Intent data is one of the most hyped and least understood categories in B2B sales. Used well, it tells you which accounts are actively researching a purchase so you can reach them first. Used badly, it is an expensive list you never action. This guide keeps it practical.
What is intent data?
Intent data is any signal that indicates a company is researching or evaluating a solution like yours. It ranges from the content an account consumes across the web, to the roles they are hiring for, to the number of times a named person visits your pricing page. All of it points at the same question: is this account in-market right now?
First-party vs third-party intent data
- First-party intent is behaviour on your own properties: site visits, content downloads, product usage. It is the most reliable because it is directly about you, but you only see accounts that already found you.
- Third-party intent is behaviour observed across the wider web and public record: topic surges, funding, hiring, technographics. It reaches accounts that have not touched your site yet, at the cost of being noisier.
First-party intent is often more reliable than third-party, but the strongest programmes layer both together with ICP fit filters.
The main types of intent data
- 1Topic/content intent. Accounts consuming content about your category.
- 2Event intent. Discrete triggers: funding, hiring, leadership changes, expansion.
- 3Engagement intent. Direct interaction with you: site visits, opens, replies.
- 4Technographic intent. Adopting or dropping tools that imply a need.
Intent data needs a confidence hierarchy
Different observations deserve different levels of trust. Direct actions on your site sit closest to a purchase, but they cover a small slice of the market. Public events cover more accounts, but require interpretation. Topic surges can be useful for prioritisation, yet rarely provide enough context to write a credible first line on their own.
- High confidence: demo requests, repeat pricing visits, product expansion, and verified replies.
- Medium confidence: funding, relevant hiring, leadership changes, expansion, and explicit product initiatives.
- Supporting context: anonymous topic consumption, broad news mentions, and weak technographic inferences.
How to actually use intent data
The mistake teams make is buying intent data and treating it as a bigger list. Intent is only valuable if it changes your timing and your message. Filter every intent signal through your ICP first, so you act on fits rather than noise. Then anchor your outreach to the specific signal, and move fast, because intent decays.
Route intent to the right action
Not every signal should create an email. High-confidence first-party activity may justify a direct sales task. A strategic account with a relevant public event may deserve a researched message. Lower-confidence activity can update account priority, notify a territory owner, or wait until a second signal appears.
- 1Decide the minimum confidence required for each action before signals start arriving.
- 2Route strong matches to a person with the source and recommended angle attached.
- 3Accumulate supporting context instead of forcing every observation into outreach.
- 4Measure meetings and pipeline by intent type so routing improves over time.
The practical version of intent data for most teams is event-based buying signals: concrete, explainable, and free to source from public records. If that sounds more useful than an opaque intent score, read our guide to B2B buying signals, or start now with SignalSend and see the signals on your own ICP.