Most B2B purchases start with research that happens long before the buyer contacts a vendor. An analyst reads comparison articles. A manager downloads a category overview. A VP searches for pricing. By the time a company fills out a demo request form, they've often already formed a shortlist.
Intent data attempts to surface that research phase while it's happening. Instead of waiting for a prospect to raise their hand, sales teams can see which companies are actively consuming content in their category and reach out during the window when the evaluation is live.
How intent data is collected
Third-party intent data comes from networks of business-focused publishers who share aggregated browsing data with intent data providers. Bombora, one of the largest, operates a cooperative of over 5,000 B2B media sites including trade publications, industry blogs, and vendor review platforms. When someone at a company reads an article about "data loss prevention software" on one of those sites, that content consumption gets tagged and attributed to the company via their IP address.
The raw signal is not a single article read. Intent data providers look for elevated activity relative to a baseline. A company where three employees have each read four to five pieces of content on a topic in the past two weeks is displaying a meaningfully different signal than a company where one employee read one article six weeks ago. The former suggests an active evaluation in progress. The latter could be anything.
IP-to-company mapping is the mechanism that connects browsing behavior to a specific business. Intent providers maintain databases that translate corporate IP ranges to company names. This works well for employees on a company's network or a corporate VPN. It breaks for employees working from home on residential internet, employees using personal devices, or companies using shared office space with mixed IP assignments.
What a surge score measures
The primary output of most intent data platforms is a surge score: a number, usually on a 0-to-100 scale, representing how much a company's research activity in a given topic has increased relative to its own historical baseline and relative to peer companies in the same industry.
A surge score of 60 or above typically indicates meaningful elevated activity. A score of 80 to 100 represents a significant spike. The score is relative, not absolute. A company that normally consumes zero content on a topic and suddenly has three employees reading articles on it gets a high surge score even though the absolute volume is low. A large company in the technology industry where someone reads about cybersecurity every single week might show a low surge score on cybersecurity regardless of volume because that level of activity is normal for them.
The practical implication: surge scores work better for identifying accounts that have deviated from their normal pattern than for measuring absolute research volume. A mid-sized logistics company with a surge score of 75 in "fleet management software" is a more actionable signal than a technology company with a surge score of 45 in "security tools," even if the technology company is a larger account.
First-party versus third-party intent
First-party intent data is everything your company already knows about how prospects interact with your own digital properties. Website visits, content downloads, webinar registrations, email opens and clicks, and pricing page views are all first-party intent signals. They are high-quality because the researcher is engaging directly with your brand, which means the IP mapping problem largely disappears and the topic relevance is exact.
The limitation of first-party intent is coverage. You only see companies that have already found you. If a company is actively evaluating your category but hasn't visited your site, your first-party data shows nothing.
Third-party intent covers the accounts you can't see yet. A company doing pre-shortlist research across review sites, industry publications, and comparison pages appears in third-party intent data before they ever visit your site. The trade-off is accuracy: the signal is noisier, the attribution is less reliable, and the topic matching depends on how well the provider's taxonomy maps to your actual product category.
The most effective use of intent data combines both. Third-party intent identifies accounts in-market that you haven't reached yet, prioritized by surge score. First-party intent tracks how deep into the funnel those accounts move once you reach them.
How sales teams act on intent signals
Intent data without a workflow change doesn't produce results. The value comes from what sales teams do differently with the information.
Account prioritization. A rep with a territory of 400 accounts cannot meaningfully engage all of them. Intent data segments that list into accounts showing active research right now versus accounts that are cold. Working the warm list first concentrates effort where purchase probability is highest.
Sequence timing. An account that just started surging in your category this week is at a different stage than an account that surged three months ago. Recent surge activity warrants immediate outreach. An account that surged and then went quiet may have already made a decision. Timing the sequence to the surge window, typically the first two weeks of elevated activity, captures the evaluation while it's live.
Message personalization. Knowing that a prospect is researching specific topics changes the pitch. A company surging on "data residency compliance" topics is probably facing a regulatory deadline or a customer requirement in that area. Leading with how your product addresses data residency specifically is more relevant than a generic product overview.
Account-based advertising. Marketing teams use intent data to trigger targeted ad campaigns at accounts showing elevated research activity. Rather than running display advertising to all accounts in a territory, campaigns activate only for accounts with a surge score above a defined threshold, concentrating ad spend during the window when it's most likely to reinforce an active evaluation.
Where intent data falls short
Intent data has real limitations that matter in practice.
Remote work degraded coverage. Before 2020, most corporate employees browsed from office networks with consistent IP ranges that mapped cleanly to company identities. With large portions of workforces now on residential internet or VPNs with rotating exit nodes, a meaningful percentage of corporate research activity is invisible to intent data providers. Some estimates put the coverage gap at 30 to 50 percent of remote workforces depending on the industry.
Intent data identifies which company is researching but not which person. A surge in "HR software" at a 2,000-person company tells you the company is looking, but the actual buyer could be in HR, IT, Finance, or the CEO's office. Outreach still requires traditional prospecting to find the right contact within the account.
False positives are common. A company that just implemented your category of software may continue showing elevated intent signals for weeks after the purchase as new users search for tutorials, documentation, and related topics. Intent data can surface recent buyers as active prospects. Overlaying CRM data on intent signals to filter out existing customers and recent churned accounts reduces noise significantly.
Signal lag is typically 1 to 2 weeks between when research happens and when the intent data is delivered. A company that started evaluating vendors in week one may have already requested demos and narrowed to a shortlist by the time the intent signal arrives in week three. Faster signal delivery from providers who offer weekly or daily refreshes reduces but doesn't eliminate this problem.
Frequently Asked Questions
What is B2B intent data?
B2B intent data is information about which topics a company's employees are actively researching online. Providers collect this by aggregating browsing behavior across large networks of business-focused websites. When employees at a company consume a higher-than-normal volume of content on a topic, that company shows elevated intent in that category. Sales and marketing teams use this signal to identify and prioritize accounts that are likely in an active buying cycle before those accounts ever contact a vendor.
What is a surge score in intent data?
A surge score measures how much more content a company is consuming on a given topic compared to its baseline. A score of 60 or above typically indicates a meaningful spike in research activity. The score is relative to the company's own historical behavior and to peer companies in the same industry, so a surge score of 80 doesn't mean the company read 80 articles. It means research activity in that category is significantly elevated compared to what's normal for that account.
What is the difference between first-party and third-party intent data?
First-party intent data comes from your own digital properties: website visits, content downloads, webinar attendance, and email engagement. It is high-signal because the researcher is directly engaging with your brand. Third-party intent data comes from external publisher networks and tracks research behavior across the broader web. Third-party intent identifies accounts in your category before they ever reach you, but signal quality depends entirely on the size and relevance of the publisher network being measured.
How accurate is B2B intent data?
Intent data accuracy varies by provider and collection method. The main limitations are IP-to-company mapping errors (home offices and VPNs break the link between browsing and company identity), the inability to identify which individual is doing the research, and time lag between research activity and signal delivery, which can run 1 to 2 weeks. Intent data works best as a prioritization filter rather than a standalone trigger. An account showing intent in your category plus a recent funding round plus headcount growth in a relevant team is a much stronger signal than intent alone.