The B2B sales industry has spent the last decade chasing intent data. The premise was compelling: if you could identify which companies were actively researching your category, you could reach them at exactly the right moment. In practice, traditional intent data has become a victim of its own success. As more teams buy the same intent signals, the advantage disappears. And as the underlying data gets noisier, the signal degrades further.
I believe event data — tracking which companies sponsor, exhibit at, and speak at industry events — is emerging as a far more reliable and actionable intent signal. Here is why.
The Decline of Traditional Intent Data
Traditional intent data relies primarily on tracking online behavior: which companies are reading articles about your category, searching for relevant keywords, or visiting competitor websites. This data is collected through ad networks, publisher cooperatives, and reverse-IP tracking. The problem is threefold.
First, privacy regulations are killing the data supply. GDPR, CCPA, and the deprecation of third-party cookies have systematically degraded the accuracy and coverage of behavioral tracking. The signals that intent providers relied on five years ago are increasingly unavailable or unreliable.
Second, the signal is commoditized. When Bombora, G2, and TrustRadius all sell the same intent signals to hundreds of vendors in the same category, the data creates a race to the bottom. Every competitor reaches the same account at the same time with the same message. The advantage collapses.
Third, the correlation between online research and actual buying intent is weaker than the industry admits. An intern reading a blog post about CRM software does not mean the company is evaluating CRM tools. A junior analyst downloading a whitepaper does not mean procurement is active. The gap between content consumption and purchase intent is wide, and traditional intent data often cannot distinguish between the two.
Why Event Participation Is a Stronger Signal
Event participation is fundamentally different from online behavior as an intent signal. When a company sponsors an event, they are committing real money — typically $10,000 to $500,000 depending on the event and tier. When they exhibit, they are deploying a team, shipping equipment, and allocating weeks of preparation. When they send a VP to speak on a panel, they are publicly declaring expertise and interest in that topic.
These are not passive signals. They are active commitments that require budget approval, cross-functional coordination, and strategic alignment. A company does not accidentally sponsor a fintech conference. They do it because fintech is a market they are investing in. This makes event participation data inherently higher quality than behavioral intent data.
A $50,000 sponsorship tells you more about a company's priorities than a thousand page views on a competitor's website.
The Three Layers of Event Intent
Not all event participation signals are equal. There is a hierarchy. Sponsorship is the strongest signal — it represents committed budget and strategic market positioning. Exhibition is the next tier — it signals active selling and customer acquisition in that market. Speaking is a different kind of signal — it indicates thought leadership positioning and often precedes product launches or market entry. Attendee data, where available, is the weakest signal but still stronger than most digital intent data because it represents physical commitment and travel budget.
Operationalizing Event Data
The challenge with event data has always been operational. Event websites are messy. Sponsor logos are embedded in images. Exhibitor lists are in PDFs. Speaker bios are scattered across agenda pages. Extracting and structuring this data manually is painful, which is why most sales teams have historically ignored it.
This is exactly the problem we built Kuration to solve. AI agents can navigate event websites, extract exhibitor and sponsor lists regardless of format, structure the data, enrich it with firmographic and contact information, and deliver outreach-ready lists. What used to take a junior analyst three days now takes under five minutes.
The playbook is straightforward: identify the 20–30 events most relevant to your ICP, extract sponsor and exhibitor data from each before and after the event, enrich with decision-maker contacts, and route the leads into your outreach sequences. Companies that do this consistently build a prospecting pipeline that is both higher quality and completely differentiated from what their competitors are working with.
The Compounding Advantage
What makes event data especially powerful is how it compounds over time. When you track which companies exhibited at the same event last year and this year, you can infer ongoing market commitment. When a company increases their sponsorship tier, that signals growing investment. When they start exhibiting at adjacent events in new geographies, that signals expansion. None of this longitudinal intelligence exists in traditional intent databases. But teams that build and maintain their own event data sets gain a compounding informational advantage that becomes harder for competitors to replicate over time.
The era of generic intent data is ending. The teams that win the next decade of B2B sales will be the ones that find and operationalize better signals. Event data is not the only answer, but it is one of the most underutilized and highest-quality signal sources available today.
