Intent Data
Intent data is behavioral information that signals when a person or company is actively researching products or solutions, indicating potential readiness to buy.
In depth
Intent data is collected from sources like content consumption, search activity, ad engagement, and on-site behavior, then aggregated into topic-level signals that flag accounts showing a spike in research. Vendors and platforms compare this activity against a baseline so a sudden surge in interest around a relevant topic becomes a prioritization cue for sales and marketing.
A frequent pitfall is treating any signal as a buying signal — a single whitepaper download rarely means an account is in-market, and noisy data drives reps toward dead ends. Within a quiz-funnel workflow, the explicit answers a respondent gives in your scorecard quiz are a clean form of intent: when someone states their problem, timeline, and budget, you capture far more reliable signal than passive third-party tracking alone.
Example in practice
Frequently asked questions
Where does intent data come from?
It comes from behavioral sources such as content consumption, search queries, ad clicks, and on-site activity. Providers aggregate these signals by topic to highlight accounts showing unusual research activity.
Is intent data always accurate?
No. Signals can be noisy, and a single action like one download rarely proves buying intent. Teams should combine multiple signals and validate with explicit data before acting.
How does a quiz capture intent data?
A scorecard quiz collects explicit answers about a respondent's problem, timeline, and budget. These declared inputs are a cleaner, first-party form of intent than passive tracking alone.