Connected TV (CTV) no longer needs an introduction. With more than 70% of U.S. households now owning at least one connected device, the shift from linear to streaming has transformed how audiences consume content and how advertisers connect with them.

CTV has quickly become the viewer’s favorite. On-demand access, flexibility, and a vast library of content have made it the natural replacement for traditional television. By 2024, viewership was already set to surpass 55 million in the U.S., with strong growth projected into 2025. This growth is not just about scale, it is also about transformation. Unlike linear TV, where advertising was based on broad demographic assumptions and limited measurement, CTV opens the door to personalized, trackable, and outcome-driven campaigns.

This evolution presents advertisers with unprecedented opportunities:

• Personalization: Ads tailored to viewing habits, interests, and purchase behavior.
• Measurement: KPIs such as reach, impressions, completion rates, CPCV, conversions, and incrementality deliver clarity on performance.
• Accountability: Unlike linear TV, CTV allows near real-time optimizations and outcome tracking.
  
  

But with opportunity comes complexity. The audience is fragmented across smart TVs, gaming consoles, set-top boxes, and streaming apps. Advertisers must learn to navigate this new ecosystem, master new tools, and rethink benchmarks to know whether their campaigns are truly working.

Against this backdrop, Episode 44 of AdTech Heroes welcomes Andy Beames, VP of Enterprise Partnerships at Samba TV, who breaks down how changing behaviors, IP-delivered data, and omnichannel extensions are rewriting the rules of TV measurement.

Below, we highlight the most critical takeaways from the conversation, enriched with insights on KPIs and contextual strategies that every advertiser should have in their playbook.

Key Highlights: Winning Audiences in the New Era of TV Measurement

• The shift from linear to CTV has redefined advertising — bringing personalization, measurable outcomes, and real-time optimization.
• IP-delivered data enables unified, privacy-safe measurement across platforms, turning fragmentation into actionable insight.
• CTV now drives both awareness and performance, allowing advertisers to measure outcomes like visits, downloads, and conversions.
• Complementing linear with CTV and digital video unlocks incremental reach and cost efficiency across audiences.
• Contextual TV and omnichannel data help advertisers connect meaningfully with underexposed households, ensuring campaigns are relevant, transparent, and outcome-driven.

TV Measurement at a Crossroads

Generational shifts are reshaping viewing. For younger audiences, Netflix and YouTube dominate the TV landscape. For viewers over 35, broadcasters still lead. This divergence means advertisers can no longer assume that a TV buy will reach a balanced spread of households.

Andy Beames points to recent BARB and Evan Shapiro data that highlight this split. Among 16–34s, the top three channels are Netflix, YouTube, and BBC, with no commercial broadcasters in the top tier. Among 35+, the top four remain broadcasters and pay TV. In other words, the value of broadcast airtime for younger audiences is rapidly diminishing, while for older demographics it still holds.

Measurement is not a call to action for the future, it is already evolving. Agencies and publishers are experimenting with new methodologies, incorporating clean rooms, and testing independent adtech tools to capture performance more holistically.

From IP Delivered Viewing to IP Delivered Data

IP delivery fractured attention, but also created the data to solve the problem. With Automatic Content Recognition (ACR) and other IP-based technologies, planners can:

• Connect broadcast, AVOD, SVOD, and social exposure at the household level.
• Use clean rooms to match datasets securely and respect privacy.
• Build unified measurement frameworks across devices and platforms.
  
  

As Andy explains, IP delivered content is both the problem and the solution. It has splintered viewing into multiple services, but it also generates the granular data advertisers need to stitch audiences back together.

When TV Drives Outcomes

Traditionally, TV was the channel for fame and reach. It built awareness at scale, but direct response and outcome metrics were limited. Today, CTV supports outcomes more typical of digital:

• Website visits and conversions
• App downloads and installs
• Store visits and purchases
  
  

This shift expands the role of TV. Advertisers no longer choose between brand or performance. They can measure both. Direct response advertisers who once relied exclusively on social platforms are now testing TV with DR-style KPIs, and brand advertisers are layering outcomes onto their traditional metrics.

The result is a richer, more flexible planning process where TV can play at every stage of the funnel.

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Learn More

• Closing the CTV Measurement Gap: Data Quality & Performance Talks
• A “Break” Down of Ad Breaks: Understanding CTV Ad Pods
• What is FAST TV & Why Marketers Are Tuning In to CTV Opportunities
• Why the oRTB Content Object is Key for Programmatic TV

Linear’s Incremental Reach Problem

One of the most striking insights from Samba’s State of Viewership report is that 92% of linear impressions in the UK reach only half of households.

The implication is clear: heavy TV viewers absorb the vast majority of impressions, creating high frequency but limited incremental reach. For advertisers, the cost of finding new or light viewers through linear alone becomes prohibitively expensive.

The solution is to complement linear with CTV, YouTube, and the open web. These environments allow brands to reach audiences who are underexposed or absent from traditional TV, often at a lower incremental cost.

Where Ad Tiers Fit Today

Premium streamers like Netflix and Disney Plus have launched ad tiers, signaling a new frontier for advertisers. However, inventory is still limited and CPMs are high. Andy notes that these tiers are best positioned for brand budgets, offering reach to audiences that are otherwise unreachable through broadcast.

For performance-driven campaigns, broader CTV supply and open web video remain essential. They provide the scale, price flexibility, and targeting precision needed to balance cost efficiency with measurable outcomes.

The CTV KPI Toolkit

To evaluate campaigns effectively, advertisers must combine traditional TV metrics with digital-style KPIs:

• Reach and Impressions: Who saw the ad, and how often
• Viewability and Completion Rate: Were ads actually watched
• CPCV and Conversions: What was the cost per complete view, and did it drive actions
• Incrementality: What additional value did CTV bring compared with other channels
  
  

Beyond campaign KPIs, advertisers should also track consequential effects like website traffic, share of voice, time on site, leads, and brand lift. This broader perspective helps prove not only whether ads ran but whether they made an impact on business outcomes.

The real advantage of CTV is the ability to tie exposure to both attention metrics and conversion metrics, delivering a more comprehensive view of ROI.

Omnichannel Reach Extension with Context

Advertisers increasingly ask how to find the households that linear misses.

This is where Contextual TV plays a key role:

• Targeting beyond genres: Align ads to the themes, topics, and emotions of the content viewers are watching, not just broad categories.
• Comprehensive reporting: Blend classic CTV KPIs with incrementality and attention metrics.
• Objective led creative: Formats designed to capture attention and drive specific outcomes.
  
  

By combining contextual intelligence with omnichannel data, advertisers can close the linear gap, connect with viewers in relevant moments, and deliver campaigns that are both efficient and meaningful.

Looking Ahead: TV measurement

Three shifts will define it's next phase :

1. Greater transparency of metadata so advertisers can verify placement, brand safety, and outcomes.
2. Cleaner and interoperable datasets that respect privacy while enabling cross-screen planning.
3. Outcome-aware benchmarks that treat TV as a multi-role channel, balancing reach, attention, and concrete business impact.
   
   

The cultural shift also matters. Andy emphasizes the importance of flexibility and empathy not only in hybrid work but also in how teams collaborate across TV, digital, and analytics. Measurement is technical, but the strategies that succeed are built on collaboration and shared understanding.

Tune In to the Full Episode

For a deeper dive into data quality, reach extension, and outcome-based TV, listen to AdTech Heroes Episode 44: “The New Rules of TV Measurement” with Andy Beames (Samba TV).

Want to become an expert in all things CTV? Explore Contextual TV and register for Seedtag Academy to learn how to measure success, target beyond genres, and design creatives built for attention.

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From scanning pages to understanding people

For decades, advertising has relied on demographics and behavioral profiles to reach audiences. Age, gender, income brackets, cookie trails, broad labels that reduce people to categories. But none of us fit neatly into those boxes. Our identities are shaped by unique passions, emotions, and intentions that demographics alone cannot capture.

Contextual targeting emerged as a privacy-safe alternative, matching ads to keywords, URLs and category labels to deliver scalable reach and brand safety, particularly on the open web. It was effective at the top of the funnel, but its foundation was classification. It could identify what a piece of content was about, not why a consumer engaged with it.

Advertising needed to evolve. Advances in neuroscience and AI opened the door to a new approach: moving beyond labels to understand the deeper drivers of attention and decision-making. This is the foundation of Seedtag’s neuro-contextual advertising, an approach designed to deliver campaigns that feel timely, resonate emotionally, and achieve measurable outcomes while remaining fully privacy-first.

Winning Audiences: Key Highlights

• Moving beyond demographics, neuro-contextual advertising taps into passions, emotions, and intentions in real time for privacy-first, relevant campaigns.
• Interest captures attention, emotion enhances recall, and intention drives action—together powering full-funnel impact.
• Agentic AI transforms insights into dynamic activation, aligning content, audiences, and creative with contextual signals.
• Advertisers win audiences by moving beyond stereotypes, creating ads that resonate deeply, feel human, and deliver measurable outcomes.

Why passions matter more than profiles

On paper, demographics can make us look predictable. Traditional demographic targeting would drop someone into a box and serve generic products. But real people are more complex. Their passions, values and intentions go far beyond labels.

As Brian Danzis, Chief Revenue Officer at Seedtag, explained in a recent blog post about AI for Advertising:

“Traditional demographic targeting would drop me into a “male, 45–54, suburban” box and push sports cars or generic gadgets. Liz’s neuro-contextual targeting sees the chef, the cyclist, and the environmental steward—and serves me organic food products, sustainable gear, boutique travel experiences, and brands that share my values.”

This is exactly where Seedtag’s neuro-contextual advertising shows its strength. By combining neuroscience principles with Agentic AI, it interprets interest, emotion and intent in real time, moving beyond classification to understand how people think, engage and decide.

At the heart of this approach is Liz, our proprietary neuro-contextual AI. Liz mirrors the sophistication of human thought by interpreting deeper signals in real time and delivering high-quality, privacy-first, full-funnel advertising across premium CTV, video and the open web. Because Liz is developed entirely in-house, we have full control over its evolution, ensuring our technology stays ahead in the privacy-first era without relying on third-party tracking or personal data.

How do interest, emotion, and intention drive superior outcomes?

At the core of neuro-contextual are three main principles that explain how advertising can capture attention, build affinity and drive action more effectively.

• Interest captures attention. When ads are placed in contexts that are relevant and familiar, they are processed more fluently. This congruence between message and environment makes them easier to notice, understand and remember.
• Emotion enhances recall and brand affinity. Emotional stimuli do not just attract attention, they command it. Content associated with positive feelings generates stronger responses, boosting both memory and decision-making. Ads placed in these environments benefit from a halo effect, building deeper brand connections.
• Intention drives engagement and action. When people are in a goal-directed state, their focus narrows to information that feels relevant to their journey. By aligning with this stage in real time, brands can activate intent at the exact moment when consumers are ready to explore, compare or convert.

When these three forces converge, advertising creates meaningful outcomes across the full funnel, always within the boundaries of evolving privacy standards.

The role of Agentic AI

Neuro-contextual technology can be thought of as the brain: it interprets signals of interest, emotion, and intent with a human-like understanding of content. But it reaches its full potential when paired with Agentic AI, which acts as the body that transforms these insights into meaningful action across the entire campaign lifecycle.

With an intuitive, conversational interface, Agentic AI dynamically:

• Aligns campaign goals with the most relevant content environments.
• Builds custom audiences based on genuine engagement patterns rather than predefined segments.
• Continuously adapts creative and messaging to resonate with the emotional tone of each placement.

This combination of neuro-contextual intelligence and agentic-driven activation has transformed contextual advertising from an advanced targeting tactic into a fully integrated media solution for privacy-first advertising.

Learn more about winning audiences

• Targeting Intention: Reshaping Performance Marketing with Custom Intent Audiences
• Pushing the Boundaries of the AI Revolution in Advertising
• What is Agentic AI And How is Transforming Digital Advertising
• Passions Over Profiles: AI for Advertising

Why this matters for advertisers

For advertisers, the promise of neuro-contextual goes far beyond improved targeting. It reshapes how campaigns are built, activated and optimized, delivering impact across the entire funnel while respecting user privacy.

• Privacy-first by design. Relevance delivered without third-party data, cookies or invasive profiling, ensuring campaigns stay compliant in an era of stricter regulation.
• Human-like contextual understanding. AI trained to comprehend text, images and video content in a way that mirrors how people naturally process information, enabling scalable strategies across CTV, premium video and the open web.
• Emotionally and semantically aligned ads. Campaigns resonate with the why behind user engagement, not just the what of content recognition.
• Higher attention and recall. Neuroscience shows that relevance is a cognitive metric: familiar, context-congruent stimuli are processed more fluently and with more positivity, leading to stronger engagement  and receptivity.
• Smarter decisions and strategic opportunities. With Agentic AI activating insights instantly, campaigns adapt continuously to context and audience signals for greater efficiency and measurable outcomes. Through Liz Agent, advertisers can unlock opportunities pre-launch and optimize across every stage of the campaign lifecycle, from planning and execution to delivery and learnings.

A smarter, more human era of advertising

Advertising has always tried to understand people, what they care about, how they feel and what they intend to do. For years, demographics and behavioral profiles reduced that complexity into categories and keywords. But today, we can go further.

With neuro-contextual advertising, brands can connect through what truly matters: people’s interests, emotions and intentions. It is advertising that feels timely, resonates deeply and delivers measurable outcomes while protecting privacy.

Emotion may be advertising’s oldest lever and now it is also its newest frontier. The best campaigns have always done more than inform. They moved us. They made us feel. And for the first time, we can measure and optimize for that too.

It is time to leave stereotypes behind and build campaigns that understand rather than interrupt. The future of advertising is more relevant, more human and more effective.

Discover how Seedtag’s neuro-contextual advertising can help your brand win audiences through their interests, emotions and intentions. Learn more here.

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Halloween goes beyond costumes and candy

Halloween has moved far beyond a one-day celebration. Today it stretches across entertainment, shopping, digital platforms and seasonal traditions, creating one of the richest periods for brands to connect with audiences.

Streaming platforms like Netflix, Prime Video and Shudder fuel the fascination with horror and supernatural genres, while events ranging from pumpkin patches and autumn fairs to large-scale haunted attractions bring communities together. Conversations peak not only around trick-or-treating, but also themed snacks, viral costumes, seasonal décor and movie marathons.

The scale speaks for itself:

In the weeks leading up to October 31st, Halloween content generated over 69,000 articles and more than 3.1 million visits, with an average presence score of 4.0 across media.

This confirms Halloween’s status not just as a seasonal holiday, but as a cultural phenomenon where entertainment, commerce and community converge.

Key Takeaways from Halloween Advertising Campaigns

• Brands can leverage neuro-contextual advertising to align campaigns with audiences’ passion, emotion, and intent.
• Halloween has evolved into a cultural phenomenon spanning entertainment, shopping, and community experiences.
• Key drivers include haunted attractions, fall activities, movies/streaming, candy, costumes, and décor.
• Candy and costumes mix nostalgia with creativity, fueling both tradition and DIY expression.
• Horror movies and streaming platforms anchor seasonal storytelling, keeping Halloween relevant for all ages.
  

The hidden map of Halloween conversations

When we look at the universe of Halloween content, some themes clearly dominate. Events and attractions lead the way, representing more than 40% of the conversation with over 16,000 articles and 637,000 visits. From pumpkin patches and farm festivals to Disneyland’s Oogie Boogie Bash and the Bronx Zoo’s Pumpkin Nights, audiences are leaning into experiences that combine festivity with community.

Close behind are fall activities and events with 14,000 articles and nearly 800,000 visits. Seasonal outings like apple picking, autumn fairs and even skywatching around the Hunter’s Moon have become part of the extended rituals, with brands like Time Out and Space.com shaping how audiences plan these experiences.

Movies and streaming also play a central role, generating 15,000+ articles and over 876,000 visits. Horror dominates the screen, from classics on Prime Video to cult hits from A24, with Netflix and Shudder cementing their place as go-to destinations for seasonal scares.

And of course, no Halloween is complete without candy, costumes and décor. These conversations are not just about what to buy, but about rituals of preparation: baking spooky recipes, crafting DIY décor, or curating the perfect outfit for the big night.

What emerges is not a single theme but a complex ecosystem of passions, one where entertainment, food and community overlap to create meaning.

Candy: nostalgia wrapped in chocolate

Halloween candy is more than sugar, it is tradition. Year after year, classics like Kit Kat, Reese’s and Snickers dominate conversations, but the real story is how these treats get reimagined. Homemade recipes turn candy into dirt pudding, puppy chow or monster themed snacks designed for parties and classroom fun.

This blend of nostalgic favorites and creative reinterpretations shows how candy fuels not just indulgence but participation. It is about crafting moments to share, whether with kids knocking on doors or friends gathering for a horror movie night.

Costumes and décor: DIY meets spectacle

Costumes have always been the centerpiece of Halloween, but the conversation today is broader. Beyond superheroes and princesses, people are embracing DIY culture mixing creativity with affordability. A red cape, some face paint, or even a pumpkin pillow can be enough to transform a living room into a Halloween set.

Decor too reflects this blend of personal expression and tradition. From fall garlands and skeletons to Pinterest worthy table settings, people are not just buying items, they are curating experiences. Halloween becomes a canvas for creativity, mixing the spooky with the playful and the homemade with the spectacular.

Movies: the heartbeat of Halloween storytelling

No other category cements the Halloween mood like movies. Seasonal classics such as Hocus Pocus, The Addams Family and The Haunted Mansion still dominate living rooms, while franchises like Halloween or Scream continue to evolve with new releases.

The cluster around horror movies and streaming reflects this passion, with 28% of visits concentrated here. From Netflix originals to A24’s critically acclaimed titles, audiences keep returning to horror as a defining ritual of the season.

At the same time, new productions and next gen horror directors keep the genre alive, attracting younger audiences and ensuring that Halloween remains both nostalgic and forward looking.

Activities: from festivals to school crafts

Halloween is no longer a one night affair. Autumn activities such as fairs, wine tastings and school crafts now form part of the extended rituals. Families explore fall outings, while kids bring the holiday spirit into everyday life.

Festivals and parties, from Mickey’s Halloween Party to Wicked Haunt Fest with its haunted walk throughs and beer gardens, showcase how Halloween thrives as a shared experience, something that unites generations, cultures and even brands looking to connect with audiences in festive, inclusive ways.

Haunted attractions and pop culture crossovers

Another cluster of interest is haunted attractions and spooky characters, generating over 317,000 visits. From New York’s Blood Manor to immersive exhibits like Dark Matter at Mercer Labs, audiences crave experiences that blend fear, art and entertainment.

Halloween also intersects with broader entertainment culture. Conversations around comics and entertainment clusters highlight Marvel, DC and Disney+ as cultural anchors, where superheroes, spooky storylines and cinematic universes merge with Halloween themes.

Learn more about Audience Insights and Marketing Performance

• Brand Marketing vs Performance Marketing​: Why Full-Funnel Collaboration Matters More Than Ever.
• Driving Growth in a Shifting Market: Strategic Insights for Automotive Marketing Success.
• Targeting Intention: Reshaping Performance Marketing with Custom Intent Audiences.
• Revving Up Growth: Deep Audience Insights for Automotive Advertising Success.

How brands can connect with meaning

This is exactly where neuro-contextual advertising makes a difference. By combining neuroscience principles with Agentic AI, it interprets interest, emotion and intent in real time, moving beyond classification to understand how people think, engage and decide.

Behind these connections is Liz, our proprietary neuro-contextual AI. By mirroring the sophistication of human thought, Liz interprets deeper signals in real time and delivers high quality, privacy first, full funnel advertising across premium CTV, video and the open web. By decoding interest, emotion and intent, Liz helps brands align their campaigns with the very moments when people are most open to engagement.

Halloween as a lesson in relevance

Halloween proves that people’s passions are richer than any demographic profile. They are not just parents or students, men or women, Gen Z or Gen X. They are movie buffs, DIY decorators, chocolate lovers and festival goers.

By understanding these signals, brands can move beyond stereotypes and build connections that feel personal, emotional and timely. Neuro-contextual advertising offers the tools to do this at scale, while respecting privacy and ensuring campaigns are both effective and responsible.

Because in the end, Halloween is not only about costumes and candy. It is about shared rituals, creativity and community, and how brands that join those moments can truly resonate

Discover how Seedtag’s neuro-contextual advertising can help your brand win audiences through their interests, emotions and intentions. Learn more here.

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In the evolving world of digital advertising, publishers face a balancing act. On one side is the need to maximize inventory monetization through programmatic advertising. On the other is growing pressure to protect user privacy and maintain brand safety across platforms. As cookies are phased out and new expectations from both audiences and advertisers take shape, publishers are reassessing their strategies starting with the role their advertising supply side platform (SSP) plays.

While first-party data and alternative targeting tactics have gained attention, one of the most effective paths forward is often overlooked: using a supply side platform built to deliver both performance and protection. Today, publishers need solutions that not only optimize fill rates and CPMs, but also prioritize context, relevance, and trust.

This post explores how a privacy-first advertising supply side platform can help publishers meet their business goals without compromising user experience or advertiser confidence.

The Changing Landscape for Publishers and Advertisers

As concerns around data privacy become more pronounced, publishers are under pressure to find monetization strategies that don’t rely on tracking users across the web. Audience targeting based on third-party cookies is fading, and in its place, new models are emerging that prioritize transparency and intent over personal data.

This shift has real economic consequences. According to industry research, publishers risk losing up to 60% of their revenue if they fail to transition away from third-party data. This makes it critical to rethink how ad inventory is packaged and sold, especially through programmatic channels.

Enter the modern advertising supply side platform. By rethinking how data is used (and more importantly, how it's not used) publishers can begin to align with the demands of both audiences and advertisers, without sacrificing scale or revenue.

How SSP Advertising Supports Brand Safety and Monetization

The core function of an advertising supply side platform is to help publishers make their inventory accessible to multiple demand sources, including networks, ad exchanges, and demand side platforms (DSPs). But not all SSPs are created equal. The right platform does more than connect publishers with buyers. It enables them to apply sophisticated controls to ensure ad placements meet both commercial and editorial standards.

Brand safety is a central part of this. Publishers need to ensure that ads shown on their sites reflect the tone, values, and credibility of their content. Poorly matched or inappropriate ads not only reduce user trust, but can also drive advertisers away.

A high-performing SSP should support this balance by offering tools that help:

• Filter out unsuitable demand sources
• Analyze content in real time using AI in publishing
• Enable granular control over ad placement
• Match ad formats to user behavior
• Support real time bidding without compromising editorial integrity
  
  

This allows publishers to maintain high standards while optimizing monetization, even as the traditional models of behavioral targeting lose relevance.

The Role of AI in Publishing and Brand Safety

Artificial intelligence is playing a growing role in how SSPs operate, particularly when it comes to ensuring brand safety and targeting precision. AI in publishing makes it possible to move beyond basic keyword matching and start analyzing context in a more human-like way.

Rather than relying on predefined taxonomies or user tracking, AI-enabled SSPs can interpret the content of an article, video, or image, assess sentiment, and understand user intent. This enables more accurate ad placement, improving both relevance and safety.

For publishers, this means greater control over which ads are shown, where they appear, and how they align with content. For advertisers, it provides confidence that their brand is represented in a meaningful, appropriate environment.

By integrating these capabilities into their SSP, publishers are able to deliver value to advertisers while keeping their own editorial and user standards intact.

Why Publishers Should Consider Upgrading Their SSP

As audience expectations shift and advertisers demand more transparency, publishers are discovering that legacy platforms may no longer meet their needs. Traditional SSPs often focus narrowly on maximizing fill rates, with limited ability to enforce context-based targeting or support real-time editorial decision-making.

An upgraded supply side platform should offer publishers:

• Real time analysis of inventory and context
• Better support for programmatic advertising models
• Compatibility with advanced ad formats, including video
• AI-powered tools for context, sentiment, and intent classification
• Built-in brand safety controls and content filters
• Clear integration with DSPs to sell ad inventory efficiently
  
  

These features make it easier for publishers to align their ad inventory with high-quality demand, while reducing the risks associated with mismatched placements or irrelevant targeting. In effect, the SSP becomes not just a sales engine, but a safeguard for both performance and reputation.

Maximizing Ad Revenue Without Sacrificing Experience

The traditional tension in digital advertising has been between scale and relevance. Publishers are often asked to choose between running high volumes of ads or ensuring that each impression delivers real value to the user and the advertiser.

A modern SSP breaks that tradeoff. By combining real time bidding with contextual analysis, publishers can match ad space with relevant creative in a way that doesn’t compromise the user experience. When an ad appears alongside content that aligns with the user’s intent or emotional state, it is more likely to drive engagement, improve recall, and lead to conversions.

From a monetization perspective, this allows publishers to:

• Increase CPMs by offering more relevant ad inventory
• Package niche or premium content for targeted campaigns
• Provide advertisers with more precise targeting options
• Improve fill rates across various channels, including header bidding and video
  
  

This integrated approach benefits the entire advertising ecosystem, from publishers and advertisers to the end user.

Contextual Intelligence Over Behavioral Tracking

A key reason contextual advertising has become more important is its ability to connect content and ads without relying on behavioral profiles. While many publishers are experimenting with email addresses, device IDs, or IP-based segmentation, these tactics still come with privacy concerns and regulatory risk.

By contrast, a supply side platform that uses contextual AI can deliver high-performance campaigns without requiring user data. This not only protects audience privacy but also helps future-proof the publisher’s business model.

When contextual advertising is backed by strong AI and built into the SSP itself, it becomes scalable. Publishers can categorize articles, videos, and other content types in real time, allowing for smarter placement of creative based on subject matter, tone, and even visual cues.

This supports better performance metrics across the board, including ad recall, time on page, and brand perception, while helping advertisers target audiences based on what they care about in the moment, not who they are across the web.

From Strategy to Execution: How Publishers Can Get Started

The first step in upgrading your approach is aligning with an advertising supply side platform that supports advanced contextual capabilities. From there, publishers can begin to:

• Define clear goals for ad performance and brand safety
• Map inventory against content categories and user interests
• Test contextual campaigns with a variety of ad formats
• Identify keywords and topics that perform well across verticals
• Use video and high-impact formats to drive engagement
  
  

With the right SSP in place, it becomes much easier to manage both the operational and technical requirements of running a privacy-first, performance-driven advertising strategy.

In a digital environment where both users and advertisers demand more accountability, publishers can no longer rely on outdated tools or data-driven models that lack transparency.

By upgrading to an SSP built for modern standards, publishers gain the flexibility, control, and insight needed to thrive. Whether it’s optimizing programmatic performance, enhancing brand safety, or protecting user experience, the SSP plays a critical role in the publisher’s toolkit.

Want to learn more? Discover how Seedtag helps publishers future-proof their advertising strategies with an AI-powered neuro-contextual approach that balances relevance and results.

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In a world where privacy reshapes how we measure and connect, digital advertising is undergoing a quiet but fundamental shift. The traditional approach of identifying users and following them around the web is giving way to something more precise, more respectful, and ultimately more effective: targeting intention.

At the center of this evolution are custom intent audiences. Unlike demographic or interest-based segments, these audiences are built around real-time purpose. They don't rely on who users are, but on what users are trying to do in the moment. For advertisers navigating a post-cookie landscape and rising expectations for both relevance and privacy, the change to intent-based marketing couldn't be more timely.

Custom Intent Audiences vs. Traditional Segments: What Makes the Difference?

Traditional audience segments work by assigning users to broad groups based on past behavior or assumed interests. A user who once browsed for electric cars might continue receiving related ads for weeks, even if their focus has shifted elsewhere. Custom intent audiences, by contrast, start with the present. They identify users based on the content they are actively consuming (articles, product comparisons, search behaviors…) and match that with the user’s likely intention.

This present-tense approach makes custom intent audiences inherently more relevant. It’s the difference between assuming someone is interested in fitness because they follow a sports brand on social media, and recognizing they’re ready to buy running shoes because they’re comparing prices on review pages.

The outcome? More qualified impressions, less wasted spend, and a clearer path to performance.

From Identity to Intention: Privacy-First Precision

One of the main advantages of custom intent audiences is how well they fit within today’s privacy-first advertising landscape.

Unlike identity-based models that depend on cookies or device IDs, intention-based targeting doesn’t need to know who a user is. It only needs to understand what they’re doing.

This difference isn’t just technical but philosophical. Instead of building user profiles based on long-term surveillance, advertisers are focusing on real-time, in-the-moment signals. These include the depth and structure of content, the tone and sentiment of the page, and the user’s position in their decision-making journey.

By using AI models trained to read these signals in real time, advertisers can detect not just interest, but readiness. And they can do so without compromising user privacy.

The Metrics That Matter

Performance is still the goal. And here, the numbers speak for themselves. When global automotive brand Nissan adopted Seedtag’s intention-based strategy to promote its C-SUV category, the results were substantial:

• A 67% reduction in Cost Per Qualified Visit (CPQV).
• A 34% drop in Cost Per Lead (CPL).
• A threefold increase in qualified visits against target.
  
  

What made the difference was simple. Ads were served only when users were showing active signals of intent; not just reading about cars, but comparing models, evaluating financing, or locating dealerships. In doing so, Nissan avoided mid-funnel waste and focused their investment where it had the most impact.

Across industries, similar results are emerging. Campaigns that embrace custom intent audiences consistently outperform those relying on static segments, particularly when it comes to mid- and lower-funnel outcomes.

Aligning Creative with Intention

Reaching the right user in the right moment is only part of the equation. The creative needs to match that moment too. When advertisers target based on intention, the creative strategy must follow suit. Messaging that resonates in a high-intent context looks different than messaging designed for awareness or passive browsing.

For example, a user reading general reviews about smartphones might respond well to informative, value-driven creative. But a user comparing two models side-by-side, looking at specifications or price breakdowns, is further along the journey. In that context, the ad should be clear, action-oriented, and directly aligned with the decision at hand.

This is where Seedtag’s AI intention models play a dual role. Not only do they assess the user’s intent, they also measure how relevant the campaign’s messaging is for that moment. By calculating both an Intention Score and a Campaign Relevance Score, Seedtag’s system ensures that ads appear not just when users are ready to act, but when the message is most likely to land.

This alignment between content, mindset, and creative is what turns impressions into outcomes.

The Case for Rethinking Audience Strategy

Marketers have spent years optimizing for attention by measuring viewability, maximizing impressions, and expanding reach. But attention alone doesn’t drive performance. Without intention, attention is passive. It doesn’t necessarily signal interest, and it rarely signals readiness.

Custom intent audiences offer a way to bridge that gap. They allow advertisers to:

• Replace volume with precision.
• Move beyond proxy metrics to actionable insight.
• Increase qualified engagement without relying on personal data.

In short, they bring intentionality into targeting, in a move that’s both ethically sound and commercially effective.

Where to Begin: Turning Strategy Into Skill

Custom intent audiences are a feature that represents a mindset shift. One that requires new ways of planning, measuring, and creating. For advertisers looking to make that shift, knowledge is the first step.

That’s why Seedtag has launched a new certification through Seedtag Academy: “Targeting Intention.” This program unpacks everything from the foundations of intent-based targeting to the role of AI in modeling user mindset in real time.

It’s designed for marketers who want to:

• Understand how intention works across the funnel.
• Activate privacy-first strategies that don’t sacrifice performance.
• Build creative that speaks to purpose, not just persona.

Whether you're in strategy, media, creative, or analytics, the course provides a practical framework for applying intention in real campaigns.

You’ll learn why performance now depends on understanding not who users are, but what they’re trying to do,  and how you can meet them there.

Enroll in the Seedtag Academy Certification

If you're ready to move beyond identity and start targeting real-time purpose, the new Seedtag Academy certification on “Targeting Intention” is now open. Learn how to activate campaigns that perform better, cost less, and respect your audience. Discover the full course and enroll today.

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Back to School is more than the return of classes and new supplies. It is a cultural reset that sparks consumer activity across fashion, technology, nutrition, and family life. Each year, this season mobilizes millions of students, parents, and educators who are making purchase decisions with purpose and intention.

For advertisers, 2025 offers a unique opportunity to connect with audiences who are actively shaping their routines and priorities. The season reflects a blend of family needs, digital-first lifestyles, and rising expectations for health, comfort, and value.

Seedtag’s neuro-contextual AI, Liz, decodes how people think, engage, and decide, empowering advertisers to truly understand audience behavior and prepare for back-to-school campaigns that feel timely, meaningful, and impactful.

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The Audiences Defining Back-to-School 2025

Back-to-School is powered by four core groups, each with unique mindsets and behaviors:

• Parents: Seek tech and healthy products for their children, along with solutions to enhance family comfort and well-being.
• Grade School Students: Interested in technology, video games, fashion, and sports, looking for ways to express themselves and have fun.
• University Students: Prioritize tech for productivity, comfortable fashion, and focus on mental health and well-being.
• Education Leaders: Seek educational tools to improve teaching and solutions for managing workload and well-being.
  
  

This audience segmentation reveals that 52% of parents are influenced by online promotions and 45% of university students engage with seasonal offers.

Key Insight: Each group interacts with content differently, and these numbers highlight just how active and responsive Back-to-School audiences are when it comes to digital engagement.

Why This Back to School Trends Matters for Brands:

Campaigns that are personalized will perform best. A neuro-contextual approach allows advertisers to target based on real interests, emotions, and intent—rather than assumptions.

What Content Really Matters This Season?

Seedtag’s analysis of back-to-school engagement reveals four major content clusters dominating attention. Each cluster signals a space where advertisers can activate with impact.

Healthy Snacks and Nutrition

Parents are prioritizing well-being, making nutrition one of the strongest back-to-school themes.

• Interest peaks around cereals, fruit, oat snacks, dairy alternatives, and wellness drinks.
• Major players: Kellogg’s, Coca-Cola, Tesco, Aldi, Danone, Innocent, Alpro, Nestlé, PepsiCo, Tropicana.

Why This Matters for Brands

Healthy snacking has become a back-to-school essential. FMCG brands can leverage this momentum with contextual activations that align with family-focused lifestyles.

EdTech and Devices

Tech and learning go hand in hand, with students and parents seeking devices that enhance productivity and entertainment.

• Hot topics include laptops, smartphones, headphones, and gaming consoles.
• Major players: Microsoft, Google, HP, Lenovo, Logitech, Samsung, Apple.

Why This Matters for Brands

With digital habits firmly established, the Back-to-School moment is prime time for tech brands to position their products as must-haves for both education and leisure.

School Clothing and Footwear

Fashion continues to define identity during Back to School.

• Strong engagement with uniforms, sportswear, sustainable apparel, and footwear.
• Major players: Adidas, Nike, Puma, Primark, Asda, Next, Marks & Spencer.

Why This Back to School Trends Matters for Brands

Students and parents look for comfort, affordability, and style. Brands that highlight cultural relevance and emotional connection will earn stronger loyalty.

Family Cars

Back to School influences mobility decisions, with parents looking for cars that deliver safety, convenience, and sustainability.

• Strong engagement around SUVs, hybrid cars, and electric models.
• Major players: Volkswagen, Toyota, BMW, Kia, Ford, Hyundai, Renault, Peugeot.

Why This Matters for Advertisers

Automotive advertisers can tap into the family conversation by linking campaigns to everyday school runs, safe travel, and eco-conscious choices.

From Insight to Connection: The Role of Neuro-Contextual Advertising

The back-to-school season is one of the most competitive moments of the year, with countless brands vying for attention. What cuts through the noise is not louder messaging, but smarter relevance.

Seedtag’s neuro-contextual AI, Liz, does not simply classify articles or surface keywords. It interprets cognitive signals in real time, decoding user interests, intentions, and emotions.

By mirroring the sophistication of human thought, Liz ensures campaigns are delivered in high-quality, privacy-first environments across premium CTV, video, and the open web. Instead of being limited to top-funnel exposure, Liz aligns brand messaging with every stage of the journey, from awareness to consideration to purchase intent.

The result is intelligence that empowers advertisers to scale relevance while respecting user privacy, enabling them to anticipate audience behavior and prepare for back-to-school campaigns that feel timely, meaningful, and impactful.

The Playbook for Back-to-School Success

• Align with healthy habits: Nutrition-driven activations will resonate with families prioritizing well-being.
• Own the EdTech conversation: Position devices and platforms as essential for productivity and lifestyle.
• Blend fashion with culture: From uniforms to sneakers, connect with audiences through identity and expression.
• Drive family relevance: Automotive brands can link mobility, safety, and sustainability to the Back-to-School journey.

From Trends to Action

Back to School 2025 is more than a seasonal spike. It is a cultural touchpoint that reflects shifting priorities around health, technology, identity, and family life.

Brands that align with these conversations and leverage neuro-contextual AI to deliver campaigns in the right moments will go beyond visibility. They will earn relevance at the very moment when audiences are most open to engagement.x

Ready to maximize your back-to-school campaigns? Discover how Seedtag’s can help you deliver impact where it matters most. Get in touch!

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At a time when marketing teams are under increasing pressure to justify every dollar spent, the gap between brand marketing and performance marketing is narrowing. What used to be considered two distinct disciplines, upper-funnel storytelling and lower-funnel conversion, are now in constant conversation.

But how can marketers truly unite both approaches to build long-term brand equity without sacrificing short-term returns?

That’s the question at the heart of the latest episode of Seedtag’s AdTech Heroes podcast. Host Dal Singh sits down with Louise Owen, Chief Performance Officer at UM, for a candid discussion about how brand and performance teams can align around a shared goal: delivering results that matter.

From Louise’s unconventional career path in engineering to her experience leading strategies across multiple global markets, the conversation moves seamlessly between frameworks, culture, and measurement.

The takeaway? Full-funnel marketing success doesn’t come from choosing between brand marketing and performance marketing. It comes from understanding how they work together.

“Brands are asked to demonstrate performance… especially for above-the-line channels where measurement takes time.”, Louise Owen, Chief Performance Officer at UM

From Engineering to AdTech: A Global Perspective

Louise’s path into media was far from linear. With a background in civil and industrial engineering, she initially focused on data analysis and optimization. That technical foundation eventually led her into search trading, where she became curious not just about how campaigns were being optimized, but why.

That curiosity fueled a career that took her to GroupM roles in the US, Colombia, Singapore, Australia, and France, before ultimately bringing her to London. The result is a uniquely global perspective on how media strategies evolve across different markets and what holds them together.

“I was always interested in how things fit together,” Louise explains. “Understanding the mechanics of media was only part of the job. I wanted to know what was driving decisions across the full brand and campaign lifecycle.”

Why Now: The Need for a Chief Performance Officer

So why introduce a Chief Performance Officer role at a network known for its branding strength? As Louise puts it, “Brands are asked to demonstrate performance… especially for above-the-line channels where measurement takes time.”

With financial pressures mounting and marketing budgets under scrutiny, CMOs are being asked to show real, measurable impact across every channel. And while branding efforts might deliver over the long term, stakeholders want visibility now. That tension is what her role aims to address, and bridging the gap between strategic vision and operational impact.

Her work focuses on helping brands understand how to mature digitally, regardless of whether they identify as performance-driven or brand-led. That means showing how each part of a media plan contributes to outcomes and how collaboration between teams can sharpen both sides of the funnel.

How Brand Marketing and Performance Marketing Drive Each Other

For Louise, the divide between brand marketing and performance marketing is largely an internal construct. “To consumers, every touchpoint is a brand experience,” she says. Whether it’s a product video, a display ad, or a sponsored post on social media, each moment contributes to perception and engagement.

This shift is forcing teams to rethink silos. Tools like unified planning platforms and shared audience insights are helping brands take a more integrated approach - one where strategy, audience segmentation, and measurement are designed from the ground up to serve both awareness and conversion goals.

She offers a simple example: search. While often viewed as a performance channel, it also serves as a visibility tool. Being discoverable at the right moment reflects how well a brand has established itself. A strong brand presence enhances search results. A clear search signal helps refine brand messaging. The two are inseparable.

This integration is about more than campaign design. It’s also about shifting measurement goals. Rather than segmenting success by tactic, brands are now starting to ask broader questions: Which audiences are engaging? What content is resonating? Where is value being created?

Audience Understanding Comes First

Behind every successful full-funnel campaign is one central factor: knowing your audience.

Louise emphasizes that aligning on target segments (real, reachable, addressable audiences) is what allows brand and performance teams to work in sync.

It starts with the basics: Who are you trying to reach? What are their behaviors, their needs, their intentions? This is where intent-based marketing powered by data plays a crucial role.

Louise points out that brand planners and performance marketers often use different data sets, which can create disconnects in messaging and targeting. Integrating those perspectives allows for smarter segmentation, more relevant messaging, and better outcomes.

Retail media, she notes, is one of the spaces where this convergence is playing out most clearly. By combining emotional engagement with direct access to purchase behaviors, retail environments offer a snapshot of how upper and lower funnel dynamics are colliding in real time.

Local Nuances, Global Lessons

Having worked across five continents, Louise has a deep appreciation for local nuance. In countries like Australia, for example, centralized infrastructure and detailed consumer research enable advanced cross-channel campaigns. In contrast, regions with more complex supply chains or data regulations require more adaptive planning.

She highlights the challenges global brands face when trying to unify their ad tech and martech stacks across regions. What works in the UK may not translate to Poland or India, due to legal constraints, supply chain issues, or market fragmentation.

Yet these differences are also opportunities and are consistently pushing brands to rethink how and where they collect data, how they define success, and how they adapt creative to local needs.

Can Brand and Performance Teams Drive Full-Funnel Success?

The answer, for Louise, is an emphatic yes but only if organizations are willing to shift how they work, not just how they plan.

She shares examples of brands using performance data to improve brand targeting, and vice versa. One case involved a brand with overlapping audiences across multiple products. By examining performance insights, that is how people engaged with different campaigns and moved between products, then the brand was able to reallocate spend, refine messaging, and reduce internal duplication.

Instead of managing campaigns in isolation, they began planning them as part of a shared ecosystem, where performance results could inform brand direction and brand signals could optimize conversion.

It’s this kind of feedback loop that Louise sees as essential to future success. And it’s why she believes that AI, if deployed correctly, could finally unlock better measurement across the board, offering real-time insights that reflect how audiences actually behave, not just how they’re expected to.

Measurement and the Road Ahead

One of Louise’s biggest hopes for the industry is smarter, more customizable measurement. As she notes, legacy approaches like marketing mix models often struggle to keep up with fast-changing digital behavior. She believes AI will play a major role in evolving these systems while helping brands understand which channels actually drive growth, and why.

She’s also candid about the role that data infrastructure plays. Too often, companies are held back by fragmented systems and years of unstructured information. If she could go back in time and give brands one piece of advice, it would be to unify their data from the beginning.

“Unification of data and signals is really what powers insights,” she says. “You need a clean dataset to build scenarios and make good decisions.”

What It Means for Marketers Today

Ultimately, Louise’s insights point to a simple but often overlooked truth: real marketing impact comes from alignment. When brand marketing vs performance marketing is seen as a choice, teams work in opposition. But when they’re aligned, from segmentation to creative to measurement, the result is smarter campaigns, more relevant experiences, and stronger business outcomes.

The challenge now is less about building new capabilities and more about connecting existing ones. For marketers, that means investing in shared tools, fostering cross-team collaboration, and reframing measurement in terms of real-world results.

Brand marketing vs performance marketing isn’t a debate. It’s a relationship. And as Louise makes clear in this conversation, the most successful brands are the ones that treat it that way.

Listen to the Full Episode
Want to dive deeper into this conversation? Listen to Louise Owen on AdTech Heroes: When Branding Meets Performance: Insights from Kinesso and hear how brands can unite storytelling and strategy for full-funnel success.

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Passions Over Profiles: How AI Sees the Real Me… and My Bees

On paper, I’m the definition of a demographic stereotype: a suburban white male in his late 40s who likes sports and wood-fired cooking. Statistically, I fit the mold—over 80% of U.S. men consider themselves sports fans, and surveys show grilling is still seen as a male-dominated activity.

But numbers only tell a fraction of my story. Beyond the smoker and team sports, I’m passionate about health, fitness, and well-being. I love creating meals from fresh, organic ingredients sourced directly from farms. Cycling is central to my lifestyle, taking me across New York State in search of the best trails and vegetable stands. That love for the outdoors and healthy eating led me to gardening, and eventually, to beekeeping—an uncommon pursuit for someone with my demographic profile.

Beekeeping isn’t just a hobby; it’s a reflection of my values: sustainability, environmental stewardship, and a handcrafted connection to nature. It’s proof that broad labels like “sports” or “barbecue” can branch into highly specific, deeply personal passions—unique combinations of interests, behaviors, and values that no demographic snapshot can reveal.

Why Seedtag’s AI Liz Makes the Difference: AI for Advertising​

This is where Seedtag’s Neural-Contextual AI, Liz, stands apart. Liz doesn’t pigeonhole me by age or gender. Instead, she understands the full context—maybe I’m browsing cycling routes, then organic cooking guides, then articles about pollinators or sustainable farming. She connects these signals to understand who I truly am, delivering relevance instead of stereotypes.

Traditional demographic targeting would drop me into a “male, 45–54, suburban” box and push sports cars or generic gadgets. Liz’s neuro-contextual targeting sees the chef, the cyclist, and the environmental steward—and serves me organic food products, sustainable gear, boutique travel experiences, and brands that share my values.

So while many people who look like me may be sports fans, that doesn’t define the whole person. Like minded affinities can reveal deeper values—care for artisanal craftsmanship, our environment and experiences. Seedtag’s AI Liz bridges these unique interests, replacing broad demographic assumptions with rich, colorfully informed context.

When brands connect with me through my passions, they’re not just serving ads; they’re starting conversations that feel relevant, personal, and worth engaging with. That’s the power of advertising in context: it speaks to who I am, not just what I look like on paper.

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Earlier this year, we introduced Neuro-Contextual Advertising, Seedtag’s new evolution in marketing innovation that combines neuroscience principles with Agentic AI to interpret interest, emotion, and intent in real time. This represents a decisive evolution from traditional contextual targeting, moving beyond reading pages to truly understanding people and what drives them.

At the heart of this transformation is Liz, our proprietary, fully in-house Neuro-Contextual AI. Liz mirrors the sophistication of human thought by interpreting cognitive signals in real time and delivering high-quality, privacy-first, full-funnel advertising across premium CTV, video, and the open web. Building on this neuro-contextual understanding, Seedtag utilizes the Liz Agent, powered by the latest advancements in Agentic AI, to autonomously activate Liz’s intelligence through an intuitive, conversational interface. Because Liz is developed entirely in-house, we have full control over its evolution, ensuring our technology stays ahead in the privacy-first era without relying on third-party tracking or personal data.

Now, this vision is being recognized on a global stage. eMarketer’s “Tech Trends H1 2025” report has named Neuro-Contextual Advertising as the number one trend at the intersection of AI and neuroscience, and placed Seedtag at the forefront of this transformation. For us, this is more than industry recognition, it is validation of a shift we have been driving for years, and a signpost for where digital advertising is headed next.

Why This Recognition Matters

As eMarketer states in its Tech Trends H1 2025 report, “AI-powered neuro-contextual advertising is revolutionizing how brands target consumers. Companies like Seedtag are combining neuroscience research with real-time emotional state detection.”

eMarketer’s recognition of neuro-contextual advertising as the top trend highlights its growing importance for brands, agencies, and publishers navigating the evolving advertising landscape. The future of advertising lies not in static keywords or third-party data, but in understanding the human psyche in a privacy-first way.

The report emphasizes several key differentiators of Seedtag’s approach:

• Real-time emotional intelligence: analyzing context and viewing patterns to detect emotional states as they happen.
• Dynamic creative alignment: adjusting ad tone from upbeat creative during high-energy moments to more subdued messaging in reflective contexts.
• Privacy-first delivery: achieving precision targeting without cookies or user tracking, aligning with the expectations of a privacy-first era.

From Marketing Innovation to Impact

When we launched Neuro-Contextual advertising, we set out to answer a critical need. We wanted to deliver advertising that feels timely, resonates emotionally, and drives measurable outcomes while respecting privacy.

Our approach is built on three cognitive pillars:

• Interest: Liz connects real-time content signals to broader user interests, helping brands reach people based on what truly matters to them.
• Emotion: Liz detects the emotional tone of content to deliver ads that align with how users feel, creating deeper and more human connections.
• Intent: By analyzing context, Liz anticipates the goal a person has in mind when engaging with content, whether they are browsing, researching, or ready to convert.

Liz is both the intelligence that extracts audience insights on interest, intent, and emotion, and the AI Agent that activates those insights to create, customize, and optimize campaigns in real time. This integration ensures campaigns are continuously optimized, and remain relevant at every stage of the funnel.

A Turning Point for the Industry

In a crowded adtech landscape, external validation from a respected source like eMarketer matters. It signals that neuro-contextual is not a niche experiment; it is a defining trend shaping the future of advertising.

As the report notes, “Companies like Seedtag are pioneering technology that understands viewer mindset… Using neuroscience-trained AI, Seedtag’s platform intuits interests, emotions, and purchase intent by analyzing context and viewing patterns.”

Advertising has always aimed to connect brands with their audiences in the right place and at the right time. Historically, digital advertising intelligence relied heavily on methods like keyword matching, URL targeting, and basic content categorization. While these tools had their place, they offered only a surface-level understanding of audience context.

Traditional contextual targeting could tell you that a user was reading an article about electric cars, but not whether the article was a glowing review or a critical takedown — or whether the reader was simply curious, seriously considering a purchase, or already decided against it. As privacy regulations tightened and consumer expectations grew, this gap became a critical weakness.

Neuro-contextual advertising closes that gap. By combining neuroscience principles with advanced AI, it moves from simply identifying “what” content is about to understanding “why” a person is engaging with it, and “how” they are likely to feel and act next.

For brands and agencies, this means

• Access to full-funnel outcomes across premium CTV, video, and open web.
• Audience intelligence that is dynamic, scalable, and privacy-first.
• A competitive advantage in engaging consumers in moments that matter most.

Looking Ahead Marketing Innovation

Recognition from eMarketer is just the beginning. We are continuing to refine Liz’s capabilities, expand the functionality of the Liz Agent, and explore partnerships in neuroscience to advance the scientific expertise at the core of our approach.

Our mission remains the same: to help brands win their audiences by tapping into their interests, emotions, and intentions, and to do so in a way that is respectful, relevant, and results-driven.

The future of advertising is not just about being seen; it is about being understood. And with neuro-contextual advertising at the forefront, that future is already here.

Source: eMarketer, Tech Trends H1 2025.

Discover how Seedtag’s Neuro-Contextual Advertising can help your brand win audiences through their interests, emotions, and intentions. Learn more about this marketing innovation trend here.

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Amid accelerating deployment of programmatic technology in TV, the openRTB Content Object has become an essential ingredient for buying and selling television media in real-time.

As the television and programmatic advertising ecosystems converge, several interesting applications and technical specifications are playing a more prominent role in how TV ads are bought and sold.

Innovative addressable TV specs are unlocking 1:1 advertising opportunities across broadcast television inventory. Competitive separation and deduplication rules, which have long been table stakes for highly-curated commercial breaks, are becoming commonplace for dynamically-constructed ad pods. And traditional creative review processes, once a tedious (yet necessary) task for programmers, are being automated at scale — just to name a few examples.  

While many of these evolving solutions are playing a pivotal role in the convergent TV arena, one critical, but often-overlooked, specification is the Content Object. Part of the IAB Tech Lab’s openRTB protocol, the Content Object helps bring powerful contextual data to programmatic marketplaces, enabling media sellers and buyers to seamlessly transact in real time off key information that historically has been used to inform direct TV buys.

As the leading convergent TV advertising platform, we often find ourselves speaking with media sellers and buyers about the opportunities surrounding the Content Object, and how it can best be deployed. Below, we’ve answered some of the most common questions we hear, hoping to shed some more light on why the Content Object is so key for programmatic TV:

What is the IAB oRTB Content Object?

The Content Object is one part of the IAB’s openRTB standard, which is a widely-adopted transaction protocol used for the programmatic buying and selling of media (in real-time). The oRTB protocol has a number of different object specifications for both bid requests and responses, including metadata like geography, users, devices, and more.

As a bid request specification, the Content Object is a set of standardized information shared by media sellers that is specific to the actual content or program in which an ad opportunity is available, rather than the app or bundle. Exchanging this type of information enables media sellers and buyers to transact off highly-valuable content metadata, such as a TV show’s name, rating, or genre.

What are the types of metadata included and exchanged via the Content Object?

The Content Object includes a wealth of contextual metadata, spanning 25 available fields in total. The metadata supported by the spec includes information common in episodic television, such as the specific series, show, episode, genre, and rating. Other information like production quality, program language, whether or not the opportunity lives within a livestream, and so forth, is also supported via the Content Object — a full version of which can be found in section 3.2.16, here.

How are programmatic media sellers and buyers using the Content Object, and what are the associated benefits?

Media sellers use the Content Object to automatically provide prospective media buyers with valuable information on the context or program in which their ad may appear (again, as part of the bid request). This is critical within programmatic marketplaces specifically, as advertisers are increasingly seeking more flexibility and transparency into their campaigns from both a content targeting and ad delivery perspective.

By transacting off the Content Object, media sellers earn premiums for their inventory by making it more transparent and enticing for buyers, which helps to drive up demand density (e.g. the number of brands bidding on their inventory). Media buyers meanwhile benefit from greater contextual targeting insights for premium TV programming, ensuring brand safety against key client criteria while allowing for more relevant and impactful advertising on the big screen.

More broadly, why is the oRTB Content Object so important as programmatic and TV converge?

As programmatic technology and oRTB protocols are increasingly deployed in both connected and traditional television, it becomes critical that consistent parameters and taxonomies are established to inform the buying and selling of TV media.

Historically, episodic TV inventory has been sold directly against a combination of audience ratings and show-level information. Ensuring the latter of these two (valuable content data) is exchanged consistently between media sellers and buyers in an automated fashion via programmatic is critical to helping all parties accomplish key objectives, from either a yield optimization or an advertising impact standpoint.

This is all the more important as privacy regulations evolve and as viewing behaviors proliferate across cable, broadcast, and connected TV. Establishing platform-agnostic and privacy-conscious transaction standards, such as via the Content Object, is key for building both a sustainable advertising ecosystem and interoperability across systems.

What should media sellers and buyers be doing in order to take full advantage of the Content Object?

If you’re a media seller, configure your bid requests to pass all relevant information within the Content Object. This ensures your inventory is made available to all relevant advertisers who are interested in buying against specific shows or genres, which ultimately helps you drive greater demand density and yield.

For media buyers, configure your advertising platform — whether that be a DSP or an internal trading desk — to accept and read the Content Object. This is a crucial first step that will allow you and your end brand clients to unlock highly-valuable contextual metadata for campaign targeting and private marketplace (PMP) curation.

To learn more about the Content Object, and how you can capitalize on all that it enables from a yield or advertising impact standpoint, reach out to us here:

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In Episode 22 of The PubWay podcast, hosts Tina Iannacchino and Mike Villalobos welcome Brian Lin, SVP of Product Management, Advertising at TelevisaUnivision. The episode dives deep into the state of CTV measurement and the broader challenges facing programmatic advertising today.

Brian, who leads advanced advertising strategy for the world's leading Spanish-language media company, shares timely insights on first-party data, evolving consumer behavior, and what publishers and advertisers need to get right if they want to improve performance across CTV environments.

The conversation touches on everything from co-viewing dynamics and data match rates to the role of AI in scaling measurement. Below, we break down the most critical takeaways from the episode.

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CTV Measurement at a Crossroads

With connected TV approaching mass adoption, advertisers and publishers alike are trying to understand how to measure campaign performance accurately. One of Brian’s early points underscores the magnitude of this shift:

“CTV is almost at the point in which it's getting close to 50% of total video consumption.”

This growth brings both opportunity and complexity. While digital tools make CTV inherently more measurable than traditional linear television, many advertisers still struggle to capture the full picture of their campaigns. One reason? Data fragmentation.

Advertisers often rely on disparate data sets stitched together through intermediaries, introducing gaps and reducing match rates. “There’s always a tradeoff between data quality and scale,” Brian explains. “You want a high match rate, but not at the expense of accuracy.”

In CTV, where brands look to measure outcomes like cost per completed view (CPCV), return on ad spend (ROAS), and unique viewer reach, missing signals can undermine performance and accountability. Improving CTV measurement starts with improving the quality and interoperability of the data itself.

Closing the Gaps with First-Party Data

For publishers and advertisers, closing the measurement gap means building stronger, more privacy-conscious data infrastructure. Brian points to TelevisaUnivision’s own first-party data strategy as a blueprint.

By building a household graph that aggregates signals from across local live events, streaming content, linear television, and audio platforms, the company now reaches 95% of US Hispanics. “It’s a game changer,” Brian notes, especially in a landscape where third-party data still struggles to identify Spanish-speaking audiences accurately.

“Some third-party datasets show only about 40% accuracy in identifying Hispanic consumers,” he explains. “That’s a huge miss for advertisers with the right intent.”

Clean rooms are emerging as an effective solution to connect first-party data from publishers and advertisers. These environments allow datasets to be combined securely, enabling granular CTV measurement while respecting privacy standards.

Measuring CTV in Multi-Viewer Environments

Traditional measurement models were built for one-to-one devices like laptops and mobile phones. But with CTV, viewers gather in living rooms, often watching together. This creates a multiplier effect on impression value and a measurement blind spot for brands focused solely on device-level data.

“Co-viewing is still one of the biggest opportunities in CTV,” Brian says.

While general market co-viewing rates hover around 1.5 to 1.7 viewers per screen, that figure rises to 2.6 to 3 for US Hispanic households.

What this means in practical terms is that a CTV ad served to one device might actually be reaching three people. Adjusting measurement frameworks to account for co-viewing can dramatically improve perceived campaign performance, especially in family-oriented or multicultural households.

But to do so, publishers must be willing to share more metadata and log-level data with advertisers. “It’s a receipt,” Brian explains. “Advertisers should know what content their ads ran against if we want them to measure and come back.”

The Role of AI in Real-Time CTV Optimization

AI is already playing a supporting role in content classification, sentiment analysis, and targeting. But its true potential lies in making CTV measurement more dynamic and adaptive.

Take metadata, for instance. In the past, CTV inventory was often sold in bulk, with little transparency about the content it would appear alongside. But as AI tools improve, publishers can now categorize programming with greater precision, identifying not just genres, but tone, emotion, and thematic context.

This opens the door for more sophisticated brand safety controls and targeting strategies. For example, an advertiser promoting family products might want to align with upbeat, co-viewed programming but avoid more intense or adult-themed content.

At TelevisaUnivision, AI is also being applied in creative ways. During the Latin Grammys, the network partnered with ShopSense and Walmart to create a second-screen experience: as celebrities walked the red carpet, viewers could scan a QR code to shop similar outfits in real time. It’s a small but tangible example of how CTV advertising can evolve beyond traditional ad pods.

Looking Ahead: What’s Next for CTV Measurement?

As the podcast wraps, Brian offers a glimpse into a future shaped by both AI and, surprisingly, quantum computing.

With current cloud infrastructure, many platforms sample data rather than process it all, limiting the granularity of insights. But new breakthroughs in quantum hardware could allow real-time analysis of massive data sets without the tradeoffs publishers face today.

“Most programmatic partners don’t look at every opportunity in the bid stream because the cost is too high,” Brian explains. “With quantum computing, that could change.”

More immediately, publishers need to rethink how they define and share content metadata. While some hesitate to expose too much information for fear of cherry-picking, withholding it entirely limits advertisers’ ability to measure outcomes, target appropriately, and ensure brand safety.

The industry will likely move toward more transparency over time, driven by advertiser demand, technology improvements, and the increasing sophistication of AI tools that can enrich CTV metadata automatically.

Realigning Expectations Around Performance

With so many variables at play, CTV advertisers often ask a simple but important question: what’s the benchmark? Did my campaign deliver what it promised?

Today, many of those benchmarks are still being written. From completion rate to exposed audience to brand lift, CTV measurement still lacks the standardization of linear television. But progress is being made.

By embracing innovations like clean rooms, metadata enrichment, and cross-platform data graphs, publishers can offer advertisers the clarity they need. And when that happens, the entire CTV ecosystem becomes more efficient, accountable, and resilient.

As Brian puts it, “When advertisers get access to the right data, and can prove effectiveness, they come back.”

Tune In to the Full Episode

For a deeper dive into data quality, CTV campaign performance, and how publishers like TelevisaUnivision are shaping the future of digital video, listen to Episode 22 of The PubWay: Navigating Data Quality & CTV Measurement.

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In the rapidly shifting landscape of digital advertising, one question is dominating every strategy conversation: What is contextual advertising and why is it central to the future of media?

Today’s advertising environment looks nothing like it did ten years ago. What was once a channel dominated by third-party cookies and behavioral data is now being reshaped by stricter privacy regulations, growing user awareness, and changing consumption habits. Advertisers are being asked to do more with less and to do it while respecting users' privacy expectations.

The answer lies in context. As traditional tracking tools phase out and reliance on personal data becomes increasingly problematic, brands and publishers need new ways to serve relevant, effective ads that drive results.

This is where contextual advertising comes in, and where our new Mastering Contextual Advertising Guide delivers the insights needed to navigate this new reality with confidence.

Understanding Contextual Advertising

At its core, contextual advertising is about delivering relevant ads based on the content a user is actively engaging with - not their personal data or browsing history.

It differs from behavioral advertising in a few key ways:

• Targeting method: While behavioral ads rely on tracking users across websites to build profiles, contextual ads are based on the actual content of the page being viewed.
• Privacy: Contextual advertising does not require cookies or invasive tracking. It's a privacy-first solution, built for a landscape where user consent and transparency are non-negotiables.
• Relevance: Because contextual ads match the environment they appear in, they tend to feel more organic, and drive stronger engagement.
• User experience: With no intrusive data collection or off-base assumptions, contextual ads offer a smoother, more user-centric experience.

And thanks to AI, contextual ads have become smarter than ever. With the ability to analyze not just keywords but entire articles, visuals, and video content, Contextual AI delivers human-like understanding at scale enabling advertisers to place messages that truly align with the moment.

Why Contextual Is Back

While contextual advertising isn’t new, its return marks a shift in priorities for advertisers.

In the early 2000s, contextual ads were widely used in search and display formats. But with the rise of behavioral tracking in the 2010s, they faded into the background. Now, with increasing regulation and consumer demand for data protection, contextual has not only returned but it’s evolved.

The latest generation of contextual tools:

• Analyze page content in real time using machine learning and semantic models.
• Place ads based on relevance rather than identity.
• Avoid the pitfalls of demographic and behavioral bias.
• Offer campaign performance without sacrificing user trust.

It’s this combination of relevance, scale, and privacy that makes contextual the most future-ready approach in digital advertising today.

The Benefits: What’s In For Advertisers

Relevance That Drives Results

Contextual ads meet users in the moment, serving messages that align with what they’re reading, watching, or listening to. Whether it's a cooking ad on a recipe site or a fitness brand on a health article, the match feels intuitive and delivers stronger click-through rates and conversions.

Higher Engagement, Lower Intrusion

Ads that reflect the user’s current interests are less likely to disrupt their experience. This means more attention, less ad fatigue, and a more positive perception of the brand.

Non-Biased Targeting

Because contextual advertising doesn’t rely on personal identifiers, it avoids the ethical concerns and stereotyping risks that can come with behavioral targeting. This results in more inclusive reach and a fairer experience for all users.

Privacy Compliance by Design

As privacy laws evolve, contextual targeting remains fully compliant, helping advertisers future-proof their strategies without compromising performance.

Powered by AI: The New Era of Contextual

Today’s contextual solutions go far beyond keyword matching. With Contextual AI, brands can understand and respond to page content in real time, factoring in everything from tone to visual elements.

This enhanced precision means:

• Better ad placements
• Higher relevancy scores
• Stronger ROI

Contextual AI also unlocks creative optimization that helps brands test, adapt, and personalize ad content depending on the page or platform it appears on.

And with formats like display, video, and even CTV now context-enabled, the reach and flexibility of contextual campaigns are wider than ever.

Ready To Launch Your Own Strategies? Start Here

In our new Mastering Contextual Advertising Guide, we cover everything you need to get started, scale up, or refine your contextual strategy.

What’s inside:

• A deeper look at how contextual advertising works
• 5 steps to developing a privacy-first, high-performance strategy
• Targeting methods explained: keywords, topics, categories
• Insights into AI-powered contextual tools
• Tips for designing creatives that resonate with the content around them
• Guidance on tracking the right KPIs to optimize for success

We also explore how contextual is expanding across channels from the open web to CTV, in-app environments, digital audio, and more.

Contextual advertising isn’t just an alternative, it’s the future. As digital privacy becomes non-negotiable, advertisers need strategies that can perform without personal data.

By aligning with content, not identities, contextual advertising builds relevance that users welcome and results that marketers can measure. And at Seedtag we have taken it to the next level with our new category, Neuro-Contextual advertising.

Want to master the strategy that’s reshaping the advertising landscape?

Download the Mastering Contextual Advertising Guide now and discover how to build smarter campaigns that resonate, perform, and respect privacy from the start.

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The Pub Way Podcast returns with an in-depth look at CTV advertising, focusing on demand side platforms (DSPs). Hosted by Tina Iannacchino (VP of Publisher Partnerships North America at Seedtag) and Mike Villalobos (SVP of Strategy and Commercial Operations, North America at Seedtag), Episode 13 welcomes Keith Gooberman, CEO and Co-Founder of Pontiac Intelligence, to discuss how DSPs are adapting to evolving data policies and the new opportunities CTV brings for publishers. Here we bring you all you publishers need to know about how DSPs are changing connected TV buys, why privacy remains central, and what it all means for publisher revenue.

Why DSPs Matter: A Crash Course For Publishers

A demand side platform (DSP) is the digital interface that enables advertisers to purchase inventory across channels (desktop, mobile, and especially CTV advertising) in a unified manner.

Historically, DSPs relied on cookie-based data for granular targeting. Now, with privacy concerns reshaping online advertising, DSPs are turning to private marketplace (PMP) deals, prioritizing direct collaboration with content owners.

Publishers stand to benefit. PMP deals typically command higher CPMs and more transparent data-sharing. As Keith observes, tomorrow’s programmatic environment will feature deeper partnerships between DSPs and content owners, creating unique revenue streams for publishers who can provide distinctive inventory or advanced targeting signals.

Shifting From Cookies To Context

Global privacy regulations are forcing a move away from broad data collection. While Google’s cookie plans fluctuate, the overall direction remains privacy-first. In a CTV context, cookies are largely irrelevant, so targeting methods must evolve. DSPs are adapting by focusing on content signals, forging direct relationships with streaming services, and negotiating PMPs that bypass the open exchange.

This is good news for publishers: those who excel at packaging content and user engagement data without compromising confidentiality will be well-positioned. Although sharing log-level data can be sensitive, it often reassures advertisers that they’re buying premium inventory, encouraging greater spend.

CTV Advertising & Log-Level Data: Striking A Balance

Advertisers increasingly seek transparency. They want show-level insights (e.g., “Which program did my ad appear in?”) to confirm brand suitability and measure effectiveness. Yet publishers understandably guard their data, worried about undercutting direct deals or exposing proprietary information.

Keith explains that with a tailored DSP approach (built around PMPs) publishers can negotiate exactly what to share. This selective data release can elevate CPMs, especially when unique audience contexts or exclusive programming is on offer.

The key is clear communication: publishers who help advertisers understand the content environment can attract stronger campaign commitments.

The New Wave Of Contextual Targeting In CTV

Traditional contextual targeting (based on keywords or page categories) now faces its biggest test in CTV advertising, where video content dominates. AI tools can parse shows at a deeper level beyond mere categories, recognizing mood, dialogue, or plot themes. This refined approach offers advertisers a better sense of what’s on screen, ensuring relevant ad placements without relying on personal data.

For publishers, robust AI-driven context elevates value. If you can detail the emotional tone or specific segments of your videos, you stand out in a crowded market. DSPs want premium signals to differentiate one CTV channel from another, and sophisticated content analytics can deliver that competitive edge.

Evolving Identity Strategies

Despite Google’s shifting timeline on cookies, the days of unrestricted data collection are numbered. Many CTV environments rely on device or IP-based identifiers rather than cookies. DSPs address this by blending partial user details with broader contextual cues and PMP agreements. Publishers with strong first-party data or advanced audience insights can fill that gap, commanding higher prices if they maintain user trust.

Key Takeaways For Publishers

1. Demand Side Platforms (DSPs) Are Central To CTV
   Publishers should recognize that DSPs are the gateway to expanding CTV ad buys. By accommodating PMP deals, you can secure premium revenue while retaining more control.
2. Privacy Shifts Ad Buying Toward Context
   As personal identifiers phase out, brand alignment rests on deeper content signals. Publishers who refine their program data and present it in user-friendly ways will see sustained interest.
3. Log-Level Data Requires Careful Sharing
   Advertisers crave transparency. Selective data disclosures like show title, genre, location, can raise advertiser confidence. Clear boundaries protect publisher advantage.
4. AI Enhances Contextual Value
   Automated tools can interpret video scenes and sentiment. Publishers who incorporate AI-based insights can stand apart and deliver more targeted inventory to advertisers.
5. Direct Communication Builds Better Deals
   Flexible PMP relationships allow publishers to define how data is shared. DSPs often welcome these refined deals, provided they gain reliable insights into inventory quality.

DSP technology once revolved around open exchanges and third-party data; now it’s pivoting to direct deals, granular content analysis, and privacy-friendly user signals. Publishers who adapt to these market realities and offer a mix of audience clarity, brand safety, and strong contextual data are poised for long-term success.

Want the full story? Tune in to Episode 13, featuring Pontiac Intelligence’s Keith Gooberman, to hear firsthand how DSPs operate, where CTV advertising is headed, and how publishers can thrive in a shifting ecosystem.

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Advertising has always aimed to connect brands with their audience, ideally in the right place and at the right time. Historically, digital advertising intelligence relied heavily on traditional methods such as keyword matching, URL targeting, or content categories. Yet, as consumer expectations and privacy regulations tighten, brands demand more nuanced solutions that understand not just what people consume, but how they think, feel and decide.

Enter neuro-contextual advertising, Seedtag’s new category that leverages neuroscience principles alongside advanced AI to interpret interest, emotion and intent in real time. This shift moves marketing from rigid, content-based triggers to a human-centric model that mirrors the brain’s information processing in order to deliver high-quality, privacy-first, full-funnel advertising across premium CTV, video and the open web.

Here, we explore how this new approach fundamentally transforms advertising strategies, shifting from simply reading pages to truly understanding people and what moves them.

Contextual Advertising: From Classification to Understanding

When programmatic advertising first emerged, contextual targeting offered a privacy-friendly way to reach audiences by matching ad placements to page-level topics. Early systems relied on static taxonomies, predefined categories such as “automotive” or “travel.” At its best, this method ensured ads appeared alongside relevant content, but it also introduced two key challenges:

1. Surface-Level Relevance
   Matching ads to pages based on keywords or tags alone often failed to capture nuance. A single article titled “The Future of Electric Cars” might garner targeted auto advertisers, yet within that page, a negative review of a specific model could mean the reader is unlikely to buy. Traditional contextual simply could not distinguish between promotional enthusiasm and critical analysis.
2. Upper-Funnel Focus
   By design, keyword- or URL-based systems excel at generating awareness while driving clicks when audiences present broad interest. However, as marketers pushed for measurable conversions, the limitations became clear. Without insight into audience intent (the stage in the buying journey), media spend risked being wasted on readers who lacked the inclination to act.

In short, traditional contextual approaches were good at placing ads adjacent to relevant content, but less adept at understanding the underlying motivations and emotions driving user behavior.

Advances in artificial intelligence advertising as part of the AI revolution in advertising improved on basic keyword matching. Modern contextual AI platforms began employing natural language processing (NLP) and computer vision to parse page structure, sentiment, tone and images. This allowed systems to identify whether an article was positive, negative or neutral about a topic, and to understand whether images depicted aspirational lifestyles or technical specifications.

Still, these algorithms primarily focused on content recognition and classifying each page into thematic buckets such as “Luxury Vehicles” or “Fuel Efficiency.” While more accurate than earlier methods, the approach remained fundamentally aligned with “What is on this page?” rather than “What does this page say about the user’s mindset?” In other words, it still lacked a true understanding of interest, emotion and intention - the three pillars of human decision-making.

Introducing Neuro-Contextual Advertising

Neuro-contextual advertising represents a fundamental leap: it mirrors how the human brain processes information, creating a more cohesive model of audience engagement. Instead of surface-level content analysis, neuro-contextual integrates neuroscience insights into artificial intelligence advertising. By interpreting interest, intent, and emotion in real-time, Seedtag’s proprietary AI, Liz, mirrors human cognitive processes, enabling highly precise, responsive, and scalable ad delivery.

What sets neuro-contextual apart? It comprehends not just the "what," but also the "why" behind user behavior, delivering advertising that resonates on deeper, cognitive levels. This translates directly into improved outcomes at every funnel stage, making neuro-contextual an essential evolution for marketers who demand more from their ad spend.

Understanding Interest: Capturing Attention

From neuroscience, we know that human brains respond more favorably to familiar, context-congruent stimuli, processing them faster and more efficiently. Neuro-contextual technology leverages these insights to position advertising precisely within moments of heightened relevance.

For instance, when a user engages with content around sustainability, Liz immediately understands their genuine interest based on intention based targeting and AI intention models. Rather than serving generic environmental ads, neuro-contextual recognizes subtle patterns, such as emotional tone, narrative focus, and visual elements… to identify deeper resonance. As a result, the advertising aligns seamlessly with the user’s attention, driving significantly higher engagement.

Decoding Emotion: Enhancing Recall and Affinity

Emotions play a central role in decision-making processes. Neuro-contextual goes beyond traditional analytical approaches by actively interpreting emotional signals within digital content, from sentiment and imagery to narrative style.

Consider an advertising campaign for luxury travel. Traditional contextual might align this campaign with content containing keywords like "travel" or "vacation." Neuro-contextual, however, evaluates the emotional nuances, placing ads within content reflecting aspiration, relaxation, or indulgence - all emotions that directly align with the luxury traveler’s mindset. This refined alignment drives deeper emotional engagement, enhancing brand recall and affinity.

Identifying Intention: Driving Action

At its core, neuro-contextual advertising is designed to not only understand user intent but also act upon it dynamically. By analyzing deeper cognitive signals, Seedtag's Liz detects when a user's engagement indicates readiness to act.

Take the example of financial products: a user reading detailed comparative content about investment options indicates a much stronger intention than someone casually exploring financial news. Neuro-contextual recognizes this intent in real-time, adjusting campaign delivery to prioritize highly specific, action-driven messaging. This precise targeting of user intention significantly enhances conversion rates, optimizing ad spend for measurable outcomes.

Neuroscience Principles in Neuro-Contextual AI

Cognitive Fluency and Emotional Encoding

At the heart of neuro-contextual lies the principle of cognitive fluency: the ease with which our brains process familiar, context-congruent stimuli. When an advertisement appears alongside content that aligns with the user’s interests or emotional state, it is processed more readily and regarded more favorably. Neuroscientific research confirms that positive emotional context enhances memory encoding which makes users more likely to recall both the content and the brand message.

Seedtag applies this by identifying emotionally charged intersections, that is pages where audience interest and sentiment peak. In each case, neuro-contextual AI analyses audio sentiment, facial expressions, color palettes and even pacing to gauge emotional intensity. Ads served in these windows benefit from the emotional resonance, translating into higher attention, recall and eventual action.

Interest, Attention and Memory

Interest acts as the gateway to attention; without curiosity or relevance, information is ignored. Neuroscience shows that attention is a limited resource as stimuli must compete for cognitive prioritisation. By matching ads to content that already captures genuine interest, neuro-contextual AI ensures that brand messages earn that scarce attention.

Furthermore, episodic and semantic memory processes work in tandem when we engage with emotionally-charged, interest-driven content. By aligning ads to these rich, multi-layered experiences, Seedtag’s technology capitalises on both types of memory encoding and thus helping brands remain top-of-mind when users transition from exploration to decision-making.

The Role of Neuroscience for Full-Funnel Outcomes

Neuro-contextual advertising moves Seedtag decisively beyond traditional contextual limitations. While conventional contextual targeting excels in awareness, Seedtag’s neuro-contextual approach supports full-funnel marketing outcomes, from initial attention through mid-funnel interest and emotional resonance, down to lower-funnel conversions.

Neuro-contextual ensures advertising remains relevant across premium CTV, video, and open web environments, with advanced embedding technologies analyzing content and context across vast digital ecosystems. Instead of pre-defined segments, Seedtag’s neuro-contextual advertising dynamically creates custom, scalable audiences based on real-time cognitive signals. This cross-environment synergy ensures marketing efforts remain aligned with consumer states of mind - no matter where or how audiences consume content.

Real-Time Optimization: From Predictive to Agentic Intelligence

Central to Seedtag’s approach is the combination of advanced neuroscience insights with sophisticated AI algorithms. Unlike predictive analytics that merely forecast outcomes, neuro-contextual applies real-time cognitive intelligence, adjusting ad delivery dynamically.

Seedtag’s Liz Agent remains an enabler, transforming Liz’s deep insights into actionable campaign configurations via a conversational interface. The agent layer interprets natural-language prompts and retrieves relevant segments and automates bid adjustments across channels. The Liz Agent plays a crucial role in realising neuro-contextual intelligence in real time, blurring the line between strategy and execution.

This is transformative for marketing strategies. Campaigns leveraging neuro-contextual advertising no longer remain static post-launch. Instead, they evolve continuously, optimizing at unprecedented speed and precision. The result? High-quality engagements precisely attuned to real-time user interest, emotion, and intent.

Connecting the Dots: Neuroscience and Digital Advertising Intelligence

The adoption of neuroscience principles within digital advertising intelligence underscores a broader trend in marketing: a shift toward understanding the holistic human experience.

The advertising landscape has outgrown the label of “contextual targeting.” Seedtag's evolution from contextual to neuro-contextual represents a decisive shift for the advertising industry. No longer confined to simple classification or upper-funnel objectives, neuro-contextual technology introduces the sophisticated cognitive insights marketers have long needed.

In an advertising ecosystem challenged by consumer privacy, evolving regulations, and increasing demand for meaningful engagement, neuro-contextual advertising presents not merely an upgrade but a necessary evolution. It reshapes digital advertising intelligence, moving from mere keyword recognition to real-time understanding of how audiences think, engage, and make decisions.

This groundbreaking approach signifies more than technological advancement as it signals a fundamental redefinition of advertising itself at every stage of the funnel.

Win Your Audience: Tap into Interests, Emotions and Intentions

Learn more about Seedtag's neuro-contextual advertising and explore how your brand can leverage cutting-edge neuroscience and artificial intelligence to deliver superior marketing outcomes.

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At this year’s Cannes Lions International Festival of Creativity, amid sun-soaked terraces and industry-wide discussions about the future of advertising, one theme overtook all conversations at the Croisette: redefining relevance through deeper user understanding. For Seedtag, Cannes 2025 marked the opportunity to return to the French Riviera and bring forward the future of artificial intelligence for marketing: neuro-contextual advertising.

Built on the idea that context is no longer enough, neuro-contextual advertising moves beyond static classifications and towards cognitive intelligence - interpreting real-time signals of interest, emotion, and intent to connect with people in more meaningful, privacy-first ways.

Defining the New Era Through Emotion, Intention, and Intelligence

Seedtag recently unveiled its new positioning by championing a model that resonates far beyond keywords or audiences. Focusing on more than just data, but on better understanding on how people feel, why they care, and what drives their decisions in the moment.

From the stage to the shoreline, our team helped define this new era of contextual advertising - one powered by neuroscience principles and made scalable by Agentic AI. Seedtag’s neuro-contextual intelligence connects not only content and creativity, but also emotion and cognition, bringing brands closer to the real drivers of consumer behavior.

In a marketplace seeking relevance without compromise, Seedtag’s approach stands as one built for privacy, designed for outcomes and powered by understanding.

A Crossover to Tune Into: AdTech Heroes x The Pub Way

One of the highlights of the week was the special crossover episode of our two flagship podcasts: AdTech Heroes x The Pub Way – Winning Audiences in a New Era of Engagement. Hosted live at The Drum’s podcast studio, the session brought together voices from across the ecosystem to answer a timely question: how can brands and publishers use real-time context and AI to engage audiences more effectively, while prioritizing passions over profiles, and meaning over assumption?

Moderated by Seedtag’s Tina Iannacchino and Marko Johns, the conversation featured Jamie Dunlop, Managing Partner at MediaPlus UK, and Tony Gemma, VP Global Head of Creative at Yahoo. Together, they unpacked the shifts in strategy required to meet audiences where they are, not demographically but behaviorally and emotionally.

Jamie unpacked how MediaPlus moved beyond demographic targeting to focus on real human behavior, arguing that knowing how people think and feel is more important than knowing who they are. “Demographics treat Prince Charles and Ozzy Osbourne as the same person,” he said. “They’re not.”

Tony, from Yahoo, made the case that the creative side of programmatic has long been neglected. “Programmatic forgot to bring its creative friend along,” he noted. The group agreed that while media and data have advanced, creativity often lags behind. The takeaway? Brands that succeed are the ones reuniting data, creative, and context while treating creative as a measurable driver of outcomes, not just a finishing touch.

From personalization at scale to creativity that aligns with intent, the conversation reflected an industry yearning for a system that doesn’t just automate targeting but understands people and delivers campaigns that connect.

Elevating Brands with Purposeful Technology

AI was examined with depth, especially in terms of its role in shaping more intelligent, ethical advertising. As Mike Villalobos, SVP of Strategy North America, noted during the AI in Action panel hosted by Sigma Software, AWS, and Ipsos:

“AI isn't a feature, but rather a core part of our foundation to accelerate and sustain our growth.”

That sentiment was echoed across the festival. The conversation has clearly shifted from curiosity around AI to a firm expectation that it delivers measurable value. The bar is no longer automation. Neuro-contextual delivers on that expectation by integrating neuroscience insights with real-time emotional understanding. It’s not just about being faster. It’s about being smarter and enabling marketers to activate campaigns that align with how people actually feel and think, in the moment.

This theme of thoughtful progress was also front and center in Cannes Truth Be Told, a panel exploring the monetization of journalism hosted by Unplugged Collective and Beeler.Tech. Representing Seedtag, Tina Iannacchino, VP of Publisher Partnerships North America, addressed the challenge of balancing brand safety with media responsibility.

“In today’s ad tech ecosystem, quality journalism is often caught in the crossfire of rigid brand safety measures.”

Keyword blocklists, while designed to protect brands, frequently end up demonetizing essential reporting on politics, conflict, or climate. That creates a disconnect where high-value editorial content is excluded from media plans, while sensational or low-quality content remains monetized.

Advertisers must move beyond blanket controls and toward more intelligent, context-aware solutions. Only then can we ensure brand safety without undermining trusted journalism.

And in a forward-looking conversation hosted by VaynerX, Seedtag’s Global Chief Revenue Officer Brian Danzis, joined executives from VaynerMedia and Digiday’s Editor-in-Chief Jim Cooper, to explore how AI is reshaping the media ecosystem. The panel challenged the industry to cut through the noise and focus on real use cases that are actively changing how content is created, distributed, and monetized.

The group discussed how AI is helping companies rethink how they reach audiences, make decisions, and define success. One example shared during the session was United Airlines’ recent campaign with Seedtag. By combining contextual AI with high-impact formats, the campaign reached premium audiences in brand-safe environments, without relying on personal data. The result? A measurable boost in attention and engagement, proving that relevance and performance can go hand in hand in a privacy-first world.

As Brian highlighted:

“Relevance drives cognition, interest, emotion and intent. That is what neuro-contextual means, and it is leading us into the new era of advertising.”

Together, these conversations reflected a broader shift at Cannes Lions this year: toward solutions that not only perform, but reflect the values and complexity of the audiences they aim to serve.

Seedtag in the Spotlight: A Full Week of Industry Impact

From private roundtables on brand safety and media integrity, to our collaboration with HUMAN for the “Collective Apéro,” Seedtag showed up to Cannes ready to share how brands, agencies and publishers worldwide can embrace the new era of digital advertising.

Whether joining VaynerMedia on stage for a sunset conversation on AI’s future in media, or exploring how to balance personalization with accountability on Île Sainte-Marguerite, our team helped shape the conversations that will guide the next wave of marketing strategy.

While the industry has long relied on contextual targeting for privacy-first reach, Seedtag’s conversations at Cannes showed how far we’ve come. Today’s marketers are looking for relevance that adapts, moment by moment, to the emotional and cognitive state of the consumer.

Seedtag’s neuro-contextual system is built to do just that. Through dynamic semantic embeddings and continuous network-level analysis, our proprietary AI Liz delivers scalable understanding of what moves people. Whether in a premium CTV environment or across the open web, campaigns adapt in real time to changing intent, interest, and emotional tone.

It’s strategic evolution - meeting the moment when creativity, audience mindset, and media come together.

From launching our latest Contextual TV capabilities to showcasing our AI Intention Models and real-time contextual insights platform, Seedtag’s presence reflected our ambition: to make advertising work better by understanding more deeply.

Engagement, Intelligence, and the Industry We Want

As Cannes Lions 2025 came to a close, one thing was clear: the most effective campaigns are no longer the ones that shout the loudest, but the ones that understand the audience most deeply.

If AI was the buzzword of the week, emotional relevance was the quiet headline underneath. And neuro-contextual advertising is where those two forces meet: scalable intelligence grounded in how people actually think, feel, and decide.

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