---
title: "Firmographic data"
description: "Firmographic data from the web: industry, headcount, HQ, locations, founding year and funding from company sites, Companies House, SEC EDGAR, Crunchbase."
canonical: https://www.zenrows.com/use-cases/firmographic-data
updated: 2026-10-18
---

# Firmographic data

Firmographic data describes a company the way demographics describe a person: industry, size, revenue band, headquarters, locations, founding year, ownership and funding. Zenrows collects these attributes from company websites, business registries and public directories, returns them as structured JSON, and refreshes them on a schedule so your segments and territories match what each company is today.

## Sample output: one firmographic profile

```json
{
  "domain": "example-foods.co.uk",
  "legal_name": "Example Foods Ltd",
  "registry": { "source": "Companies House", "number": "01234567", "status": "active", "incorporated": "2009-03-17" },
  "sic_codes": ["10890"],
  "industry": "Food manufacturing",
  "headquarters": { "city": "Leeds", "country": "GB" },
  "other_locations": ["Manchester", "Rotterdam"],
  "employees_band": "200-499",
  "employees_source": "company about page",
  "ownership": "private",
  "parent_company": null,
  "funding": { "last_round": "Series B", "year": 2024 },
  "founded": 2009,
  "observed_at": "2026-10-17",
  "sources": [
    "https://find-and-update.company-information.service.gov.uk/company/01234567",
    "https://example-foods.co.uk/about"
  ]
}
```

An illustrative profile that merges a registry record with the company's own about page; each attribute names the source it came from.

## Firmographic data attributes and sources

Firmographics are a handful of attributes, but each one has a best source. Registries are authoritative on legal facts, the company's own site is freshest on locations and size, and directories fill in funding and category.

| Job | Data you collect | Typical sources |
|---|---|---|
| Legal identity | Registered name, company number, status, incorporation date, registered address | Companies House, SEC EDGAR, state business registries, OpenCorporates |
| Industry classification | SIC or NAICS codes, self-described category, product lines | Registry filings, company about and product pages |
| Company size | Employee band, office count, revenue band where filed | About pages, annual accounts, careers pages, LinkedIn company pages |
| Locations and footprint | Headquarters, offices, plants, countries served | Contact, locations and imprint (Impressum) pages |
| Ownership and structure | Public or private, parent company, subsidiaries, ticker | Annual reports, investor relations pages, MarketScreener |
| Funding and growth stage | Last round, year, investors | Crunchbase profiles, company press pages |

## Why firmographic data goes wrong

Bought company databases age between refreshes, and the long tail of small and non-US companies is thin. Building firmographics from the web fixes freshness, but only if you can read hundreds of different site layouts and a few protected sources.

| What breaks | What it looks like | How Zenrows handles it |
|---|---|---|
| One layout per company | Headcount sits in a footer on one site and an about-page sentence on the next | Extract returns structured fields from pages you have never mapped |
| Protected directories | Company profile pages answer with a challenge page from protections such as Cloudflare or PerimeterX | Zenrows' stealth gets through those protections and returns the profile page |
| Registry pages behind forms | The record only appears after a search and a click | Page actions fill the search and click through before the page is returned, or [Browser](/products/browser) runs the full flow |
| Conflicting values | The registry says 2009, the about page says "since 2010" | Keep both values with their source URLs and apply your own precedence rules |
| Ageing records | Offices close and headcount bands change between your quarterly checks | Batch re-collects every profile on a schedule you set |

## How to build firmographic data with Zenrows

1. **Fix the attribute list.** Decide which firmographics drive your segments and territories, and which source wins for each one.
2. **Read the company's own pages.** Fetch the about, contact and imprint pages with automatic structured extraction to get name, locations and size in JSON.
3. **Add the registry record.** Fetch the registry page for the company number, naming the fields with CSS selectors so legal fields arrive with fixed names.
4. **Refresh in bulk.** Submit the full list of profile URLs to Batch each quarter and store `observed_at` with every attribute.

```python Python
# pip install requests
import requests

response = requests.get("https://api.zenrows.com/v1/", params={
    "apikey": "YOUR_ZENROWS_API_KEY",
    "url": "https://example-foods.co.uk/about",
    "mode": "auto",  # Adaptive Stealth Mode
    "extract": "auto",
})
about = response.json()
print(about)  # company name, locations, size statements, contact details
```

```bash cURL
# Example selectors: replace them with the registry page's own
curl -X POST "https://async.api.zenrows.com/v1/jobs" \
  -H "X-API-Key: YOUR_ZENROWS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "type": "regular",
    "status": "closed",
    "zenrows_params": {
      "mode": "auto",
      "css_extractor": "{\"name\":\"h1\",\"status\":\".company-status\",\"incorporated\":\".incorporation-date\",\"sic\":\".sic-code\"}"
    },
    "tasks": [
      { "url": "REGISTRY_PAGE_URL_1", "external_id": "example-foods" },
      { "url": "REGISTRY_PAGE_URL_2", "external_id": "example-tools" }
    ]
  }'
```

```bash CLI
npx -y @zenrows/cli init
# Structured JSON from a company's contact and about pages
zenrows extract https://example-foods.co.uk/contact --autoparse
zenrows extract https://example-foods.co.uk/about --autoparse --out about.json
```

```text Claude Code (MCP)
# Connect once
claude mcp add zenrows -e ZENROWS_API_KEY=YOUR_ZENROWS_API_KEY -- npx -y @zenrows/mcp

# Then ask:
Use Zenrows to read the about, contact and careers pages of example-foods.co.uk and return a firmographic profile as JSON: legal name, industry, headquarters city and country, other office locations, employee band and founding year, with the source URL for each value.
```

## Which Zenrows product fits

| If you need to | Use | Why |
|---|---|---|
| Read attributes from company sites with different layouts | [Extract](/products/extract) | Automatic structured extraction returns the data without per-site selectors |
| Pull fixed fields from a registry or directory template | [Fetch](/products/fetch) | Name the fields with CSS selectors and they come back under your own field names |
| Refresh 100,000 company profiles each quarter | [Batch](/products/batch) | The whole URL list runs as one job, results by webhook |
| Check a few companies by hand or from a script | [CLI](/cli) | One command returns a page's structured data in the terminal |

## What success looks like

| Measure | What good looks like | How to check it |
|---|---|---|
| Attribute fill rate | Industry, size band, HQ country and founding year are present for most companies | Report empty values per attribute after each refresh |
| Source agreement | Registry and website values agree, or the conflict is flagged | Count records where two sources disagree on the same attribute |
| Long-tail coverage | Small and non-US companies have profiles as complete as large US ones | Compare fill rates by country and size band |
| Record age | No attribute is older than your refresh cycle | Alert on `observed_at` past the cycle |
| Segment stability | Accounts move between segments only when the company changed | Review accounts that switched segment and confirm the cause |

## Firmographic data FAQ

### What is firmographic data?

Firmographic data is the set of descriptive attributes of a company: industry, employee count, revenue band, location, legal structure, ownership, founding year and funding stage. B2B teams use it to define an ideal customer profile, segment accounts, assign sales territories and size a market. It is the company-level counterpart of demographic data about people.

### What are examples of firmographic data?

Common examples are "food manufacturing, SIC 10890", "200 to 499 employees", "headquartered in Leeds, offices in Manchester and Rotterdam", "private, founded 2009" and "Series B in 2024". Industry, size and location are the core three; ownership, funding, revenue and growth signals such as new offices are often added.

### What is the difference between firmographic and technographic data?

Firmographics describe what a company is: its industry, size, location and structure. Technographic data describes which technologies it runs, such as its CRM, ecommerce platform or analytics tools. Most account scoring models combine both, since a company can fit your size and industry and still run a stack you cannot integrate with.

### Where does firmographic data come from?

From public business registries such as Companies House, SEC EDGAR and state registries, from company websites, from annual reports and investor relations pages, and from directories such as Crunchbase. Commercial databases compile the same sources. Collecting it yourself gives you the source URL and date for every value.

### Is there a firmographic data API?

Zenrows works as one: send a company URL to the API and get its attributes back as JSON. Point Extract at an about or contact page for name, locations and size, and name the fields with CSS selectors on registry pages such as Companies House so legal data keeps fixed keys. Batch runs a full account list as one job, so a quarterly refresh of 20,000 companies is a single submission.

### How do I use firmographic data for segmentation?

Turn each attribute into a bucket, for example size bands, industry groups and regions, then score accounts on how many buckets match your best customers. Keep the raw values and sources next to the buckets so you can re-bucket later without collecting again. Re-run collection before each planning cycle so territories reflect current headcount and locations.

### How often does firmographic data change?

Legal name, founding year and industry rarely change. Headcount, office locations and funding change often, especially at growing companies. A quarterly refresh suits most segmentation work. If you route inbound leads by size band, refresh headcount and locations monthly.

## Related use cases

- [Technographic data](https://www.zenrows.com/use-cases/technographic-data.md): Which CRM, ecommerce, analytics and chat tools each company runs, detected from its pages and job posts.
- [Lead enrichment](https://www.zenrows.com/use-cases/lead-enrichment.md): A domain in, an account record out: pricing, hiring, product and review signals from the company's own web.
- [Public records API](https://www.zenrows.com/use-cases/public-records-api.md): Permits, violations, licenses and registry filings from city, county and state portals, returned as JSON on demand.
- [Alternative data for investors](https://www.zenrows.com/use-cases/alternative-data.md): Hiring, pricing, app ranks, reviews and store counts per ticker, collected weekly as point-in-time series.
- [Market research web scraping](https://www.zenrows.com/use-cases/market-research-web-scraping.md): Assortments, prices, reviews and forum talk across a whole category, for sizing studies and recurring trackers.

Start free: https://app.zenrows.com/register. Docs: https://docs.zenrows.com