What does intent data mean in B2B sales?
In B2B, fit data describes a company: industry, size, location, tech stack. Intent data describes what the company or its people are doing: reading about a topic, comparing vendors, visiting a pricing page, asking peers for advice. Fit tells you who could buy. Intent suggests who might be buying now.
Two distinctions matter more than any vendor label. First, who collected the data: you, a partner, or a third party that aggregates many sites. Second, what level it describes: an account ("someone at this company is reading about payroll software") or a person ("this founder asked for payroll software recommendations"). The rest of this guide follows those two lines.
Treat all intent data as a probability, not a fact. It helps you rank accounts; it does not tell you that a purchase is underway.
Which intent data terms will you hear in a demo?
Vendors use overlapping words for similar things. Pin these down before you compare offers, because two products that both promise "buyer intent" can deliver very different data.
Intent topic
A subject the provider tracks, such as "employee onboarding software" or "SOC 2 compliance". You usually pick a list of topics that map to your product. A topic that is too broad catches everyone who reads industry news; one that is too narrow may never register any activity.
Surge
A rise in an account's activity on a topic compared with its own usual level. Because a surge is relative, a large company with steady interest in your topic may never surge, even in the middle of a purchase, while a small spike at a quiet company can.
Account identification
The step that ties anonymous activity, such as a page view, to a company, most often by matching the network the visit came from. It is the weakest link in most third-party data, for the reasons covered under limits below.
Person-level intent
Intent tied to an identifiable individual: someone who asked a question in public, filled in a form on your site, or was identified by a visitor identification tool. It is more actionable than account-level data, and more sensitive under privacy law.
Buying stage and in-market
Some platforms, such as 6sense, estimate where an account sits in its purchase, from early research to decision, by combining several signals in a predictive model. "In-market" is shorthand for likely to buy within a period. Ask each vendor for its definitions and the period they cover, then check them against your own sales cycle.
Signal decay
How quickly a piece of intent loses value. A public request for a tool can be answered by someone else within days. A hiring plan stays relevant for weeks. An account surge is only as current as the provider's refresh schedule, so ask how often it updates.
First-, second- and third-party intent data: what is the difference?
The first question to ask about any intent data is who collected it. The closer the collector sits to the buying decision, and to you, the more the data tends to mean.
Review sites are the classic second-party source: G2, for example, sells buyer intent data based on activity on its own site. Third-party data is what most people mean by "intent data". Bombora, one of the best-known providers, builds its Company Surge scores from content consumption across a cooperative of B2B websites. Account-based marketing platforms such as 6sense and Demandbase combine several sources with their own models to rank accounts.
First-party intent is the easiest place to start because you already own it. Inbound tools such as Qualified's Piper act on it in real time, talking to visitors while they are still on your site.
| Type | Who collects it | Examples | Strength | Main limit |
|---|---|---|---|---|
| First-party | You, on your own properties | Visits to your pricing page, demo requests, product sign-ups, replies to your emails | Most accurate, and about your product specifically | Only covers people who already found you |
| Second-party | Another company, from its own audience, shared with or sold to you | A review site reporting which companies viewed your category or your profile | Close to a buying decision, often names competitors | Limited to that partner's audience |
| Third-party | A provider aggregating behavior across many sites | Topic surges built from reading activity across a network of B2B publishers | Covers accounts that never visited you | Account level, indirect and hard to verify |
Topic surges or public post signals: which kind of intent?
A topic surge says that an account is consuming more content on a topic than its usual baseline. It is broad, it covers many companies, and it arrives as a score. It does not tell you who at the company is reading, why, or whether that person is a buyer, a student or a competitor doing research.
A public post signal is a single statement by a person: a question on Reddit, a post on X, a comment under a launch. It is rarer and messier to collect, but it is explicit, it names a need in the buyer's own words, and you can link to it. That makes it easy to check and natural to mention in a first message.
| Account-level topic surge | Public post signal | |
|---|---|---|
| Unit | A company, often resolved from an IP address or domain | A person and a specific statement |
| What it tells you | Research on a topic is above normal | A stated need, complaint or request |
| Volume | High: many accounts every week | Low: depends on how much your market posts |
| Can you verify it? | Not directly; you see a score | Yes, with a link to the original |
| Best use | Prioritizing a known list of accounts | Timely, specific first messages |
How do intent data providers collect it?
Methods differ a lot, and the method decides how much you can rely on the output. The main categories:
- Publisher cooperatives. B2B media sites share anonymized reading activity with a provider, which maps it to companies and topics and flags unusual increases.
- Review and comparison sites. A software marketplace sees which companies view a category, a vendor profile or a comparison page, and shares that with the vendors listed.
- Website visitor identification. Tools match the IP address of a visit to a company. This powers first-party alerts ("an account from your list is on your pricing page") and some third-party networks. We compare tools of this kind on our Warmly alternatives page.
- Advertising data. Some providers derive signals from ad-tech data about the pages where ads are shown. Ask about this one carefully: quality and consent vary.
- Public sources. Job posts, press releases, funding filings, technology footprints on websites, and public posts in communities and social networks. These are verifiable and often person-level, but they need classification to separate a real need from noise. Community-signal tools are covered in Common Room alternatives.
Reach companies with a reason to buy this week
Startories finds the buying signal, verifies the decision-maker and runs the outreach until they book a call.
What are the limits of intent data?
Accuracy
- IP matching is imperfect. Remote work, VPNs, mobile networks and shared offices all blur the link between a visit and a company.
- Topics are coarse. A surge on "email marketing" can come from a new hire learning the basics, a student, an agency serving its clients or a competitor.
- Small companies are often invisible. A 15-person startup does not generate enough reading activity to stand out from its own baseline.
- Scores lag. Aggregated scores are computed on a schedule, so the moment may have passed by the time the score reaches you.
Privacy
Intent data about identifiable people is personal data, including when the person is a business contact. In the EU, the GDPR requires a lawful basis and transparency for processing it. In California, the CCPA gives residents rights over their personal information, and the temporary exemption for business contact data ended in 2023.
Ask every provider how the data was collected, whether people were informed, and whether it contains personal data or only company-level scores. If a vendor cannot answer clearly, you inherit the risk.
How do you choose an intent data source?
Choose the source that matches how your buyers research, not the one with the most impressive dashboard. Most teams end up with their own first-party data plus one external source that suits their market. Use your ideal customer profile to decide which row describes you.
| Your situation | Start with | Why | Watch out for |
|---|---|---|---|
| You sell to a named list of a few hundred larger accounts | Third-party topic surges, often inside an ABM platform | Ranks a fixed list by research activity | Contract cost, and scores you cannot check; large accounts surge for many reasons |
| Your website already gets steady traffic from your market | First-party visits and visitor identification | Accurate, and about your product specifically | Only covers people who already found you; person-level identification has consent rules |
| Buyers in your category compare vendors on review sites | Second-party data from those sites | Close to a decision, often names the competitor | Only as broad as that site's audience |
| You sell to small companies or a niche that discusses problems in public | Public post signals and company events | Person-level, dated and linkable | Lower volume; needs classification to separate needs from noise |
| You have no traffic and no fixed account list yet | Company events such as launches, hiring and funding, plus a few saved searches | Cheap to start and easy to verify | More manual reading at first |
How intent data is sold
Third-party intent is usually priced through a sales conversation rather than a public price list, and it is often bundled into a larger platform: an ABM suite, or a sales intelligence database. ZoomInfo, for example, sells intent signals alongside its contact data and describes its approach in its own intent data guide. We compare databases of that kind on our ZoomInfo alternatives page.
Questions to ask any provider
- Which sources feed the data, and in what proportion?
- Is the output account-level, person-level, or both?
- How often is it refreshed, and how old is a typical signal when it reaches me?
- How are companies identified, and how well does that work for companies of my target size?
- Was notice or consent given where the law requires it, and can you document it?
- How is it priced (per topic, per account, per seat or bundled), and how long is the contract?
- What happens to the account lists and contacts I upload?
- Can I see a sample on my own target accounts before I sign?
How do you use intent data in outbound?
Start from fit
Filter by your ideal customer profile first. Intent from a company you cannot serve is noise, however strong the surge.
Use intent to order the list
Within the accounts that fit, contact the ones showing intent first, and give them more research time.
Look for a second signal
Before writing, confirm the surge with something you can see: a job post, a launch, a public question. Two independent signals are worth far more than one score.
Write about the problem, not the tracking
Never open with "we noticed your team researching X". Write about the problem the topic suggests, or about the public event you confirmed.
Set a time window
Act on public requests within days and on account surges within a couple of weeks. After that, move the account back to normal priority.
Measure against a baseline
Run part of your list without the intent filter for a month. If intent-ranked accounts do not reply or book more often, the data is not earning its cost.
| What the data shows | Do not write | Write instead |
|---|---|---|
| An account surging on "employee onboarding" | "We noticed your team researching onboarding software." | "Saw 14 open roles across three states on your careers page. At that pace, first-week paperwork is usually what slows new hires down." |
| A known account visited your pricing page twice | "I saw you were on our pricing page yesterday." | "Teams your size usually ask how pricing works past 50 users, so here is the short version in three lines." |
| A review site shows the account compared you with a competitor | "Our data says you are comparing us with {competitor}." | "If you are weighing tools in this category, here is a one-page comparison, including where {competitor} is the better fit." |
| A manager asked in public which onboarding tool suits a 60-person team | A generic "quick question" email that ignores the request | "You asked which onboarding tool works at 60 people. Here is how we would set it up, plus two questions to ask any vendor." |
A worked example: from 200 target accounts to one week of outreach
The numbers below are invented to show the method; they are not benchmarks. Assume you sell employee onboarding software to US companies with 50 to 500 employees, mostly in software and professional services. You have a target list of 200 accounts and a third-party feed that tracks the topic "employee onboarding". For more on this market, see lead generation for HR tech.
Read the feed against the list
This week, 18 of your 200 accounts show a surge on the topic. On its own, that tells you where to look, not what to say.
Check fit again
Four drop out on a second look: an HR consultancy that probably reads about onboarding for its own clients, a current customer, and two companies that grew past 500 employees since the list was built. Fourteen remain.
Look for something you can see
Spend five minutes per account on public sources. Six have many open roles at once (hiring signals), two announced a new office (expansion signals), and at one, an HR manager asked in a public community which onboarding checklist tool others use (tool requests). Five show nothing visible.
Match the effort to the evidence
The nine accounts with a visible signal get a researched first email this week, written around that event. The five surge-only accounts get a lighter sequence about the general problem, or wait two weeks for something you can reference.
Build a comparison group
Pick 30 accounts from the same list that fit but show no surge, and send them the same lighter sequence. You now have three groups: surge plus a visible signal, surge only, and no surge.
How to start using intent data
Start with the intent you already own: website visits, pricing page views and replies. Then add one external source that matches how your buyers behave. If they research on review sites, look at second-party data. If they ask peers in public communities, public post signals will tell you more than topic surges. Whatever you add, run the three-group comparison above before you renew.
Startories focuses on that second kind: it detects public posts and company events, keeps the link to each source, and turns them into scored, verified leads with personalized outreach. See how it works for AI lead generation, or compare plans on the pricing page.
Frequently asked questions
Is intent data accurate?
It is directionally useful but imprecise. Account-level surges depend on matching activity to companies, which fails with remote work and VPNs, and on broad topics. Use it to rank accounts you already want, and confirm with a visible signal before you write.
Is using intent data legal?
It can be, but it depends on how the data was collected and where the people are. Person-level data is personal data under laws such as the GDPR and the CCPA. Ask providers to document their sources and notices before you buy.
What is the difference between intent data and buying signals?
Intent data is usually an aggregate measure of research activity, often at the account level. A buying signal is one specific event, such as a funding round or a public request for a tool, that you can point to and mention in a message.
What is the difference between intent data and technographic data?
Technographic data lists the tools a company uses, such as its CRM or website platform. Intent data describes what it is researching or asking about. A change in technographics, like adding or dropping a tool, can itself be a technographic buying signal.
Can small companies use intent data?
Yes. Start with first-party data from your own website and emails, which costs nothing and is accurate. Public post signals also suit small teams, because they work in niche markets where third-party surges rarely show enough activity.
Do I need third-party intent data for outbound?
Not necessarily. It helps most when you sell to a defined list of larger accounts. For founder-led teams selling to smaller companies, public signals and company events are usually more specific and easier to act on.