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Intent Data: What It Is, the Main Types and How to Use It for Outbound

Intent data is information that suggests a company or a person is researching something you sell. It comes from online behavior such as reading articles on a topic, comparing vendors on a review site, visiting a pricing page or engaging with posts about a problem. Sales and marketing teams use it to decide who to contact first and what to say. It shows interest, not a decision to buy, so it works best combined with a fit check and a message that names the reason you are writing.

Disclosure: Looply publishes this guide and makes cold email software that finds prospects from buying signals. Facts about Bombora, G2 and LinkedIn come from their official pages, checked on October 16, 2026. This guide is not legal advice.


What intent data is, and what it is not

Intent data answers one question: who is showing interest in a topic right now? It does not tell you that someone has budget, authority or a deadline. A company reading about "email deliverability" might be planning a purchase, writing a blog post or training a new hire.

That is why good teams treat intent data as a timing signal on top of fit:

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Fit says the account could buy: right industry, size, region and tech stack.
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Intent says the account may be looking now.
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A message connects the two: why you, why them, why this week.

Fit without intent gives you a long list with no urgency. Intent without fit fills your pipeline with companies that will never buy.

The main types of intent data

Intent data is usually grouped by who collects it.

TypeWho collects itExample signalsLevelBest use
First-partyYou, on your own channelsPricing page visits, demo page views, product sign-ups, email clicksAccount or personFollow up with people already looking at you
Second-partyAnother company, about its own audienceComparisons and category views on a review site, activity on a publisher's siteUsually accountReach accounts comparing vendors in your category
Third-partyA provider, across many sitesRising research on a topic across a network of B2B sitesUsually accountFind accounts researching a problem before they find you
Public buying signalsAnyone, from public eventsJob changes, funding rounds, hiring, posts and reactions on LinkedInPerson or companyStart a conversation with a clear, visible reason

First-party intent data

First-party data is the most reliable because you collected it yourself and you know what each action means. A visit to your pricing page from a target account is a stronger signal than any topic score. The limit is reach: it only covers people who already found you.

Second-party intent data

Second-party data is another company's first-party data, shared or sold. Review sites are the common example. G2 says its Buyer Intent data is based on activity on G2 such as product and category page views, competitor comparisons, pricing page engagement, reading and writing reviews, and engagement with your G2 profile. These actions sit close to a purchase decision, but they only cover buyers who research on that site.

Third-party intent data

Third-party data is collected across many websites and sold by a provider. Bombora, for example, runs a data co-op of publishers and B2B brands. It says it compares the most recent three weeks of activity for each account and topic against a 12-week baseline, and flags a "surge" when research rises above that account's normal level. Some providers also use bidstream data, which comes from online ad auctions. Ask each provider exactly which sources it uses.

Third-party data reaches accounts that have never heard of you. The trade-off: it is usually account-level, so it tells you that someone at a company is researching, not who.

Public buying signals

Public signals are events anyone can see: a new VP of Sales, a funding announcement, a burst of job listings, a post about a problem, or people reacting to a competitor's page. They are not always called intent data, but for outbound they are often the most useful kind, because:

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they usually point to a person, not just a company;
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you can cite them in the first line, so the email explains itself;
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they are fresh, and timing is most of the value.

How the big platforms collect intent

Three examples show how different the sources are. Each fact below comes from the provider's own page.

Bombora Company Surge collects research activity through a consent-driven tag on the sites in its data co-op. It scores each account and topic against that account's own baseline, and sends the results to ad, marketing, sales and CRM platforms.

G2 Buyer Intent is based on what buyers do on G2: viewing your product and category pages, comparing you with competitors, engaging with pricing and reading reviews. G2 says customers can see which accounts are researching their product, their category or their competitors.

LinkedIn Sales Navigator Buyer Intent is available only on the Advanced and Advanced Plus editions. LinkedIn builds it from activity on LinkedIn (such as comments, reactions and following a company page), interactions with your ads, InMail accepts and declines, and, if you install the LinkedIn Insight Tag, visits to your website. It labels accounts High, Moderate, Neutral or Negative.

How to use intent data in cold email

Intent data only pays off when it changes who you contact and what you write. A simple process:

1.
Define fit first. Write down the industries, company sizes, regions and roles you sell to. Drop every account that fails the fit check, however strong its intent.
2.
Pick a few topics or signals that map to your offer. Choose the problems your product solves, your competitors' names and the events that create a need, such as a new sales leader or a funding round.
3.
Find the person. Account-level intent tells you that a company is researching. You still need the right contact: the role that owns the problem, ideally someone who showed the signal.
4.
Act within days. Interest fades. A signal from this week is worth more than a strong score from last quarter.
5.
Name the reason in the first line. Mention what you saw and where, in plain words. If you cannot cite it, do not pretend: use a fit-based opener instead.
6.
Ask one easy question. Interest is not a decision. Offer something useful and ask a yes-or-no question.
7.
Measure by signal. Track positive replies and meetings for each signal type, keep the ones that work and drop the rest.

Two short examples:

Plain text
Subject: your new role at [Company]

Hi [First name], congrats on joining [Company] as [role] last month. New sales leaders often review how the team finds its next accounts in the first 90 days. We help teams like yours start each campaign from a buying signal instead of a static list. Is pipeline quality on your list this quarter?
Plain text
Subject: [Competitor] comparison

Hi [First name], I noticed you engaged with [Competitor]'s page on LinkedIn this week. If you are comparing tools for [problem], I can send you the three questions we would ask any vendor, including us. Want them?

For 40 more examples built on signals, see our cold email templates.

Looply watches the LinkedIn signals you choose, scores each person against your ideal customer profile and drafts the first email for you to review. Start the 7-day free trial or read about buyer intent software.

Account-level vs person-level intent

Account-levelPerson-level
What you learnSomeone at the company is researching a topicA named person did something you can see
Typical sourcesThird-party co-ops, review sites, website visit toolsPublic posts and reactions, job changes, your own email and site activity
StrengthWide coverage, early warningYou know who to write to and why
WeaknessYou still have to find the right personSmaller volume per signal
Best forAds, account lists, prioritizing sales territoriesCold email and LinkedIn outreach

Most outbound teams use both: account-level data to rank target accounts, person-level signals to decide who gets an email this week.

How to judge an intent data provider

Ask every provider the same questions before you sign:

QuestionWhy it matters
Where exactly does the data come from?Co-op sites, a review site, ad auctions and public events carry very different meaning.
How is a visitor matched to a company?IP-based matching can be wrong for remote workers and shared networks.
Is the data account-level or person-level?Account-level data needs a second step to find the contact.
How fresh is it, and how often is it updated?Scores that update weekly can lag behind the moment you want to reach.
How many of my target accounts does it cover?Ask for a match rate on your own account list, not a global number.
How was consent collected, and in which countries?You inherit the provider's privacy choices when you act on its data.
Where does it go?Check the CRM, ad and outreach tools you already use.
Can I run a pilot first?Test it on your own accounts for a few weeks and compare replies against a control group.

Privacy and compliance

Intent data is often about companies, but outreach reaches people, so privacy rules apply.

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United States: commercial email must follow CAN-SPAM: accurate headers, honest subject lines, a postal address and a working opt-out. Our cold email templates guide covers the 2026 sender rules for Gmail, Yahoo and Outlook.
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California: the CCPA exemption for business-to-business personal information expired on December 31, 2022, so data about business contacts is covered.
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United Kingdom: the ICO says you do not need consent under PECR to email corporate subscribers such as limited companies, but you must not hide your identity and you must give a valid opt-out address. UK GDPR still applies to named business contacts, and sole traders count as individuals. The ICO notes this guidance is under review after the Data (Use and Access) Act.
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European Union: GDPR applies, and electronic-marketing rules vary by country. For France, see our guide to CNIL rules for B2B prospecting.

In every case, honor opt-outs fast, keep a suppression list, and only say in an email what you actually saw.

Common mistakes

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Treating a topic score as a buying decision. Interest is a reason to write, not a promise to buy.
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Skipping the fit check. Intent from the wrong segment wastes your best timing.
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Waiting too long. A signal is worth most in its first days.
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Writing "I saw you are in market". It sounds like surveillance. Name a public, specific reason or none at all.
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Buying data you cannot act on. If no one owns follow-up, scores just sit in the CRM.
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Measuring opens. Judge each signal by positive replies and meetings held.

FAQ

What is intent data in B2B?

It is information that suggests a business is researching a topic, a product category or a vendor. It comes from first-party sources (your site and emails), second-party sources (such as review sites) and third-party sources (providers that collect research activity across many sites).

What is the difference between intent data and buying signals?

Intent data usually means scored research activity, often at the account level. Buying signals is a wider term that also covers public events such as job changes, funding rounds, hiring and engagement with posts. For cold email, signals that point to a person and can be cited are often the easiest to use.

How accurate is intent data?

It varies by source. First-party data is the most reliable. Third-party data depends on how the provider matches activity to companies, which can be wrong for remote workers and shared networks. Test any source on your own accounts before you rely on it.

Generally yes, if you follow the rules where your recipients are, such as CAN-SPAM in the United States, the CCPA in California, and GDPR and electronic-marketing rules in the UK and the EU. Ask each provider how it collected consent. This guide is not legal advice.

How much does intent data cost?

It depends on the provider, the number of topics and accounts, and the contract length. Many providers quote prices on request, so ask for a pilot on your own target accounts before you sign.

Official sources checked

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Bombora: Company Surge intent data, checked October 16, 2026
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G2: Buyer Intent, checked October 16, 2026
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ICO: Business-to-business marketing, checked October 16, 2026
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California Attorney General: CCPA, checked October 16, 2026

Start from a signal you can name

Looply finds people showing buying signals on LinkedIn, such as engaging with competitor pages or moving into a role you sell to, checks them against your ideal customer profile and drafts the first email. Start the 7-day free trial or see pricing.

Written by

Benjamin Gouleau
Founder at Looply

Benjamin builds Looply and writes about buyer signals, prospect qualification, and practical outbound systems.