Intent data earned its place by answering a real question: which accounts should we work first? For prioritization, a topic surge is better than a static list. But over the last few years every team bought from the same intent vendors, fed the same signals to the same agents, and the edge flattened. The deeper problem was always there: intent is an inference about an anonymous account, and a vendor decision is made by named people. The gap between those two is where deals are won and lost.
Intent data, and where it stops working
Intent data tells you an account might be researching a topic. It can't tell you who, and it can't tell you a competitor is already in the deal. Here is what intent data is, where it breaks, and the verified signal that picks up where it leaves off.
What is intent data?
Intent data is information that suggests a company may be in market for a product, inferred from behavior like content consumption, keyword research, and website activity. It is almost always account-level, anonymous, and probabilistic: it estimates that an account might be researching a topic, not which named person is acting or what they decided. Teams use it to prioritize outreach toward accounts that look in market.
The types of B2B intent data
B2B intent data comes in three common forms, and all three share the same ceiling:
- First-party intent: behavior on your own properties, like website visits and content downloads. The most reliable, but limited to accounts that already found you.
- Third-party (bidstream) intent: topic research tracked across publisher networks and sold by data vendors. Broad reach, but noisy and anonymous.
- Co-op intent: signals pooled from a shared data network. Wider than first-party, still account-level.
Every type points at an account showing topic interest. None of them identifies the individual buyer, and none reveals which competitor that buyer is evaluating.
Is intent data accurate?
Intent data is probabilistic, so accuracy varies and false positives are common. Because most of it is account-level and anonymous, a spike can come from a researcher, a job seeker, a student, or a team with nothing to do with the deal. It cannot confirm a real buying motion or name a person. That does not make it useless, it makes it directional: good for sorting a list, not for knowing a specific deal has turned.
Where intent data stops working
The limits are structural, not a vendor quality problem:
- It is account-level, not person-level. It tells you a company is curious, not which buyer to call.
- It is anonymous and inferred. It is a probability, not a confirmed event, so a rep cannot act on it with confidence.
- It never names the competitor. The single fact that decides a competitive deal, who the buyer is evaluating, is exactly what intent cannot see.
- Everyone has the same feed. When every team buys the same intent and feeds the same agents, the output converges and the edge disappears.
What comes next: the verified, evaluation-stage signal
The evolution past inferred intent is a confirmed, person-level event. Instead of an anonymous account-level probability, it is a named buyer at one of your accounts who accepted a reachout from a named competitor, verified to the contact. Intent predicts who might be looking; this confirms which of your accounts a competitor is already inside, and names the rival, so a rep knows exactly who to reach and what is actually happening.
That is what Deal Intelligence provides: verified competitor activity in your accounts, delivered into Clay, Claude, your CRM, and Slack. For the head-to-head, see intent data vs verified competitor activity, Deal Intelligence vs 6sense, and which signals actually convert.
Questions, answered.
What is intent data?
Information that suggests a company may be in market, inferred from behavior like content consumption and keyword research. It is account-level, anonymous, and probabilistic: it estimates an account might be researching a topic, not which named person is acting or what they decided.
What is B2B intent data?
Intent data applied to business buying: signals a company is researching a category, from third-party (bidstream) networks, co-op data, or a vendor's own first-party properties. It points at an account showing interest, but does not identify the buyer or name the competitor they're evaluating.
Is intent data accurate?
It is probabilistic, so accuracy varies and false positives are common. Because most of it is account-level and anonymous, a spike can come from a researcher or an unrelated team, and it cannot confirm a real buying motion or name a person. It is directional, not a confirmed event.
What are the types of intent data?
First-party (your own site behavior), third-party or bidstream (topic research bought from publisher networks), and co-op (pooled from a shared network). All three are account-level and inferred; none confirm a named buyer or a named competitor.
How is verified competitor activity different from intent data?
Intent infers that an account might be researching a topic, anonymously. Verified competitor activity is a confirmed, person-level event: a named buyer accepted a reachout from a named competitor, verified to the contact. Intent predicts who might be looking; verified competitor activity confirms which of your accounts a competitor is already inside.
What is the best intent data alternative?
A verified, evaluation-stage signal. Instead of an anonymous account-level probability, Deal Intelligence supplies a confirmed event, a named buyer engaging a named competitor, delivered into Clay, Claude, your CRM, and Slack. It replaces a guess about who might care with evidence of who is choosing a vendor now.