Disclosure: GTM Bud is our product. We include it alongside competitors to give you a complete picture, and we call out its limitations honestly.
Buyer intent data is behavioral data that shows which companies are actively researching a topic, product category, or solution, so you can prioritize accounts that look in-market instead of treating every name on a list the same. Every intent vendor pitches it as knowing who is ready to buy. This guide explains what the data actually is, what it can and cannot tell you, what the major providers cost in 2026, and the honest answer for small outbound teams, which is different from the answer the category’s pricing assumes.
We come at this from the execution side. Our parent agency, Referral Program Pros, has run more than 4,000 outbound campaigns and booked over 7,000 meetings for clients, and we built GTM Bud on that same playbook, backed by a reply-rate guarantee of 5 percent positive replies on LinkedIn or 1.5 percent on email, or a full refund. Running campaigns downstream of every kind of targeting input is how we learned where intent data earns its contract and where a cheaper signal does the same job.
What is buyer intent data?
Buyer intent data is behavioral information indicating which companies are actively researching a topic, product category, or solution, collected from the pages they read, the searches they run, and the products they compare. It is sold in three forms. First-party intent data comes from your own properties: website visits, pricing-page views, content downloads, trial signups. Second-party intent data is another company’s first-party data licensed out to you, most commonly review-site activity such as G2’s Buyer Intent feed, which reports accounts viewing your profile, your category, or your competitors on G2. Third-party intent data is aggregated from across the wider web by providers like Bombora, 6sense, and Demandbase, which model which accounts are surging on topics relative to their normal reading behavior. The critical nuance sits in the unit of measurement: nearly all of it is account-level, not person-level. It tells you that someone at a company is researching a topic, not who, and not that they are ready to buy.
One boundary before going deeper. Intent data is a data category, one input among several. The outbound motion built on top of signals like these, including trigger events such as job changes and funding rounds, is its own discipline, and we cover it separately in our guide to signal-based outreach. This article stays on the data itself: where it comes from, what it costs, and whether to buy it.
First-party vs second-party vs third-party intent data
The three types differ in who collects the data, how close it sits to a real purchase, and what you pay for it. The table below is the map.
| Dimension | First-party intent | Second-party intent | Third-party intent |
|---|---|---|---|
| Who collects it | You, on your own properties | A platform with its own audience, licensed | A provider aggregating across many sites |
| Typical signals | Site visits, pricing views, trials, email opens | Profile views, category and competitor views | Topic surges, content consumption, searches |
| Example sources | Your analytics, product, CRM | G2 Buyer Intent, TrustRadius, Peerspot | Bombora, 6sense, Demandbase |
| Granularity | Often person-level | Account-level | Account-level |
| Purchase signal | Strongest: they came to you | Strong: active category evaluation | Weakest: research interest, modeled |
| Coverage | Only prospects who already found you | Only buyers who research on that platform | Broadest: accounts that have never heard of you |
| Typical 2026 cost | Free, you already own it | Five-figure annual add-on | Five to six-figure annual contract |
Read the granularity and purchase-signal rows together and the pattern is clear: the data gets broader and more expensive exactly as it gets weaker and more anonymous. First-party intent is the strongest signal you will ever have, and it is free. Third-party intent covers accounts you could never see otherwise, and you pay for that reach with modeling uncertainty.
How third-party intent platforms actually work
Third-party providers differ mainly in where their raw behavior comes from. Bombora, the best-known name in the category, runs a data cooperative its own documentation describes as more than 5,000 B2B websites whose publishers contribute reader behavior, monitored against a taxonomy of over 21,600 topics. Its Company Surge score does not flag raw traffic; per Bombora’s published methodology, it compares an account’s most recent three weeks of research on a topic against that account’s own 12-week baseline, so a surge means unusually elevated interest for that specific company. 6sense and Demandbase are broader ABM platforms that combine licensed and modeled intent, including bidstream data inferred from ad-exchange traffic, with account identification, predictive scoring, and advertising orchestration. Bidstream sourcing is the contested part of the category: collected from ad auctions rather than consented publishers, it is widely criticized across the industry for keyword-level false positives. The practical takeaway: ask a provider where the behavior comes from before you trust the score built on it.
Second-party platforms skip the modeling problem by owning the audience. G2 records accounts researching your product page, your category, and your competitors directly on G2, per its own Buyer Intent documentation, which makes the signal purchase-proximate but limited to buyers who research through review sites. LinkedIn sits in the same family: Sales Navigator’s Buyer Intent feature aggregates more than 180 signals, such as company-page engagement and InMail acceptance, into an account-level score, per LinkedIn’s Sales Navigator documentation, and it comes bundled with Advanced plans rather than sold as a separate contract.
What can buyer intent data actually tell you?
Buyer intent data can tell you which accounts are statistically more likely to be in-market, and that is genuinely valuable, because at any given moment most of your total market is not buying. Research by Professor John Dawes at the Ehrenberg-Bass Institute, popularized with the LinkedIn B2B Institute as the 95:5 rule, estimates that up to 95 percent of business buyers are not in the market for a given category at any one time. Anything that helps you find the in-market few is leverage.
What it cannot tell you matters just as much. It cannot name the person doing the research, because the data is account-level and IP-matched. It cannot distinguish a buying committee from a student, a competitor, or an employee researching for a blog post. It cannot tell you the account is ready now: a topic surge means elevated reading, not an approved budget. And it degrades where IP matching degrades, which after years of remote work is a real caveat. Treat intent as a prioritization layer over a well-built list, never as a list source, and never as permission to open a message with “I noticed your team has been researching us.”
That last distinction is the line between this article and outreach strategy. Intent data ranks accounts. Deciding what event triggers a message, what you say, and how fast you move is the signal-based outreach motion, and it deserves its own playbook.
What does buyer intent data cost in 2026?
Third-party buyer intent is enterprise-priced: no major provider publishes a price list, every contract is annual and custom-quoted, and third-party 2026 pricing research consistently reports five to six figures per year. The table summarizes what named sources report; where sources disagree, we show the disagreement rather than picking a number.
| Provider | What it is | Reported 2026 cost | Source |
|---|---|---|---|
| Bombora Company Surge | Co-op topic-surge data, 5,000+ site cooperative | Entry contracts about $25,000 to $45,000/yr, mid-market $60,000 to $120,000, enterprise above $250,000 | Docket’s 2026 pricing research |
| 6sense | ABM platform: intent, account ID, ads, scoring | Median contract roughly $55,000 to $63,000/yr depending on the tracker, deals reported from the low tens of thousands to over $175,000 | Vendr transaction data cited in 2026 guides |
| Demandbase | ABM platform: intent, advertising, orchestration | Median contract roughly $66,000 to $69,000/yr, deals reported from about $24,000 to $164,000 | Vendr data cited in Landbase’s 2026 guide |
| G2 Buyer Intent | Second-party review-site signals | Add-on to a paid G2 profile; 2026 reviews report roughly $10,000 to $40,000/yr mid-market, with some guides citing up to $60,000 | SalesHive’s and ContactLevel’s 2026 reviews |
| Sales Navigator Buyer Intent | LinkedIn engagement signals, account-scored | Bundled with Sales Navigator Advanced plans, no separate intent contract | LinkedIn’s Sales Navigator documentation |
Two things stand out in that table. First, every third-party figure is a reported estimate, because the vendors publish nothing; MarketBetter’s 2026 quote data, for example, reports Bombora entry contracts near $30,000 where Docket reports a $25,000 to $45,000 band, and both are plausible because every deal is negotiated. Second, the intent feed is rarely the whole bill. These platforms are built for ABM programs: the intent score feeds advertising audiences, account identification, and orchestration modules, each priced separately, and the contact data to actually reach people at surging accounts is another subscription on top. Intent data is not contact data, and no intent contract includes the emails and phone numbers outbound runs on; that market is its own comparison, covered in our B2B data providers guide.
Do small outbound teams need buyer intent data?
For most teams under ten people, no, and the reason is structural rather than budgetary. Enterprise intent platforms are built to orchestrate ABM advertising and hand account scores to a marketing operation that can act on them; the contract sizes above assume that operation exists. A small outbound team buying a topic-surge feed gets a ranked account list and no machinery to exploit it, which is the intent-data version of buying a console with no one to play it.
For a small outbound team, the practical substitute for an enterprise intent platform is a stack of three cheaper signals that cover most of the value. First, exhaust your first-party layer: pricing-page visits, trial signups, webinar attendance, and the people engaging with your LinkedIn content are stronger purchase signals than any modeled topic surge, and you already own every one of them. Second, use reachability and activity signals to rank a well-targeted list: whether a prospect has been active on LinkedIn this month predicts whether your message gets seen at all, which modeled intent cannot do. Third, respond fast to hand-raisers, because a reply, a profile view, or a connection acceptance is intent you did not have to buy, and it decays in days. This is the layer an AI SDR for a small business should automate before anyone signs an annual intent contract.
That is the layer GTM Bud operates. It is not an intent data provider and does not sell topic surges; it runs the outbound motion, researching prospects, prioritizing by activity and fit, writing personalized messages, and executing LinkedIn and email sequences, at a flat monthly rate per connected LinkedIn sending account. The honest limitation: if you run a mature ABM program with an advertising budget and an ops team, an enterprise intent platform does things this model does not, and you are the buyer those contracts were designed for.
Frequently asked questions about buyer intent data
What are buyer intent keywords?
Buyer intent keywords are search terms that signal someone is close to a purchase, such as queries containing “pricing,” “alternatives,” “vs,” or a specific product name, as opposed to informational terms like “what is” or “how to.” The phrase comes from SEO and paid search, where you target those terms with ads and comparison pages. It is related to but distinct from buyer intent data, which is behavioral data about which accounts are researching topics, sold by providers like Bombora and 6sense.
How accurate is buyer intent data?
It depends heavily on the collection method. Co-op data like Bombora’s, gathered from consented publisher sites and scored against each account’s historical baseline, is considered the more reliable end. Bidstream data, scraped from ad exchanges, is widely criticized for false positives. All third-party intent shares one structural limit: accounts are identified by IP address, which remote work and VPNs degrade, and a topic surge can be triggered by research that has nothing to do with buying.
Is buyer intent data legal under GDPR?
Reputable providers collect co-op and review-site data under publisher consent frameworks and publish compliance documentation, and because most intent is account-level rather than person-level it carries less personal data than a contact database. But the controller responsibility still sits with you: how you act on the data, and any personal data you attach to it downstream, needs its own lawful basis. Review a provider’s data processing agreement before you buy, exactly as you would with a contact data vendor.
Can you get buyer intent data for free?
You can get first-party intent free: your own analytics, pricing-page visits, trial signups, and the people engaging with your LinkedIn content are all intent signals you already own. LinkedIn bundles Sales Navigator’s Buyer Intent feature into Advanced plans rather than selling it separately. What you cannot get free is third-party topic-surge data; Bombora, 6sense, and Demandbase all sell annual contracts. Most small teams should exhaust the free first-party layer, then put their budget into acting on it with automated lead generation rather than into a data feed.
Should you mention intent signals in your outreach message?
No. Telling a prospect you know their company has been researching a topic reads as surveillance and burns trust, and because the data is account-level you would often be wrong about the individual anyway. Use intent to decide who to contact and when, then write the message about the problem you solve. The signal belongs in your targeting logic, not in your opening line.
Spend on execution before you spend on intent
Buyer intent data is a prioritization layer: first-party signals you own, second-party signals from review platforms, and third-party topic surges modeled by providers like Bombora, 6sense, and Demandbase. It can tell you which accounts look in-market. It cannot name the buyer, confirm a budget, or send a single message, and in 2026 the third-party tier is priced for enterprise ABM programs, not small outbound teams.
So run the honest sequence. Mine the intent you already own, rank a tight list by fit and activity, move fast on hand-raisers, and only then ask whether a five-figure topic-surge feed would change what you send. If the bottleneck is execution rather than data, put the budget there: GTM Bud runs LinkedIn outreach automation end to end, from prospect research through personalized sequences, at a flat monthly rate per connected sending account, with the reply-rate guarantee carrying the risk.