Intent data: what it is and how to read it
Intent data is the difference between guessing who will buy and knowing who is looking right now. We explain where it comes from, how reliable it is and how to turn it into action.
Imagine you could know which companies are actively researching a solution like yours, this week, before they fill in any form. That is what intent data promises. The promise is powerful, but also surrounded by hype. Let us put it in its place.
What intent data actually is
Intent data is behavioral signals that suggest a person or company is in a buying process. It is not an explicit statement ("I want to buy"), but a pattern that correlates with intent: content consumption on a topic, repeated searches, provider comparison, product-page visits, company changes.
Where it comes from
There are two big families. First-party intent happens on your own channels: who visits your site, what they download, what emails they open. Third-party intent comes from data networks that observe content consumption across many sites and aggregate it by topic and account.
First-party is the most reliable but the most limited in volume. Third-party widens the radar but requires more care: it is probabilistic, not certain. A good capture system combines both and cross-references them with firmographic data to reduce noise.
- Content consumption about your category
- Searches and provider comparisons
- Recurring visits to product pages
- Organizational changes (new lead, funding round)
- Adoption or abandonment of competing technology
- Engagement with campaigns and events
The false-positive problem
Intent is not destiny. A company can consume content on a topic out of curiosity, for training or because an employee is writing a report. Treating every signal as a hot opportunity leads to contacting at the wrong time and burning credibility. That is why intent should be weighted, not obeyed.
The serious way to use it is to combine it: an intent signal on an account that also fits your ICP and has the decision-maker identified is worth a lot. The same signal on a company that does not fit is worth almost nothing. Intent sharpens prioritization; fit still rules.
How to read it and act
- Filter by fit first: discard signals from accounts that are not your ICP.
- Weight the strength of the signal: an isolated visit is not a sustained pattern.
- Cross with the account moment: recent changes amplify intent.
- Define a next action per signal level; do not contact everyone the same.
- Measure the result and re-tune the thresholds: intent is calibrated with real data.
Used well, intent data turns outbound from a blind shot into an aimed one. Used badly, it is an expensive excuse to spam. The difference is in the rigor with which it is filtered and weighted before it reaches your team.