Firmographic vs technographic vs intent data

Firmographic, technographic and intent data are the three building blocks of most B2B go-to-market data stacks. They are often sold together and described in overlapping terms, which makes it hard to know which one you need. In short: firmographics describe who a company is, technographics describe what it uses and intent data suggests what it is researching now.

Quick definitions

Type	Answers	Typical refresh	Main use
Firmographic	Who is this company?	Monthly to quarterly	Segmentation, targeting, enrichment
Technographic	What technology does it use?	Weekly to monthly	Competitive displacement, fit scoring
Intent	What is it researching now?	Daily to weekly	Timing and prioritisation

Firmographic data

What it contains

Firmographic data describes the stable characteristics of a business: legal name, trading names, website domain, industry codes (such as NAICS, NACE or SIC), employee count or band, revenue band, headquarters and site addresses, founding year, legal form and ownership status. Richer products add corporate hierarchy, growth indicators and registration numbers.

Where it comes from

Common sources are official company registries, financial filings, company websites, job postings, partner data and contributory networks. Many providers combine several sources and resolve them into one record per company.

What it is good for

• Defining your ideal customer profile and total addressable market.
• Segmenting and routing accounts by size, region and industry.
• Enriching inbound leads and CRM records so forms can stay short.
• Territory planning for sales teams.

Limits

Revenue and employee figures for private companies are often estimates or bands. Industry codes can be assigned inconsistently, especially for diversified companies. Coverage of small businesses varies a lot by country. Browse firmographic data to compare coverage by country.

Technographic data

What it contains

Technographic data lists the software, hardware and cloud services a company uses, typically with a first-seen and last-seen date and sometimes a confidence score or estimated spend. Examples include the e-commerce platform, analytics tools, CRM, hosting provider or programming frameworks.

Where it comes from

• Website scanning: detecting scripts, tags and headers on public websites.
• DNS and network records: mail providers, content delivery networks and verification records.
• Job postings: skills and tools mentioned in job descriptions.
• Public documents and case studies.
• Surveys and partner data for back-office systems that cannot be seen from outside.

What it is good for

• Finding customers of a competitor for displacement campaigns.
• Scoring fit, for example targeting only companies that run a platform you integrate with.
• Sizing the install base of a technology in a market.
• Personalising messaging around a prospect's stack.

Limits

Website scanning sees front-end tools well but internal systems poorly. A detected tag may be a leftover from a cancelled subscription, so last-seen dates matter. Ask how each technology was detected. See technographic data for typical schemas.

Intent data

What it contains

Intent data signals that an organisation is actively researching a topic, such as "data warehouse migration" or "fleet telematics". It usually comes as company, topic, a score or surge flag, and a time window.

First-party and third-party intent

• First-party intent comes from your own channels: website visits, content downloads, product usage and email engagement. You own it and it is specific to your offer.
• Third-party intent is collected across many publishers, review sites or networks and attributed to companies, often by matching IP addresses or business identities. It shows research activity before a company reaches your site.

What it is good for

• Prioritising which accounts sales should contact this week.
• Timing campaigns to companies showing a surge in relevant topics.
• Spotting competitive research or churn risk among existing customers.

Limits

Intent is a probabilistic signal, not a statement of purchase plans. Attribution of anonymous activity to companies is imperfect, especially with remote work, and topic taxonomies differ between providers. Privacy rules also shape how intent data can be collected and used in each market. Treat it as a prioritisation input, and test it against your own pipeline history. Compare offers under B2B intent data.

How they work together: a worked example

A company selling a payments integration for online stores wants to plan a quarter of outbound work:

1. Firmographics define the market: online retailers in the UK, Germany and the Netherlands with 20 to 500 employees.
2. Technographics narrow it to stores running the two e-commerce platforms the integration supports, and flag those using a competing payments tool.
3. Intent ranks the remaining list, moving accounts researching "checkout conversion" or "payment provider comparison" to the top for the next two weeks.
4. Contact data then supplies the right people at each account, such as heads of e-commerce and finance leads.

Each layer answers a different question. Removing any one of them makes the list either too broad, poorly fitted or badly timed.

Choosing and buying

• Start with firmographics. Without clean company records and identifiers, the other layers are hard to join.
• Check identifiers. Domains and registration numbers make joining datasets far easier than company names.
• Test on your own accounts. Send a list of customers and lost deals; good technographic and intent data should separate them better than chance.
• Ask about refresh and decay. Firmographics age slowly, technographics faster and intent within days.
• Clarify the licence. Using data to score accounts internally is different from showing it in a product or using it for outreach.

You can compare providers for all three types by searching DataStoa, or post a data request describing your segments and the systems you need the data in.

Frequently asked questions

Which should I buy first?

Usually firmographic data, because it defines your market and provides the identifiers that technographic and intent data join to. Add technographics if product fit depends on technology, and intent when you need help with timing.

Is intent data accurate?

It is a signal, not a fact. Accuracy depends on the sources, how activity is attributed to companies and the topic taxonomy. Test it against your own historical pipeline before relying on it.

Can technographic data see internal software?

Only partly. Scanning finds website and network technologies reliably, while internal systems are inferred from job postings, documents or surveys. Ask providers how each detection was made and how recent it is.

Do these data types include personal data?

Firmographic and technographic data are mostly about companies. Intent data and any contact layer can involve personal data depending on how they are collected, so check the provider's legal basis and the rules in your target markets.