Intent data
Intent data is behavioral information that signals a company or person is actively researching a product, category or solution — indicating they may be in-market to buy. It includes first-party signals (activity on your own site and content) and third-party signals (content consumption and search behavior across a data provider's network of sites).
How it works
First-party intent comes from your own properties — pricing-page visits, demo requests, repeat content downloads. Third-party intent is aggregated by providers who observe research activity (topic surges) across many sites and attribute it to companies, flagging accounts showing spiking interest in your category.
Why it matters
Reaching an account while it is actively researching, rather than cold, dramatically improves relevance and timing. Intent data lets teams prioritize the accounts most likely to be in-market — but third-party intent is probabilistic and noisy, so it works best combined with ICP fit and first-party signals.
How Autocloz handles it
Autocloz captures first-party intent signals — email opens, clicks, replies, site and content engagement, call outcomes — on one contact timeline, so reps can prioritize the leads showing the strongest engagement without stitching signals across tools.
FAQ
What is the difference between first-party and third-party intent data?
First-party intent is behavior on your own channels (your site, emails, content) — high-confidence but limited to people already engaging with you. Third-party intent is research activity observed across a provider's network and attributed to accounts — broader reach but more probabilistic and noisier.
Is intent data accurate?
First-party intent is reliable because it's your own observed behavior. Third-party intent is a probabilistic signal — useful for prioritization but imperfect in attribution and timing. Treat it as one input alongside ICP fit and first-party engagement, not as a guarantee of buying intent.
Related terms
Lead enrichment is the process of automatically adding missing data to a lead or company record — job title, company size, industry, verified email, phone, LinkedIn, technographics — from third-party data sources, so reps can segment, personalize and prioritize without manual research.
An Ideal Customer Profile (ICP) is a description of the company that gets the most value from your product and is easiest to win and retain — defined by firmographics like industry, company size, revenue, geography and technology stack. It targets accounts (the company), distinct from a buyer persona, which describes the individual within the account.
Lead scoring is the practice of assigning a numeric value to each lead based on how well they fit your ideal customer profile (demographic/firmographic fit) and how engaged they are (behavioral signals like email opens, site visits, demo requests). The score ranks leads so sales works the hottest ones first.
A Marketing Qualified Lead (MQL) is a lead that has shown enough interest and fit — through behaviors like downloading content, attending a webinar or repeated site visits — that marketing deems it worth passing to sales for follow-up. It is more engaged than a raw lead but not yet vetted by a salesperson.