Sales Blueprint
Map Decision Makers & Buying Committee
Identifies C-suite, technical champions, economic buyers, and stakeholders from public data.
What problem does this solve?
Identifies decision makers and stakeholders at a prospect company by extracting names, titles, and roles from team pages and LinkedIn signals. This removes the guesswork about who to reach out to and reveals warm paths through shared connections.
How does it work?
Run /sales contacts <url>. The skill analyzes the company's team page, leadership section, and LinkedIn profile data to identify decision makers by role and seniority. It maps the buying committee structure and flags warm paths (industry peers, alumni networks). Output: list of 4-12 identified decision makers with titles, roles, and outreach priority ranking.
What's required to run this?
contact_finder.py uses beautifulsoup4 to parse team pages and extract structured contact data; accuracy depends on company website completeness and LinkedIn API availability.
Key Features
/sales-contacts
Identifies C-suite, department heads, and technical champions with titles and reporting lines
Buying Committee Mapping
Structures decision makers by role (economic buyer, technical buyer, champion, influencer) and identifies reporting relationships
Warm Path Detection
Flags shared connections, alumni networks, and mutual acquaintances for warm outreach
contact-finder.py
Extracts team data from HTML, parses titles and org structure, matches to public profiles
About This Blueprint
- Industry
- Sales & Revenue Operations
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