Definition
Third party intent data is a record of which companies are researching a topic on websites you do not own, such as publishers, review sites and ad networks. Providers match that reading to company names and report rises in interest. First party intent data is the same idea, collected on your own site and emails.
Why it matters when you sell B2B
Your own website only sees the few buyers who already found you. Third party data tries to see the rest of the market: companies reading about your category before they ever visit you.
It is popular because it scales. It is weak because the match from a reader to a company is often a guess, and reading is not buying.
A worked example
Say a provider reports 400 companies "surging" this week on a topic you sell into.
From a surge to accounts worth a callExample
- 400companies
Show a surge on the topic, according to the provider.
- 120companies
Also fit your ideal customer profile.
- 15companies
Show a second sign you can check yourself, from a different source: a job ad, a new leader, a pricing page visit.
Use the surge as a first filter, then look for a second sign you can check. Fifteen accounts with a checkable reason beat 400 with a score.
That is how buyer intent becomes something a rep can use. The reading happened somewhere you cannot see, in the dark funnel; the second sign is something you can.
Common mistakes
- 1Treating a surge as a lead. A surge says someone read something. It does not say who, or why.
- 2Not asking how the match works. Matching readers to companies by network address is error-prone, especially with remote work.
- 3Choosing topics that are too broad. A broad topic surges for students, job seekers and your own rivals.
- 4Letting the buyer know you watched them. Never mention the data in outreach. Use it to choose who, not what to say.
- 5Using one source only. Without a second, checkable sign, you cannot tell a buyer from noise.
Questions to ask an intent data provider
- How do you match a reader to a company?
- What share of matches are wrong, and how do you know?
- Which websites does the data come from?
- How recent is a surge when we see it?
- Can we test it against our own past deals before we buy?