What Is Buyer Intent Data? Types, Examples and How to Use It in B2B Sales

94% of B2B buying groups rank their preferred vendors before they ever contact a seller, and they end up buying from that early favorite 77% of the time, according to 6sense's 2025 Buyer Experience Report. The same research found that buyers first contact sellers about 61% of the way through their journey. Most of the decision happens before your team knows a deal exists.

Buyer intent data is how sales and marketing teams see that hidden research phase. This guide explains what intent data is, the main types and examples, how it's collected, how to use it in B2B sales without wasting effort, and where it falls short.

What is buyer intent data?

Buyer intent data is information that shows a company or person is actively researching a product, service or problem, which suggests they may be preparing to buy. It's based on behavior, such as the content people read, the pages they visit, the products they compare and the changes happening at their company.

"Buying intent" simply means the likelihood that someone plans to make a purchase soon. Intent data turns that idea into signals you can act on: which accounts to prioritize, when to reach out and what to talk about.

Examples of buyer intent data

Intent data covers many different signals. Common examples in B2B sales include:

Topic research: several people at a company are reading articles about a topic related to your product, such as "CRM data cleanup" or "sales engagement software".
Website visits: a target account visits your pricing page three times in a week.
Review-site activity: a company compares your product with a competitor's on a software review site.
Hiring: a company posts job ads for roles your product supports, such as several new SDRs.
Funding: a startup announces a new funding round and starts scaling its team.
Leadership changes: a new VP of Sales joins and starts reviewing the tool stack.
Job changes: a former champion moves to a new company that fits your profile.
Product usage: a free-trial user invites teammates or hits a usage limit.

Strictly speaking, the first three are research intent and the rest are buying signals, but most teams use both together.

The 3 types of intent data

Intent data is usually grouped by who collects it.

The three types of intent data compared: first-party, second-party and third-party, with sources, examples, strengths and limits — The 3 types of buyer intent data. Source: SPONA

First-party intent data comes from your own channels: website visits, content downloads, email engagement, product usage and chat conversations. It's the most accurate and relevant, because it shows interest in you specifically, but it only covers people who already found you.

Second-party intent data is another company's first-party data that you access through a partnership or platform, such as activity on a software review site where buyers research your category or compare vendors. It's highly relevant to purchase decisions but limited to that one platform.

Third-party intent data is collected across many websites you don't own, typically by aggregating research activity from networks of B2B publishers and sites. It reveals accounts that haven't visited you yet, which is its biggest strength, but it's usually account-level and noisier than first-party data.

How intent data is collected

A common question is how providers actually know who's researching what. The main methods are:

Your own tracking. Website analytics, form fills and reverse IP lookup show which companies visit which pages. Our guide to identifying anonymous website visitors explains how.
Data cooperatives. Some providers, such as Bombora, collect content consumption from a network of B2B websites that share data, then detect when a company reads significantly more about a topic than usual.
Review and comparison platforms. Software review sites see which companies browse category pages, vendor profiles and comparisons.
Public signals. Job postings, funding announcements, leadership changes and company news are tracked and matched to companies.
Product and engagement data. Free-trial usage, webinar attendance and email engagement feed into intent scores.

Most of this data is matched to companies, not individuals. That's an important limit to understand before you buy.

Account-level vs. person-level intent

Most third-party intent data tells you that a company is researching a topic, not which person. A surge on "data enrichment" at a 2,000-person company could come from sales, marketing, RevOps or a student intern, so you still need to work out who to contact.

Person-level identification exists for website visitors in some markets. RB2B, for example, identifies individual visitors in the US. In Europe, privacy rules make person-level tracking far more limited, so account-level intent combined with good contact data is the practical approach.

RB2B's pricing page shows how person-level visitor identification is packaged for US traffic.

How to use intent data in B2B sales

Intent data only creates value when it changes what your team does. These are the plays that work best:

Six intent signals and the sales play for each: pricing page visits, topic surges, competitor comparisons, funding, new leaders and champion job changes — Turning intent signals into sales plays. Source: SPONA

Prioritize accounts. Rank your target account list by intent so reps spend their time on accounts that are actively researching, not on the whole list equally.
Time your outreach. Reach out while research is active. A pricing-page visit or a topic surge is a reason to contact the account this week, not next quarter.
Personalize the message. Use the topic the account is researching to choose your angle. If they're reading about data decay, lead with CRM accuracy, not your full feature list.
Multi-thread the buying group. Gartner research puts the typical buying group at six to ten decision-makers, so when an account shows intent, contact several roles rather than one.
Re-engage closed-lost deals. Intent from an account that went quiet months ago is often the best timing signal you'll get.
Coordinate sales and marketing. Run targeted ads to accounts showing intent at the same time as SDR outreach, so your name is familiar when the email arrives.

The goal isn't to mention their research in your email, which can feel intrusive. It's to show up with a relevant offer at the right time.

Relevance is the point: in a Gartner survey, 73% of B2B buyers said they actively avoid suppliers who send irrelevant outreach.

How to build a simple intent score

Raw signals are hard to act on. A simple score that combines fit and intent helps reps know which accounts to work first. Here's a starting model you can adapt:

Fit, up to 50 points: how closely the account matches your ideal customer profile on industry, size, region and technology.
Intent strength, up to 30 points: first-party signals such as pricing-page visits score highest, review-site research next, then third-party topic surges.
Recency, up to 20 points: full points for signals from the last seven days, falling to zero after about a month.

Accounts above roughly 70 points go straight to reps for outreach this week. Accounts between 40 and 70 enter lighter, automated campaigns. Accounts below 40 stay on your watch list. The exact numbers matter less than the principle: never let intent outrank fit, and let scores decay so old signals don't keep accounts at the top forever.

Review the model after a quarter by checking which score bands actually produced meetings and deals, then adjust the weights.

Intent data for ABM

In account-based marketing, intent data decides which accounts move from your target list into active campaigns. A typical setup scores every target account on fit and intent, moves accounts with a strong surge into a focused sales and marketing play, and keeps low-intent accounts in lighter, always-on campaigns. Our guide to intent-based marketing covers the marketing side in more depth.

The limitations of intent data

Intent data is useful, but it's easy to overestimate. Keep these limits in mind:

It's usually account-level. You still need to find the right people and their verified contact details.
It can be noisy. Researchers, students, job seekers and existing customers all create signals that look like buying intent.
It's not always timely. Some signals are aggregated weekly, so a surge may be days old when you see it.
It can be expensive. Vendr's purchase data puts the median Bombora contract at $25,000 a year, and intent features in larger platforms often sit on higher tiers.
It doesn't replace fit. An account with strong intent that doesn't match your ideal customer profile is still a poor lead.

Buyer intent data providers

Intent data comes from specialist providers and from features inside broader sales tools:

Bombora is the best-known third-party intent provider, built on a data cooperative of B2B websites.
G2 Buyer Intent shows companies researching your category and competitors on G2.
6sense and Demandbase combine intent with account-based marketing platforms.
ZoomInfo includes intent data from its Copilot Advanced tier, as covered in our ZoomInfo pricing guide.
Lusha includes buying intent topics on paid plans, with each intent topic per company using one credit.
HubSpot offers Buyer Intent tracking that uses 10 HubSpot credits, or $0.10, per tracked company per month.
Apollo adds buying intent signals from its Professional plan.

For a broader comparison, see our guide to the best B2B data providers.

Is it legal to use intent data?

Generally, yes, when it's collected and used lawfully. Account-level intent data describes company behavior and raises fewer privacy issues than person-level tracking. When intent data leads you to contact individuals, privacy laws such as GDPR in Europe and CCPA in California apply to how you use their personal data, including having a lawful basis for contact and honoring opt-outs. Ask providers how they collect their data and what consent mechanisms they use. This isn't legal advice.

The full text of the GDPR sets out the lawful bases for processing personal data in the EU.

How to measure whether intent data works

Compare accounts with intent signals against similar accounts without them over the same period:

Reply and meeting rates from outreach to intent accounts versus non-intent accounts.
Speed to opportunity: how quickly intent accounts turn into pipeline.
Win rate and deal size for opportunities that started with an intent signal.
Cost per meeting, including what you pay for the intent data itself.

If intent accounts don't convert noticeably better after a few months, the signals aren't tuned to your market, or your team isn't acting on them fast enough.

AI is making this analysis easier: Salesforce's State of Sales research found 87% of sales organizations use AI for tasks such as lead scoring.

How Spona combines signals with verified contacts

Intent data tells you which accounts are interested. It doesn't tell you who to contact or how to reach them. Spona closes that gap. You describe your ideal customer and the signals that matter to you in a chat, and Spona's AI mines 40+ data sources, finds the companies and the right people, verifies each lead across its digital footprint and scores it against your criteria, with the reasoning behind every match.

Signal-based leads. Qualified, scored and signal-based leads cost 100 to 500 credits each, or about $0.80 to $5.00, with credits at $0.008 to $0.01 depending on your plan.
Funding as a signal. Spona's venture data lets you target companies that recently raised money, together with verified contacts.
Net-new leads over time. Spona keeps adding fresh leads that match your target profile.
Free samples first. Every search starts with free sample leads and a per-lead price.

Customers report better results on the phone: Qonto saw an 80% higher connect rate and Kaiko a 65% higher connect rate after switching to Spona data. For more on turning signals into pipeline, see our guide to identifying buying signals.

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FAQ

What is buyer intent data?

Buyer intent data shows that a company or person is actively researching a product, service or problem, which suggests they may be preparing to buy. It's based on behavior such as content consumption, website visits, review-site activity and company changes.

What is an example of intent data?

A target company's employees reading several articles about "sales engagement software", or the same company visiting your pricing page three times in a week, are both examples of intent data.

What are the 3 types of intent data?

First-party intent data comes from your own channels, second-party from a partner platform such as a review site, and third-party from activity across many external websites.

How accurate is intent data?

First-party intent data is the most reliable. Third-party intent is usually account-level and noisier, so it works best combined with fit criteria and verified contact data.

How much does intent data cost?

Costs range from about $0.10 per tracked company per month in HubSpot to annual contracts of $25,000 or more for specialist providers, based on Vendr's median for Bombora.