Firmographics

Firmographics are demographics for companies instead of people — the hard, verifiable facts about an organization that predict whether it's a fit before anyone picks up a phone. Industry code, employee count, annual revenue, headquarters location, funding stage, number of office locations, ownership structure. None of it tells you if the company wants to buy. All of it tells you whether they're allowed to, whether they can afford it, and whether your product was built for a business their size.

What Firmographic Data Includes

Standard firmographic fields: industry/SIC or NAICS code, employee count, annual revenue, headquarters and office geography, funding stage (bootstrapped, Series A through public), ownership type (private, PE-backed, public), and growth signals like headcount change over the trailing 12 months. Technographic data — what CRM, cloud provider, or dev tools a company runs — sometimes gets bundled in as a firmographic extension, though it's technically a separate category sourced from web scraping rather than public filings or LinkedIn data.

How Firmographics Are Scored

Firmographic fit is usually a weighted point system layered under lead scoring: each attribute earns or loses points against the defined ICP, and accounts below a threshold get filtered out of outbound entirely before a rep ever sees them.

Worked Example

Two inbound leads land the same week. Company A: 45 employees, bootstrapped, healthcare staffing, HQ in a market the product wasn't built for. Company B: 800 employees, Series C, mid-market SaaS, US-based. Run both through the scoring table above and Company A scores -5 (too small, wrong industry, no funding signal), Company B scores +55. A firmographic filter routes Company B straight to an AE's queue and either kills Company A's lead or routes it to a self-serve motion instead of burning AE time on a deal that structurally can't close at the deal size the model needs.

When Sales and Marketing Teams Use Firmographics

Marketing uses firmographics to build total addressable market models and to scope ad targeting before a single dollar of spend goes out. RevOps builds routing rules on it — which leads go to enterprise AEs versus SMB reps versus the self-serve funnel. Account tiering frameworks lean on firmographics as the objective half of the score, paired with behavioral signals like intent data for the subjective half. Recruiters and comp analysts occasionally use firmographic filters too, screening candidate companies by size and funding stage to normalize OTE comparisons across employers.

Limitations and Misuse

Firmographics answer "can they buy," never "will they buy." A perfectly-scored account — right size, right industry, right funding stage — can sit dead in a CRM for two years because the champion left and nobody replaced them; firmographic fit has no opinion on urgency, budget cycles, or internal politics. The more common failure is a stale ICP definition: a company raises average deal size, target company profile shifts upmarket, and nobody updates the scoring thresholds for six quarters, so reps keep getting routed enterprise-scored leads that are actually starving for budget. Firmographic data also decays fast — headcount, funding stage, and revenue change constantly, and a scoring model refreshed quarterly instead of continuously is already routing leads on six-month-old facts by the time a rep dials.