What intent data is and how to actually use it.

Intent data is behavioral data that shows which people and companies are actively researching a product, problem, or topic right now. It's built from what people actually do online, not from job titles or company size. Marketers and sales teams use these buying signals to find in-market buyers earlier, before anyone fills out a form or replies to an email.

That's the short version. The longer version is where most teams get it wrong.

Because intent data has become a catch-all term. One vendor means "this company looked active last quarter." Another means "this exact person read three articles about your category yesterday." Those are not the same product. Treating them the same is how budgets get burned.

So let me break it down to first principles. What the term actually means, the types you'll run into, how the signal works, and whether it does anything for pipeline at all.

What is the meaning of intent data?

Intent data answers one question: who is in the market right now?

Most of your data tells you who someone is. Firmographics say a company has 500 employees in SaaS. Demographics say a contact is a VP of Marketing. Useful, but static. None of it tells you whether that person is doing anything about a problem you solve this week.

Intent data is different. It's evidence of action. Someone searched a term, read a comparison page, watched a category webinar. Each of those is a buying signal. A small piece of behavior that, in aggregate, says "this person is paying attention to my category."

You'll hear three terms used for roughly the same thing: intent data, buying signals, intent signals. They overlap. "Intent data" is the SEO-friendly umbrella. "Buying signals" and "intent signals" are what the behavior actually is on the ground. I'll use all three, because that's how buyers and vendors actually talk.

The point of any of them is the same. Stop guessing who's interested. Watch what people do, and reach the ones already leaning in.

How does intent data work?

At the simplest level, intent data works in three steps: observe behavior, tie it to an identity, deliver it as a feed.

First, behavior gets observed across the open web: content consumption around specific topics. Then that behavior gets resolved to an identity, either an account or a named person. Finally it lands in your hands as a list, a score, or an API response you can act on.

Here's where the fork in the road matters: account-level versus person-level.

Account-level intent says "a company that looks like Acme Corp is researching CRM software." You get a domain and a topic. You don't get a person. So you target the whole company on LinkedIn, or you hand the account to a rep who has to guess which of 40 people actually cares.

Person-level intent ties the signal to an individual. With Buyerfeeds, a feed row carries a hashed email you can match as a custom audience in LinkedIn, Meta, Google, or TikTok, plus a name when available, location, LinkedIn URL when available, and a stable identity token. You're not reaching "a company." You're reaching the person who showed the signal.

That difference changes everything downstream. Account-level intent is a prioritization tool. It tells a rep where to look. Person-level intent is an activation tool: you can run ads to it, enrich your CRM with it, or load it straight into Outreach or Clay.

Buyerfeeds also lets you search free-text. You don't pick from a fixed list of predefined topics. You type any topic you want and get people back. Most legacy intent is locked to a category taxonomy. If your niche isn't on the list, you're out of luck. Free-text means your search is the search.

What are the types of intent data?

There are three types, sorted by where the signal comes from: first-party, second-party, and third-party.

First-party intent is your own data. Visits to your website, product usage, email opens, demo requests. It's the highest-quality signal you have because it's about your specific brand. The limit is obvious. It only sees people already on your properties. It can't tell you about demand happening everywhere else.

Second-party intent is someone else's first-party data that you license directly. The classic example is a review site sharing which companies viewed your category page. It's narrower than third-party but often more precise, because the source is a single high-intent property.

Third-party intent is aggregated from across the open web by a provider, then sold as a feed. This is what most people mean when they say "buying intent data." It's how you see demand far beyond your own site: people researching your category who have never heard of you yet.

Buyerfeeds is third-party intent, built at the person level. Roughly 30 billion-plus open-web intent signals flow through it on a daily rolling basis, resolved against an identity graph of around 1.8 billion-plus contacts. The output isn't a score on an account. It's people, with a hashed email attached, refreshed every 24 hours.

Most teams should run first-party and third-party together. First-party tells you who's already engaging. Third-party tells you who's in market but hasn't found you. The gap between those two is your demand-gen opportunity.

Does intent data actually work?

Yes, but only under two conditions. The signal has to be fresh, and you have to act at the person level.

Here's why most intent programs disappoint. A team buys account-level intent, gets a weekly list of "surging" accounts, drops it into a quarterly review, and assigns accounts to reps a month later. By then the buyer signed with someone else. The signal was real. The speed killed it.

Buying intent decays. By the time a buyer talks to a vendor's sales team, they're usually deep into their research and already short-listing. Gartner found B2B buyers spend only 17% of their total buying journey meeting with potential suppliers. If you wait for the form fill, you're meeting them at the end. Intent data is supposed to get you in earlier, but that only happens if you move on it fast.

The second condition is the level. Account-level intent gives a rep a hint. Person-level intent gives you something you can run a campaign on today. Push the hashed emails to a LinkedIn custom audience and serve ads to the exact people showing intent. Sync them to HubSpot or Salesforce. Drop them into Outreach, Salesloft, Apollo, or Clay. Or pull them via the API and batch-enrich up to 1,000 contacts in a single call.

That's the test. If your intent data ends in a dashboard nobody opens, it doesn't work. If it ends in an audience, a sequence, or a piece of direct mail this week, it does.

So the honest answer isn't "intent data works" or "intent data is hype." It's: the data is only as good as the speed and precision of what you do next.

Who offers the best intent data?

There's no single best. There's best for what you're trying to do. Here's how the main options actually differ.

Bombora is the category creator and the standard for account-level, predefined-topic intent, sourced through its data co-op. If you want broad account surge scores and don't need to know the individual, it's a credible pick. ZoomInfo bundles intent inside its larger data platform, which suits teams already living in ZoomInfo. G2 and TechTarget are strong if your buyers research on their specific properties.

Buyerfeeds is the person-level, free-text option. You search any topic and get back people, each with a hashed email you can activate directly. Pricing is published, not hidden behind a sales call: Starter runs $2,000–$5,000/mo, Growth $5,000–$15,000/mo, and Wholesale starts at $25,000/mo for unrestricted access. There's a free 14-day evaluation key, no demo required.

Pick on three axes: do you need the person or just the account, do you need free-text topics or can you live inside a taxonomy, and do you want to see pricing before you talk to anyone. Your answers point you to the right vendor faster than any analyst grid.

Go deeper.

→ Person-level intent data — why reaching the individual beats targeting the account.

→ Intent signals — the specific buying signals that make up an intent feed.

→ Intent data providers — a full comparison of the vendors and how they differ.

→ Intent data for advertising — how to turn intent into custom audiences on LinkedIn, Meta, and Google.