Definition
Firmographic data is the set of company-level attributes used to describe and segment businesses: industry, employee count, revenue, location, ownership type, founding year, and funding stage. It's the B2B equivalent of demographics. Where demographic data describes a person, firmographic data describes the firm, which is where the name comes from.
Each account record in a B2B CRM is a stack of firmographic fields. When those fields are filled and current, you can segment, score, route, and forecast on them. When they're blank or stale, each downstream system inherits the gap.
What fields count as firmographic data?
The core set is small. What varies is how each field gets represented and how quickly it goes wrong.
| Field | Example value | What to watch for |
|---|---|---|
| Industry | For example: a NAICS code or an internal "B2B SaaS" category | Each vendor uses a different taxonomy. Mapping between them is its own project. |
| Employee count | 250-500 | Drifts with each hiring wave and layoff. Ranges beat point estimates. |
| Annual revenue | $10M-$50M | Modeled, for private companies. Can be off by multiples. |
| Location | Austin, TX (HQ) | HQ vs. branch confusion breaks territory assignment. |
| Company type | Private, PE-backed | Changes silently at acquisition. Parent-subsidiary links go stale fastest. |
| Founding year | 2014 | The one field that rarely decays. Enjoy it. |
| Funding stage | Series B | A strong buying signal with a short shelf life. |
Some vendors fold growth signals into firmographics too: headcount growth rate, hiring velocity, recent funding events. Useful, but treat them as a separate freshness tier. A funding round is stale news in a quarter.
Firmographic fields describe companies, but a delivery can also contain personal data. Keep the source, purpose, permitted fields, retention, deletion, and applicable jurisdiction documented for that portion of the file.
Firmographic vs. demographic vs. technographic
The three get mixed up because targeting can use them together. Demographic data describes people: title, seniority, department, personal location. Technographic data describes the tools a company runs: its CRM, cloud provider, marketing automation platform. Firmographic data describes the company itself.
A segment like "VP-level marketing leaders at SaaS companies over 200 employees running HubSpot" uses one demographic filter, two firmographic filters, and one technographic filter. The distinction earns its keep at maintenance time, because the three decay independently. A person changing jobs breaks demographic fields and leaves the firmographics intact. A merger does the reverse.
Where does firmographic data come from?
Nobody types it in by hand at scale. The sources, roughly in order of reliability: government registries and regulatory filings, the company's own website and job postings, professional networks, and commercial data vendors that aggregate everything upstream and resell it. Public company revenue comes from filings and is trustworthy. Private company revenue is modeled from headcount, industry, and comparable firms, so two vendors will confidently give you two different numbers.
This is why single-source firmographics disappoint. One vendor has the right employee count and a wrong industry label, the next has the reverse. Cross-referencing several sources, and having a person review the conflicts, is what separates fields you can filter on from fields you quietly stop trusting. That verification step is most of the work in a firmographic enrichment project.
What do B2B teams use firmographic data for?
Four jobs cover most usage. Segmentation and ICP definition: deciding which companies you sell to, expressed as firmographic filters. Lead scoring: weighting inbound leads by how well their company matches that ICP. Routing and territory planning: assigning accounts to reps by size, region, or industry. And market sizing: counting how many companies fit your filters, which is the entire arithmetic behind a TAM model.
Notice four are only as good as the fields underneath. A lead score built on blank employee counts scores the blanks, and a TAM built on a wrong company count multiplies the error. Measure change against a dated baseline instead of applying a general decay benchmark, then set the review cadence from the changes observed in your own system.
Example
Measure change against a dated baseline instead of applying a general decay benchmark, then set the review cadence from the changes observed in your own system. Their lead scoring model weights both fields, so nearly half of inbound leads score as "unknown" and route to a generic queue. Enriching the missing firmographics from multiple verified sources fills the fields, the scoring model starts working on the whole database, and territory assignments stop depending on which rep noticed the account first. The fix took two days, since firmographic fills run fast once matching is solved.
Common Mistakes
- Segmenting on modeled revenue as if it were reported revenue. Private company revenue estimates are directional. acceptable for tiering, risky for anything contractual or quota-bearing.
- Treating it as a one-time fix. Firmographics decay with hiring, layoffs, moves, and acquisitions. A file enriched six months ago has already drifted.
- Using a single data source. No vendor gets each field right. Cross-reference, and route the conflicts to a human.
- Ignoring taxonomy mismatches. "Software" in one source is "Information Technology" in another and NAICS 5112 in a third. Standardize to one scheme before you build reports on it.
Review checkpoint
Before activation, sample the fields that drive eligibility, routing, and scoring. Record the source, observation date, confidence, and disposition for each reviewed value. A field can be complete yet unsuitable for a decision if its taxonomy or business-entity level does not match the workflow.
Frequently Asked Questions
What is firmographic data?
Firmographic data is the set of company-level attributes used to describe and segment businesses: industry, employee count, revenue, location, ownership type, founding year, and funding stage. It's the B2B equivalent of demographics.
What are examples of firmographic data?
Industry, employee-count band, revenue band, headquarters location, company type, founding year, and funding stage are common examples. Each describes the company rather than a person working there.
What is the difference between firmographic and demographic data?
Demographic data describes individual people: age, job title, seniority, personal location. Firmographic data describes companies. A contact record in a B2B CRM usually carries both, and they decay on different schedules. A person changing jobs breaks the demographic fields, while a merger breaks the firmographic ones.
Is technographic data the same as firmographic data?
No. Technographic data covers the software and infrastructure a company runs, such as its CRM, cloud provider, or marketing automation platform. Firmographics cover what the company is. A targeting segment can combine both kinds of fields.
Where does firmographic data come from?
Government registries and filings, company websites, job postings, professional networks, and commercial data vendors that aggregate those sources. Revenue for private companies may be an estimate modeled from headcount and industry, which is worth noting before you segment on it.
How accurate is firmographic data?
Measure change against a dated baseline instead of applying a general decay benchmark, then set the review cadence from the changes observed in your own system. Employee counts drift with each hiring wave and layoff, revenue estimates for private companies can be off by multiples, and industry labels vary between taxonomies. Cross-referencing multiple sources and refreshing periodically keeps the fields usable.
Related Terms
Related: All Glossary Terms | Enrichment Services | Cleaning Services