What is technographic data?

Written by the Lusha content team. Lusha facts come from our documentation, linked in Sources. The live example was run through the Lusha connector on November 15, 2026.

Technographic data is information about the technology a company uses: its CRM, its marketing tools, its cloud provider, its data warehouse, its security and finance systems. Sales and marketing teams use it to find companies whose tech stack makes them a good fit, and to open a conversation with something true about how the buyer already works.

This page explains what technographic data includes, how it is collected, how far to trust it and what to do with it. It ends with a live example: one search that returned 721 companies, and one account checked tool by tool.

Key takeaways

• Technographic data describes what a company runs. Firmographic data describes what the company is. Intent data and buying signals describe what is changing there.
• It is observed, not declared. Nobody files their tech stack anywhere. The data is put together from websites, job posts and other public traces, so read it as a record and not as a fact.
• “No record” does not mean “does not use”. Tools that run behind a login leave fewer traces than tools on a website.
• The filter is where it earns its keep. One search for “runs this, does not run that” turns a market into a list. In our live run that was 721 companies for one credit.
• It works best next to other data. Tech stack says the account could buy. Fit and timing say whether to call this week.

What technographic data includes

The website layer is often called front end technographics, because anyone can see it. Everything else sits behind the firewall and has to be inferred. Lusha documentation says its Technology filter covers both.

Technographic, firmographic and intent data: the difference

Three kinds of company data. Technographic data sits between who the company is and what is changing there.

How technographic data is collected

• Website scans. Scripts, tags and page code show which analytics, chat, ad and content tools a site loads.
• Public technical records. Domain and mail records point to email providers, hosting and some security tools.
• Job posts. A posting that asks for five years with a named data warehouse says the company runs it.
• What companies publish. Case studies, integration directories, partner pages and engineering blogs name tools directly.
• Surveys and partner data. Some providers add responses from buyers or data shared by vendors.

Each method sees a different part of the stack. Website scans are strong on the website layer and blind to finance and HR systems. Job posts reach behind the firewall but only when the company is hiring for that tool. Good technographic data combines several methods. Lusha documentation does not state which methods sit behind its technology data.

What sales and marketing teams do with technographic data

1. Sell a complement. If your product integrates with a platform, companies that run the platform are your market. Run it: build a list of companies using a specific tech stack.
2. Sell a replacement. Companies that run a competing tool already have the budget line and the problem.
3. Find the gap. Companies that run the platform but have no record of the category you sell are the cleanest list of all.
4. Sharpen the ideal customer profile. Look at what your best customers run. Tools that show up again and again belong in your targeting next to industry and size.
5. Write the first line. “You run X, and teams on X usually hit this problem” beats a line about company size.
6. Pick accounts for account based marketing. Group target accounts by stack so each group gets a message about the tools it runs.

How accurate is technographic data?

It depends on the layer and on how old the record is.

• Website tools are the easiest to trust, because they can be seen directly and checked again at any time.
• Tools behind the firewall are inferred. A record means a trace was found. No record means no trace was found, which is not the same as the company not using it.
• Records age. Companies switch tools, and a trace from a job post two years ago can outlive the contract.
• Large companies run more than one of everything. A record of two CRMs is often true: one for each business unit.

The working rule: use technographic data to decide who goes on the list, and confirm the stack in the first conversation before you build a proposal on it. For how Lusha measures and reports its contact data, see the data accuracy FAQ.

How to identify the technologies a company uses

1. Look at the website. A browser extension or the page source shows the website layer in a minute.
2. Read the job posts. Engineering, data and operations roles name the tools the team runs.
3. Check what the company says. Its integrations page, case studies and engineering blog name vendors.
4. Use a data provider. For one account the first three steps are enough. For a market you need a filter that runs across every company at once.

A live example: one search, 721 companies, one account checked

We ran two things through the Lusha connector in Claude.

The search. We asked for US software companies in the 201 to 500 employee band that have a Salesforce record and no HubSpot record. Lusha returned 721 companies. The first page of ten used one credit, with nothing revealed.

The check. We took one company from that list, checked it for six more tools one at a time, and read one more from its company profile.

Company confirmed live via Lusha connector, November 15, 2026. Account: R., a US data software company. The company name is masked. “On record” means Lusha returned the company for that technology. “No record” means it did not, which is not proof the company does not use the tool.

What the run showed:

• One search sized the market. 721 companies matched “Salesforce, no HubSpot” in one segment. That number is the start of a territory plan.
• The check reads like a brief. Salesforce with Marketo, Snowflake and Okta describes an enterprise style revenue and data stack. A seller of a Salesforce integration has an opening. A seller of support software has a question to ask, because no support tool came back.
• “No record” stayed a question. Workday and Zendesk did not come back. That tells the rep what to ask on the call, not what to assume.
• Check names before you search. One vendor can appear as many separate technologies. A lookup for Salesforce returned dozens of entries, from Sales Cloud to CPQ, so pick the ones you mean.
• The cost was visible. Each check that found a record used one credit. The checks that found nothing were not charged.

How Lusha handles technographic data

• A Technology filter in search. In Lusha Search you filter contacts or companies by the technologies they run. You can include or exclude each technology, and choose whether a company must match any of them or all of them. The documentation lists the coverage.
• The same filter in the API and in Claude or ChatGPT. The prospecting API filters companies by technologies, and the Lusha MCP brings that search into an AI assistant, which is how the live example above was run.
• Next to fit and timing. Technology is one filter among industry, size, location, funding and buying signals, so one search can ask for the stack, the segment and a recent signal together.
• From list to people. Once the companies are on the list, you find the buying group and reveal contact details for the people you choose.

To run a stack question on one account or a whole segment, use the Tech Stack Snapshot Skill.

How to use technographic data in five steps

1. List the tools that matter to your sale. Three groups: tools you integrate with, tools you replace, and tools that signal the buyer is ready.
2. Check your best customers. See which of those tools your closed won accounts have on record. Keep the ones that repeat.
3. Build the list. Search for companies that run the platform and lack the category you sell, inside your segment.
4. Add timing. Sort the list by buying signals so the accounts that are hiring or growing come first.
5. Confirm on the call. Ask what they run before you pitch against it, and correct the record in your CRM.

FAQ

What is technographic data?

Technographic data is information about the technology a company uses, such as its CRM, marketing automation, cloud provider, data warehouse and security tools. Sales and marketing teams use it to target companies by tech stack.

What is an example of technographic data?

“This company runs Salesforce, Marketo and Snowflake, and has no record of a support platform” is technographic data. It tells a seller what the buyer already works with and where there may be a gap.

How is technographic data collected?

From website scans, public technical records, job posts, what companies publish about their own tools, and surveys or partner data. Each method sees a different part of the stack, so providers combine several.

How accurate is technographic data?

Website tools are the easiest to trust because they can be seen directly. Tools behind the firewall are inferred from traces, and records age as companies switch tools. Treat a record as a strong lead and confirm it in conversation.

What is the difference between technographic and firmographic data?

Firmographic data describes the company: industry, size, revenue, location. Technographic data describes the technology the company runs. Teams use both to define an ideal customer profile.

How do I find companies that use a specific technology?

Use a technology filter in a B2B data platform. In Lusha you include the technology, exclude any you do not want, add industry, size and country, and get the matching companies back. The same search runs in Claude and ChatGPT through the Lusha MCP.

Related: What is a B2B data layer? and how Lusha scores and ranks leads.

Sources

All pages accessed November 15, 2026.

• Lusha docs: Technology filter (Technographics)
• Lusha docs: Filters breakdown
• Lusha docs: Data Catalog