What is intent data? Definition, sources, and how it differs from buying signals

“Intent data” and “buying signals” are often used as if they meant the same thing. They are in fact two different things, which are not sold at the same price, do not serve the same teams and do not produce the same kind of message. Mixing them up leads to paying for data you don’t know how to use.

What is intent data?

Intent data measures a company’s interest in a topic. It is built from aggregated digital traces: articles read, searches made, content downloaded, pages visited. It comes in two forms:

• First-party: what happens on your side. Visits to your website (identified at company level through the IP address), opens of your emails, downloads of your white papers.
• Third-party: what happens elsewhere. Providers aggregate content consumption across networks of websites and media, then report that a company is reading “more than usual” about a given topic.

The output is a score or an alert at account level: “Company X shows growing interest in cybersecurity”. You don’t know who in the company is reading about the topic, or why.

What is a buying signal, and how is it different?

A buying signal is a dated, visible fact, tied to a person or a company, that shows a need is starting to appear. A finance director commenting on a post about mandatory e-invoicing. A manufacturer hiring a buyer to review its subcontractor panel. A new sales director starting in the role.

The difference comes down to three points:

1. Level: intent data is about an account; a buying signal is often about an identified person.
2. Visibility: intent data is invisible to the prospect (they don’t know their reading was measured); a buying signal is public (they posted it themselves, or their company announced it).
3. Use: intent data helps you decide which accounts to prioritise; a buying signal gives you a reason to write now, and a topic for the first sentence.

For a full list of signals, see our 25 examples of B2B buying signals. And to find out where to look for B2B buying intent when your target rarely posts on LinkedIn, see the other possible sources.

Intent data vs buying signals: the comparison in one table

Criterion	Intent data	Buying signal
What it tells you	“This account is interested in this topic”	“This is happening, now, for this person or company”
Level	Company	Person or company
Source	Website visits, content networks, searches	Posts, reactions, job postings, press, appointments
Visible to the prospect	No	Yes, they or their company made it public
Usable in a message	No, it risks making people uneasy	Yes, as a starting point
Team that uses it	Marketing, ABM, structured sales teams	Salespeople, founders, small teams
Price (as of September 2026)	Often on quote; for example Leadfeeder €369/month (Activate, intent filter) to €2,089/month, Common Room from $2,500/month	Tools from €89 to €300/month based on our market survey

Prices are those shown publicly in September 2026 and change quickly. We go through the tools in each family in our comparison of buying signal and intent data software.

Where do firmographics fit in?

Firmographics describe a company: industry, size, revenue, location. They answer the question “is this a company for me?”. They say nothing about timing.

The three layers work together:

1. Firmographics filter: you only talk to companies that match your target.
2. Intent data prioritises, when you have it: among those companies, some are interested in the topic right now.
3. The buying signal triggers: a specific person, in one of those companies, has just done or said something that makes your message relevant today.

Prospecting on firmographics alone means writing to thousands of companies that have no project under way. That is often what lies behind a low reply rate, and behind the feeling that “prospecting doesn’t work any more”.

Why is intent data hard to turn into a message?

Because you can’t say it. Imagine receiving: “I noticed your company has been reading a lot of content about payroll software.” You immediately wonder how the sender knows, and you don’t reply.

So intent data forces you to write a generic message on the topic, which amounts to a cold message sent to a slightly warmer account. A buying signal, on the other hand, gives you a fact the prospect knows and has made public. You can pick up on it without quoting it word for word.

Illustrative example

Available data: a high intent score on “payroll software” for an SME with 150 employees. At the same time, its HR director posts an ad for a payroll administrator, the third this year.

Opener that falls flat (built on intent data): “Hi, your company seems to be interested in payroll solutions. Our software helps SMEs save time. Could we have a chat?”

Opener that gets a reply (built on the signal): “Three payroll hires in a year is often a sign the job has become too much for one person. What’s weighing on you most at the moment: the number of payslips or the rule changes?”

The first talks about the seller. The second talks about a problem the HR director is living with, uses a fact she recognises and ends with a simple question. That question opens the conversation, and then the meeting.

Which should you choose for your situation?

The answer depends less on the quality of the data than on what your team can do with it.

Intent data is a good fit if:

• you sell to large accounts, with long cycles and several decision-makers;
• your website gets enough traffic to identify companies;
• you have a marketing team able to turn a score into a campaign (targeted ads, content, account-based sequences).

Buying signals are a good fit if:

• you are an SME or mid-sized company selling to other businesses, without a dedicated prospecting team;
• your buyers can be identified by their role and are active on LinkedIn, even quietly;
• you want every first message to start from a concrete reason.

Both together make sense when you already have a list of priority accounts: intent data (or your CRM) tells you which ones to watch, signals tell you when to write and to whom.

How do you get from signal to meeting?

A signal is only a starting point. To turn it into a meeting, you need to follow through:

1. Check the person: role, company, real link to your offer. A signal from the wrong person is worth nothing.
2. Write the opener from the signal, without quoting it, with a question about their situation.
3. Reply quickly and simply when the person answers: one qualifying question, then a specific time slot.
4. Measure by signal: which signals produce replies, which produce meetings. Keep the first, cut the rest.

That is the approach we chose at MeetMagnet, our signal-based prospecting AI: start from public LinkedIn signals (reactions and posts), filter against the target, then write a different first message for each prospect based on their signal. Account-level intent data can add a layer of prioritisation, but it does not replace the reason to write. To understand what happens on the buyer’s side before a signal becomes visible, see the B2B buying journey and the dark funnel, and for the sources available, our pages on signals by source.