Intent Data

Intent data is any behavioral signal that suggests a prospect is actively evaluating a solution category right now, rather than sitting in a static ICP list with no recent buying activity. The signals come from multiple sources. First-party signals include website visit patterns, content downloads, pricing-page views, and demo requests on your own properties. Third-party signals come from providers like Bombora, 6sense, G2, and TrustRadius, which track research behavior across publisher networks and review sites. A prospect who downloaded three competitor comparison guides in the last fourteen days is materially different from one who has never engaged with the category.

For funded teams running outbound, intent data is the layer that turns a 500-touch-per-day cadence from cold to warm. The same AI SDR that researches an account against LinkedIn and funding signals also pulls intent signals from RB2B for anonymous site visits and from third-party providers for category research. Prospects showing high intent in the last 7 days get prioritized in the sending queue. The cadence still runs across the full ICP, but the high-intent slice receives touches first and gets the most heavily researched first message. Reply rates on the intent-flagged slice typically run 2 to 3x the baseline cadence.

Intent data is most valuable when combined with lead enrichment, not in isolation. Knowing a company is researching "AI ops platforms" tells you they are in-market. Knowing they raised a Series B six weeks ago, hired a new COO last month, and are growing engineering headcount tells you why and gives the first touch a specific angle to land. The combination is what separates a researched warm-feel email from a creepy "we saw you visited our site" note that trains prospects to delete future emails. The AI Sales Department operates this combination by default.