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Most B2B marketers are wasting ad spend because the intent signals they rely on are late, incomplete, and disconnected from how buyers actually research today. Buyers now learn privately—in LLMs, like ChatGPT, Claude, Gemini, and Perplexity) communities, and closed networks—long before they ever visit a vendor site. Intent still matters, but the old signalverse doesn’t. What matters now is how signals connect to real engagement, performance, and revenue.
Intent signals are meant to indicate when demand may be forming inside an account. The basic idea is simple: if people from a company are reading articles, visiting websites, and downloading guides related to a problem you solve, there’s a good chance they’re researching solutions. So the account gets flagged as “in market.”
That logic worked when digital behavior was scarce and easier to interpret.
Today, it breaks down.
Most third-party intent is aggregated, delayed, and disconnected from real outcomes. You’re not seeing buyers in motion. You’re seeing anonymous activity that may or may not matter by the time it reaches you. A page visit could be curiosity, a student, a competitor, or an AI crawler. Even multiple visits from the same company don’t tell you who’s involved, why they’re there, or whether it will ever turn into revenue.
The issue isn’t a lack of signals.
It’s trusting a signalverse that mistakes activity for intent—and intent for readiness.
Here’s the uncomfortable truth: you’re probably wasting a large portion of your ad budget right now.
When you run ads to your entire target market, you’re paying to reach thousands of companies that aren’t buying. Some are perfectly happy with their current solution. Some don’t know they have the problem you solve. Others just signed a long-term contract with a competitor.
Intent signals help you narrow your focus. They point you toward the part of the market where demand may be forming right now—not next year, not someday.
But targeting alone isn’t the win.
The real advantage comes from what happens after the signal—how accounts respond when you engage them, what messages resonate, which channels move them forward, and what actually creates pipeline.
Here’s what that shift enables:
Your ad budget goes further:
Instead of spreading $50k across 10,000 accounts, you concentrate spend on the few hundred showing meaningful buying behavior. Not just clicks—responses. Conversion rates improve because your ads show up where interest already exists.
Sales stops ignoring your leads:
When sales sees accounts that are already engaging with campaigns, content, and offers—not just showing anonymous web activity—they pay attention. Context replaces guesswork.
You close deals faster:
You’re no longer starting cold. Buyers have momentum. Your job is to reinforce it, not manufacture it.
The outcome isn’t better metrics.
It’s a clearer line from spend to pipeline to revenue.
Intent data comes in multiple forms. Each plays a role. None works well in isolation.
First-party intent signals are actions buyers take on your own properties—your website, product, emails, ads, and CRM.
They’re reliable because you know exactly where they came from. But they’re also limited and often late.
If someone from Acme Corp spends time on your pricing page, that’s a strong signal. But it only tells you how buyers are reacting to you, not how they formed their opinion before arriving.
Examples of first-party signals:
Visits to pricing or product pages
Multiple people from the same company engaging with content
Case study or guide downloads
Demo video views
Email opens and clicks
First-party data shows response.
It does not show the full buying journey.
Second-party intent fills the gap between first and third party data.
This is behavioral data from trusted partners and ecosystems—publishers, communities, events, platforms, and networks where your buyers actively learn and exchange ideas.
Examples include:
Engagement with industry newsletters and media
Participation in professional communities and Slack groups
Attendance at virtual events and roundtables
Interaction with platforms adjacent to your product
Second-party intent is powerful because it’s earlier than first-party, more contextual than third-party, and closer to how buyers actually make decisions today.
It gives you visibility into demand before buyers ever raise their hand.
Third-party intent signals come from data providers that track activity across large portions of the web. They monitor publisher networks, review sites, forums, and content consumption to identify which companies are researching specific topics.
This provides scale and market-level direction.
Third-party intent can show:
Which accounts are researching your category
Which companies are surging on relevant topics
Which businesses may be exploring alternatives
The downside is precision. Third-party intent is noisy, non-exclusive, and best used as a directional signal—not a trigger.
On its own, it’s a guess.
Combined with response and performance data, it becomes useful.
| Data type | Where it comes from | What you get | What you don’t get |
|---|---|---|---|
| First party | Your site, ads, CRM | Reliable response signals | Early context, off-site behavior |
| Second party | Communities, partners, publishers, review sights | Early, contextual insight | Full buyer identity |
| Third party | Data providers, networks, website | Market-wide direction | Precision, timing |
The real power doesn’t come from stacking intent sources.
It comes from connecting signals to outcomes.
A list of “hot accounts” doesn’t create revenue by itself. Signals only matter if you act on them—and learn from what happens next.
Instead of advertising to your entire ICP, focus on accounts showing meaningful buying behavior across multiple signals. Use intent to guide where you spend, not to decide everything for you.
The goal isn’t just clicks.
It’s observing how accounts respond when engaged.
If you know an account is researching your category, show them what’s most relevant to that stage.
Not personalization for its own sake—but relevance that removes friction and advances the conversation.
Sales doesn’t need more leads. They need context.
Instead of “50 people downloaded an ebook,” give them insight into why an account is being prioritized and what they’ve engaged with across channels.
That’s the difference between cold outreach and informed conversations.
This is where most teams stall. They collect intent data, review dashboards, and then stop.
Turning signals into revenue requires a system—not spreadsheets.
Bring first-party, second-party, third-party, and performance data together so you can see how accounts behave end-to-end.
Signals without outcomes are just activity.
“In market” isn’t a single action. It’s a pattern.
Define buying readiness based on ICP fit, signal consistency, engagement, and response—not one isolated spike.
Manual uploads don’t scale. Buying cycles move faster than weekly CSVs.
When signals change, audiences should update automatically. Campaigns should adapt in real time. Budget should follow performance, not assumptions.
That’s how you move at the speed of the buyer.
Intent signals aren’t magic. They won’t fix weak messaging or a broken sales process. But ignoring them—or trusting them blindly—is worse.
Winning teams don’t chase intent.
They use signals to learn what works, reinforce momentum, and invest where results show up.
Revenue doesn’t come from more data.
It comes from better decisions, made faster, based on real buyer response.
If you’re ready to stop wasting spend on cold accounts and start building systems that learn, it’s time to rethink how intent fits into your go-to-market motion.
Frequently Asked Questions (FAQ)
What is the difference between intent signals and engagement?
How much does intent data typically cost?
Can you use intent signals for account based marketing?
How long does it take to see results from using intent data?