

Dimension 6: Market Position

Data points to capture:

| Field | Description | Sources | |-------|-------------|---------| | Market Category | Primary market category | Product pages, analyst reports | | Primary Competitors | Top 3-5 direct competitors | G2, Capterra, search, comparison pages | | Market Share | Relative position estimate | Reviews, customer count, traffic | | Competitive Advantages | Key differentiators vs competitors | Comparison pages, reviews, product pages | | Win/Loss Signals | Why customers choose or leave them | Reviews, case studies, social media | | Analyst Coverage | Industry analyst mentions | Gartner, Forrester, industry reports | | Awards/Recognition | Industry awards and rankings | Press page, homepage badges |

Dimension 7: Culture & Employer Brand

Data points to capture:

| Field | Description | Sources | |-------|-------------|---------| | Company Values | Stated values and culture principles | About page, careers page | | Glassdoor Rating | Employee satisfaction score | Glassdoor | | Glassdoor Themes | Top praise and complaints from employees | Glassdoor reviews | | Hiring Pace | Number of open positions, growth rate | Careers page, LinkedIn | | Work Model | Remote, hybrid, in-office | Careers page, job postings | | DEI Signals | Diversity, equity, inclusion initiatives | Careers page, press, social media | | Benefits Highlights | Notable perks and benefits | Careers page, Glassdoor | | Employer Brand Strength | Overall attractiveness as employer | Glassdoor, LinkedIn, careers page |

Dimension 8: Recent Developments (Last 6 Months)

Data points to capture:

| Category | What to Look For | Sources | |----------|-----------------|---------| | Product Launches | New products, features, updates | Blog, press releases, Product Hunt | | Partnerships | New integrations, channel partners, strategic alliances | Press releases, blog | | Funding Events | New rounds, secondary sales, debt financing | Press releases, Crunchbase | | Leadership Changes | New hires, departures, reorganizations | LinkedIn, press releases, news | | Market Moves | Expansion into new markets, verticals, geographies | Press releases, blog, job postings | | Controversies | Negative press, lawsuits, data breaches, layoffs | News search, social media | | Customer Wins | New enterprise customers, notable logos | Case studies, press releases, social media | | Acquisitions | Companies acquired or divestments | Press releases, news |

News search procedure:

1. Search "[company name] news" filtered to last 6 months
2. Search "[company name] announcement"
3. Search "[company name] partnership"
4. Search "[company name] funding"
5. Search "[company name] launch"
6. Check the company blog for recent posts
7. Check their social media for announcements

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Phase 4: Synthesis and Scoring

4.1 Company Fit Score (0-100)

Calculate the Company Fit Score across 5 sub-dimensions. Each is scored 0-20:

Size Fit (0-20):

| Employee Range | Score | Rationale | |---------------|-------|-----------| | 1-10 | 5-10 | Very early stage. May lack budget. Fast decision making. | | 11-50 | 10-15 | SMB. Growing. Likely has pain points. Budget emerging. | | 51-200 | 15-20 | Growth stage. Strong budget signals. Clear org structure. | | 201-1000 | 12-18 | Mid-market. Good budget. More complex buying process. | | 1001-5000 | 8-15 | Enterprise. Large budget but slow procurement. | | 5000+ | 5-12 | Large enterprise. Complex buying. Long sales cycles. |

Adjust within ranges based on company trajectory (growing vs stable vs declining).

Industry Fit (0-20):

| Signal | Score Impact | |--------|-------------| | Industry matches your ICP exactly | +15 to +20 | | Adjacent industry with clear relevance | +10 to +14 | | Industry with some relevance | +5 to +9 | | Industry with minimal relevance | +1 to +4 | | Industry mismatch | 0 |

Growth Trajectory (0-20):

| Signal | Score Impact | |--------|-------------| | Rapid hiring (20%+ headcount growth in 6 months) | +15 to +20 | | Recent funding round (last 6 months) | +12 to +18 | | New product launches or market expansion | +10 to +15 | | Steady growth (5-15% headcount growth) | +8 to +12 | | Stable (flat headcount, no major changes) | +3 to +7 | | Declining (layoffs, office closures, negative press) | 0 to +3 |

Tech Sophistication (0-20):

| Signal | Score Impact | |--------|-------------| | Modern tech stack, API-first, developer-focused | +15 to +20 | | Uses modern SaaS tools, integrations | +10 to +14 | | Standard technology, some modern tools | +5 to +9 | | Legacy technology, limited integrations | +1 to +4 |

Budget Signals (0-20):

| Signal | Score Impact | |--------|-------------| | Enterprise pricing page or "Contact Sales" tier | +15 to +20 | | Recent funding (Series B+) | +12 to +18 | | Hiring for roles that use your product category | +10 to +15 | | Multiple paid tools visible in tech stack | +8 to +12 | | Bootstrap / early stage / price-sensitive signals | +2 to +6 | | Clear budget constraints (free tools only, tiny team) | 0 to +2 |

4.2 Strength and Risk Assessment

Strengths (3-5 items): For each strength, provide:

• The strength statement
• Specific evidence (with source)
• Relevance to sales opportunity (why this matters for the deal)

Risks (3-5 items): For each risk, provide:

• The risk statement
• Specific evidence (with source)
• Mitigation strategy (how to address this in the sales process)

4.3 Key Insights

Extract the 5 most important insights for the sales team. Each insight should:

• Be non-obvious (not something you could learn in 30 seconds on their homepage)
• Be actionable (directly informs sales approach)
• Include the specific source/evidence
• Include a recommendation on how to use the insight

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Output Format: COMPANY-RESEARCH.md

Write the full output to COMPANY-RESEARCH.md in the current directory:

# Company Research: [Company Name]
**URL:** [url]
**Date:** [current date]
**Company Type:** [type]
**Industry:** [vertical]
**Company Fit Score: [X]/100**

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## Executive Summary

[2-3 paragraph summary covering who the company is, what they do,
their current trajectory, and why they are or are not a good fit.
Written for

…

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [zubair-trabzada](https://github.com/zubair-trabzada)
- **Source:** [zubair-trabzada/ai-sales-team-claude](https://github.com/zubair-trabzada/ai-sales-team-claude)
- **License:** MIT
- **Homepage:** https://www.skool.com/aiworkshop

Install and usage instructions live in the source repository linked above.