Buying intent data is signal that indicates an account is researching a product category, evaluating vendors, or moving toward a purchase decision. It is captured from web behavior, content consumption, search activity, review-site visits, and direct interactions with the seller. Revenue teams use buying intent data to prioritize accounts, time outreach, and personalize messaging so the team works the accounts most likely to buy now rather than someday.
Common buying intent signals include: keyword research surges on tracked topics, repeated visits to comparison and pricing pages, downloads of evaluation content, review-site reads, and engagement with competitor properties. The intent data glossary catalogs the full vocabulary; buyer intent data covers a closely related construct that focuses on the individual buyer rather than the company.
Buying intent splits into first-party (signals on the seller's owned properties) and third-party (signals on the broader web aggregated by a vendor). Most mature programs combine both; first-party signal carries higher precision, and third-party signal extends coverage to accounts the seller has never seen.
Intent without fit is noise. Strong programs gate intent action through the ICP so reps do not chase signal from out-of-ICP companies, and they pair intent with engagement to confirm that the account is also responding to the seller's outreach.
Programs typically track three signal families: category-level surges (research on the broader product category), competitor signals (research on named alternatives), and adjacent-tool signals (research on prerequisite or complementary technologies). The mix informs how a rep frames the first conversation.
Engagement is interaction with the seller's owned touches. Intent is research behavior, often on third-party properties, that signals an active evaluation. The two are correlated but distinct.
Accuracy varies by vendor, topic, and account size. Mid-market and enterprise resolution is generally stronger than SMB. Backtest signals against closed-won pipeline before trusting them as triggers.
Most teams set a threshold that surfaces 10 to 20 percent of the TAL per week as actionable. Tighter thresholds reduce noise; looser thresholds widen coverage.
ABM platforms, CRM workflow, marketing automation, and sales engagement tools. Mature stacks centralize intent in a shared account graph so every system sees the same signal.
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