Glossary
What is intent data?
Data that shows a company or person is researching a problem or product, so you can reach them while they're looking.
Definition
Intent data is information that shows a person or company is actively researching a problem, a product category or a specific vendor. Sales and marketing teams use it to reach buyers while they're in the market, instead of contacting everyone who fits on paper.
How intent data works
Buyers leave traces while they research: pages visited, content downloaded, reviews read, posts engaged with. Intent data collects those traces, ties them to a company or person where possible, and flags when activity on a topic rises above that account's normal level. The output is usually a list of accounts with topics and a score or surge flag.
Signals fade fast. A research spike this week means far more than one from three months ago, so most teams act on intent within days and drop it if nothing follows.
First-party vs third-party intent data
- First-party. Signals from your own channels: pricing page visits, demo page views, email clicks, webinar attendance, trial usage. Usually the most accurate, because the interest is in you specifically.
- Second-party. Another company's first-party data shared with you, such as a review site reporting which companies viewed your category or your profile.
- Third-party. Activity collected across many outside websites and publishers by a data provider, then sold. Wider reach, but noisier, and usually at the company level rather than the person level.
An example
Say you sell payroll software to restaurants. Third-party data shows a 12-location restaurant group reading about tip pooling compliance several times this week, and your own site logs show a visitor from that company on your pricing page. That account moves to the top of the list, and the opener talks about tip pooling, not payroll in general.
Why it matters for small teams
A small team can't contact everyone who fits its ICP. Intent narrows the list to accounts showing activity now. Start with first-party signals, which are cheap and precise, and treat third-party intent as a reason to research an account, not proof that someone wants to buy.
A common mistake is a message that reveals the tracking, like "I saw you were on our pricing page." Use the signal to choose who to contact and what to lead with, not as the opening line.
How Siela AI uses it
Siela AI's AI SDR can track keywords and competitors on LinkedIn and X and use keyword engagement and competitor engagement as signals. Its "Hot leads" mode contacts only people with a buying signal right now.
Questions
What is an example of intent data?
Employees at a company reading several articles comparing CRM tools this week is intent data. So is someone from a target account visiting your pricing page twice, or a prospect commenting on a competitor's LinkedIn post. Each suggests active interest in a problem you solve.
Is intent data accurate?
First-party intent from your own site and emails is fairly reliable, because it's about you. Third-party intent is probabilistic: it infers company interest from scattered activity, so expect false positives. Use it to prioritize research and timing, not as proof someone is ready to buy.
What is the difference between intent data and a trigger event?
Intent data shows research behavior, like reading about a topic. A trigger event is a change in a company's situation, like new funding, a new executive or a hiring push. Triggers suggest a need may exist, while intent suggests someone is already looking.
Less jargon, more conversations.
Siela AI finds people with a fresh reason to talk, reaches them on LinkedIn, X and email from your own accounts, and keeps your social going.