Intent data and buying signals: what they are and where they come from

Intent data is a record of what companies and people are researching right now: the topics they read about, the competitors they engage with and the searches they run. Buying signals are the parts of that data that suggest someone is moving toward a purchase, such as comparing vendors or looking at pricing.

The signals that predict purchases come from real research behavior. Generic company events, like a hiring spree or a funding round, tell you far less than most sales tools suggest.

What is intent data?

Every B2B purchase leaves a trail before anyone talks to sales. People read about the problem, look at a few vendors, compare prices and ask peers. B2B intent data captures part of that trail and ties it to a company, and sometimes to a person.

There’s a good reason this matters more than it used to. A Gartner survey of 632 B2B buyers, published in June 2025, found 61% prefer a rep-free buying experience and most prefer to research through digital channels. If buyers do most of the early work alone and online, that research is often the first sign you get that they’re in-market.

Intent data comes in two broad types.

First-party data is precise but narrow. Most of your market never visits your site in a given month. Third-party data is what lets you see buyers before they find you, which is why it drives a Sales-ready list.

Buying signals that predict a purchase

Not every signal is equal. These three are the ones worth paying attention to.

Research on your category

People at the company are reading about topics tied to what you sell. A security company might watch “SOC 2 compliance”. A sales tool might watch “sales engagement software”. One article is curiosity. Repeated research across related topics, by several people, is a project.

Competitor engagement

People are spending time with your competitors: their sites, their pricing pages, their content. Few signals are clearer. A company looking at your competitors is evaluating your category right now, and you want to be in that comparison.

Search queries

What people search for shows where they are in the process. Informational searches (“what is account-based marketing”) mean someone is learning. Commercial searches (“ABM platform pricing”, a competitor’s name plus “alternatives”, “best tools for…”) mean someone is shopping.

The difference between informational and commercial intent, and how combinations of both change an account’s priority, is covered in account scoring.

Generic signals: hiring, funding and other news

Hiring, funding rounds, new executives and office openings get sold as buying signals. Most of the time they aren’t.

• They describe capacity, not demand. A funding round means a company has money. It doesn’t mean anyone there is looking at your category.
• Everyone sees them. Funding and hiring news is public. The week a round is announced, the company’s inbox fills with vendors who saw the same headline.
• The timing is vague. A newly hired VP might buy something in six months, or might keep the current tools for years.
• There’s no topic. A hiring signal doesn’t tell your rep what to talk about.

There are exceptions. If you sell recruiting software, a hiring spree is close to real intent. And these events can be useful as fit criteria or context: a Series B company might fit your ICP better than a seed-stage one. But for most offers they belong in the fit score, not the reason to call.

How intent data is collected

Providers gather research activity in a few different ways. Knowing which one sits behind a dataset helps you judge it.

• Your own tracking. Analytics, forms, chat and ad engagement give you first-party intent. Website visitor identification tools try to match anonymous visits to companies or people.
• Content consumption across B2B sites. Publishers and networks record which topics their readers engage with, and providers aggregate that by company and topic.
• Search activity. Queries that show someone looking for a type of product or a named competitor.
• Review and comparison sites. Visits to category pages, competitor profiles and comparisons.
• Ad-auction data. Some providers use data from programmatic ad auctions, known as bidstream data. It’s the most debated method on privacy grounds.

How the data is collected also decides how it can be used. Consent, notice and the rules in each country matter, and the B2B data compliance guide covers the basics.

Where AdsGTM’s intent data comes from

AdsGTM builds on Contactlevel’s own data, which covers 1.2 billion business contacts worldwide, with the deepest coverage in North America, then the EU and UK. The intent signals are real-time web traffic data, engagement with competitors and search queries: what people are actually researching. Hiring and funding news isn’t used as intent.

Account-level vs contact-level intent

Intent data can sit at two levels.

Account-level intent says a company is showing more research than usual on a topic. That tells you which door to knock on, but not who is behind it.

Contact-level intent says which people are doing the research. That tells reps who to reach first and what each person cares about.

Both are useful together. Forrester points out that three people in one buying group each taking a single action is a stronger signal than one person taking several, so activity spread across an account matters. And contact-level detail turns an account signal into an actual conversation. In an AdsGTM list, every contact row carries an intent topics field alongside its list and priority.

How fresh does intent data need to be?

Very. Research windows are short. A company comparing vendors this month may have signed with one by next month, and contact data, which changes as people switch jobs, ages more slowly than intent.

The intent data behind AdsGTM lists refreshes every 24 hours and can be backfilled up to 14 days. The backfill matters as much as the refresh. A single day of research is noisy. Two weeks shows a pattern, and it means a new build doesn’t start blind on day one. Contact records refresh every 14 days, and every work email is checked with an email verifier before delivery.

Your delivered list is still a snapshot of the day it was built. To get a new read on who is in-market, you order a refresh for $1,000 or ask about a monthly Sales-ready refresh. B2B data accuracy covers how contact data decays and how verification works.

Website visitor identification

Website visitor identification is the most direct form of first-party intent. Someone from a company on your list reading your pricing page is a strong signal.

It has two limits. It only covers people who already visit your site, which is a small slice of your market in any month. And identification coverage varies with where visitors are, how the tool matches them and the rules in each country. Treat it as one input next to third-party research, not a replacement for it.

How to use buying signals

1. Score them with fit. A strong signal from a company outside your ICP is still noise. Combine both in your account scoring.
2. Route the overlap to sales. ICP-fit contacts with current intent make up your Sales-ready list.
3. Write about the problem, not the signal. The same Gartner survey found 73% of B2B buyers actively avoid suppliers who send irrelevant outreach. Use the topic to make the message relevant. Don’t tell people you watched them research it.
4. Keep warming everyone else. Contacts without intent today are tomorrow’s buyers. Your Marketing-ready TAM is where that work happens.

Questions to ask about any intent data

• Where does the data come from, and how is consent handled?
• How often is it refreshed, and can it be backfilled?
• Is it account level, contact level or both?
• Are the topics tailored to your offer and competitors, or picked from a fixed list?
• Does it separate informational from commercial intent?
• How does it match to your TAM, and what happens to signals from companies outside it?