Firmographic data says who a company is: its industry, its size, where it is based and who owns it. Technographic data says what it runs: the analytics, advertising, commerce and CRM tools on its website. A marketing team needs both to draw a segment, and the two behave differently enough that a list built without regard to the difference looks more exact than it is. This guide compares them field by field, names a documented source of each kind, and builds one segment that uses both.
Who a company is, and what it runs
Firmographics describe an organisation. The fields are the ones a registry, an annual report or a credit file would hold: legal name, industry, number of employees, headquarters, parent company, year founded. They change slowly, and most of them are stated, by the company or by an authority.
Technographics describe a website, and through it the company. The fields are observations: a tool was seen on this domain on this day. Nobody states them, and they can change in an afternoon.
| Firmographic data | Technographic data | |
|---|---|---|
| Question it answers | Who is this company? | What does this company run? |
| Typical fields | Industry, employees, location, ownership, age | Technologies by category, with the dates first and last seen |
| Unit described | A legal entity or a group | A website |
| Where it comes from | Registries, filings and company statements | Detection on websites and in DNS records |
| How it changes | Slowly, often once a year | On any day a tag is added or removed |
| Stated or observed | Mostly stated | Observed |
| Used for | Defining a market, territories, size tiers | Fit by stack, displacement, partner targeting |
Where each kind comes from
Firmographic data starts with registries and filings. Dun & Bradstreet is a documented example. Its D-U-N-S Number is described as a unique nine-digit identifier used exclusively for businesses. Its explanation of the number says other businesses can use it to reach firmographic data such as a company's legal name, entity type, address and branch or subsidiary information, and that the number links to a business credit file. Its page on its data says the data is sourced from public registries, websites and partners, and counts corporate family tree relationships and trade payment experiences among its holdings.
Technographic data comes from reading websites. BuiltWith is a documented example. Its website states that it covers more than 127,000 internet technologies, among them analytics, advertising, hosting and content management systems, and its FAQ says it finds them by indexing the internet and tracking the signals a website gives off. Its Domain API returns the technology information of a website, and its Lists API returns the websites that use a given technology.
The two kinds of evidence barely overlap, which is the practical point. A registry records that a company exists, its legal name and its legal form, and holds nothing about its analytics tags. A website shows its tags to anyone who reads it and is silent on turnover. Large providers combine several sources, so ask of any file what each field is built from.
What Fokals delivers of each
Fokals delivers both kinds on one company index, collected from first-party company sources and public records and processed in-house. The table below lists the datasets by kind, and each is specified in the data dictionary.
| Attribute | Kind | In Fokals data |
|---|---|---|
| Identity | Firmographic | One stable company ID. A listed company carries its ticker, MIC, ISIN, LEI and share-class FIGI, and its SEC CIK where it has one |
| Ownership | Firmographic | A brand or subsidiary carries the identifiers of its listed parent |
| Size | Firmographic | Employee Headcount: stated headcount over time, each figure with the date it refers to |
| Industry | Firmographic | An industry label from a set of 21, used as the industry dimension of Market Series |
| Markets served | Between the two | Website Profile: the markets, languages and currencies of each website |
| Website traffic | Between the two | Web Traffic: the monthly traffic tier of each website |
| Technologies | Technographic | Technology Stack: every technology a company runs, with its category and its first-seen and last-seen dates |
| Changes to the stack | Technographic | Technology Changes: a dated event for every adoption, removal and platform migration |
The rows in the middle deserve a note. The markets, languages and currencies a website declares, and its traffic tier, are observed like technographics and describe the business like firmographics. A site that adds a currency or a country version has shown a market its site now addresses, which a registry does not record.
How fast each changes, and why dates matter
Firmographic values move slowly, which tempts teams to store them without a date. A record of Employee Headcount is a stated figure with the date it refers to, so the series reads as the company's own statements over time. Store the date beside the value and segment on the latest record.
Technographic values can move on any day, so each needs two dates. In Technology Stack the first-seen and last-seen dates bound the period over which a tool was observed, and Technology Changes records each adoption and removal as a dated event. A first observation sets a baseline and is never counted as a change, so an adoption in the record is one that happened under observation. Read the first-seen date as the first observation of a tool, and go to Technology Changes when the question is when a tool was adopted.
Both kinds are safe to use point-in-time. Every record carries the time it was observed, and daily and weekly datasets are written once, after the period closes, and are never revised, so a segment rebuilt for any past day returns what was known on that day.
Building a segment on both
Take a segment as a marketing team might write it on a whiteboard: companies with 201 to 1,000 employees that run Salesforce. Size is firmographic and comes from Employee Headcount, the tool is technographic and comes from Technology Stack, and the company ID joins them.
with size as (
select company_id, employees, as_of,
row_number() over (
partition by company_id order by as_of desc
) as rn
from company_headcounts
)
select t.company_id, t.domain, s.employees, s.as_of, t.first_seen_at
from company_technologies t
join size s
on s.company_id = t.company_id
and s.rn = 1
where t.technology = 'salesforce'
and t.missing_since is null
and s.employees between 201 and 1000;Four things decide whether the result means what the whiteboard said.
- Headcount is a stated figure. The inner join returns the companies whose stated headcount puts them in the band, so report the segment beside the number of accounts in your list that carry a figure.
- Headcount is a series over time. The query ranks each company's records by date and keeps the latest, so the segment rests on the most recent stated figure. Keep the date in the output, so a reader sees how current each figure is.
- A company with two websites returns two rows, one for each domain. Count distinct company IDs to size the segment, and keep the domains when a campaign is planned for each brand.
- A brand or subsidiary carries the identifiers of its listed parent. Decide whether the unit you market to is the brand's website or the group before you count.
Illustrative: Acme Robotics appears once, with a stated headcount of 640 and Salesforce present in its Technology Stack. It belongs in the segment, and each of the two facts carries its date, so a reviewer can see how current the row is.
Which to use for what
| Task | Start with | Then add |
|---|---|---|
| Defining a market | Firmographics: industry, size, country | Technology, to count the accounts that can use you |
| Describing your ideal customer | Firmographics of the accounts you won | The tools that separate won from lost |
| Planning territories | Firmographics: location and size | Hiring or technology only as a tie-break |
| Displacing a competitor | Technographics: who runs the competing tool | Size, to order the list |
| Tailoring a campaign | Technographics: the stack decides the message | Industry, to choose the proof |
The order matters. Firmographic rules make the first, large cut of a market, and technographic rules narrow what is left to the accounts that can use what you sell. Run them the other way round and you size a market on a filter that sees only web-visible tools. The guides to defining an ideal customer profile from data and sizing a market with technographic counts work through both steps.
How to read each kind
Firmographics describe the organisation, so they set the boundary of a market. What a company runs is the technographic question, and when it is likely to buy is a question of timing: see technographic data vs intent data.
A detection shows presence on the website. The marketing stack dataset is detected from page content, scripts, network requests, response headers and DNS records, so it describes the customer-facing stack: advertising, analytics, commerce, CRM and marketing tools. Fokals adds the tools named in each company's job postings, which reach the systems behind the website, on the same company ID.
Both kinds are company-level data. A segment built on them is a list of companies and websites, keyed on a company ID and a domain, ready to join to the accounts in your CRM.
How Fokals delivers it
Employee Headcount and Web Traffic are part of the announcements and scale dataset, refreshed daily to every three days. Technology Stack, Technology Changes and Website Profile are part of the marketing stack dataset, refreshed daily to weekly. Both are delivered direct, by REST API and as bulk files in JSON, JSON Lines or CSV, which you load into the system where you build segments.
Frequently asked questions
What is the difference between firmographic and technographic data?
Firmographic data describes a company as an organisation: its industry, number of employees, location, ownership and age. Technographic data describes the technology it runs, such as the analytics, commerce and CRM tools detected on its website. Firmographics are mostly stated by the company or a registry and change slowly. Technographics are observed and can change on any day. Segmentation usually starts with the first and narrows with the second.
What are examples of firmographic and technographic data?
Firmographic examples are an industry classification, an employee count or size band, a headquarters country, a parent company and a year of founding. Technographic examples are the content management system a website is built on, its analytics and advertising tags, its commerce platform and its email provider, each with the dates it was first and last seen. Revenue is firmographic too, though only companies that publish accounts state it.
Which should come first in segmentation, firmographic or technographic data?
Firmographic data, in most cases. Industry, size and country define the market and remove the companies you could never sell to. Technographic data then finds the accounts inside that market that run a tool you work with or one you replace. The exception is a product tied to one technology, where the stack is the market and firmographics only order the list.
Where do firmographic and technographic data come from?
Firmographic data comes from company registries, regulatory filings, annual reports, credit files and what companies say about themselves. Technographic data comes from detection on websites: page content, scripts, network requests, response headers and DNS records, matched against a catalogue of known technologies. The sources differ, so ask of any file how each field is produced.
What firmographic and technographic data does Fokals deliver?
Fokals delivers both kinds on one company ID. The firmographic side is identity and scale: ticker, MIC, ISIN, LEI and FIGI on every listed company, the listed parent of a brand or subsidiary, stated headcount over time, an industry label and the monthly traffic tier of each website. The technographic side is Technology Stack, with first-seen and last-seen dates for every technology, and Technology Changes, a dated event for every adoption, removal and platform migration. Both are delivered by REST API and as bulk files.
The queries and code on this page are examples to adapt. Test them in your own environment before you rely on them.
What this page says about the products it names was checked against their public documentation on 4 October 2026. Product and company names are trademarks of their owners. Fokals is not affiliated with them or endorsed by them.