AdTech Collective by Seedtag

Sep 2026

mins

Publishers, agencies, and brands don't always sit on the same side of the table. But at the end of the day, they're facing the same challenge.

For publishers, the question is how to create content relevant enough that brands and agencies want to advertise within it. For agencies, it's where to place their clients and which environments are truly brand safe. For brands, it's where to invest to build a closer connection with their customers. The perspectives are different, and so are the priorities. But the challenge is shared: as the way people discover information keeps evolving, quality content needs to keep being found, valued, and sustained.

That challenge was one of many conversations we brought to Barcelona. From September 15 to 17, the Seedtag Innovation Summit gathered clients and partners from the United States, Latin America, and Europe, opening at the Joan Miró Foundation.

During the Summit, Brian Gleason, our CEO, added another layer: "We're more connected than we've ever been, but we're more distracted than we've ever been." For Brian, finding out how to connect in that moment is the most important thing, whether you're a brand, an agency, or a publisher.

The agenda combined dedicated sessions for the supply side and the demand side with joint sessions that put both in the same room. Topics ranged from the agentic shift and AI search to attention measurement, brand safety, CTV, creative, and life after the traffic. At lunches and dinners, the conversations kept going.

Across all of them, one thing became clear. The challenges facing the adtech ecosystem aren't local. They're global. And they become easier to solve when both sides look at them together.

Key Takeaways

Consumers are more connected and more distracted than ever, and connecting with them in the moment matters for brands, agencies, and publishers alike.
The same person makes different decisions in different situations, shaped by signals like time of day, screen, weather, and place.
Fewer impressions carry identifiers, but audiences haven't gone anywhere, and reaching them requires a new structure.
Interest, emotion, and intent shape how people process advertising, while viewability alone says nothing about that processing.
Publishers, agencies, and brands face the same challenges from different perspectives, and the conversation is global, spanning the United States, Latin America, and Europe.

What Are the Biggest Challenges Facing the Digital Advertising Landscape?

Throughout the Summit, Brian Gleason put the consumer at the center of the conversation. For him, it's the one thing the industry doesn't focus on enough. We talk about acronyms, LLMs, and chats, but rarely about what consumers are doing every day or what their world is like.

And that world is full of noise. Attention is fleeting, and capturing it is hard. At the same time, clients are under pressure to grow and differentiate, and Brian raised an open question about what happens to them as products become commoditized in AI chat environments.

Grego Martínez, our Chief Product Officer, pointed to another challenge: media buying itself.

In CTV, most buying happens at the platform level, yet streaming services rarely have exclusive content. To illustrate the point, Grego shared a simple example: in Spain, Harry Potter is available on eight different platforms. So when a brand buys one of them, it's buying the service, not the moment. It learns nothing about the show being watched, the emotion it creates, or the hour and day it's being seen.

Buying through demand side platforms (DSPs) has a similar limitation. Brands and agencies can target IAB categories, keywords, domains, geography, or day part, but combining all of those signals to build moments manually is very complicated. The signals exist, but programmatic fragmentation keeps them apart.

Why the Adtech Ecosystem Is Moving From Understanding the Who to the Moment

For Grego, solving that fragmentation starts with a simple idea: the same person can make very different decisions depending on the situation they're in.

Picture someone commuting to work on a rainy Monday morning, phone in one hand, about to lose connection in five or six minutes. Any message has to be fast. Now picture the same person on a sunny Sunday morning, planning the week ahead with Monday off. They might spend 90 seconds on a powerful long video, one that takes them to the next step.

Nothing about them has changed. Only the moment has.

The same happens with a recipe. On a Tuesday evening after work, someone looking one up wants something fast. On a Saturday morning, with family and friends coming over, they're far more open to a message tied to that interest. The article is exactly the same. The moment is not.

That's why content is only one piece of context. The hour, the day of the week, and the season all matter. So do the type of screen someone is using, the weather, and the place they're in. On their own, these signals won't massively improve advertising. Combined, they create a scenario where advertising works much better.

Moments also change across environments. On mobile, things happen faster. On desktop, people are usually sitting down and paying more attention. CTV is often watched in a group rather than alone.

"We've spent more than 20 years understanding the who. Now, I think the future will be won by those who understand the moment much better," Grego said as he closed his session.

Audiences Were Never Identifiers

Hannes Sieling, our VP of Data & AI, started from programmatic advertising's long reliance on identifiers. They gave data teams structure, plus the reach to find people again. Today, fewer impressions carry them, but the reality hasn't changed. The same people are consuming the same content. And audiences were never identifiers in the first place.

What the industry needs is a new structure, built around the content people consume. That's the idea behind vector-based targeting: grouping similar content together so brands and agencies can find the environments closest to their goals, while balancing reach and precision.

Hannes also pointed to the technology that makes this possible: "Embedders are a little bit the hidden champions, the unsung heroes of the whole rise of large-language models."

The real question is what counts as similar. For him, the answer needs to go beyond clicks or categories and help find the right environment at the right moment. Understanding how people actually process what they see is a key part of that answer.

The Science Behind Attention, Emotion, and Intent

Professor Tino Meitz from the University of Münster explained how people process advertising. Who we are stays fairly stable, but how we feel and what we're focused on can change in milliseconds. When people consume media or advertising, that state of mind matters most.

That's also why viewability isn't enough. It shows that an ad could be seen, but says nothing about whether it was actually processed.

Three contextual signals shape that processing:

Interest: If people aren't motivated to watch a show, they're unlikely to engage with the advertising within it.
Emotion and affect: The brain relates new situations to past experiences, so a context that connects to familiar feelings makes new information easier to process.
Intent: People need to be in the right situation for a message. If you want to buy a mid-sized SUV, you probably won't walk into a Ferrari dealership.

Tino was careful to separate affect from emotion: "Affect is something you can't govern. It's something that's happening, it's also, to a certain extent unconscious. Emotion is an evaluation of your affect afterwards."

How Can Supply and Demand Collaborate Across the Adtech Ecosystem?

Rob Beeler, who led the Two Sides, One Signal working session, explained why collaboration and supply and demand alignment matter. “Both sides are trying to solve the same things. This is a relationship-driven industry, and relationships are built by talking to each other in person. When both sides start working together, he said, they can be more effective for advertisers”, he said.

Kevin Donker, Head of Programmatic & Media Automation at Omnicom Media, brought that same spirit to the agentic conversation. For Kevin, agentic buying is still in its infancy, and the industry will have to come together to adopt protocols that make it reliable. When that happens, the productivity gains from AI should be reinvested in people.

In his view, the winners will be organizations that use AI to boost creativity, leadership, and judgment. The ones left behind will simply put an AI layer on top of an already fragmented workflow.

Brian Gleason echoed that idea in his closing remarks. He pointed to the feedback shared over the three days on different ways of working, ad inventory sources, and ways to measure. He also stressed the importance of trust: when you know you can trust someone, you know they'll do what they say they're going to do.

"There are a lot of pressures and challenges we think about in the world, and the things we shared over the last few days were brilliant. That's what we love to do: share information. It's an ecosystem that works together, and that's what we're trying to create", Brian Gleason.

How Does Neuro-Contextual Advertising Bridge the Gap Between Supply and Demand?

If both sides face the same challenge, they also need a shared way to understand the moment. That's what Neuro-Contextual Advertising offers.

Liz, our Neuro-Contextual AI, reads signals of interest, emotion, and intent to understand the moment behind each impression, without personal data or identifiers. For brands and agencies, that means reaching people when it matters most. For publishers, it means their content is valued for the moments it creates.

And it goes beyond advertising. Bringing value back to the open web helps keep quality content alive, and that's a responsibility the whole industry shares.

From Barcelona to the Next Conversation

Over three days, publishers, agencies, and brands from the United States, Latin America, and Europe approached the same questions from different perspectives. How do we capture attention? How do we reach audiences without identifiers? How do we make sure quality content keeps being found and valued as the way people discover information changes?

For us, at Seedtag, those conversations reinforce the vision behind Neuro-Contextual Advertising: understanding people's interest, emotion, and intent in the moment they're in.

It's not about knowing who. It's about understanding the moment.

Thank you to everyone who joined us in Barcelona. If you'd like to keep the conversation going, our team is here.

Highighted

From Vector to Meaning: Understanding the Moment with Agentic Audiences

AdTech

Sep 2026

mins

The loudest conversation in advertising right now is about agents: buyer agents who plan campaigns, seller agents who respond to them, and standards that let the two talk. Yet a quieter, more consequential evolution is taking place beneath the noise. The industry is finally agreeing on how agents should describe an audience: as an embedding, a point in a mathematical space where "similar" is a distance you can actually measure.

Media has named the practice vector-based targeting. The IAB Tech Lab has now standardized it as Agentic Audiences. For us, at Seedtag, this isn't a new trend. It’s the exact foundation we’ve been building on for years.

Key Takeaways

A vector is only as good as the model behind it. Standardizing vectors gives the industry a common language for describing audiences, but it doesn’t standardize what those vectors actually mean. The training behind the model determines what “similar” really means.
Traditional targeting misses the moment. Behavioral data tells us what someone has done, language tells us what content is about, and taxonomies tell us where content belongs. None fully understands the reader's current state of mind.
The future of targeting is about finding the right moment, not just the right audience. As agentic advertising develops, shared audience standards will become increasingly important. But the real competitive advantage will come from the quality of the underlying map: understanding an audience’s interests, emotional state, and intent as they unfold in real time.
Content alone isn't enough either. The same article read at different moments carries different value, which is why moment, not just meaning, has to be built into the map.

‍

A little context before we get to the point. We wrote a full introduction to vector-based targeting and vector embeddings in an earlier post. Put simply, an embedding is how an AI translates content—a webpage, a video scene, a TV show, or a campaign brief—into a position on a map. A map of meaning. The model reads the content and places it so related concepts sit close together, regardless of the exact words used. A pressure-cooker review and a weeknight-stew recipe land near each other; a match preview and a mortgage guide land far apart.

‍Vector-based targeting is simply buying the impressions that cluster around that map location. You describe what you want as a starting point—the seed—and buy the impressions closest to it. The seed can come from a plain language brief like "home cooks upgrading their kitchen”, or from a brand's first-party data showing what its existing customers are engaging with, landing on the same map as coordinates. Two things follow immediately. Reach becomes flexible: widen the circle around your coordinate, and you expand your scale.

Distance becomes a score: how well does this impression fit this audience? Measure how close it sits. There are no keyword lists to maintain because the geometry does the judging. In fact, the new standard even comes with an open-source scorer that demonstrates this exact embedding-to-audience matching.

The map of meaning. Every dot represents a page, TV show, or images and video resources mapped purely by context so related topics cluster together. A brand's brief or first-party data lands as the seed point. Targeting captures the content nearby—widen the circle for scale, or measure the distance to judge the fit.

So, is audience targeting solved? Not quite. The IAB standard makes it easy to agree on the benefits of using vectors, but it leaves the real challenge untouched: what those vectors actually mean. It doesn't define how a vector should be trained, nor what makes one location in the map of meaning superior to another. In fact, the standard leaves the real challenge untouched by requiring buyers and sellers to use the exact same model; otherwise, their vectors can't be compared. But meaning lives in the model, not in the envelope. The hard part hasn't been standardized. It has been named.

A Vector Alone Doesn't Solve Targeting

Why is everyone turning to vectors in the first place? To reclaim the reach lost as user IDs disappear. Cookies are fading, and vast parts of the Open Web and CTV are out of reach. But let’s be clear: a vector alone doesn’t magically restore that reach with precision. It simply shifts the core question: reach toward what? Similar to whom, and based on what?

“Close” on a map only means something because of how the map was drawn: items are close because of what the AI model was trained to see as similar. So the critical question to ask any vendor pitching vector-based targeting isn't, “How many dimensions do you use?” It's: “What did you train the model to consider similar, and why does that definition serve my campaign goals?”

Two Ways the Industry Builds Embeddings, and What Both Miss

Embeddings built from behavior. Inside the big, logged-in walled gardens, this is a proven formula: model what users did (clicks, views, purchases) and represent each person by their history. It works in this setting because the platforms see every action of every logged-in user. But this breaks down on the Open Web, where signals are sparse, identities are fragmented, and interests evolve faster than models can adapt. Behavioral models also suffer from a subtle bias: they learn exclusively from audiences a platform has already reached, making them brilliant at finding more of the same while remaining blind to receptive audiences who never happened to log in.

Embeddings built from language. The other route is to build a space from text, and the off-the-shelf embedding models anyone can license do exactly that. To be fair, they're genuinely good at semantics: two pages don't need to share a word to sit close together; modern models understand the underlying meaning. But semantic proximity isn't the metric a media plan relies on. Two pages about the exact same topic can perform completely differently: one crackles with curiosity, the other drips with anger. The meaning of the text isn't the meaning of the moment.

The pre-vector baseline—the traditional taxonomy—isn't even a space; it's just a lookup table. A page matches a category, or it doesn't. There's no concept of "close," and no room to expand.

Here's what all three miss: the moment. Behavior tells you who: that someone once did something similar, not whether now is the moment. Language tells you what the text means, not the emotional impact on the user. A taxonomy tells you which shelf the page sits on. None of them evaluate the reader's current state of mind—the interest, emotion, and intent surrounding an impression. And those signals are present on every single impression, on every device, with no identifier required.

How Our Embeddings Go Further

This is where years of experience matter. Off-the-shelf vector spaces weren't built for media performance, so we trained our own. And it's the training, not the architecture, that takes AI beyond language understanding and gives it a human-like understanding of interest, emotion, and intent.

The Seedtag Neuro-Contextual embeddings model reads three signals from every piece of content: Which interest is it relevant to? What emotion does it trigger? What intent does the reader bring—is it just browsing, actively learning, or ready to buy? Those three signals aren't tags stapled on afterward; they're core coordinates baked directly into the map. Built on more than a decade of contextual inventory, with hundreds of millions of pages and hundreds of thousands of videos and shows analyzed, our space is continuously shaped by real impression performance. So on our map, “close” doesn't mean “uses similar vocabulary.” It means “performs similarly for the same type of campaign brief.”

Two examples show why this matters:

Consider two football articles filed under the exact same taxonomy node: a transfer rumor charged with curiosity and a post-match report heavy with anger. A rigid taxonomy puts them on the same shelf, but our model reads the emotional tone, pushing them far apart on the map where targeting decisions are made. The taxonomy isn't enough; the content reading is what tells these two apart.

Now imagine reading just one of those articles twice: on your phone during the morning commute versus late at night on the sofa. Same words, same inferred interest and emotion, but not the same context—and not the same value to a brand. Reading the content alone isn't enough either. Content × the moment is what really matters.

Same taxonomy shelf, different moments. A lookup can't tell the two articles apart; in Seedtag's space, emotion and intent push them far apart—and distance is exactly what targeting acts on.

The same is true for individuals. A single reader experiences a curious morning, a distracted lunch break, and a relaxed evening all in one day. User identifiers flatten this nuanced journey into a single label: “sports fan.” But reaching the same user in different moments requires fundamentally different approaches.

This brings us to the “neuro” in Neuro-Contextual, because precision matters here. We didn’t put neuroscience inside the model: decades of research established which dimensions drive attention, memory, and receptivity (emotional state, motivation, timing), and our models operationalize those constructs at a scale no lab could reach. Whether the model’s interpretation matches human response is testable, and we keep testing it against measured human behavior. Neuroscience identifies what drives human attention; machine learning delivers the scale; real-world testing proves it works.

And because the tech is ours, the same approach can go further. For strategic partners, we can build custom fine-tuned embeddings that continuously adapt the space to their specific domain and its goals. Take travel: a fine-tuned embedding could learn the nuanced differences between audiences interested in luxury resorts, mountain hiking, or city sightseeing, recognizing the distinct interests, contexts, and emotional drivers within each. Over time, it can build a richer, domain-specific embedding space from new insights and real campaign performance, while preserving everything the Seedtag Neuro-Contextual embeddings already understand.

The industry is finally agreeing on how agents should describe an audience. That’s real progress, but it’s a bit like agreeing that everyone will give directions using a map: useful only if the map is any good. Standardizing the coordinates doesn’t make the underlying geography more accurate.

A map drawn from the words on a page will send you to pages that sound alike. A map drawn from what people clicked last month will send you back to the audiences you already reached. A map drawn from how people actually experience those pages sends you somewhere more valuable. What are they interested in? How does the content make them feel? What are they trying to do, and at what moment? Answer those, and you're pointed toward impressions that are more likely to perform. The distinction matters because the industry isn't really trying to find things that are similar. It's trying to find the right opportunities.

Where the Agentic Future Is Headed

Which brings the conversation back to agents. We share the excitement about what agents can do, but we also believe their potential depends on the quality of the models they interact with underneath.

Agents won't act at the level of a single bid request or a single embedding; that layer belongs to smaller, faster models. Agents will plan, negotiate, and activate at the audience level, interacting with models that understand the underlying meaning of content and audiences. Because even the most sophisticated agent won't reach the right destination if the map underneath it doesn't describe the landscape accurately.

That's why the conversation between agents and what they exchange must be about understanding, not bags of numbers. A seller agent should be able to explain what an audience is made of, show its value, and make the case for why it matters. Ours already does: our Liz Agent builds an audience from a plain-language brief and explains every component.

Language in, geometry underneath, explanation out. That’s the agent-to-agent conversation worth standardizing.

Highighted

Sports Advertising: Why Context Wins in Live Streams

Sep 2026

mins

Live sports have never attracted bigger audiences, but they have also never been more expensive to deliver. As media rights continue to rise, subscription growth slows, and viewing fragments across multiple digital platforms, sports advertising has become increasingly important to sustaining premium content.

For rights holders, broadcasters, and sports leagues, the challenge is no longer simply selling more ads. It's creating advertising experiences that keep sports fans engaged while generating greater value for advertisers.

In this episode of The Pub Way Podcast, Mike Villalobos and I spoke with Scott Young, Co-Founder and Chief Product Officer at Transmit, about how in-stream advertising is reshaping live sports.

Rather than relying exclusively on traditional commercial breaks, Scott explains how contextual advertising experiences built around real-time moments can create new inventory, improve viewer engagement, and unlock better outcomes for publishers and brands.

Key Takeaways

Ad-supported streaming is becoming essential as subscription growth slows and media rights become more expensive.
In-stream advertising creates new, addressable inventory beyond traditional ad pods.
Contextual ads tied to live moments generate stronger engagement than generic placements.
Cross-device attribution remains one of the biggest measurement challenges in sports advertising.
Industry-wide standards will be just as important as new technology to support future innovation.

Why Sports Advertising Is Moving Beyond Traditional Ad Breaks

For decades, sports marketing strategies centered around a familiar model: commercial breaks inserted into natural pauses in the game. But as streaming audiences grow and premium sports rights become more expensive, simply increasing the number of ad slots is no longer enough to support sustainable monetization.

Instead, Scott sees the future in in-stream advertising. Picture-in-picture placements, dynamic overlays, and contextual graphics allow advertisers to engage viewers while the action continues, creating new inventory without disrupting the viewing experience.

Rather than adding more ads, the goal is to create more relevant ones that complement the moment instead of interrupting it.

Why Context Matters More Than Ever

One of the biggest sports marketing trends is the growing importance of real-time relevance.

Transmit's platform identifies key moments during a sporting event, including a touchdown, home run, or game-winning play, and uses them to trigger contextual advertising. That allows brands to respond to what sports fans are experiencing in real time. A fan whose team has just scored might see a celebratory message, while fans on the other side receive different creative.

Scott compared this approach to meeting someone at a conference. The best conversations don't begin with a sales pitch; they begin by understanding what the other person cares about. Advertising works the same way. When brands respond to the moment viewers are already experiencing, advertising becomes part of the experience instead of an interruption.

While live sports provide some of the clearest examples, the same approach applies across FAST channels, news, and entertainment, wherever real-time context can make messaging more relevant.

What Challenges Do Advertisers Face with Cross-Device Attribution?

As live sports continue expanding across connected TVs and other digital platforms, measuring campaign performance has become increasingly complex.

Scott explained that a single connected TV may represent one viewer or an entire household, making it difficult to understand who actually engaged with an ad. Privacy restrictions add another layer of complexity, limiting advertisers' ability to connect exposure on one device with actions taken on another.

Although second-screen experiences offer significant potential, the industry still needs stronger cross-device measurement and greater standardization before advertisers can fully understand campaign performance across multiple devices.

What Results Are Brands Already Seeing?

Despite those challenges, contextual in-stream advertising is already demonstrating measurable impact.

Scott shared research showing ten times greater message recall compared with traditional ad pods. When context, creative, and timing aligned, viewers were also 20% more likely to take action, such as scanning a QR code. Additional studies measuring offline outcomes found that campaigns generated five times the return on ad spend in retail environments.

These results reinforce a broader shift in sports marketing: success depends less on increasing the volume of advertising and more on delivering experiences that feel relevant to viewers in the moment.

Looking Ahead

As premium properties like the Super Bowl, the World Cup, and other major sporting events continue attracting massive audiences, the future of sports advertising will depend on delivering more personalized experiences that respond to what viewers are experiencing in real time.

For Scott, innovation isn't simply about adding new technology. It's about building common standards across platforms so publishers, advertisers, and technology partners can work together more efficiently. Combined with smarter in-stream advertising, that collaboration can help create better experiences for viewers while opening new monetization opportunities for sports teams, media companies, and brands alike.

Watch the full episode of The Pub Way Podcast to hear Scott Young share how contextual, in-stream advertising is reshaping the future of live sports.

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Cannes Lions 2026: The Advertising Trends Shaping This Year

Jun 2026

mins

Every year, the Cannes Lions Festival offers a glimpse into where advertising is heading next. But Cannes Lions 2026 arrives at a moment when the industry feels fundamentally different.

Across the Croisette, inside the Palais des Festivals, and throughout Cannes France, this year, one theme is expected to shape many of the biggest conversations: relevance is becoming intelligence-driven.

The advertising industry is entering a new phase. For years, digital media optimized around identity resolution, automation, and user-level targeting. But today’s environment looks far more fragmented. Attention moves constantly between streaming platforms, creator ecosystems, connected TV, mobile experiences, and AI-generated content environments. Privacy expectations continue to rise. Identity signals continue to weaken. And consumers are exposed to more content than ever before.

In this landscape, scale alone no longer creates advantage.

The brands, publishers, and platforms expected to stand out in this year’s Cannes Lions advertising conversations are likely to focus on something deeper: understanding context, attention, and mindset in real time.

That shift is expected to define many of the most important advertising trends discussed across Cannes Lions 2026.

Key Takeaways

Cannes Lions 2026 conversations are expected to focus heavily on AI, contextual relevance, and attention-based advertising.
The advertising industry is continuing to shift from identity targeting toward understanding moments, interests, intent, and emotion.
Premium media environments are likely to become even more valuable as AI-generated content saturation increases.
Publishers are expected to prioritize AI solutions that improve monetization without relying on identity-based targeting.
Creativity and context are becoming increasingly interconnected across Cannes Lions Festival discussions.

The Industry Is Moving Beyond Identity

One of the clearest trends expected to emerge from Cannes Lions 2026 is the growing shift away from identity-based advertising models.

For over a decade, digital advertising optimized around audience profiles, identity signals, and user-level targeting. But the effectiveness of those systems is becoming harder to sustain in a privacy-first environment shaped by fragmented media consumption and signal loss.

At the same time, consumer attention itself has become more dynamic.

People move fluidly between premium editorial content, streaming platforms, live sports, creator ecosystems, and mobile experiences throughout the day. The emotional and cognitive environment surrounding attention changes constantly depending on context.

This is reshaping how marketers think about relevance.

The future of advertising is no longer about collecting the most data on consumers. It is increasingly about understanding the moment people are in when they engage with content.

That includes:

emotional alignment,
contextual relevance,
audience mindset,
and real-time intent.

Across Cannes Lions Festival conversations, this shift is expected to become increasingly visible. The industry is moving from targeting users toward understanding environments where attention naturally concentrates.

Context is no longer simply a targeting tactic. It is becoming the intelligence layer behind modern advertising.

AI Is Becoming About Quality, Not Just Automation

Artificial intelligence is expected to remain one of the dominant themes across Cannes Lions 2026. But compared to previous years, the conversation around AI is likely to feel far more mature.

Earlier industry discussions focused heavily on automation, scale, and content generation. This year, marketers are expected to ask more advanced questions about quality, adaptability, and human understanding.

As AI-generated content rapidly expands across the open web, abundance is creating noise. Consumers are being exposed to more information, more ads, and more media experiences than ever before. As a result, premium environments and contextual relevance are becoming increasingly valuable.

This tension is expected to shape many of the Cannes Lions advertising conversations happening across Cannes this year.

AI alone is no longer the competitive advantage. Intelligent relevance is.

Marketers are increasingly exploring how AI can improve contextual understanding, strengthen creative performance, and help advertising feel more aligned with the surrounding moment rather than simply optimizing delivery.

This shift is expected to make contextual AI more important across modern advertising infrastructure.

Not as a replacement for creativity, but as the intelligence layer that allows creativity to perform better.

Publishers Want Sustainable Monetization

Another major trend expected to shape Cannes Lions 2026 is the growing focus on sustainable publisher monetization.

For publishers, AI conversations are no longer theoretical. They are operational.

Premium media companies are navigating:

rising privacy expectations,
evolving monetization pressures,
fragmented identity signals,
and increasing competition for advertiser attention.

Publishers are expected to look for technologies capable of connecting premium content with meaningful advertiser demand without relying on identity-based targeting or outdated assumptions about audiences.

This conversation is expected to become especially important across connected TV and premium video environments, where attention remains highly engaged but identity-based targeting has become increasingly inconsistent.

As CTV budgets continue to grow, publishers are also looking for better ways to communicate the value of their streaming inventory beyond traditional reach and frequency metrics. Increasingly, the focus is shifting toward content-level relevance, viewer attention, and contextual signals that provide a deeper understanding of audience engagement.

For both publishers and agencies, this represents an opportunity to rethink how premium video environments are bought, sold, and measured. Rather than relying exclusively on household-level targeting, the industry is beginning to explore approaches that align advertising with the content being consumed, helping brands connect with audiences in more meaningful ways.

Across Cannes, many discussions are likely to focus on how publishers can monetize premium content more intelligently while maintaining trust, quality, and long-term sustainability.

The broader shift is becoming increasingly clear.

The future of monetization is moving away from surveillance-driven personalization and toward smarter contextual understanding capable of interpreting nuance, emotional tone, and audience mindset more effectively.

Creativity Still Depends on Context

Cannes Lions has always celebrated creativity. But one of the strongest themes expected to define Cannes Lions 2026 is the growing relationship between creativity and context.

Even exceptional creative can fail when it appears in the wrong environment or disconnected from the surrounding moment.

People respond differently depending on what they are reading, watching, feeling, and experiencing at a given time. A message that resonates during a live sports moment may feel completely disconnected inside a financial news environment later in the day.

Context shapes attention.

That idea is expected to become central to many of the conversations happening across Cannes this year. Marketers are increasingly exploring how advertising can become more adaptive, emotionally aligned, and responsive to audience mindset across fragmented media environments.

This is especially relevant across streaming, connected TV, and mobile ecosystems, where traditional identity targeting models have become less reliable.

For many industry leaders, that challenge is also becoming an opportunity.

The opportunity is to build advertising systems designed around understanding moments rather than tracking users.

The Future of Advertising Is Intelligent Relevance

Looking ahead, Cannes Lions 2026 is expected to reflect a broader transformation happening across the advertising industry itself.

AI is becoming more intelligent. Context is becoming more dynamic. Creativity is becoming more connected to emotion and attention. And advertising is becoming increasingly human-aware.

The conversations expected to shape Cannes Lions this year suggest the industry is moving toward a new model built around intelligent relevance at scale.

Not surveillance-driven personalization. Not static audience assumptions. Not automation for its own sake.

But advertising capable of understanding the emotional and cognitive environments surrounding attention itself.

Because the future of advertising will belong to the brands that understand the moment best.

Open Web vs Walled Gardens: Why Transparency Matters More Than Ever

Jun 2026

mins

AdTech

For years, the advertising industry has debated the merits of the open web vs. walled gardens.

The conversation usually centers on scale, targeting, reach, and performance. Which environment offers better audiences? Which delivers stronger results? Which deserves a greater share of media investment?

Those questions still matter. But they are no longer the only ones.

As signal loss and fragmentation continue to reshape advertising, and AI plays a larger role in planning and activation, a more important question is emerging:

Where can advertisers operate with genuine transparency?

The industry has spent years optimizing around demographics, identifiers, and behavioral signals. But those approaches were built for a different era. As privacy regulations reshape how user data can be collected and activated, many of the assumptions that defined digital advertising are being challenged.

More importantly, people have never been as simple as the systems built to reach them.

A 35-year-old woman, married, in a dual-income household with two children under ten, is not an audience. She might be researching sustainable travel after work. Comparing mortgage options. Reading about marathon training. Planning a family vacation.

The demographic label remains the same. The context, motivations, emotions, and intent behind each moment do not.

This is why the future of advertising is not simply about finding new ways to identify people. It is about developing a better understanding of the moments that shape attention and decision-making.

And it is why the conversation around open web vs walled gardens is evolving into something larger. Not a debate about channels. A conversation about transparency, understanding, and how advertising creates relevance in a privacy-first world.

Key Takeaways

The debate around open web vs walled gardens is evolving from audience access to transparency and accountability.
Traditional targeting methods built around demographics and identifiers are becoming less effective in a privacy-first advertising landscape.
Advertisers need greater visibility into how campaigns are planned, activated, and measured across media environments.
The open web provides transparency, independent measurement, and contextual intelligence that help brands understand audiences beyond demographic profiles.
Unified Ad Platforms and End-to-End Platforms simplify activation but also raise important questions around visibility and verification.
The future of advertising will depend on balancing scale, transparency, and a deeper understanding of human attention.

Open Web vs Walled Gardens: Why the Debate Still Matters

Both walled gardens and the open web play an important role in modern digital advertising.

Walled gardens, including platforms operated by major tech giants, provide access to large logged-in audiences, rich first-party user data, and highly integrated advertising products. Their scale and simplicity have made them a cornerstone of many media strategies.

The open web offers a different advantage.

It provides access to a diverse ecosystem of premium publishers, content environments, and independent technology partners. Rather than operating inside a single closed platform, advertisers can activate campaigns across a broad range of trusted environments where consumers actively engage with content.

This distinction matters because the way people consume media continues to evolve.

Consumers spend their time across multiple channels, devices, and content experiences. They move seamlessly between social platforms, streaming services, publisher websites, mobile apps, and connected TV.

The question is no longer whether advertisers should choose the open web or walled gardens. The real question is how each environment contributes to a broader media strategy.

Why Transparency Matters More Than Ever

As the industry evolves, transparency is emerging as one of the most important considerations for advertisers.

For years, digital advertising benefited from an abundance of user-level signals. Audience targeting became increasingly sophisticated, allowing brands to reach consumers based on demographics, interests, and online behaviors.

Today, that landscape is changing.

Privacy regulations continue to reshape data collection practices. Browser restrictions limit access to traditional identifiers. Consumers expect greater control over how their information is used.

At the same time, AI-powered systems are increasingly responsible for planning, activation, optimization, and measurement decisions.

This creates a new challenge.

There is still an enormous amount of data available. But there is often less visibility into how that data is interpreted and transformed into campaign decisions.

As automation increases, advertisers need confidence not only in outcomes but in the processes that generate those outcomes.

Transparency is no longer simply a reporting feature. It is becoming a strategic advantage.

Demographics Oversimplify People

The shift toward privacy-first advertising is also changing how marketers think about audiences.

For decades, advertising strategies have relied heavily on demographic segmentation:

Age
Gender
Income
Location

These signals can be useful, but they provide only a partial view of human behavior.

Two people with identical demographic profiles may have completely different motivations depending on the content they are consuming and the context surrounding that moment.

A parent reading about summer travel plans is in a different moment than that same person consuming breaking news. A sports fan researching match statistics has different intentions than when browsing home improvement content.

Demographics describe people. They do not explain moments. This is where Neuro-Contextual intelligence is becoming increasingly valuable.

Rather than focusing exclusively on who someone is, our Neuro-Contextual AI can help advertisers understand what matters to people in a specific moment by analyzing signals related to content, interest, emotion, and intent.

Because relevance is not only about identity. It is also about context.

Why Premium Advertisers Are Re-Evaluating Ad Spend

The shift in ad spend toward the open web is not driven by a single trend. It reflects a broader change in how brands evaluate media investments.

Advertisers increasingly want greater transparency into campaign performance, inventory quality, and measurement methodologies. They want to understand where ads appear, how decisions are made, and whether results can be independently validated.

The open web provides access to premium publisher environments where consumers actively engage with trusted content.

It also allows advertisers to work with a wider range of measurement and verification partners, creating additional visibility throughout the campaign lifecycle.

This does not mean brands are abandoning walled gardens. Far from it.

Many advertisers continue to rely on closed platforms for scale, activation, and performance marketing objectives.

However, they are increasingly seeking a balance between the efficiency of walled gardens and the transparency offered by the open web.

What Are Unified Ad Platforms and End-to-End Platforms?

Alongside traditional walled gardens, another trend is reshaping digital advertising: the rise of Unified Ad Platforms (UAPs) and End-to-End Platforms.

These solutions bring multiple functions, including planning, activation, data management, optimization, and measurement, into a single platform.

The appeal is clear. One workflow. One technology stack. One operational environment.

For many advertisers, these platforms simplify campaign execution and reduce complexity.

However, they also introduce an important consideration.

When planning, activation, optimization, and reporting all occur within the same ecosystem, advertisers may have fewer opportunities to independently verify how decisions are being made.

This does not make End-to-End Platforms inherently problematic. They solve real operational challenges.

But as automation and AI become more influential, advertisers must consider how much visibility they retain into the systems guiding campaign performance.

The question is not whether these platforms create value. The question is how transparency and accountability evolve within increasingly automated environments.

Understanding the Moment, Not Just the User

This is where the conversation ultimately moves beyond open web vs walled gardens.

The future of advertising is not simply about finding audiences. It is about understanding people. Not as demographic categories. Not as identifiers. Not as data points. But as individuals navigate thousands of moments throughout their day.

Modern contextual AI can help advertisers understand those moments by analyzing the content people engage with and identifying signals related to interest, emotion, and intent.

This creates a privacy-first approach to advertising that does not depend on personal identifiers to deliver relevance.

This philosophy powers our Neuro-Contextual intelligence.

Through Liz, our proprietary Neuro-contextual AI, we analyze content across premium publisher environments to understand the context surrounding every advertising opportunity.

Because meaningful advertising starts with understanding. Not just who people are. But what matters to them in the moment.

Looking Ahead

The future of advertising is unlikely to be defined by a single environment.

Walled gardens will continue to play an important role, particularly where first-party relationships and logged-in audiences create value. The open web will continue to provide transparency, flexibility, and access to premium content environments where attention naturally happens.

The more important question is not where advertisers spend every dollar.

It is whether they have enough visibility to understand why those investments work.

As media planning becomes increasingly influenced by AI, fragmented signals, and privacy-first frameworks, transparency is becoming more than a reporting feature.

It is becoming a competitive advantage.

The brands that succeed will not simply optimize for reach. They will optimize for understanding. Understanding the content. Understanding the context. And understanding the moments that shape how people think, feel, and act.

How to Turn Automotive Marketing Research Into World Cup Ads

Jun 2026

mins

The FIFA World Cup 2026 will generate an unprecedented volume of attention across digital media. For automotive brands, that scale creates enormous opportunity but also a significant challenge: standing out in an environment where every advertiser competes for the same audience.

The difference between visibility and impact comes down to understanding intent. Not every football fan is equally receptive to a brand message, and not every page view signals genuine engagement.

During major sporting events, audiences move between match coverage, transfer rumors, national team narratives, player stories, entertainment content, and countless adjacent interests. Within those moments lie valuable signals that can help brands identify when consumers are most open to engagement.

The question is no longer how to reach World Cup audiences. It is about identifying the moments when attention becomes meaningful engagement.

Below, we explore the audience insights shaping fan behavior during the tournament and how automotive brands can use Neuro-Contextual advertising to transform World Cup attention into meaningful consideration.

Key Takeaways

The difference between a browser and an engaged consumer often lies in intent signals, not audience segments.
World Cup audiences engage with far more than football, creating valuable opportunities across adjacent interests and passion points.
Emotions such as excitement, curiosity, admiration, and optimism play a key role in how fans engage with content throughout the tournament.
Neuro-Contextual advertising goes beyond keywords and categories to align messaging with interests, emotions, and intent.
Dynamic creative optimization allows automotive campaigns to adapt in real time around tournament moments, audience context, and sentiment.

Automotive Marketing Insights for the World Cup 2026

The Gap Between Looking and Engaging

Scale is not the challenge. During a World Cup, automotive brands can reach millions of consumers across the open web, connected TV, and streaming environments.

The challenge is identifying the difference between someone casually consuming content and someone demonstrating signals of genuine engagement.

Traditional targeting approaches often rely on keywords, categories, or broad audience segments. A page mentions "SUVs" or "electric vehicles," and an ad is served. While these signals can provide relevance, they do not always reveal what matters most: what the consumer is thinking, feeling, or looking for in that moment.

A reader exploring vehicle reviews out of curiosity may require a very different message from someone actively comparing models ahead of a purchase. Understanding that distinction helps brands move beyond simple reach and toward meaningful engagement.

Where Fan Attention Really Goes

One of the biggest misconceptions about the World Cup is that fans spend the tournament focused exclusively on football.

In reality, audience attention extends across a much broader ecosystem of content.

Audience interest also evolves throughout the tournament. Our insights show that engagement increases significantly during key moments such as the group stage, quarter-finals, and high-tension knockout rounds. Importantly, some of the largest spikes are driven not only by match results but also by player narratives, rivalries, and stories surrounding the competition.

Football-related interests such as domestic leagues, transfer rumors, national team stories, and club rivalries remain major drivers of engagement. But fans also spend time consuming content connected to celebrity culture, motorsports, entertainment, lifestyle topics, and national identity narratives.

These adjacent interests are not distractions from football fandom. They are part of how fans experience the tournament.

For automotive marketers, this creates additional opportunities to connect with audiences in contexts that may be less crowded than traditional sports environments while still maintaining strong relevance to fan interests.

Understanding these passion points allows brands to expand beyond match-day targeting and build a more comprehensive view of where their audiences spend time and attention.

The Emotional Signals Behind Engagement

The World Cup is not only a media event. It is an emotional one.

Across markets, football content generates a range of emotional responses, including excitement, curiosity, admiration, optimism, and even sadness. These emotions shift throughout the tournament as audiences react to victories, defeats, player performances, speculation, and national narratives.

While excitement consistently emerges as one of the strongest drivers of engagement, emotional responses vary across markets. Some audiences gravitate toward stories of national pride and sporting heroes, while others engage more deeply with tournament speculation, player narratives, or broader cultural conversations surrounding the event. Understanding these nuances can help brands deliver more relevant messaging throughout the competition.

For automotive brands, these signals offer valuable context. The emotions that shape engagement during the tournament can also influence how consumers respond to brand messaging, particularly in categories where consideration and aspiration play an important role.

Many vehicle purchase journeys are influenced by emotional factors alongside practical considerations. Curiosity about new technology, optimism about future ownership, excitement around a new model, and aspiration tied to lifestyle choices all play a role in consideration.

When brands understand the emotional context surrounding content consumption, they can align messaging more effectively with the consumer's interests, emotions, and intent in that moment.

How the Neuro-Contextual Approach Changes Automotive Marketing

Industry-standard targeting often relies on predefined content taxonomies and broad category classifications. Neuro-contextual approaches take a different path by analyzing content more deeply to understand interests, emotions, and intent signals in real time.

The difference between targeting a broad automotive category and identifying audiences such as Family Upgraders, First-Time Car Buyers, Urban Drivers, or Off-Road Adventure Enthusiasts is significant.

Rather than focusing solely on what content someone is consuming, Neuro-Contextual intelligence helps brands understand why that content matters to them.

For automotive marketers, this means identifying environments where signals of curiosity, optimism, excitement, and consideration are already present and aligning messaging accordingly.

The goal is not simply to be present. It is to be relevant.

Dynamic Creative That Moves With the Tournament

The World Cup unfolds in phases, and audience behavior evolves with it.

Interest levels rise during key matches, emotional intensity increases during knockout rounds, and fan conversations shift as new narratives emerge.

The content driving engagement during the group stage may be very different from the stories capturing attention during the quarter-finals or final, making flexibility a critical advantage for advertisers.

Creative should evolve alongside those changes.

Dynamic Creative Optimization (DCO) allows campaigns to adapt messaging based on factors such as tournament stage, location, time of day, weather conditions, and emotional sentiment.

A message delivered during a high-tension quarter-final may require a different creative approach than one served during the group stage. Likewise, audiences engaging with family-focused content may respond differently than audiences consuming performance or technology-related content.

By aligning creative with context, brands can create more relevant experiences throughout the tournament.

Measuring What Actually Matters

Clicks and viewability remain useful metrics, but they do not tell the full story.

For automotive brands operating within long and consideration-heavy purchase journeys, understanding campaign impact requires a broader measurement framework.

Attention metrics help reveal whether advertising was genuinely processed by consumers. Brand lift studies can demonstrate shifts in awareness, perception, and consideration. Incremental reach helps determine whether campaigns are connecting with new audiences rather than repeatedly reaching the same users.

Together, these measurements provide a clearer view of how campaigns influence consumer behavior throughout the World Cup journey.

From Research to the Road

The FIFA World Cup 2026 presents a unique convergence of attention, emotion, and engagement.

Success will not belong solely to the brands with the largest budgets or the widest reach. It will belong to those who understand where fan attention is going, what emotions are driving engagement, and how to identify moments of genuine intent.

Traditional research helps identify the audience. Neuro-contextual intelligence helps identify the moment.

And during the world's biggest sporting event, that difference can determine whether a campaign is simply seen or truly remembered.

To learn more about the audience insights, emotional signals, and activation opportunities shaping FIFA World Cup 2026 campaigns, download the full Automotive Insights report.

Cannes Lions Festival of Creativity: From Profiles to Human Understanding

May 2026

mins

Every year, the Cannes Lions Festival of Creativity offers a glimpse into where advertising is heading next. But in 2025, the conversations across the Croisette felt especially revealing.

At the heart of Cannes Lions 2025 was a growing realization that the future of advertising will depend less on identifying audiences and more on understanding people. Across beachfront stages, private dinners, podcast studios, and conversations inside the Palais des Festivals, the industry repeatedly returned to the same challenge: how can brands create more relevant experiences in an increasingly fragmented, AI-driven media landscape?

For Seedtag, Cannes 2025 became an important moment to help shape that conversation.

Throughout the week, Seedtag explored how Neuro-Contextual Advertising is redefining the relationship between media, creativity, and human understanding. From discussions around AI and emotional relevance to debates about journalism, contextual intelligence, and audience mindset, the company’s presence reflected a broader industry shift already reshaping modern advertising.

And now, as the industry prepares for another year in Cannes, France, those conversations are evolving even further.

Key Takeaways

The Cannes Lions Festival of Creativity highlighted the industry’s move from audience profiling toward deeper human understanding.
Cannes Lions 2025 conversations focused heavily on AI, contextual relevance, emotional engagement, and privacy-first advertising.
Seedtag’s Neuro-Contextual approach emerged as part of a broader industry shift toward understanding interest, emotion, and intent.
Creativity, media, and data became increasingly interconnected across the Cannes Lions International Festival.
New discussions heading into Cannes 2026 are expanding beyond targeting and toward adaptive, human-aware advertising experiences.

What Cannes Lions 2025 Revealed About Advertising

The International Festival of Creativity has always reflected the priorities of the advertising industry. In 2025, those priorities shifted noticeably.

Artificial intelligence dominated discussions across nearly every stage and meeting space. But while AI remained central, the industry conversation matured significantly compared to previous years. The focus was no longer simply on automation or content generation. Instead, marketers increasingly questioned how technology can help advertising become more meaningful, more adaptive, and more emotionally aligned with people.

That tension defined much of Cannes Lions 2025.

Consumers today move fluidly between streaming platforms, creator ecosystems, social content, sports, commerce, and live cultural moments. Attention is fragmented, audience behavior changes constantly, and traditional identity-based targeting models are becoming less effective in a privacy-first world.

As a result, the industry is beginning to rethink what relevance actually means.

For us at Seedtag, that conversation connected directly to Neuro-Contextual Advertising. Rather than relying on static audience profiles or demographic assumptions, our approach focuses on understanding real-time signals of interest, emotion, and intent across the open web and premium media environments.

The idea is simple: people are more than profiles.

And increasingly, the advertising industry is starting to agree.

From Profiles to Passions

One of the defining conversations during Cannes 2025 centered on the limitations of traditional targeting.

For years, digital advertising has relied heavily on demographic segmentation and behavioral assumptions. But across the Cannes Lions Festival of Creativity, industry leaders repeatedly discussed the need to move beyond identity alone and focus more deeply on audience mindset, context, and motivation.

We explored this shift directly during the live crossover episode of AdTech Heroes x The Pub Way, hosted at The Drum’s podcast studio.

The conversation brought together leaders from across media, creative, and advertising to discuss how brands can better engage audiences through real-time understanding rather than static assumptions.

A recurring theme emerged quickly: marketers have spent years trying to understand who consumers are, while paying far less attention to why they engage in the first place.

That distinction matters.

People are shaped by passions, interests, emotions, and cultural moments that evolve continuously. Someone watching sports content during a major tournament may not respond to messaging the same way they would while reading financial news or consuming entertainment content later in the day.

Context changes mindset.

This idea became central to many discussions throughout the Cannes Lions International Festival. Relevance is no longer about reaching the right demographic. It is about understanding the emotional and cognitive environment surrounding attention itself.

AI Became About Understanding, Not Just Automation

AI remained one of the dominant themes across Cannes, France, but the industry conversation evolved significantly compared to previous years.

Earlier conversations around AI often focused on speed, scale, and automation. At Cannes Lions 2025, the emphasis shifted toward intelligence, adaptability, and human understanding.

Marketers are now asking more complex questions. How can AI help interpret the audience mindset? How can it improve contextual relevance? How can it support creativity without reducing advertising to generic automation?

These discussions appeared repeatedly across panels, roundtables, and private conversations.

Our perspective centered on the idea that AI should not simply optimize delivery. It should help brands better understand the moments in which people engage with content.

This is where Neuro-Contextual Advertising becomes increasingly relevant.

By combining neuroscience principles with AI-powered contextual understanding, Liz, our Neuo-Contextual AI, is designed to interpret signals of interest, emotion, and intent in real time. The goal is not to identify individuals, but to understand the meaning surrounding the moment itself.

That approach reflects a larger shift happening across the industry.

Advertising is moving away from static targeting systems and toward adaptive environments capable of responding dynamically to changing emotional and contextual signals.

Creativity and Context Are Becoming Reconnected

Another major theme across the Palais des Festivals was the growing relationship between creativity and contextual relevance.

For years, programmatic advertising has often separated creative storytelling from media strategy. But at Cannes Lions 2025, many industry leaders argued that creativity can no longer function independently from context and audience understanding.

As media environments become increasingly fragmented, brands face growing pressure to create campaigns that feel synchronized with the emotional tone surrounding the content experience.

This is especially important across premium video, streaming, and creator-driven ecosystems where audiences expect advertising to feel more integrated and less disruptive.

Throughout the week, conversations increasingly focused on how creative effectiveness improves when messaging aligns with the real-time audience mindset.

That shift is transforming how marketers think about personalization itself.

Rather than personalizing around identity, advertisers are beginning to personalize around context, emotion, and intent.

This idea also appeared in conversations surrounding contextual TV, curated supply, and premium media environments. Brands are looking for advertising experiences that feel more thoughtful, more emotionally aware, and more aligned with the content moments consumers actively choose to engage with.

Journalism, Trust, and Smarter Contextual Understanding

Beyond AI and creativity, Cannes Lions 2025 also highlighted growing industry concerns around journalism, trust, and responsible monetization.

We participated in discussions exploring how rigid keyword blocklists and simplistic brand safety systems can unintentionally harm quality journalism.

This became an important conversation across the International Festival of Creativity because advertisers increasingly recognize that brand safety cannot rely exclusively on broad exclusions or outdated contextual assumptions.

High-quality journalism covering politics, climate, economics, or global conflict often becomes demonetized despite offering trusted, premium environments for advertisers.

That creates a difficult contradiction for the media ecosystem.

The solution discussed throughout Cannes 2025 was not abandoning brand safety altogether, but evolving toward more intelligent contextual systems capable of understanding nuance, tone, and meaning more effectively.

This conversation reinforced one of the industry’s broader shifts: context is becoming more sophisticated.

Modern contextual understanding is no longer limited to keywords alone. It increasingly depends on a deeper interpretation of emotional tone, audience mindset, and environmental relevance.

Looking Ahead to Cannes Lions 2026

As the industry prepares for the next Cannes Lions Festival of Creativity, many of the conversations that defined 2025 are continuing to evolve.

This year, we will expand those discussions further at La Perle, our Cannes space designed for meetings, collaborative sessions, workshops, and thought leadership conversations.

The upcoming agenda reflects many of the themes that emerged throughout Cannes Lions 2025.

Sessions such as “The End of Guesswork: How to Reach Consumers Who Are Actually Ready to Listen” will explore how advertisers can move beyond stale targeting proxies and align campaigns with real-time emotion, interest, and intent.

Other conversations will focus on curated supply, contextual TV, AI and creativity, neuroscience, media responsibility, and human-centered advertising experiences.

We will also introduce experiential activations such as the “Scent of Context” lab, an immersive workshop designed to explore how emotion, memory, and sensory environments shape contextual understanding.

Together, these experiences reflect a broader evolution happening across advertising itself.

The industry is no longer asking only how to target people more efficiently. It is asking how to better understand the emotional and cognitive moments that shape attention.

From Profiles to Human Understanding

Looking back, Cannes Lions 2025 represented more than another industry gathering. It reflected a meaningful turning point in how advertising thinks about relevance.

AI became more mature. Context became more intelligent. Creativity became more connected to audience's mindset. And marketers increasingly recognized that understanding people requires more than data points alone.

For us at Seedtag, those conversations continue shaping the future of Neuro-Contextual Advertising.

Because the future of advertising will not belong to the brands that know the most about consumers. It will belong to the brands that understand the moment best.

And increasingly, that future is becoming more human-aware.

‍

Publisher Ad Management: From Scale to Supply Quality

The Pub Way Podcast

May 2026

mins

Publishers

Publisher ad management used to be a relatively straightforward operational exercise: connect to enough demand sources, maximize fill rates, increase ad impressions, and optimize ad placements across available inventory. For years, scale was the dominant strategy.

But that approach no longer reflects how digital advertising works.

Today’s publishers operate in a far more complex ecosystem, where monetization depends not just on how much inventory is available, but on the quality of supply paths, the transparency of partnerships, and the value of the data attached to each opportunity. More scale does not automatically mean more revenue. In some cases, it creates inefficiency, duplication, and margin erosion instead.

That shift was a central theme in an episode of The PubWay Podcast, where Tina Iannacchino and Mike Villalobos spoke with Tyler Romasco, EV, Commercial at OpenX. Their conversation explored curation, supply quality, sustainability, biddable CTV, AI, and the changing economics of publisher monetization.

The bigger takeaway was clear: publisher ad management is no longer just about operational execution. It has become a strategic monetization discipline.

Key Takeaways

Publisher ad management is shifting from scale-first execution to quality-first monetization.
Curation can create incremental revenue, but only when it adds real value beyond repackaged open market inventory.
Supply quality issues such as request duplication and multi-hop reselling directly affect publisher monetization.
The right advertising supply side platform should improve transparency, efficiency, and revenue outcomes.
CTV creates premium monetization opportunities, but publishers must manage content signals and inventory carefully.
AI will increasingly shape ad management in real time, but publishers still need clear controls and strategic oversight.

Why Publisher Ad Management Needs a Reset

Historically, publisher ad management focused on operational optimization. The objective was simple: increase available ad inventory, connect to more ad exchange partners, improve fill rates, and maximize ad revenue across different types of ads, from display and native ads to video ads.

But scale-first monetization created unintended consequences.

As supply chains became increasingly fragmented, publishers often added more intermediaries in pursuit of incremental revenue. More SSPs, more demand integrations, more routing paths. In theory, this created more competition for inventory. In practice, it often introduced duplication, inefficiency, and reduced transparency.

The industry is now confronting the limits of that model. As Tyler noted during the episode, there is growing recognition that bigger is not necessarily better. Quality-first strategies are increasingly outperforming scale-first approaches because buyers are prioritizing cleaner supply paths, stronger signals, and more transparent access to inventory.

That represents a meaningful shift in publisher monetization.

Instead of treating ad management as a back-end function focused primarily on displaying ads, publishers are increasingly treating it as a strategic lever that shapes yield, advertiser trust, and long-term business outcomes.

We explore this broader evolution in Rethinking Publisher Monetization Strategy.

Publisher Ad Management: From Scale to Supply Quality

Curation Only Works When It Creates Incremental Value

Few topics in adtech have gained momentum as quickly as curation. But as Tyler explained during the conversation, curation is not a single tactic. It spans multiple approaches.

Inventory-based curation focuses on supply characteristics, such as direct publisher inventory, premium ad formats, or excluding MFA environments.

Audience-based curation uses first-party or third-party data to reach defined target audiences through identifier-based activation.

Data-driven curation moves beyond identity altogether, using contextual intelligence, AI optimization, and performance models to align supply with advertiser goals.

For publishers, the real question is not whether curation matters. It is whether it creates incremental value.

That distinction matters because if curated deals simply repackage inventory that would already clear through the open market, publishers may end up absorbing additional fees without meaningful revenue upside. But when curation introduces differentiated demand, stronger targeting intelligence, or higher-value activation strategies, the economics change significantly.

That is where publisher ad management becomes strategic.

Publishers should understand how curated packages are built, what data layers are applied, and whether the curation model improves CPMs, win rates, or advertiser outcomes in measurable ways. Transparency matters because not all curation is created equal.

Supply Quality Is Becoming a Competitive Advantage

One of the strongest themes from the conversation was supply quality.

For years, many quality discussions focused on fraud, bot traffic, and MFA. Those issues remain important, but the next frontier is more structural.

Request duplication is a clear example.

When the same ad opportunity is sent multiple times through different paths, buyers face duplicated requests that create noise, inefficiency, and wasted processing. Multi-hop reselling compounds the issue by routing the same inventory through layers of intermediaries before it reaches a buying platform.

For buyers, this reduces access to true unique supply. For publishers, it creates reputational risk.

Supply quality is increasingly tied directly to monetization performance because buyers want efficient, transparent access to premium inventory. Publishers that create cleaner supply paths are becoming more attractive partners.

This requires a mindset shift. Instead of asking how many partners can be connected, publishers should be asking which partners create the most efficient, transparent, and value-generating routes to demand.

In this environment, fewer high-quality partnerships may outperform a sprawling network of loosely managed integrations.

What Publishers Should Expect From an Advertising Supply Side Platform

This is where the role of the advertising supply side platform becomes especially important.

A modern SSP should not simply function as a connection point to more demand. It should actively support smarter publisher ad management.

That includes:

transparent fee structures
clean supply path architecture
protection against unnecessary request duplication
support for high-quality curated deals
visibility into how demand sources access inventory
stronger controls around ad placements and supply optimization

Publishers should expect clarity around how curation fees are structured and whether third-party partners are delivering measurable incremental value.

They should also expect SSP partners to improve supply quality rather than amplify inefficiencies.

As supply path optimization continues to reshape buyer behavior, publisher infrastructure decisions matter more than ever. We explored this dynamic further in How Publishers Can Future-Proof Brand Safety and Revenue with the Right Advertising Supply Side Platform.

CTV Is Changing Publisher Monetization Economics

CTV introduces a different monetization equation.

Premium content, high-attention environments, and premium video ads create meaningful revenue opportunities. But they also increase the importance of inventory management discipline.

Tyler made a strong case that quality in biddable CTV begins with direct publisher inventory. Buyers want confidence that they are accessing premium environments from broadcasters, OEMs, and FAST channels, not opaque layers of resold supply.

That expectation changes how publishers should think about ad inventory.

Unlike traditional web monetization, where first-party signals were often pushed broadly into bidstreams, CTV publishers are taking a more deliberate approach. Many are separating inventory tiers based on signal access, creating differentiated value depending on the metadata and contextual signals made available.

That strategy makes sense because CTV content is expensive to produce, and premium inventory should command premium economics.

For publishers, this means stronger control over data exposure, pricing, and inventory packaging.

Publisher ad management in CTV is not just about serving more video ads. It is about preserving value in premium environments.

AI Will Reshape Ad Management, But Publishers Need Control

No modern adtech conversation avoids AI, and this episode was no exception.

But the most useful perspective here was not hype-driven.

Tyler framed AI as a practical enabler: better optimization, faster media buying decisions, improved curation, and smarter matching between advertiser objectives and available inventory.

That aligns closely with how publisher ad management is evolving.

AI can improve decision-making in real time, identify higher-value opportunities, and reduce operational inefficiencies that once required manual intervention.

But AI does not remove the need for judgment.

Intent, contextual nuance, supply quality definitions, and monetization tradeoffs still require strategic oversight.

Publishers that embrace AI thoughtfully will likely improve efficiency and revenue performance. Publishers that treat AI as a replacement for governance may introduce new risks instead.

Looking Ahead

Publisher ad management has fundamentally changed.

It is no longer defined by how many ad units can be monetized or how many demand sources can be connected. It is defined by how intelligently publishers manage supply quality, inventory access, monetization controls, and partner transparency.

Quality is becoming the differentiator: cleaner supply paths, better curation, smarter use of first-party signals, stronger SSP relationships, and more disciplined CTV monetization strategies.

Those are the building blocks of sustainable publisher monetization.

In a more fragmented digital advertising ecosystem, publisher ad management is no longer a back-end operational function.

It is a strategic growth discipline.

Listen to the Full Episode

Curation, supply quality, biddable CTV, AI, and publisher monetization are reshaping how publishers approach growth.

For a deeper dive into the ideas discussed in this article, listen to this episode of The PubWay Podcast, where Tina Iannacchino and Mike Villalobos speak with Tyler Romasco, EV, Commercial at OpenX, about the future of publisher ad management, supply quality, curation, and monetization strategy.

Listen to the full episode here.

Sports Marketing Strategies That Win World Cup Attention

May 2026

mins

Every four years, the FIFA World Cup becomes more than a sporting event. It becomes a global cultural ecosystem where passion, identity, emotion, and attention collide in real time.

For sports brands, that creates an enormous opportunity, but also a challenge.

Because in 2026, the best sports marketing strategies will not be defined by visibility alone. They will be defined by the ability to understand how sports fans think, feel, and engage throughout the tournament.

During the World Cup, sports fans do not engage with football in isolation. They move between transfer rumors, national team pride, multisport interests, player storylines, jersey culture, and live match moments that evolve by the hour.

In the UK alone, more than 90% of World Cup-related engagement connects directly to football content, while adjacent passions, including celebrity culture, Formula 1, boxing, and cricket, continue shaping how fans experience the tournament.

That shift is transforming how sports marketing campaigns are planned.

To better understand these evolving fan behaviors, Liz, our Neuro-Contextual AI, analyzed World Cup and football-related media consumption across key markets, uncovering the emotional signals, passion points, and engagement patterns shaping fan engagement during the tournament.

The findings reveal something important: World Cup advertising is no longer about chasing audiences. It is about understanding the moments that move them.

Key Takeaways

The best sports marketing strategies during the World Cup are built around emotion, timing, and contextual relevance
Football-related content drives 90.6% of World Cup topic engagement in the UK, while adjacent cultural interests create additional engagement opportunities
Peak fan attention occurs during knockout rounds and emotionally intense moments, not only during the final
Excitement is the strongest emotional driver of World Cup engagement, especially in the UK and France
Sports marketing trends increasingly rely on understanding interest, emotion, and intent rather than static demographic targeting
Real-time creative optimization and contextual alignment help sports brands create engaging campaigns during live sporting moments

Why the World Cup Is Reshaping Sports Marketing Strategies

The FIFA World Cup has always delivered massive scale. Few sports events rival its global reach, emotional intensity, or cultural relevance.

But scale alone no longer guarantees impact.

Today’s sports fans consume the tournament across a much broader ecosystem of content and conversation. They follow player narratives long before kickoff and continue engaging long after the final whistle. Transfer rumors, team selection debates, jersey launches, multisport interests, and celebrity storylines all become part of how fans experience the tournament.

This creates a far more dynamic attention landscape for brands.

Instead of relying on broad reach or static audience profiles, sports marketing strategies now require a deeper understanding of how attention evolves throughout the tournament.

The World Cup has become an environment driven by moments. Moments of anticipation. Moments of pride. Moments of tension. Moments of celebration. Moments of curiosity.

The brands that succeed are the ones capable of aligning with those moments while they are happening.

That shift is also changing how the broader sports media ecosystem approaches advertising innovation.

In episode 33 of The PubWay podcast, Scott Young, Co-Founder and Chief Product Officer at Transmit, explained that sports streaming platforms are under growing pressure to rethink how advertising experiences work during live sports. As subscription growth slows and media rights become increasingly fragmented, ad-supported streaming models are becoming central to the future of sports monetization.

But according to Young, sustaining viewer attention is now the real challenge.

Media companies are no longer focused only on inserting more ads. They are looking for ways to create more dynamic, personalized, and conversational advertising experiences that feel integrated into the viewing moment rather than disruptive to it.

That idea sits at the center of modern World Cup advertising.

Sports Marketing Strategies - Sports marketing trends - World cup advertising

What Sports Fans Actually Care About During the World Cup

One of the most important findings from our World Cup Sports Goods insights is that fan attention extends far beyond football itself.

In the UK, 90.6% of visits related to World Cup topics directly connect to football content. But even within football, engagement is layered across multiple passion points.

The largest driver of engagement comes from domestic leagues and football giants, representing 68.1% of football-related interest. Fans actively follow club performance, tactical discussions, and league narratives throughout the year.

Transfer market conversations account for another 15.4% of engagement, proving that speculation and player movement remain central to fan behavior even outside active transfer windows.

National pride and legacy discussions generate an additional 7.1% of engagement, especially around qualification journeys and national team performance heading into the tournament.

But the opportunity expands even further when brands look beyond football-only environments.

Connected interests also play a major role in fan engagement. Royal and celebrity connections linked to football personalities generate 4.4% of engagement. Multisport interests, including boxing, Formula 1, and cricket, contribute another 2.6%. WAGs and celebrity culture account for an additional 2.4% of engagement.

This is where some of the best sports marketing strategies emerge.

Rather than limiting campaigns to match-day inventory alone, brands can connect with sports fans across adjacent moments where attention and emotional engagement are already active.

Because during the World Cup, fan identity stretches far beyond the pitch.

How Fan Behavior Changes Across Markets

Another major insight from the report is that sports fans are not homogeneous.

Every market engages with the World Cup differently, with unique passion points shaping how audiences consume content.

In the UK, fans heavily follow domestic leagues, club giants, and transfer rumors, while celebrity culture and multisport interests strongly influence engagement.

In Spain, national team patriotism drives 34% of engagement, alongside growing interest in women’s football and practical viewing solutions.

French audiences gravitate toward domestic football rivalries and multisport content, including rugby, tennis, and golf.

German audiences, meanwhile, remain highly engaged with club routines, qualification updates, and broader football debates.

These differences matter because successful sports marketing campaigns cannot rely on a one-size-fits-all approach.

The World Cup may be global, but passion remains deeply local.

That is why the best sports marketing strategies adapt creative, messaging and contextual alignment to the cultural DNA of each audience.

The Emotional Side of World Cup Advertising

If interest explains what captures attention, emotion explains what drives engagement.

According to our analysis, excitement is the single strongest emotional driver during the World Cup, especially among UK and French audiences.

But emotion during the tournament is far more layered than celebration alone.

Fans also engage through curiosity, admiration, optimism, and even sadness.

Spanish and German audiences show particularly high levels of admiration toward global football stars and club legends. Italian audiences display stronger optimism while also consuming emotionally heavier football stories that drive social conversation.

This emotional diversity changes how sports brands should think about fan engagement.

Brands can no longer depend exclusively on broad contextual categories or keyword targeting. They need to understand how audiences feel within each moment.

That emotional alignment becomes especially powerful during knockout rounds, national team milestones, emotional victories, player comeback stories, jersey launches, and moments of national pride.

When creative reflects emotional context, campaigns feel more natural, more timely, and more relevant.

Scott Young described this shift during The PubWay episode by explaining that the strongest advertising experiences in live sports are the ones that speak to viewers based on what they are actively watching and feeling in that exact moment.

In practice, that could mean dynamically adapting creative around a major winning moment, a dramatic comeback, or a crucial goal.

It is no longer just about serving an ad during a live game. It is about aligning with the emotional energy surrounding it.

When Sports Fans Pay the Most Attention

One of the clearest patterns is how attention intensifies around key tournament stages.

Our analysis of previous football competitions reveals that traffic increased 4.3x during men’s quarterfinals compared to normal days, while women’s tournament traffic increased 3x during quarterfinals.

Live events themselves generate major audience activation spikes. But interestingly, the biggest engagement surges are not always driven by goals or tactics.

Many viral moments center around emotional narratives, celebrity culture, player personal lives, confrontation stories, and behind-the-scenes content.

This changes how sports brands should think about timing.

The best sports marketing strategies are not limited to the final or the biggest live sports moments. They are built around the emotional rhythm of the tournament itself.

That includes pre-match anticipation, qualification tension, transfer speculation, jersey release conversations, national pride, and post-match reactions.

Attention during the World Cup behaves like a wave, not a straight line. And increasingly, advertising innovation is being built around that reality.

Young also explained during the podcast that advertisers are seeing stronger results when contextual timing, emotional relevance, and messaging work together inside live sports environments.

According to the study mentioned in the episode, viewers exposed to integrated in-content ad experiences demonstrated 10x greater message recall compared to traditional ad pod experiences.

When timing and contextual alignment improved, viewers were also 20% more likely to scan and purchase.

That reinforces a growing reality within sports marketing trends: Attention alone is not enough. Relevance is what drives action.

How Sports Brands Should Plan World Cup Advertising Campaigns

So how should sports brands approach World Cup advertising in 2026?

The report points toward a major strategic shift away from static targeting and toward contextual understanding.

Fans no longer engage as broad demographic groups. They engage through interests, emotional identities, and passion ecosystems.

Some audiences follow jersey culture and kit releases. Others engage through multisport interests, football gaming, sports fashion, player admiration, or national identity.

That means sports marketing campaigns need to become more fluid and responsive.

Creative also needs to evolve alongside fan behavior.

That is why creative is becoming more dynamic during live sports moments, adapting in real time based on factors like competition stage, emotion, weather, location, and fan mindset.

The goal is not simply to increase visibility during sports events. It is to create engaging experiences that feel synchronized with the emotions surrounding the moment.

That is especially important in streaming and CTV environments, where sports fans increasingly consume content across connected viewing experiences.

Our report also highlights how contextual TV targeting can combine Open Web intelligence with enriched CTV signals to better align messaging with audience interests and viewing behaviors in real time.

For sports brands, this creates an opportunity to move beyond generic sponsorship visibility and toward more emotionally aware advertising experiences.

Turning Attention Into Advantage With Neuro-Contextual Advertising

At the center of this approach is Liz, our Neuro-Contextual AI.

Rather than relying exclusively on keywords or static contextual categories, Liz analyzes interest, emotion, and intent signals in real time to understand why audiences engage with specific content moments.

For sports brands, this creates a more responsive approach to fan engagement.

Our Sports Goods analysis highlights how brands can identify positive emotional responses, purchase intent signals, national team excitement, jersey demand moments, and emotionally engaged fan segments.

For example, fans actively searching for upcoming national jersey releases represent high-intent engagement moments tied directly to excitement, optimism, and desire.

This allows sports brands to move beyond static targeting and connect with audiences while interest is actively building.

Because in the end, the future of sports marketing strategies is not about reaching the largest possible audience. It is about understanding the moments that matter most.

Where Sports Marketing Goes Next

The FIFA World Cup continues to evolve from a sports tournament into a global attention ecosystem.

That shift is redefining World Cup advertising.

The brands that win during the tournament will not simply be the loudest. They will be the most relevant. The most emotionally aligned. The most contextually aware.

Because modern sports fans do not experience the tournament through a single behavior or a single passion point. They move fluidly between live match moments, transfer speculation, emotional storylines, sports culture, and real-time conversations that shape how the World Cup is experienced across the open web and streaming environments.

Get your Sports Goods Insigts

Align product demand with national team engagement and tournament milestones

Understanding those moments is what transforms visibility into engagement

And increasingly, that is what separates presence from performance in modern sports marketing campaigns.

To explore the full FIFA World Cup 2026 Sports Goods insights deck and uncover deeper fan engagement trends, emotional signals, and activation opportunities across markets, download the Sports Goods insight report from Seedtag.

You can also check out Episode 33 of The PubWay Podcast, “Ad Innovation in Live Sports Streaming,” to explore how live sports, streaming innovation, and contextual advertising are reshaping fan engagement during major global sporting events.

CTV Targeting Is Rewriting the Rules of TV Advertising

May 2026

mins

CTV

Television was built on broad assumptions for decades. Brands bought airtime, targeted demographic averages, and measured success through estimates rather than actual behavior. Reach mattered more than precision, and advertisers accepted that a large percentage of impressions would inevitably land on the wrong audience.

CTV targeting is changing that equation.

As streaming reshapes viewing habits, connected TV advertising is transforming television into a more measurable, adaptable, and outcome-driven channel. What once operated primarily as a one-to-many medium now behaves much closer to digital advertising, powered by audience signals, contextual understanding, and real-time optimization.

But the shift is bigger than targeting alone. CTV is changing how advertisers think about performance, how publishers monetize premium content, and how the industry measures attention across screens.

The old rules of TV advertising are no longer enough.

Key Takeaways

CTV targeting expands TV buying beyond broad demographic assumptions by incorporating audience, contextual, and behavioral signals.
Connected TV advertising combines the storytelling impact of television with the precision and measurability of digital media.
Measurement and targeting now work together, helping advertisers optimize campaigns around outcomes instead of estimated reach alone.
Attention on CTV tends to be stronger because viewers actively choose content across streaming environments.
Fragmentation across platforms, devices, and identity systems remains one of the biggest structural challenges in the CTV ecosystem.

From Reach to Relevance

Traditional television advertising was designed for scale. Brands purchased placements around specific programs or time slots, hoping the right audience would be watching at the right moment.

That model worked when viewing behavior was predictable and audiences gathered around the same channels. Streaming changed that dynamic entirely.

Today, audiences move fluidly across smart TVs, streaming apps, gaming consoles, FAST channels, and on-demand platforms. Viewers choose what to watch, when to watch it, and on which screen. As attention fragmented, advertisers needed more precise ways to reach audiences without wasting impressions.

That is where CTV targeting became essential.

Unlike linear TV, connected TV advertising allows advertisers to layer audience signals such as viewing behavior, household insights, contextual alignment, and content preferences into campaign activation strategies. Instead of relying only on broad demographic assumptions, campaigns can increasingly adapt to relevance, engagement patterns, and viewing environments in near real time.

This shift is redefining what television advertising can actually deliver.

Why CTV Targeting Changed Measurement

Targeting and measurement are no longer separate conversations.

One of the biggest advantages of connected TV advertising is that campaigns can now be measured with a level of granularity that traditional television never offered. Advertisers are no longer limited to panel-based estimates or generalized reach assumptions. They can evaluate campaign performance using impression-level signals, completion rates, incrementality, conversions, and cross-device behaviors.

This changes how brands evaluate success.

CTV measurement frameworks now combine exposure, engagement, and outcomes into a more complete understanding of campaign performance. Metrics like CPCV, view-through rate, incremental reach, and conversion activity help advertisers understand not only who saw an ad, but whether that exposure created meaningful impact.

At the same time, the ecosystem still faces challenges around standardization, deduplication, and cross-platform attribution. As streaming environments continue to fragment, advertisers increasingly rely on unified measurement frameworks, identity solutions, and interoperable datasets to create a more consistent view of performance.

The combination of targeting and measurement also improves optimization. Campaigns can evolve dynamically based on performance signals, allowing advertisers to adjust strategies while campaigns are still running rather than relying entirely on post-campaign analysis.

In many ways, CTV transformed television from a largely estimated medium into a more accountable one.

For a deeper look at how performance frameworks are evolving across streaming environments, explore Closing the CTV Measurement Gap: Data Quality & Performance Talks and How to Measure Connected TV Ad Performance.

Attention Became More Intentional

One of the most important shifts in connected TV advertising is not just technological. It is behavioral.

Linear television often operated as background media. CTV environments are different because viewers actively choose content across streaming platforms, creating more intentional viewing experiences. That attention carries significant value for advertisers.

Because CTV is typically consumed in lean-back, full-screen environments, advertisers increasingly evaluate attention signals alongside traditional reach metrics. Completion rates on CTV are often higher than standard digital video, while intentional viewing behavior can contribute to stronger ad recall and engagement.

This is also where contextual alignment becomes more important.

As identity-based targeting becomes more restricted across the advertising ecosystem, advertisers are increasingly turning to contextual and content-based signals within CTV environments. Rather than relying solely on personal identifiers, campaigns can align with the themes, tone, and viewing environment surrounding the content itself.

The result is a stronger balance between relevance, performance, and user experience.

The Fragmentation Challenge

The evolution of CTV targeting also introduced new complexity.

The ecosystem remains fragmented across platforms, publishers, devices, operating systems, and identity frameworks. Data exists in multiple environments, measurement standards vary, and advertisers often struggle to unify signals across screens.

This fragmentation creates challenges around:

frequency management
attribution consistency
identity resolution
cross-platform reporting
incremental reach analysis

As a result, the industry is increasingly investing in unified measurement frameworks, clean room environments, contextual intelligence, and privacy-safe identity solutions that help advertisers connect performance signals more effectively.

AI is also playing a growing role in helping advertisers navigate this complexity. AI-driven contextual systems are increasingly being used to interpret content, viewing behavior, emotional alignment, and consumption patterns in near real time, helping advertisers improve relevance while maintaining privacy-safe approaches to targeting.

For publishers, this creates both pressure and opportunity.

Premium publishers with strong metadata, high-quality content environments, and richer contextual signals are becoming more valuable partners within the CTV ecosystem. As advertisers prioritize transparency, suitability, and measurable outcomes, publishers capable of delivering stronger audience understanding gain a competitive advantage.

This evolution is also reshaping programmatic buying models. Learn more in How Demand Side Platforms (DSPs) Are Reshaping CTV And What Publishers Need To Know.

Where CTV Advertising Goes Next

CTV is no longer simply the digital version of television.

As the ecosystem matures, advertisers will continue shifting from broad reach strategies toward more adaptive, signal-based planning approaches that prioritize relevance, accountability, and measurable outcomes.

The next phase of connected TV advertising will likely depend on how effectively the industry solves fragmentation while maintaining privacy-safe personalization and transparency across platforms.

But one thing is already clear. CTV targeting did not just improve television advertising. It fundamentally changed how television itself is bought, measured, optimized, and monetized.

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The Future of Media Planning and Activation Starts With Understanding the Moment

Joseph Meehan

Apr 2026

mins

Media planning and activation are being rebuilt in real time. Not because marketers suddenly changed how they think about audiences, but because the system they relied on to reach them no longer behaves the way it used to.

Signals are still present across the digital market, but they no longer form a stable foundation. They are fragmented and increasingly difficult to connect into something reliable. What once felt like a structured process now feels increasingly disjointed, with audience definition, media platforms, and activation no longer fully aligned.

Part of this shift is technical, but a larger part of it is structural. Across major global markets, privacy-first regulation and platform-level changes are redefining how data can be collected and used. What was once a stable identity layer is now constrained by design, not just by decay.

Even if signal fragmentation were not a factor, this shift alone would fundamentally limit how identity-based media planning can operate.

For media planners, this creates a quiet but persistent tension.

There is more data available than ever before, yet less certainty about what that data represents. Planning becomes more complex, while execution becomes more reactive. The connection between strategy and outcomes starts to weaken.

Underneath that tension sits a deeper issue.

The foundation behind most media buying platforms and ad exchange environments was never designed to understand what it delivers. It was built to move impressions efficiently, not to interpret the context in which those impressions appear.

As long as identity signals were stable, that limitation was easy to overlook. Now it is becoming central to how media planning and strategy work.

Because when signals fragment, the system has no fallback. It cannot explain what it is buying. It cannot adapt to what is missing. And it cannot fully support the kind of decisions modern media strategies require.

This is where the shift begins. Not with more data, but with a different way of understanding the moment in which attention happens.

Key Takeaways

Media planning and strategy are shifting from identity-based targeting to a foundation built on understanding the moment
Fragmented signals are exposing the limits of traditional media buying platforms and ad exchange models
Contextual media planning strategy is evolving from classification to true content understanding
NeuroX introduces a new foundation where every impression is understood through interest, emotion, and intent
The future of media strategies depends on aligning planning, activation, and measurement through consistent intelligence

When Media Planning Outgrows Its Foundation

For years, media planning followed a clear and familiar logic.

Planning is the process of defining who you want to reach, mapping those audiences across media channels, and activating campaigns through media buying platforms that deliver scale and efficiency. That approach shaped how effective media plans were built and how media spend was distributed across digital media environments.

It worked because identity made it work.

Audience segments could be defined, tracked, and activated with a level of consistency that connected planning to execution. Media planners and media buyers operated within the same system, even if their roles were different.

But as identity becomes less reliable, that system begins to lose coherence.

Signals vary by region, by platform, and by environment. In some markets, they are increasingly restricted by regulation. In others, they still exist but require multiple layers of data stitching to become usable. What once felt like a stable foundation now introduces variability at every stage of the workflow.

This is why building a media plan today often feels more complicated than it should. The system has not been redesigned. It has been extended. And that extension is starting to show its limits.

The Return of Context, and Its Limitations

As identity weakens, contextual media planning strategy has moved back into focus.

But the way contextual is implemented today often reflects the same limitations it is trying to solve.

Most contextual systems still rely on classification. Content is labeled, categorized, and grouped into predefined structures. That allows campaigns to expand beyond identity, but it does not fundamentally change how media strategies are built.

Because classification is not the same as comprehension.

Knowing what a piece of content is about does not explain why someone is engaging with it. It does not capture the mindset of the reader, the emotional tone of the content, or the stage of decision-making that defines how a message will be received.

This is where traditional contextual approaches reach their limit. They provide information, but do not understand.

For media planning and activation, that distinction matters. This is where our Neuro-Contextual approach becomes critical. Moving beyond basic classification, this method uses Liz, our proprietary AI, to interpret interest, emotion, and intent within the content itself. Unlike standard systems that just label a page, Neuro-Contextual advertising is built on how the brain actually processes content and advertising. Without that depth, even well-structured media strategies struggle to maintain precision across execution

Where Planning and Media Buying Begin to Drift

The impact of this limitation becomes more visible when looking at planning vs media buying.

Media planning sets direction. It defines priorities, allocates media spend, and determines how audiences should be reached across media channels.

Media buying translates that strategy into execution. It operates within the constraints of media platforms, optimizing campaigns based on performance signals and available inventory.

When identity-based signals like cookies and device IDs are stable, the connection holds. However, as identity signals break down and become inconsistent, planning and execution begin to drift. NeuroX addresses this structural challenge by embedding intelligence directly into the exchange, ensuring every impression is fully decoded and understood even when identity is absent.

Audience definitions lose clarity as they move into activation. Campaign optimization becomes dependent on surface-level signals rather than underlying context. Performance becomes harder to interpret because the system cannot fully explain why certain outcomes occur. Over time, this creates a disconnect.

The signals used to build a good media plan are not always the same signals used to activate it. And the insights generated during execution do not always feed back into strategy in a meaningful way. This is not simply a workflow challenge. It is a limitation of the foundation itself.

A New Foundation for Media Planning and Strategy

NeuroX has actually been the engine powering Seedtag since 2018. While it has always been our core infrastructure, we are now externalizing it to give agencies direct programmatic access on their own terms. This is more than just a new product; it is a shift toward a more resilient infrastructure that makes every impression addressable via Neuro-Contextual targeting, regardless of whether identity signals are present in the bidstream.

Rather than adding another layer to an already complex system, it changes what the system is built on at its foundation.

NeuroX is Seedtag’s Neuro-Contextual Exchange, where understanding is embedded directly into the system.

Every impression is interpreted before it enters the auction. That interpretation is powered by Liz, our proprietary AI, which decodes the interest, emotion, and intent expressed in content. And this changes how impressions are valued.

They are no longer dependent on identity to become addressable. They are understood in context, which allows them to be activated with clarity, even when identity signals are inconsistent or absent.

It also creates something the current system struggles to deliver: consistency at scale. By making impressions usable regardless of identity, NeuroX unlocks incremental, addressable reach across both the open web and CTV environments, while maintaining the level of precision modern campaigns require.

For media planners, this creates a different starting point. Planning no longer begins with assumptions about who the audience is. It begins with an understanding of the moment in which attention is happening, and what that moment reveals about intent and relevance.

When Understanding Connects Planning and Activation

When understanding becomes part of the foundation, media planning and strategy begin to behave differently.

The relationship between planning and execution becomes more direct. The signals used to define audiences are the same signals used to activate campaigns. The transition from strategy to execution becomes less dependent on translation and more grounded in continuity.

This has practical implications. Media planners can build more coherent strategies because the inputs are more stable. Media buyers can execute with greater precision because the signals they rely on are embedded in the supply itself. Measurement becomes more meaningful because performance can be interpreted in context, not just in isolation.

Across media channels, this approach creates alignment.

Whether campaigns run across web or CTV environments, the same intelligence layer applies. This allows media strategies to scale without losing coherence, even as the ecosystem becomes more complex.

Over time, this reduces one of the most persistent challenges in digital media: the gap between what is planned and what is delivered begins to close.

What Changes for Advertisers

As this shift takes hold, expectations around media planning and strategy are evolving.

A good media plan is no longer defined only by how efficiently it distributes media spend across channels. It is defined by how well it connects understanding, activation, and outcomes into a single system.

This changes how media platforms are evaluated. It is no longer enough to ask how much inventory a platform can deliver. The more important question is whether that inventory is understood, and whether that understanding can translate into better decisions across the workflow.

Flexibility remains important, but in a different way. It is not about adding more tools. It is about ensuring that the same intelligence can be accessed across different activation models, whether through open marketplace buying, curated deals, or managed service.

Most importantly, it requires alignment. The signals used to define audiences, activate campaigns, and measure performance need to be consistent. Without that consistency, even the most advanced media strategies struggle to deliver predictable outcomes.

From Automation to Understanding

At the same time, the industry is evolving toward more automated systems.

If you are exploring this shift, it is worth understanding What is Agentic AI and how it is shaping the way campaigns are planned and executed.

But automation alone does not resolve the underlying challenge. Without a foundation of understanding, automation simply accelerates existing limitations.

This shift is why the externalization of NeuroX is such a pivotal moment. By embedding Seedtag’s Neuro-Contextual AI directly into the exchange, we ensure that every impression is fully decoded and understood before the auction even begins. It is this NeuroX exchange architecture, where intelligence is the operating system rather than a bolt-on filter, that provides the consistent foundation needed to bridge the gap between strategy and real-world outcomes.

Where Media Planning and Strategy Go Next

Media planning has always been about making decisions with incomplete information. What is changing is how those decisions are informed.

In a fragmented ecosystem, where identity signals are inconsistent, and the digital market continues to evolve, the advantage no longer comes from access to more data.

It comes from understanding: understanding the content, understanding the moment, and understanding how people think, feel, and decide within that moment.

This is the shift that is redefining media planning and strategy. Not from one signal to another, but from signals to meaning.

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World Cup Advertising 2026: Turning Moments Into Advantage

Apr 2026

mins

Every four years, the FIFA World Cup becomes more than a tournament. It becomes a global cultural moment where attention intensifies, emotions rise, and audiences engage across platforms, content, and conversations.

In 2026, World Cup advertising is no longer about being seen. It is about understanding what people are doing and feeling in the moment.

Fans are not just watching matches. They are reading stories, following players, reacting in real time, and engaging with content that reflects how they feel as the 2026 football World Cup unfolds. Attention is no longer fixed. It moves, builds, and shifts depending on context, emotion, and timing.

To help brands better understand how fans behave during the tournament, we created the World Cup Intelligence Arena. It brings together insights across markets and verticals to show what fans care about and how they engage throughout the FIFA World Cup 2026.

Because in today’s landscape, understanding attention has become the priority.

Key Takeaways

World Cup advertising in 2026 is driven by moments, not just reach
Fans engage across football, culture, and adjacent content ecosystems
Emotional signals shape how audiences consume and respond to content
Attention peaks during key stages but is influenced by narrative and context
Effective strategies align with interest, emotion, and intent in real time

From Global Reach to Contextual Relevance

The FIFA World Cup has always been one of the most powerful sports events in the world. For advertisers, it has traditionally represented scale, offering unmatched reach through live broadcasts and mass audiences.

But the dynamics of World Cup advertising are changing.

The 2026 football World Cup will still deliver scale, but scale alone does not guarantee impact. As our insights show, visibility without strategy becomes noise in an environment where attention is constantly shifting.

Fans today engage with the tournament across multiple touchpoints. They move between live matches, news articles, social media world cups conversations, and cultural content. Their journey is continuous and non-linear.

This shift requires a new approach.

Instead of focusing only on exposure, brands must focus on relevance. That means understanding what fans are doing, where they are spending time, and how their mindset evolves across the tournament.

What Will Fans Care About During the FIFA World Cup 2026?

One of the most important insights for World Cup advertising trends 2026 is that fan attention extends far beyond the match itself.

Football remains the dominant driver, accounting for more than 90% of visits to World Cup-related content. However, this attention is layered with a wider set of interests that shape how audiences interact with the tournament.

Fans follow domestic leagues, transfer updates, and national team performance throughout the year. These ongoing narratives build familiarity and keep audiences engaged long before kickoff and long after the final.

At the same time, attention expands into adjacent areas such as celebrity culture, multisport events, and lifestyle content. These connections transform the FIFA World Cup into a broader cultural moment that reaches beyond traditional football audiences.

This is what makes the tournament unique. It is not just a sporting event. It is a connected ecosystem where culture, media, and entertainment intersect.

For brands, this creates new opportunities to connect with audiences in environments where engagement is already active.

The Role of Emotion in World Cup Advertising

If interest explains what captures attention, emotion explains what makes it matter.

The FIFA World Cup is driven by a range of emotional signals, from excitement and curiosity to admiration and optimism. Among these, excitement stands out as the most powerful driver, particularly during key moments of anticipation and match progression.

However, emotional responses are not static. They evolve throughout the tournament and vary across markets. Moments of pride, tension, or even disappointment can generate strong engagement, shaping how audiences consume content and respond to messaging.

This has important implications for World Cup advertising. It is no longer enough to align ads with content categories or keywords. Brands must align with the emotional context of each moment.

When messaging reflects how people feel, it becomes more relevant, more engaging, and more effective.

When Moments Matter Most

Attention during the FIFA World Cup builds around moments of intensity.

Data from previous tournaments shows clear spikes during key stages such as knockout rounds and high-tension matches. These moments can drive significant increases in traffic and interaction compared to regular periods.

However, these peaks are not driven by match outcomes alone. Narratives play a central role. Fans engage with player stories, personal journeys, and cultural conversations that extend beyond the game itself. In many cases, these stories generate as much attention as the matches themselves.

This reinforces a critical point. World Cup advertising trends 2026 are shaped by meaning, not just by events. Brands that recognize this can position themselves within the moments that matter most, instead of reacting after the fact.

How to Build a World Cup Advertising Strategy

Building an effective World Cup advertising strategy in 2026 requires a shift from static planning to dynamic understanding.

The first step is identifying where meaningful engagement happens. This involves focusing on environments where audiences are actively interested, rather than simply present.

Creative also needs to evolve. Messaging should reflect both the content and the mindset of the audience. When creative aligns with context, it feels more natural and resonates more strongly.

Another critical element is intent. Not all interactions carry the same value. By identifying signals of genuine engagement, brands can focus on moments where audiences are more likely to take action.

Finally, measurement must go beyond traditional metrics. Attention, brand impact, and engagement provide a clearer picture of how campaigns perform during the tournament.

Together, these elements create a more responsive and effective approach to World Cup advertising.

From Attention to Advantage With Neuro-Contextual Advertising

At the core of this approach is Liz, our Neuro-Contextual AI.

Liz is designed to interpret deeper signals of interest, emotion, and intent by analyzing content meaning and audience behavior in real time. Rather than relying on keywords or predefined categories, she focuses on understanding why people engage with content in specific moments.

This shift changes how World Cup advertising works.

Instead of targeting audiences based on static profiles, brands can align with the context people are in and the mindset they bring to it. Whether fans are following match analysis, exploring player stories, or engaging with cultural conversations around the tournament, Liz helps identify the signals that define those moments.

This makes it possible to move beyond visibility and into relevance.

In the context of global sports events like the FIFA World Cup, where attention is constantly evolving, this level of understanding allows brands to respond with greater precision and connect when audiences are most receptive.

Inside the World Cup Intelligence Arena

These insights come together in the World Cup Intelligence Arena.

The Arena brings together 14 insight decks across markets and verticals, offering a detailed view of how fans behave in different contexts throughout the FIFA World Cup 2026. It highlights what audiences care about, how their interests evolve, and how engagement shifts across the tournament.

By combining multi-market analysis with real-time signals, the Arena provides a clearer picture of where attention is building and how it connects to fan behavior.

This allows brands to move from observation to action. Instead of relying on assumptions, they can plan and activate based on how audiences actually engage during the tournament, identifying the moments that matter and responding with greater confidence.

Where World Cup Advertising Goes Next

The FIFA World Cup 2026 marks a shift in how World Cup advertising works. It is no longer defined by reach alone. It is defined by the ability to understand attention as it forms, evolves, and peaks throughout the tournament.

The World Cup Intelligence Arena reflects this shift, helping brands move from visibility to relevance, and from presence to impact.

Because in the end, success in World Cup advertising is not about being seen.
It is about being understood.

Explore the World Cup Intelligence Arena

To go deeper into these insights, explore the World Cup Intelligence Arena, where 14 insight decks across markets and verticals reveal how fans think, feel, and engage throughout the FIFA World Cup 2026.

From emerging passion points to emotional signals and real-time engagement patterns, the Arena is designed to help brands turn insight into action while attention is still in play.

→ Explore the World Cup Intelligence Arena and download the insights

The Intelligence Gap in Agentic Advertising

Ibrahim Ennafaa

Apr 2026

mins

AdTech

Between November 2025 and March 2026, virtually every major advertising platform launched an AI agent. The term dominated CES 2026, took over IAB ALM, and even prompted AdExchanger to launch a dedicated new conference called Programmatic AI in 2026, alongside its flagship Programmatic I/O. If you only read the press releases, you would think the entire advertising ecosystem has been reinvented overnight.

The reality is more nuanced and more interesting. A lot of what is being called “agentic” today is not. But something genuinely important is happening underneath the hype. And the companies that understand the difference between relabeling automation and building real intelligence will be the ones that define what comes next.

Key Takeaways

Not all AI agents are truly agentic. Much of what is being called agentic today is not, and understanding the difference between relabeling automation and building real intelligence is critical.
The industry is entering an “agentwashing” phase. Many vendors are rebranding existing capabilities as agentic, even though fewer than 130 companies today demonstrate real agentic capabilities.
A true agent goes beyond interface and automation. A genuine agent can take a campaign brief, reason about context and audience signals, build a strategy, identify what is missing, and prepare it for activation within a single workflow.
The real shift is happening at the intelligence layer. The programmatic ecosystem is being restructured around AI agents, but long-term value will come from understanding context, content, and what drives attention, not just infrastructure.

The biggest gap is understanding the moment, not automating tasks. Most AI systems can optimize and execute, but they struggle to explain why something works, especially how content and context shape human attention and response.

The Agentic Gold Rush

To understand the current moment, it helps to look back at the timeline.

In the span of five months, the industry saw a wave of product launches all claiming the agentic label. Major DSPs introduced AI-powered campaign creation tools. Verification companies added agent-based planning features. Commerce platforms launched recommendation services designed to power AI shopping assistants. Microsoft shut down its Xandr DSP, replacing it with a Copilot-powered buying interface, consolidated under the Microsoft Advertising Platform. This was an explicit bet that the traditional DSP model is becoming obsolete.

The pace is striking. But pace alone does not equal progress.

Gartner has already warned the industry about what it calls agentwashing, the rebranding of existing products without substantial agentic capabilities. Their prediction is sobering. Over 40% of agentic AI projects will be canceled by the end of 2027 due to escalating costs, unclear value, or inadequate risk controls. Forrester calls 2026 a year of reckoning, noting that buyers are now seeking proof over promises.

This is the context in which any honest conversation about AI agents in digital advertising needs to take place.

What "agentic" actually means - and what it does not

The word agent is being used to describe at least three different things, and conflating them is making it hard to have an honest conversation about where the industry actually stands.

If you are asking, “What is Agentic AI”, the answer starts here.

The first is genuine agentic AI systems, which can receive an objective, break it into steps, make decisions, use tools, and adapt based on what they find, without a human directing each action. These systems don't just respond; they pursue a goal across a workflow.

The second is LLM-enhanced tooling. These are interfaces powered by large language models that make existing platforms more accessible and easier to use. You describe what you want, and the system translates it into actions. Faster than manual setup, genuinely useful, but the intelligence is mostly in the interface, not in any autonomous reasoning.

The third is rebranded machine learning. Bid optimization, predictive targeting, and budget pacing have existed for years. Today, many of these AI systems are simply being relabeled as agentic because the market rewards them.

A genuine agent can take a campaign brief, reason about context and audience signals, build a strategy, identify what’s missing, and prepare it for activation, all within a single workflow, with minimal human intervention at each step. An LLM wrapper helps you navigate a platform faster.

Both have value. Treating them as equivalent is how “agentwashing” happens, and why Gartner estimates that of the thousands of vendors claiming agentic capabilities today, fewer than 130 are the real thing.

The Infrastructure Fight that Matters More Than the Product Launches

While the industry debates product features, a quieter but more consequential battle is playing out at the protocol layer.

Two camps are working to define how AI agents should communicate in advertising. On one side, the Ad Context Protocol (AdCP), backed by Yahoo, PubMatic, Scope3, Magnite, and roughly twenty other companies, builds new, purpose-built schemas on top of emerging agent-to-agent standards, with interoperability designed from the start. On the other hand, IAB Tech Lab's Agentic RTB Framework (ARTF) extends existing programmatic standards like OpenRTB and OpenDirect, arguing that a decade of infrastructure should not be discarded. ARTF's containerized architecture is designed to reduce bid latency by up to 80%, not by replacing the stack, but by making it dramatically faster and more agent-friendly.

Both approaches have merit, and they are not mutually exclusive. What they share is a common bet: that the programmatic ecosystem will not be replaced by agentic AI, but restructured around it. The pipes will get smarter. The question is what flows through them.

This is where the economic tension becomes real. Infrastructure that simply routes transactions is under pressure. Intelligence that makes those transactions better, by understanding context, content, and what actually drives attention, becomes more valuable. An agent still needs to know where to buy. The hard problem is knowing why a placement is right and how to solve problems in real time.

At Seedtag, we are building Liz Agent to be protocol-agnostic, because the transport layer will converge regardless of which standard wins. What will not converge is a proprietary understanding of how content environments shape human attention and response. That is the layer that compounds over time. And it is the layer that makes an agent's recommendations worth acting on.

Why Context is Becoming the Foundation, Not the Alternative

Alongside the agentic wave, a deeper structural shift is reshaping what advertising intelligence actually means.

The global contextual advertising market has surged past $225 billion and is projected to reach between $380 and $468 billion by 2030, according to industry estimates from sources such as Statista and Fortune Business Insights. This is not a niche category. It is becoming the foundation of how advertising works. We have seen this firsthand. Seedtag was built without cookies from day one, so the shift everyone else is preparing for is one we have been operating in for over a decade.

The infrastructure that identity-based advertising relies on is disappearing from multiple directions simultaneously. Google killed Privacy Sandbox in October 2025 after the industry invested an estimated $2.3 billion preparing for cookie alternatives that never materialized, according to industry reports.

Oracle abruptly shut down its entire advertising division, including Grapeshot, one of the largest contextual targeting platforms, redistributing hundreds of millions in annual spending. Third-party cookies survived in Chrome, but roughly 47% of the open internet is already unaddressable by traditional trackers, and Apple continues escalating with iOS 26, stripping platform-specific click identifiers from all browsing sessions.

But the bigger story is that technology has fundamentally changed. Contextual advertising is no longer keyword matching. Modern contextual systems use transformer-based models, computer vision, sentiment analysis, and deep learning to understand content at a semantic, emotional, and intent level. Many of these advancements are powered by generative AI and advanced artificial intelligence systems. The best systems classify content across thousands of categories, identify hundreds of objects and situational contexts in visual content, and process tens of millions of articles daily in real time.

The performance data increasingly support this shift. Research shows contextual targeting delivers significantly lower cost-per-click and cost-per-impression than behavioral approaches, with meaningfully better ad recall and engagement. Nearly 80% of consumers report being more comfortable with contextual ads than behavioral ones, according to multiple industry studies.

CTV is accelerating this further, with the industry moving from genre-level to program-level and even scene-level contextual analysis, a domain where identity-based approaches cover only a fraction of available inventory. It is why we have expanded our capabilities in CTV and partnered with platforms like IRIS.TV for content-level signals, building contextual intelligence natively into streaming, not bolting it on after the fact.

The Gap That Most AI Agents Still Cannot Close

Here is the honest assessment of where the industry stands.

Most AI systems in advertising, even the good ones, are optimized for efficiency. They process data faster, automate setup, and streamline execution. These systems perform tasks efficiently and can automate complex workflows. These are real gains. But they tend to operate on the surface of what makes advertising effective.

Relevance in modern advertising is not just about reaching the right person or placing an ad next to the right keyword. It depends on understanding the conditions of the moment, the cognitive and emotional context in which a message appears. How does the content around an ad shape the way that ad is perceived? What is the reader's mindset? Are they in a mode of exploration, comparison, or decision-making?

These are questions that standard optimization models, even sophisticated ones, are not designed to answer.

They can tell you what is happening. They struggle with why it matters.

A concrete example: An optimization engine can tell you that a running shoe ad performed 40% better on a wellness article. It cannot tell you that the article was about training for a first marathon at 45, and readers were in a mindset of personal reinvention, which is why the message resonated.

This is where the combination of AI and contextual intelligence becomes genuinely differentiated.

Not AI applied to the same data everyone else has, but AI applied to a proprietary understanding of how content environments shape human attention and response.

What We are Building with Liz Agent

So, where does Seedtag fit in all of this?

Seedtag was built from inception without cookies or personal identifiers. For over a decade, our engineering team has been developing Liz, a proprietary AI engine that processes over 60 million articles daily across 30,000+ publishers.

Liz combines NLP, deep learning, computer vision, and sentiment analysis to understand content at a level that goes far beyond keyword matching or standard IAB taxonomy, thousands of contextual categories, hundreds of visual objects and situational contexts, across 10+ languages in real time.

Our Neuro-Contextual methodology takes this further. Working with Professor Moran Cerf at Columbia University, we used EEG measurements to study how context shapes cognitive processing. The results were concrete: 3.5x higher neural engagement versus non-contextual ads. A 30% lift versus standard contextual. A 26% increase in positive, approach-oriented emotional response.

Liz Agent, which we launched in February 2026, is our entry into the agentic AI system space.

It is built on a multi-agent orchestration engine that combines LLMs with a Retrieval-Augmented Generation (RAG) framework grounded in Seedtag's proprietary data. This allows the system to operate with strong human oversight while still enabling automation where it matters.

Let me explain why the RAG architecture matters. A lot of AI agents in advertising are built on generic LLMs. They are smart, but they do not know anything specific about contextual intelligence, content environments, or how audiences respond to different contexts. They can hallucinate. They generalize. They produce outputs that sound right but are not grounded in real data.

Liz Agent's RAG framework means every response, every insight, every recommendation, every strategic direction is grounded in our proprietary Neuro-Contextual data, not generic knowledge. When Liz Agent analyzes a campaign brief, it draws on a decade of contextual intelligence infrastructure and neuroscience research, not a pretrained model's best guess.

Through a conversational interface, we can move from insights to campaign activation within a single workflow. Liz Agent integrates directly with our proprietary data for real-time contextual and audience intelligence, leverages our models to turn content from our publisher network into real-time embeddings, extracting audience signals and competitive insights that are native to our ecosystem, not scraped from generic sources, and connects strategy directly to activation across our global inventory.

Our intelligence, our proprietary contextual data, our Neuro-Contextual methodology, and our decade of models are what make Liz Agent's outputs actually useful, not just fluent.

The Real Question for 2026

The industry is asking whether AI agents will transform advertising. I think that is the wrong question.

AI agents will compress workflows, make platforms more accessible, and automate tasks that currently consume disproportionate time. That much is certain.

The better question is: what intelligence are these agents built on?

An agent built on generic data will produce generic outputs. An agent built on a deep, proprietary understanding of how content environments shape human attention and response will produce something qualitatively different. Not just faster answers, but better ones.

Forrester now includes agentic AI as a formal scoring criterion for advertising platforms. Gartner predicts 33% of enterprise software applications will include agentic AI by 2028, up from less than 1% today. Meanwhile, the IAB's 2026 State of Data report found AI-improved measurement alone could unlock $26.3B in media investment.

The opportunity is real. But in a market flooded with agentwashing, the differentiation will not come from who has the best chatbot interface. It will come from those who have the deepest understanding of what actually drives relevance, and the AI architecture to act on it.

In a fragmented, privacy-first digital environment where nearly half of all inventory is already cookieless, relevance is no longer built on identity data. It is built on understanding the moment, the content, the context, and the cognitive and emotional conditions in which a message appears.

The question I would ask any vendor pitching you an AI agent: Show me the data it is grounded in. If they cannot answer that, you are probably looking at a chatbot with a marketing budget.

From Innovation to Recognition: Seedtag Wins AI Awards

Kartal Goksel

Mar 2026

mins

In an industry defined by constant change, recognition doesn’t come from keeping up. It comes from redefining the way things are done.

I’m proud to share that Seedtag has been named a winner in the 2026 Artificial Intelligence Excellence Awards. Hosted by the Business Intelligence Group, this global program has spent more than a decade recognizing the companies and AI solutions that are redefining what responsible, results-driven artificial intelligence looks like in practice. This year’s awards brought together winners across 36 industries and more than 15 countries.

For me, Seedtag being named among this year’s AI awards winners is more than a milestone. It reflects a broader shift happening across advertising. Artificial intelligence is no longer just about automation or efficiency. It’s about understanding people more deeply, more responsibly, and in a more human way.

But the real story isn’t the award itself. It’s what it represents.

Key Takeaways

AI awards are evolving to recognize AI solutions that prioritize human understanding, not just scale
The most impactful AI solutions interpret context, emotion, and intent, not just data signals
Artificial intelligence is shifting from automation to meaning, enabling more relevant and respectful advertising
Neuro-Contextual AI reflects this new standard, aligning technology with how people think, feel, and decide
The future of advertising is built on understanding the moment, moving from relevance to resonance

A New Standard for AI in Advertising

For years, AI in advertising has been associated with scale. More data. More signals. More optimization. But scale alone doesn’t create relevance.

What I’m seeing now, and what these AI awards are beginning to recognize, is a shift toward a different kind of AI solution. One that doesn’t just process information faster, but understands context with greater depth and nuance. One that moves beyond identifying patterns to interpreting meaning.

This is where artificial intelligence starts to feel less like a machine and more like a system designed around how people actually think, feel, and decide.‍

From Data Processing to Human Understanding

Traditional approaches to AI in advertising have relied heavily on categorization. Keywords, segments, and predefined audience groups.

But people don’t experience content in categories. They experience it in moments. That idea has shaped how we’ve built our technology from the very beginning.

Our Neuro-Contextual AI, Liz, was designed to move beyond static signals and into dynamic human understanding. It interprets interest, emotion, and intent across content environments to identify when someone is most receptive to a message.

Because relevance isn’t about reaching more people. It’s about reaching people in the right moment.

Intelligence Grounded in How People Think

I’ve always believed that technology reaches its full potential when it aligns with human behavior, not when it tries to override it.

That belief is what led us to develop our Neuro-Contextual approach. By combining neuroscience with advanced AI, we set out to create a more human-like understanding of content and context.

Instead of relying on who someone is, we focus on what matters in the moment:

What captures attention
What shapes emotional response
What signals intent

From a technical perspective, this shift changes everything. When AI is built around human cognition, advertising stops feeling like an interruption and starts becoming part of the experience.

Innovation That Delivers Real Impact

Being recognized in these AI awards also reflects something I care deeply about. The need for measurable, meaningful impact.

Innovation alone isn’t enough. It has to perform.

That’s why our Neuro-Contextual approach has always been grounded in both science and results. Research shows that aligning advertising with human signals like interest, emotion, and intent drives stronger engagement and more positive responses.

At the same time, building an AI solution at a global scale comes with responsibility. Processing millions of signals across the open web and CTV while remaining privacy-first isn’t a feature. It’s a requirement.

That balance between intelligence, performance, and responsibility is what defines the next generation of AI solutions.

What This Means for the Future of Advertising

The future of advertising won’t be defined by how much data we can collect. It will be defined by how well we understand the moment.

For brands and agencies, this creates a real opportunity:

To move from targeting audiences to understanding people
To move from impressions to a real, human connection
To move from relevance to resonance

And for the industry as a whole, it signals something bigger. A future where artificial intelligence doesn’t just optimize advertising. It elevates it.

Recognition is meaningful, but transformation is what truly matters. Being named among this year’s AI awards winners is a moment I’m proud of. More importantly, it reinforces the direction I believe the industry must take.

Toward AI solutions that are not only smarter, but also more human. Toward advertising that doesn’t just reach people, but understands them.

Because in the end, the most powerful technology isn’t the one that processes the most data.

It’s the one that best understands people.

Rethinking Publisher Monetization Strategy

Tina Iannacchino

Mar 2026

mins

Publishers

Publisher monetization has always been a balancing act. You want to protect the reader experience, protect advertiser trust, and still hit revenue goals in a market where demand signals shift fast. Now add falling search traffic, new AI discovery patterns, and brand safety rules that still default to blunt blocking. The margin for error gets thin.

In this episode of The PubWay Podcast, Mike and I sat down with Amanda Gomez, SVP of Revenue Operations and Ad Technology at the New York Post, to unpack how a modern news publisher is navigating that reality. We talked about how they’re thinking about the business beyond pageviews, why “more banner ads” is no longer a strategy, and what it takes to build a monetization engine that can hold up in an AI-shaped advertising ecosystem.

Below are the key takeaways, plus practical implications for publishers who are trying to protect revenue potential while keeping users and advertisers onside.

What publishers are optimizing for right now

A theme kept coming up in our conversation with Amanda. Publishers are not just future-proofing content. They are future-proofing the business model.

That means expanding beyond the written word into audio, video, podcasts, events, and product experiences that can withstand volatility in search and social distribution. It also means treating user experiences as a revenue input, not a nice-to-have. If your pages load slowly or feel overloaded, you lose user engagement. And with fewer pageviews to work with, every lost session costs more.

Amanda put it plainly: the days of “just add more 300x250s” are long gone. The goal now is to create an ad experience that earns attention without punishing the user.

What this looks like in practice

Testing ad-light experiences on new launches to protect speed and session depth
Measuring the trade-off between fewer ad units and stronger time on site
Investing in owned channels like apps, newsletters, and direct return visits
Building franchises in categories that drive consistent demand, like sports and entertainment

These aren’t just product decisions. They’re publisher monetization decisions.

What is a publisher monetization strategy?

A publisher monetization strategy is the plan a publisher uses to turn audience attention into sustainable revenue while protecting long-term user trust. In digital advertising, that typically includes how you price and package ad inventory, how you balance direct and programmatic demand, and how you design user experiences that support both engagement and advertising revenue.

In 2026, a strong monetization strategy usually includes:

Inventory strategy: ad formats, ad density, and placement rules that protect speed and usability.
Demand strategy: a mix of direct sold, programmatic, and curated deals to reduce volatility.
Data driven decision-making: performance monitoring in real time across yield, latency, and engagement.
Audience strategy: building loyalty through apps, newsletters, and repeat visitation.
Revenue diversification: options like affiliate marketing, subscriptions, events, and sponsorships.

The big shift Amanda emphasized is that publishers can’t solve only for the page. They have to solve for the brand. If you’re building a media brand, you create more revenue opportunity across formats, not just within one URL.

Brand safety is still a revenue problem for news

When the conversation turned to brand safety in advertising, Amanda didn’t sugarcoat it. News publishers still face a constant uphill battle. Many buyers still rely on legacy keyword blocklists because they’re easy. They feel “safe.” But they are also blunt. They can misread context, ignore sentiment, and block coverage that is responsible, balanced, and high quality.

Amanda gave a strong example. Coverage around a death can include a lot of positive sentiment. Think tributes, community response, and gratitude. Yet many systems see the word “died” and flag the page. That creates a direct brand safety in advertising impact on publisher monetization because premium impressions get excluded from bids, even when the content is clearly suitable.

The important nuance is this: brand safety is not just an advertiser setting. It shapes how the open web gets funded.

What buyers respond to now: suitability, sentiment, and proof

Amanda also shared something encouraging. Some advertisers are more open to testing than they used to be. Instead of shutting the door on “news,” buyers will engage when publishers can show side-by-side examples and prove that a page is suitable.

That proof often comes from three places:

Sentiment and context signals that go beyond keywords.
Performance data showing lift when content is correctly classified.
Clear packaging that makes it easy for buyers to buy with confidence.

We also discussed how certain “negative” contexts can be highly relevant depending on the category. Insurance brands, home improvement retailers, and generator companies may want to appear near natural disaster content because it’s timely and useful. That is suitability in action. It’s not about avoiding reality. It’s about aligning message, moment, and audience need.

How do PMPs improve publisher monetization strategy while supporting brand safety in advertising?

Private Marketplace deals, or PMPs, help publishers and advertisers meet in the middle. They create a controlled path to premium demand while improving transparency and suitability.

Here’s why PMPs can strengthen a publisher monetization strategy:

1) They create cleaner buying paths

PMPs reduce the chaos of open exchange buying by defining who can buy, under what rules, and with what expectations. That stability improves revenue potential.

2) They support brand safety through structure, not fear

Instead of broad blocking, PMPs can be built around curated segments, contextual rules, and suitability standards. Advertisers get more control without punishing quality journalism.

3) They reward high quality environments

When buyers can see what they’re buying and why it works, CPMs tend to reflect that quality. PMPs can unlock advertising revenue that gets lost when inventory is treated as generic.

4) They protect user experiences

Because PMPs often favor premium placements and predictable demand, publishers can reduce the pressure to overload pages with units. That improves speed, reduces latency, and supports higher user engagement.

In short, PMPs can connect publishers and advertisers in a way that improves outcomes for both, while keeping the advertising ecosystem healthier overall.

Practical publisher monetization ideas from this episode

If you’re looking for publisher monetization ideas you can act on, Amanda’s playbook points to a few clear priorities:

Start with user experience. Measure load, latency, and engagement like revenue drivers.
Build strong “safe” content franchises (sports, entertainment) that are easy for buyers to fund.
Use the app as a loyalty engine and a first-party channel for product experimentation.
Treat AI as part of distribution and product, not just an editorial tool.
Push suitability conversations with proof, not opinions. Examples and performance data change minds.

Looking ahead

Publishers are operating in a world where attention is scarce, discovery is changing, and monetization platforms must work harder to translate signal into value. What I took from this conversation is that the publishers who win will be the ones who stay flexible. They’ll protect user experiences, insist on smarter brand safety in advertising, and build demand paths that reward quality rather than penalize it.

Listen to the full episode of The PubWay Podcast to hear Amanda’s full perspective on balancing brand safety, user experience, and publisher monetization in a rapidly shifting market.

March Madness Trends 2026: What Marketers Should Know

Mar 2026

mins

Every spring, March Madness becomes one of the most intense cultural moments in sports. The NCAA tournament delivers dramatic upsets, emotional fan reactions, and nonstop conversation across media platforms. But for marketers, the event represents more than a series of basketball games. It reveals how audiences gather around shared moments of excitement, competition, and entertainment.

The biggest March Madness trends in 2026 show that the tournament audience is far more complex than a single sports fan profile. Some viewers follow every bracket prediction and game analysis. Others tune in for the social experience of watching with friends. Many engage with the tournament through sports storytelling, entertainment content, and broader cultural conversations surrounding the games.

Our analysis shows that March Madness engagement spans 77 connected content genres, extending well beyond basketball coverage. Fans move between sports commentary, documentaries, entertainment programming, and lifestyle content as the tournament unfolds. This connected ecosystem reflects how the modern March Madness tournament audience experiences the event today.

For brands exploring March Madness marketing, understanding these behaviors is essential. Advertising success during the tournament does not come from simply appearing during games. It comes from aligning campaigns with the moments, emotions, and content environments that shape how fans engage with March Madness.

Below, we explore the biggest March Madness trends in 2026, how fan behavior is evolving, and what these changes mean for marketers planning March Madness advertising.

Key Takeaways

The biggest March Madness trends in 2026 are driven by three core audience groups: Bracket Devotees, Watch Party Goers, and Cultural Lifestyle viewers.
March Madness attention spans 77 different content genres, showing how the tournament extends far beyond basketball coverage.
Key content clusters include sports documentaries, weekend sports discussion shows, entertainment programming, and college basketball analysis.
Bracket Devotees represent nearly half of the March Madness ecosystem and respond strongly to bracket predictions and tournament analysis.
Watch Party Goers engage with the tournament as a social viewing experience driven by group reactions and entertainment content.
Cultural Lifestyle audiences follow March Madness through sports culture, storytelling, and broader media narratives.

What Are the Biggest March Madness Trends in 2026?

These insights highlight a major shift in March Madness audience trends. The tournament is no longer just about watching games. It has become a broader cultural moment shaped by emotion, context, and shared experiences.

One of the most important March Madness trends is the expansion of the tournament beyond basketball coverage.

Fans still follow the games closely. But the surrounding media ecosystem has grown significantly. Engagement now flows across sports documentaries, entertainment shows, sports commentary programs, and lifestyle content.

Four key content clusters dominate the conversation during the 2026 March Madness:

Documentary sports storytelling
Weekend sports discussions
Entertainment and lifestyle programming
College basketball analysis

These clusters reveal how fans engage with the tournament through multiple entry points.

Some viewers focus on bracket predictions and game matchups. Others watch sports documentaries or entertainment shows tied to the tournament atmosphere. Many participate in the broader cultural buzz surrounding the games.

This shift reflects evolving March Madness historical trends. In earlier years, fan engagement centered primarily on live games and sports news coverage. Today, March Madness exists within a much broader media ecosystem.

For marketers, this evolution creates new opportunities for March Madness advertising ideas. Brands can reach audiences across many contextual environments rather than relying only on live-game placements.

Why Does March Madness Attract Advertisers?

Few sporting events generate the same level of sustained attention as March Madness. The tournament runs for several weeks, creating multiple waves of engagement and conversation across media platforms.

This extended timeline is one reason March Madness sports marketing remains so valuable. The tournament produces several distinct engagement phases:

Early bracket speculation and predictions
Game-by-game tournament drama
Unexpected upsets and viral highlights
Final Four anticipation and championship momentum

Each phase generates fresh audience attention and new opportunities for brands.

Another reason March Madness attracts advertisers is the emotional intensity of the tournament. Every game carries the possibility of a surprise outcome. Fans experience a mix of excitement, tension, joy, and curiosity as the bracket unfolds.

These emotions drive attention. When audiences feel emotionally invested, they become more engaged with the surrounding content environment.

For marketers, this creates ideal conditions for March Madness advertising. Campaigns placed within emotionally aligned contexts feel more relevant and less disruptive to the viewing experience.

How Do Fan Behaviors Change During March Madness?

Understanding March Madness fan engagement requires recognizing that different audiences interact with the tournament in different ways.

Our analysis highlights three key audience segments shaping the March Madness ecosystem.

Each group approaches the tournament with a distinct motivation.

Bracket Devotees

Bracket Devotees represent the largest segment of the March Madness ecosystem.

These fans follow the tournament closely. They analyze matchups, track predictions, debate potential upsets, and monitor bracket outcomes throughout the competition.

This audience thrives on uncertainty. Every upset reshapes the bracket and fuels new discussions.

Because of this behavior, March Madness bracket trends remain one of the most important signals for marketers. Content focused on predictions, expert analysis, and tournament strategy attracts close attention from these viewers.

Advertising that aligns with competitive excitement and real-time tournament dynamics often resonates strongly with this group.

Watch Party Goers

Another important audience segment experiences March Madness primarily as a social event.

Watch Party Goers engage with the tournament through group viewing experiences. They gather with friends, react to big plays together, and follow live commentary across multiple screens.

Their viewing habits often include entertainment content and social discussions alongside the games themselves.

This behavior reflects a broader shift in March Madness audience trends. The tournament has become a shared cultural moment where sports, entertainment, and social interaction intersect.

For advertisers, this audience responds well to creative that reflects the energy and excitement of communal viewing.

Cultural Lifestyle Audiences

The third audience segment connects with March Madness through culture and storytelling.

These viewers are drawn to narratives surrounding players, sports documentaries, and broader conversations about athletes and competition.

They may not watch every game. But they remain engaged with the personalities and stories shaping the tournament.

This segment shows how March Madness 2026 extends beyond the bracket itself. The tournament generates cultural conversations that blend sports, entertainment, and storytelling.

For brands, this audience represents an opportunity to appear within narrative-driven environments rather than strictly sports-focused placements.

What Advertising Strategies Work During March Madness?

The most effective March Madness advertising strategies recognize that audiences respond to different types of content environments.

Rather than approaching the tournament as a single advertising moment, marketers should align campaigns with the motivations driving each audience group.

Align with competition-driven environments

Bracket Devotees respond strongly to programming that emphasizes tournament dynamics, predictions, and game analysis. Advertising placed within these contexts benefits from the excitement surrounding bracket outcomes.

Support the social viewing experience

Watch Party Goers engage with entertainment-driven programming and real-time commentary. Advertising within these environments can feel like a natural extension of the shared viewing experience.

Connect with sports storytelling

Cultural Lifestyle audiences respond to sports documentaries and narrative-driven content. These environments allow brands to align with curiosity and a deeper sports culture.

Across all audiences, the strongest March Madness advertising ideas share one important trait: they match the emotional tone of the surrounding content.

When advertising aligns with the context fans are already engaged in, it becomes more relevant and more memorable.

How Do Brands Use March Madness for Marketing?

Brands use the tournament to connect with audiences during one of the most emotionally engaging moments in sports.

Successful March Madness marketing strategies typically follow three key principles.

Contextual alignment

Campaigns perform best when they appear alongside content audiences are already consuming. During March Madness, this includes sports commentary, entertainment programming, and documentary storytelling related to the tournament.

Emotional relevance

March Madness engagement is driven by excitement, joy, and curiosity. Advertising that reflects these emotions resonates more strongly with fans.

Multi-environment presence

Because the tournament ecosystem spans dozens of connected content genres, brands can reach audiences across many contextual placements.

This broader approach allows marketers to move beyond traditional sports advertising and engage fans throughout the wider March Madness media environment.

The Biggest Lesson for Marketers

March Madness reveals an important insight about how modern audiences engage with sports events. The tournament does not revolve around a single type of fan. Instead, the ecosystem is shaped by multiple motivations:

competition and bracket predictions
social viewing experiences
sports storytelling and cultural curiosity

Each of these motivations drives attention in different ways.

For marketers, the opportunity lies in understanding those differences. Campaigns that recognize the emotional and contextual diversity of the March Madness tournament audience can connect with fans more effectively.

March Madness will always be about basketball. But the tournament’s real power comes from the shared experiences it creates around the game.

Brands that understand those experiences are the ones most likely to win the moment.

To explore the full analysis behind these insights, including audience segments, contextual environments, and the signals shaping March Madness fan engagement, download the full March Madness report and discover how Seedtag helps brands turn cultural moments into more human and relevant advertising.

Seedtag Reports 46% Year-Over-Year Growth in North America, Accelerating Neuro-Contextual TV and Client Expansion

Mar 2026

mins

Seedtag, the global Neuro-Contextual advertising company, today announced 46% year-over-year growth in North America in 2025. The region’s strong acceleration was driven by deepening partnerships with major brands and agencies that continue to see measurable value in Seedtag’s custom contextual audiences, premium inventory access, and actionable cross-channel insights.

In the United States, Seedtag reported 35% year-over-year revenue growth in January 2026. In Canada, where operations launched in 2024, the business achieved profitability last year and remains Seedtag’s fastest-growing market, posting 325% year-over-year growth in January.

Expanding Brand Portfolio Across Key Verticals

Recent client additions span multiple industries:

Financial Services: Discover Card, Charles Schwab, HSBC
Travel: British Airways, Qantas, United Airlines
Automotive: Infiniti, Toyota, Volkswagen, Acura
FMCG: Keurig Dr Pepper, Colgate, Conagra, Henkel
Healthcare: Merz, AbbVie, GSK, Galderma
Retail & QSR: Red Lobster, Target, L.L.Bean, Amazon XCM/Retail

“The diversity of our brand roster brings stability to our business and underscores how critical contextual targeting has become in modern media planning,” Brian Danzis, Chief Revenue Officer at Seedtag.

‍

Neuro-Contextual TV Momentum Accelerates

Seedtag’s Neuro-Contextual TV solution continues to gain traction following the full integration of CTV sell-side platform Beachfront into its offering. With a presence that is both growing and recognized as a Top 15 CTV SSP by Jounce Media, Seedtag offers advertisers direct pathways to key inventory from Paramount, Samsung, Charter, LG, Scripps, among others.

Valerie Andari, Investment lead at Good Apple on Amneal Pharmaceuticals shares: "Seedtag brings a truly consultative approach to every campaign. Their ability to leverage AI-powered contextual insights helps us navigate complex healthcare audiences and uncover new opportunities to drive meaningful engagement."

Demand continues to surge, with 2025 CTV revenue growing 157% year over year. In January 2026 — traditionally one of the slowest months for streaming video — Seedtag continued to see triple-digit CTV growth.

Leah Askew, SVP, Head of Precision Media | Digitas NA, added: "Our partnership with Seedtag moves us beyond outdated demographics like '18–54' or 'moms' and into the world of deep audience intelligence. Their team digs beneath the surface of the RFP to uncover the nuanced motivations that actually drive consumer behavior. They function as an extension of our own team, serving as strategic partners who engage in the high-level industry dialogue necessary to keep our clients ahead of the curve."

Team Growth and Workforce Highlights

Seedtag’s North American team grew to well over 100+ employees in 2025, continuing the company’s rapid growth in the region. The workforce is increasingly diverse, with women representing 53% of employees and 63% of people managers. Employee engagement remains strong, with an NPS of 69, reflecting a motivated and committed team driving the company forward.

“Seedtag’s strength lies in our connected ecosystem,” said Amanda Pui, VP Canada at Seedtag. “We’ve spent the last year intentionally scaling the successes of our colleagues in the US, LATAM and EMEA to benefit our Canadian partners. This cross-regional strategy allows us to provide global clients with a level of scale and sophisticated Neuro-Contextual data that is unmatched in the market.”

Looking Ahead

As demographic-based targeting declines in favor of interest-driven strategies, Seedtag is positioned to lead this transformation. The company empowers publishers seeking smarter monetization and brands looking to build more authentic, high-performance audience connections.

“We’ve truly only just begun,” Lora Feinman, SVP North America, said. “As marketers move away from legacy targeting methods, we’re building the infrastructure for the future of modern media planning. Along with identity and commerce data signals, Neuro-Contextual intelligence is a core component of the modern targeting trifecta. It’s privacy-compliant, grounded in interest, intent, and emotion — and built to scale.”

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