Firmographic data is information that describes a company instead of a person. Typical examples are industry, number of employees, annual revenue, headquarters location, ownership type, years in business, funding stage and hiring activity. B2B teams use these fields to sort accounts into groups, decide who fits their ideal customer profile and choose who to contact first. Below you get the full list of examples, what each one tells you, which ones to trust for hard filters and how to combine them with buying signals.
TL;DR
- Firmographics are the B2B counterpart of consumer demographics: they describe organizations and how they operate, not individual buyers.
- The core fields are industry, company size, revenue, location, ownership, age and structure. The dynamic fields are funding, hiring, layoffs and leadership changes.
- Stable, observable fields (industry, headcount, location) suit hard filters. Estimated or fast-changing fields (revenue, growth stage) work better as scoring inputs.
- Firmographics tell you who could buy. A buying signal tells you who is looking now. You need both.
Table of Contents
- What firmographic data is, in one minute
- Firmographic data examples: the core fields
- Dynamic firmographic examples that change quickly
- A worked example: one company, many fields
- Which firmographic fields are safe for hard filters?
- How teams actually use firmographic data
- Where firmographics stop and buying intent starts
- Turning firmographic fit into conversations
- Keeping your firmographic data accurate
- FAQ
- Sources
What firmographic data is, in one minute
Think of a firmographic record as a company's profile card. It answers: what does this business do, how big is it, where is it and how is it organized? Contentful's guide describes it as descriptive attributes of businesses and organizations, and calls it the B2B equivalent of consumer demographic data.
The contrast with other data types is simple:
| Data type | Describes | Example fields |
|---|---|---|
| Firmographic | The organization | Industry, size, revenue, location |
| Demographic | The individual | Age, job title, income, preferences |
| Technographic | The tools a company uses | CRM, cloud vendor, e-commerce platform |
| Intent / buying signal | What the company is doing right now | Searching for a vendor, posting a job, requesting quotes |
HubSpot notes that job roles and buying power can sit in both the firmographic and demographic camps, while technology is a separate, complementary dataset. In practice the lines blur a little, and that is fine. What matters is that you know which question each field answers.
Firmographic data examples: the core fields
These are the attributes that appear in almost every B2B database, spreadsheet and CRM. Together they form the backbone of any segmentation.
1. Industry
The sector a company operates in: software, logistics, dental clinics, commercial roofing. It is usually the first filter a team applies, because pain points, buying cycles and vocabulary differ sharply by sector.
In the US, industry is most often coded with NAICS. The North American Industry Classification System divides the economy into 20 sectors and is shared by the US, Canada and Mexico, which makes it a solid common language for lists. Using a code rather than a free-text label means "IT consulting" and "technology services" do not end up as two different segments.
2. Company size (employee count)
Headcount separates startups, small and medium-sized businesses and large enterprises. SurveyMonkey's guide explains that employee count helps you target more precisely, since a 15-person agency and a 5,000-person group buy in very different ways.
Common bands are 1 to 10, 11 to 50, 51 to 200, 201 to 1,000 and 1,000+. Pick the bands that match how your own customers actually buy, not a generic template.
3. Annual revenue
Revenue is a proxy for budget. A company with $2 million in revenue is unlikely to sign a six-figure contract, and one with $500 million may ignore a $50 tool entirely. For private companies revenue is usually an estimate, which matters for how you use it (more on that below).
4. Headquarters and office locations
Country, state, city and sometimes the full list of satellite offices. HubSpot points out that location can include headquarters and satellite offices, and that size can mean physical scale as well as staff. Location drives time zones, regulation (for example GDPR for EU contacts), language and territory assignment.
5. Ownership and legal structure
Public, private, venture-backed, family-owned, subsidiary, nonprofit, government. An agency selling to a subsidiary may actually need approval from a parent company in another country. A nonprofit has different goals and buying rules than a profit-seeking business.
6. Years in business (company age)
Founded date is one of the most stable fields. It separates young companies still building their stack from established ones with entrenched vendors. LogRocket lists founded date next to industry, size, amount raised, headquarters, revenue and cloud vendor as standard firmographic examples.
7. Organizational structure
Single site or multi-site, centralized or decentralized, number of departments, franchise or independent. Structure offers clues about who decides and how long approval will take. A franchise owner often decides alone. A multi-division corporation usually does not.
8. Market share and market size
Where a company stands among competitors and how large its addressable market is. Contentful's examples include market size, profit potential, growth trends and competitors alongside the basics.
9. Customer base and products
Who the company sells to and what it sells. If you offer onboarding software, a prospect whose own customers are other businesses has different needs from one serving consumers.
Dynamic firmographic examples that change quickly
Some attributes move month to month. They are the most useful for timing, and the most likely to be stale in a database that is not refreshed.
10. Funding stage and amount
Seed, Series A, Series B and beyond. A company that just closed a round usually has budget to spend and pressure to grow. Founded date is stable, but growth-stage labels change fast and need continuous monitoring, so always check when the data was last updated.
11. Hiring activity
Open roles reveal where a company is investing. A firm hiring its first head of sales may need CRM tools, outbound help or lead sources. A firm hiring ten engineers may be scaling product, not marketing.
12. Layoffs and contraction
The opposite signal. A company cutting staff may be shopping for cost savings rather than growth tools, which changes your pitch entirely.
13. Leadership changes
A new CMO, CRO or head of operations often reviews vendors in the first months. It is a classic window for outreach.
14. Business lifecycle stage
Startup, growth, maturity or turnaround. This blends several fields (age, funding, hiring trend) into one story about where the company is heading.
15. Operating status
Active, acquired, dormant or closed. It sounds basic, but sending campaigns to companies that no longer exist is one of the most common causes of wasted spend and bounced emails.
A worked example: one company, many fields
Here is a made-up record, so you can see how the fields read together. It is an illustration, not a real business.
| Field | Value |
|---|---|
| Industry | Commercial HVAC services (NAICS-coded) |
| Employees | 85 |
| Revenue | Estimated $14 million |
| Headquarters | Columbus, Ohio, with 2 satellite offices |
| Ownership | Private, family-owned |
| Founded | 2004 |
| Funding | None |
| Hiring | 6 open roles, including a sales manager |
| Technology | Field-service software, cloud accounting |
Seen as a list this is just facts. Seen as a profile it tells a story: an established, mid-sized, owner-run business that is hiring in sales. If you sell lead generation, appointment-setting or CRM tools to service companies, this is a strong fit. If you sell enterprise analytics, it is not.
Which firmographic fields are safe for hard filters?
Not every field deserves the same trust. A practical rule: use observable fields as filters and estimated fields as scores.
- Safe for hard filters: industry, employee count, country or state, ownership type, operating status. They are checkable and change slowly.
- Better as scoring inputs: estimated revenue, funding stage, growth rate. They are modeled, dated or volatile. Excluding every company below a revenue guess can remove good prospects unfairly.
- Watch the local picture: a global employee count may not reflect the staff in the market you sell into. If you sell to the US team of a multinational, local headcount can matter more than the worldwide total.
Always record where a value came from and when. A field with no source and no date is a guess dressed as a fact.
How teams actually use firmographic data
Define the ideal customer profile
Look at your best ten customers and note the shared industry, size band, region and structure. That pattern is your ideal customer profile (ICP). The more fields you can quantify, the sharper it gets.
Segment accounts
HubSpot says the primary goal is to sort potential customers into meaningful categories so teams can act on pre-sorted groups instead of cleaning data first. A simple version: three segments by size (small, mid-market, enterprise), each with its own message and offer.
Size the market and plan territories
Count how many companies match your ICP by state or region. If 4,000 firms match and you can contact 200 a month, you know your runway. The same counts split territories fairly between reps.
Score and prioritize leads
Assign points: +20 for target industry, +15 for the right size band, +10 for a recent funding round, +10 for open sales roles. Firmographic fit sets the baseline, and signals add urgency.
Personalize outreach
A message that references a company's sector, size or recent hiring reads as written for them. "Teams of 50 to 200 in logistics usually struggle with X" beats a generic pitch every time.
Where firmographics stop and buying intent starts
Firmographics answer "could this company buy from us?" They do not answer "is it looking to buy right now?" Two companies can have identical industry, size and revenue, and only one of them may be actively searching for a vendor this month. Treating them the same wastes your best hours on the one that is not ready.
That is why strong prospecting layers a live signal on top of fit. The signal can be a company searching for a solution, posting a job that implies a need or requesting proposals. We explain how this works in our guide to what buy-intent leads are.
Our perspective
We built Buy Intent Leads on a simple observation: a perfect firmographic match who is not in the market is still a cold lead. Filters on industry and size shrink a list. They do not make anyone answer.
So every lead we deliver is hand-filtered to include only contacts showing active interest, meaning companies that are actively searching or hiring. We leave out profiles that are not. Each contact goes through three checks for email deliverability, and each comes with its source and opt-out details, so you can work within GDPR expectations.
Our advice to any sales team: keep your firmographic ICP, it is the right starting frame. Then ask of every list, where is the evidence that these people want something now? If the answer is "none", you have a database, not leads.
Polat
Turning firmographic fit into conversations
If you already know your ICP and want contacts who match it and show buying signals, you can skip the weeks of list building. Our leads arrive live in chat in under 60 seconds, and you download them as an Excel file ready for your CRM, with the source and opt-out information included.
Credit packs are one-off purchases, and each credit redeems for one triple-verified, buy-intent lead:
| Pack | Price |
|---|---|
| RADAR 50 | 50 € one-off |
| 150 credits | 150 € one-off |
| 1000 credits | 499 € one-off |
Get your first verified leads in chat and judge the quality on real contacts.
Want to compare options first? Our guides on how much B2B leads cost and how to buy B2B leads safely walk through the decision, and the difference between verified leads and scraped lists explains why source and verification matter.
Keeping your firmographic data accurate
Company data decays. People change jobs, firms get acquired and funding stages move on. A few habits keep your records usable:
- Store a source and a date next to every field you cannot verify at a glance.
- Refresh dynamic fields (funding, hiring, status) far more often than stable ones (industry, founded date).
- Standardize values with codes and fixed bands instead of free text.
- Verify emails before sending. Good firmographics attached to a dead address still produce a bounce.
- Deduplicate by company domain so one account is not contacted by three reps.
FAQ
What is firmographic data in simple terms?
It is facts about a company, such as its industry, size, revenue, location and ownership. It plays the role for businesses that demographics play for consumers. Marketers and sales teams use it to group companies and decide which ones to approach.
What is the difference between firmographic and demographic data?
Firmographic data describes an organization. Demographic data describes a person: age, income, job title, preferences. In B2B you usually need both, since you sell to a person inside a company.
What is the difference between firmographic and technographic data?
Technographic data is a narrower slice that covers the software and tools a company uses, such as its CRM or cloud provider. Firmographic data covers who the company is and how it is built. Many teams use technographics as an add-on layer to their firmographic segments.
Which firmographic fields matter most?
Start with industry, employee count and location, because they are easy to verify and change slowly. Add revenue, funding and hiring status as scoring signals. The right mix depends on what you sell and who buys it today.
Is firmographic data enough to find buyers?
No. It shows fit, not timing. Pair it with a live buying signal, such as a company actively searching or hiring, to focus on prospects who are ready to talk.
Sources
- How to Get the Most Out of Firmographic Data, HubSpot
- The ultimate guide to firmographic data, Contentful
- 12 Essential Firmographic Variables, SurveyMonkey
- An overview of firmographic data, LogRocket
- North American Industry Classification System, United States, 2022, US Census Bureau