Seedtag is stepping beyond conventional ad placement and into real-time predictive targeting. The company just launched its AI Intention Models, a new tool that helps advertisers reach people who are actively ready to take action—without collecting personal data.
The move is a big shift from keyword-based targeting. Instead of matching ads to broad categories, Seedtag now reads between the lines of what people are reading, and spots who’s just browsing versus who’s about to buy.
Contextual Advertising That Goes Deeper
Traditional contextual advertising works by matching ads with page topics or keywords. It’s been useful—but blunt. The same ad might be shown to someone doing light research and someone ready to make a purchase. That’s a missed opportunity.
Seedtag’s AI, called Liz, now goes further. It evaluates content not just by what’s being said, but how it’s being said. It looks at tone, sentiment, engagement level, and how far someone has gone in researching a topic.
For example, an article comparing leasing and buying a car might signal early-stage curiosity. But a detailed review of a specific vehicle might indicate the reader is ready to choose. Liz can now tell the difference.
How the AI Intention Models Work
These models aren’t static. They are:
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Trained with intent-specific datasets to tell the difference between someone who’s exploring and someone who’s evaluating.
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Campaign-specific, adjusting scores based on each brand’s goals and conversion paths.
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Dynamic in real-time, updating based on what’s happening with users and content across the open web.
This lets advertisers spend their budget more efficiently. Instead of spreading ads thin, they can zero in on moments that matter—when users are ready to take the next step.
Real-World Example: Nissan’s Campaign in Spain
Seedtag worked with Nissan to raise interest in the Qashqai among shoppers in the C-SUV segment. The campaign focused on users already comparing options or looking for deeper information—what marketers call the “evaluation” phase.
The results showed how effective the AI models could be. Nissan’s Cost per Quality Visit (CPQV) came in 68% lower than projected. Cost per Lead (CPL) dropped by 35%. And the number of qualified visits was three times the original goal.
José Manuel Muries, Cluster Director at Nissan United, called the results a clear improvement across all parts of the campaign. “With Seedtag’s intent-based segmentation, we reduced CPQV by 68% and improved performance across all stages,” he said.
Why This Approach Matters Now
Privacy rules are tightening. Cookies are going away. Many brands are struggling to reach relevant audiences without relying on third-party data.
Seedtag’s solution gives advertisers a way forward. By analyzing context instead of behavior, it sidesteps privacy concerns entirely. The result is a smarter strategy—ads based on what users care about right now, not on who they are or where they’ve been.
Where Seedtag Is Headed
Founded in 2014, Seedtag has grown into a global player in contextual advertising. Its AI technology, Liz, is already working across 10,000+ premium publishers. Now, with the introduction of intention models, Seedtag adds another layer to its strategy.
This shift makes context not just a way to show ads—but a signal for action. Advertisers don’t have to wait for conversions to see impact. They can target intent directly, improve efficiency, and measure performance in clearer ways.
More details about Seedtag and its AI Intention Models are available at seedtag.com.
Smart Ads Without Surveillance
In a market that’s moving away from personal tracking, Seedtag is offering a different route—one built on context, not cookies. With AI that spots intent in real-time, brands can finally connect with the right users at the right stage of decision-making. No privacy trade-offs, no guesswork.
