Intent data is the sales tech category built on a simple premise: companies researching a problem leave traces before they ever fill in a form. Vendors collect those traces, attach them to accounts, and sell the result as a ranked view of who might be in market. How useful that view is depends on where the traces came from and how the team acts on them.
The premise matters more as buyers avoid sellers. In a Gartner survey of 646 B2B buyers conducted in August and September 2025, 67% said they prefer a rep-free buying experience, and 45% reported using AI during a recent purchase (Gartner, 2026). When more evaluation happens without a rep, those signals are among the few early indicators a sales team gets.
Where the signals come from
Intent data is usually split by who owns the source.
First-party intent is activity on properties a company controls: its website, product, webinars, emails and chat. It is the most specific signal available, because the prospect was looking at that vendor's pricing page, not a general article. Its limit is reach: it only sees accounts that already found the vendor.
Third-party intent is collected from sites the company does not own. Bombora describes its Company Surge data as coming from a co-operative of B2B publishers and brand sites that carry a consent-based tag (Bombora). The score compares an account's most recent three weeks of content consumption on a topic against a 12-week baseline (Bombora), and Bombora's guidance treats a score of 60 or above as a meaningful spike (Bombora).
A third group sits between the two: software review sites selling activity from their own users. G2 grades accounts High, Medium or Low based on the recency and frequency of visits to a vendor's profile, category, alternatives, comparison and pricing pages, and assigns a buying stage of Awareness, Consideration or Decision (G2).
How the main approaches differ
The practical difference is what each signal measures. Topic surge data measures interest in a subject relative to an account's own history. It is broad and early, which makes it better for deciding which accounts to warm up than for deciding whom to call today.
Review-site data measures evaluation behavior inside a software-buying context. It covers fewer accounts but sits closer to a purchase decision.
Predictive platforms combine sources and model the outcome directly. 6sense produces a 0-100 intent score from a model estimating the likelihood that an account opens an opportunity in the next 90 days (6sense), and places accounts in one of five predicted buying stages: Target, Awareness, Consideration, Decision and Purchase (6sense). The trade-off is transparency. A modeled score is easier to act on and harder to audit.
What it changes for SDR and AE workflows
For SDRs, intent data mostly changes prioritization. Instead of working a territory list in firmographic order, the day's queue can be sorted by accounts showing fresh activity on relevant topics. The message can change too: an account surging on a specific topic gives the rep a reason to reach out that is about the prospect's problem rather than the product.
For AEs, the more useful signal usually sits inside open deals and existing accounts. Comparison-page activity on a review site during an active opportunity, or a renewal account researching alternatives, is information an AE would otherwise learn late.
What to check when buying
- Collection method. Ask where each signal originates: a consented publisher co-op, review-site activity, the vendor's own model, or something else. Forrester lists treating all intent data sources the same among its ten biggest intent data mistakes (Forrester).
- Account resolution. Many third-party signals are tied to a company by IP address. That match weakens when employees work on home internet connections or use privacy services such as Apple's iCloud Private Relay, which hides a user's IP address from websites (Apple). Ask the vendor how it resolves remote traffic and what share of its matches it rates as high-confidence.
- Taxonomy fit. Check that the vendor's topic list includes topics specific to the product, not only broad ones that every large company surges on.
- CRM delivery. A score in a separate tool rarely changes rep behavior. Check whether signals land on the account record and in the sequencing tool reps already use.
What commonly goes wrong
A common failure is treating intent as a lead list. A surge says an organization is reading about a topic. It does not name the person, the budget or the timeline, so it does not replace qualification.
Another is ignoring decay. Forrester notes that intent is among the most time-sensitive data types, and that stored signals without decay rules eventually make every company in a database look active (Forrester).
A third is privacy. Forrester also cautions against relying on the vendor alone for compliance: the buying company still needs its own lawful basis for storing and using prospect data (Forrester). Where prospects are in the EU or UK, that question belongs with legal counsel before signals feed automated outreach.
The test for any intent program is narrow and measurable: whether reordering the rep queue by signal produces more qualified meetings than the order it replaced.
Sources
- Gartner. "Gartner Sales Survey Finds 67% of B2B Buyers Prefer a Rep-Free Experience." 2026. https://www.gartner.com/en/newsroom/press-releases/2026-03-09-gartner-sales-survey-finds-67-percent-of-b2b-buyers-prefer-a-rep-free-experience
- Bombora. "Company Surge." https://bombora.com/intent/
- Bombora. "Data science methodology behind Company Surge." https://knowledge.bombora.com/b2b-data-co-op/data-science-methodology-behind-company-surge
- Bombora. "Score & Topic Thresholding." https://customers.bombora.com/crc-coop/scoresthresholds
- G2. "Learn about Buyer Intent signals." https://sell.g2.com/quick-start-guides/leverage-insights/learn-about-buyer-intent-signals
- 6sense. "Intent Model." https://support.6sense.com/docs/intent-model
- 6sense. "Predictive Buying Stages." https://support.6sense.com/docs/predictive-buying-stages
- Forrester. "The 10 Biggest Intent Data Mistakes For B2B Marketing And Sales." https://www.forrester.com/blogs/the-10-biggest-intent-data-mistakes-for-b2b-marketing-and-sales/
- Apple. "About iCloud Private Relay." https://support.apple.com/en-us/102602