Glossary
What is intent data?
Intent data explained: what it is, first-party vs third-party intent, examples of B2B intent signals, and how sales teams use it to time outreach.
By the GTM Plays teamUpdated 2 min read
Definition
Intent data is information about the online behaviour of people or companies that suggests they are researching a problem, a product category or a specific vendor. Sales and marketing teams use it to prioritise accounts and time outreach for when a buyer is most likely to be interested.
Intent data is information about online behaviour that suggests a person or company is researching a problem, a category or a vendor. Examples include pricing-page visits, engagement with a competitor's LinkedIn posts, or reading about a topic across many sites. Sales teams use it to decide who to contact first and when.
Types of intent data
First-party intent
Signals from channels you own: website visits, pricing-page views, demo requests, product usage, webinar attendance and email engagement. It is the most reliable kind, because you see the behaviour directly.
Third-party intent
Signals from outside your channels: research activity across publisher and review sites, and public social activity such as following a competitor or commenting on posts in your category. It shows interest before a buyer ever reaches you.
Account-level vs person-level
Some intent data tells you that a company is researching a topic. Other data, such as public LinkedIn engagement, tells you which person is paying attention. Person-level signals are easier to act on, because you know who to talk to.
Examples of B2B intent signals
- Visiting your pricing or comparison pages.
- Engaging with, or following, a competitor on LinkedIn.
- Commenting on posts about the problem you solve.
- Hiring for a role linked to your category.
- A new leader joining a target account.
- Leaving a review of a competitor.
Our guide to buying signals ranks these by strength, and our roundup of LinkedIn buying signal tools shows which tools capture them.
How to use intent data well
- Combine intent with fit. Score every signal against your ideal customer profile. Intent without fit wastes time.
- Act quickly. Intent decays, so a signal is most useful in the days after it happens.
- Reference the signal. Mention what the buyer engaged with, without being creepy about it.
- Respect privacy. Use sources and methods that comply with the laws in your markets.
This is the core of signal-based selling.
Intent data and GTM Plays
GTM Plays puts intent data to work on LinkedIn. Its agent finds intent signals, scores each person for fit against your ICP, writes a message that references the signal, sends it from your own LinkedIn account, and brings replies into one inbox. You take the conversation from there. Start a 7-day free trial.
Frequently asked questions
What is an example of intent data?
Examples include a prospect visiting your pricing page, engaging with a competitor's LinkedIn post, following a competitor's company page, or an account researching your category across publisher sites.
What is the difference between first-party and third-party intent data?
First-party intent comes from your own channels, such as your website, product and content. Third-party intent comes from outside sources, such as publisher networks, review sites or public social activity.
Is intent data accurate?
It is a probability, not a guarantee. Intent data is most useful when combined with fit: a strong signal from a poor-fit account is still a poor lead.
How do sales teams use intent data?
To prioritise accounts, time outreach and write more relevant messages that reference what the buyer is actually paying attention to.
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