AdTech Collective by Seedtag

Notizie, tendenze e approfondimenti sulla pubblicità digitale

Evidenziato

Every week, the internet tells you what's trending. It rarely tells you how any of it felt.

Open any trends page, any weekly recap, any "most talked about" list, and the logic is the same. Volume wins. Whatever generated the most clicks, shares, or mentions gets ranked first, regardless of what that attention actually meant. A blockbuster movie premiere and a last-minute playoff upset can sit side by side on the same list, indistinguishable by the metric used to rank them.

But attention and emotion are not the same thing. A story can dominate headlines and still leave people cold. Another can spike quietly in wonder, anger, or admiration without ever cracking the top of a trends page. Volume tells you where people looked. It says nothing about what they felt while looking.

That gap between the content people consume and how they actually feel about it is exactly where Neuro-Contextual advertising begins.

From Signal to Spotlight: Introducing the Seedtag Emotion Quotient

Today, we're putting Liz, our Neuro-Contextual AI, to work with the launch of the Seedtag Emotion Quotient, a weekly ranking of the five cultural moments that generated the strongest measured emotional response, not the ones simply generating the most volume. 

Each moment is scored against its own emotional baseline. Take The Odyssey: admiration and anticipation for Nolan's epic were real, but off-screen romance between its stars ended up generating the strongest emotional signal of all, stronger than the film itself. And sometimes, what stands out is how differently the same event can be felt. At this year’s US Open, coverage around Carlos Alcaraz drove admiration to 3.93x its usual baseline, while stories around Novak Djokovic's early exit pushed sadness to 2.37x. Same tournament, same week, but two very different ways of experiencing it. For advertisers, that's an important distinction. Knowing that the US Open is capturing attention is one thing. Understanding whether that attention is being shaped by admiration or sadness gives brands a much more precise read on the moment and how their message can fit within it.

That's the point of the Emotion Quotient. It's the same intelligence behind Liz, our Neuro-Contextual AI, made visible: reading not just what a moment is about, but how it's genuinely felt.

Key Takeaways

  • The Seedtag Emotion Quotient turns that same Neuro-Contextual analysis into a public, weekly view of the five cultural moments the internet felt the most.
  • Liz, our Neuro-Contextual AI, reads interest, emotion, and intent across content in real time, without relying on personal data.
  • Emotional signals rarely appear alone. Liz identifies the multiple emotions layered within a single piece of content.
  • Traditional contextual targeting can identify what a piece of content is about. Neuro-Contextual advertising reads why it matters, understanding what sets one piece of content apart from another and how it's likely to land with the person engaging with it.
  • Understanding why, not just what, is what makes Neuro-Contextual advertising fully resonant, and it's the foundation of full-funnel outcomes across the open web and CTV.
It's Not About Who Someone Is. It's About What They're Passionate About, In This Moment. 

What Is Neuro-Contextual Advertising?

Contextual targeting has been part of digital advertising for years. At its most basic, it matches ads to content using keywords and categories. A travel article gets travel ads. A sports recap gets sports ads. It works, but it reaches its limit there. Classification is as far as it goes.

More advanced systems now use vector embeddings, numerical representations that place related concepts closer together in meaning, even when they share no keywords at all. That's a real improvement in how machines read content. But embeddings alone only summarize meaning. They don't explain why a moment matters to the person reading it.

That's the gap Neuro-Contextual advertising is built to close.

Neuro-Contextual Advertising, our approach at Seedtag, adds a purpose-built layer of business logic on top of that foundation, one built to interpret interest, emotion, and intent within content itself. 

Two articles can sit in the exact same category and still mean entirely different things. Someone reading a spoiler-filled recap of a finale and someone reading a spoiler-free review are both talking about the same show, but their intent runs in opposite directions: one wants closure, the other wants to be convinced to watch. Knowing what the content is about can't tell them apart. Understanding why each reader is there can.

The same holds for emotion. A product launch event and a product recall story can both sit under "tech news," yet one carries excitement and anticipation, the other frustration and concern. That same underlying intelligence, reading interest, emotion, and intent together, is what powers everything we build, the Seedtag Emotion Quotient included.

The same logic applies to people, not just pages. Two readers can share every demographic box, same age, same income, same zip code, and still care about completely different things. Demographics describe who someone is on paper. They say nothing about what actually moves that person in the moment. Neuro-Contextual advertising shifts the question from "who is this person?" to "what are they passionate about right now?", and content itself is where that answer shows up first.

The Tech Behind the Ranking

Behind every score in the ranking is Liz, our Neuro-Contextual AI, reading content at scale and in real time. Liz scans more than 100 million URLs every day, with native understanding across 10+ languages and access to inventory from more than 30,000 premium media publishers globally, spanning the open web, video, and CTV.

That scale matters because the Seedtag Emotion Quotient isn't built from isolated pieces of content. Liz understands the connections between content across this broader ecosystem, identifying signals of interest, emotion, and intent as they emerge. The result is a view of cultural moments grounded not in a snapshot, but in what is happening across the content universe around us.

From there, understanding goes deeper than keywords. Liz maps the relationships between topics using vector embeddings grounded in neuroscience, which is how the ranking can isolate the specific terms driving a spike, not just name the general subject behind it.

Because human reactions are rarely singular, Liz reads emotion in layers rather than assigning one flat label. A single moment can carry curiosity and excitement at once, or admiration alongside real tension, and the ranking is built to reflect that complexity.

All of this happens without relying on personal data. Liz reads the content environment itself, not the individual people engaging with it, which is what keeps the ranking privacy-first by design.

Each week, the Seedtag Emotion Quotient publishes a new read on the five moments that generated the strongest measured emotional response over the week prior. It's built to be explored, not just read: every entry breaks down the specific emotions behind it, the story driving the spike, and how that moment's emotional profile compares to its usual baseline, a starting point for thinking through which emotional signals are worth aligning a campaign with, and when.

Why Does Measuring Emotion Matter for Advertisers?

The Seedtag Emotion Quotient makes something visible that advertisers should care about directly: emotion is measurable, and it predicts performance.

That's not just true for the moments in this ranking. It holds inside real campaigns too.

The same Neuro-Contextual intelligence behind the ranking already drives stronger performance where it counts most: inside live campaigns. Liz, our Neuro-Contextual AI, is the same engine behind Seedtag NeuroX, our Neuro-Contextual Exchange, powering both from the same underlying intelligence. NeuroX connects that intelligence at scale across 30,000+ premium publishers and broadcasters, making every impression understood whether or not identity is present in the bidstream.

Working with Professor Moran Cerf from Columbia University, our neuroscience research measured real-time brain responses and found that Neuro-Contextual ads drive 3.5 times higher neural engagement than non-contextual ads, and a 26% stronger emotional response than standard contextual advertising. Full-funnel outcomes, from awareness to conversion, are consistently stronger when a message aligns with the emotional state of the moment it appears in.

Is Neuro-Contextual advertising the future of targeting? As identity signals keep fragmenting across the open web, understanding the moment becomes the only foundation that holds.

It's not about knowing what content people consume. It's about understanding how that content makes them feel.

The Seedtag Emotion Quotient is live now. Explore this week's ranking.

Evidenziato

The industry has always chased one promise: delivering the right message to the right person at the right time. The surprising part of advertising automation in 2026 is that the creative side of that promise is largely solved. Dynamic creative platforms, modern ad servers, and workflow automation have brought the industry much closer to making personalization at scale a reality.

What hasn't caught up is measurement.

That gap between what advertising automation can execute and what teams can actually measure is where many agencies still struggle. Closing it requires more than adopting another AI tool. It demands smarter workflows, disciplined testing, and connected data that turns execution into measurable business outcomes.

In this episode of AdTech Heroes, I sat down with Lisa Markou, Executive Vice President, Platforms at Publicis Collective, to explore what advertising automation actually looks like inside a modern agency, why measurement remains the industry's biggest challenge, and how leading teams are deciding what to automate first.

Key Takeaways

  • Creative automation has made personalized advertising at scale possible, but measurement and attribution have yet to keep pace.
  • Advertising automation in 2026 is less about adding new AI tools and more about simplifying technology stacks and eliminating inefficient workflows.
  • The biggest advertising automation benefits often come from workflow automation, replacing manual processes that slow teams down and introduce errors.
  • The most successful automation strategies begin with small, focused tests before expanding across larger marketing campaigns.
  • Connected data—not disconnected platforms—is what allows automation to deliver meaningful business outcomes.

Creative Automation Has Solved What Measurement Still Can't

Creative technology has advanced rapidly over the past few years. According to Markou, the technology behind creative automation, including dynamic creative platforms and modern ad-serving capabilities, has finally reached a point where that vision is achievable.

Measurement, however, remains the missing piece.

Connecting metadata, taxonomy, creative assets, and media signals across multiple platforms continues to be one of advertising's biggest operational challenges. While renewed attention on brand metrics and engagement signals can help marketers understand campaign performance sooner, accurately attributing business outcomes still requires significant work behind the scenes.

For marketers, this means the next competitive advantage won't come from delivering more personalized creative alone. It will come from proving which creative actually drives results.

Advertising Automation

What Is Advertising Automation, and How Are Agencies Using It in 2026?

Ask five people to define advertising automation, and you'll probably get five different answers. For Markou, the definition extends far beyond AI or generative tools.

Her teams apply workflow automation to the tasks that historically consumed the most time, from dashboard creation and reporting to media planning and operational processes that once relied on manual spreadsheets. The objective isn't simply greater efficiency. It's freeing the marketing team to focus on strategy instead of repetitive work.

At the same time, not every legacy system needs replacing. Sometimes a manual workaround is more effective than forcing a new marketing automation platform into an existing workflow. The real challenge is knowing when consolidation genuinely improves performance, and when it simply adds complexity.

Rather than asking, "What new tool should we adopt?", agencies are increasingly asking, "Which process no longer deserves to exist?"

The Best Way to Test AI-Driven Automation Before Scaling

One of the biggest mistakes organizations make is trying to automate everything at once.

Markou advocates for a different approach: start small. Whether it's a single campaign, a tentpole event, or one portion of the media budget, focused testing allows teams to understand the trade-offs before investing in a broader rollout.

Just as importantly, every test needs a clear objective. Without defining what success looks like upfront, even promising automation pilots generate little actionable learning.

Breaking automation into smaller experiments reduces risk, builds internal confidence, and gives leadership the evidence needed to scale successful initiatives across future marketing campaigns.

Advertising Automation

The Biggest Advertising Automation Benefits Start With Better Workflows

Throughout the conversation, one theme kept resurfacing: agencies often overcomplicate automation by focusing on what new technology to add rather than what unnecessary process they can remove.

Markou described how outdated spreadsheets, redundant platforms, and legacy approvals frequently remain in place simply because replacing them feels disruptive. Yet the long-term cost of maintaining inefficient processes often outweighs the temporary effort required to redesign them.

The biggest advertising automation benefits rarely come from the newest AI feature. They come from reducing manual work, improving collaboration, and building automated workflows that help teams move faster with fewer errors.

Connected Data Is the Foundation of Modern Advertising Automation

Even the most sophisticated automation depends on one thing: connected data.

Markou explained that aligning taxonomy, naming conventions, customer data, and measurement across vendors and platforms remains one of the industry's most complex challenges. Add evolving privacy regulations, regional differences in first-party data onboarding, and increasingly fragmented marketing channels, and it's easy to see why automation alone isn't enough.

As the saying goes: good data in leads to good decisions out. Without a strong data foundation, even the most advanced marketing automation software struggles to deliver meaningful results.

For marketers, success increasingly depends on connecting systems, not simply adding more of them.

Where Advertising Automation Goes From Here

Advertising automation is no longer a side experiment. It is quickly becoming the operating standard for modern media organizations.

The agencies moving ahead aren't necessarily the ones adopting every new AI capability first. They're the ones willing to rethink outdated workflows, test new approaches deliberately, and build connected systems that turn data into better decisions.

As automation continues to evolve, competitive advantage won't come from adding more technology. It will come from understanding which processes to simplify, which experiments to scale, and how to connect every part of the marketing process into a more measurable, efficient whole.

For a deeper look at how leading agencies are approaching automation, connected data, and modern media operations, watch the full conversation with Lisa Markou in AdTech Heroes, Episode 60.

Evidenziato

Every summer, the back-to-school season sneaks up faster than expected. Families start planning while the last day of school is still weeks away, and by the time September arrives, most of the shopping decisions have already been made. 

For marketers, this creates a familiar challenge: the back-to-school marketing window opens earlier every year, and audiences are far more layered than a simple parent-buying-supplies narrative suggests.

This season is no longer just about pencils and backpacks. It stretches across education, food, community, technology, and fashion, often overlapping in ways brands don't expect. Understanding that complexity is the real key to a stronger back-to-school ad strategy.

Below, we break down the trends, timing, and audience behaviors shaping back-to-school marketing this year,  along with what these shifts mean for seasonal marketing overall. 

Key Takeaways

  • Back-to-school marketing now spans far more than school supplies, touching food, technology, sports, and fashion content.
  • Education-related content leads the conversation, with food and lunch prep following close behind.
  • Liz, our Neuro-Contextual AI, uncovered 14 distinct contextual neighborhoods within the season, each reflecting a different shopper motivation.
  • Shoppers fall into distinct interest groups, from test prep researchers to homeschooling parents to sports families.
  • Some of the most valuable back-to-school trends this year come from unexpected overlaps between categories.

What Are the Key Back-to-School Marketing Trends for This Year?

One of the clearest back-to-school trends this year is just how education-driven the season has become. Education leads the back-to-school content universe at 67% of mentions, covering everything from test prep to classroom learning tools.

Food and drink content follows as the second biggest driver, with a strong focus on lunchbox packaging and baking. This shows how deeply back-to-school planning is tied to daily routines rather than a single shopping trip.

Beyond these two leading categories, Liz, our Neuro-Contextual AI, uncovered 14 custom contextual neighborhoods within the back-to-school content universe, connecting topics like homeschooling, online learning, athletics, and craft making. 

This fragmentation is exactly why generic back-to-school advertising ideas tend to underperform. The audience isn't one shopper. It's many shoppers with very different needs happening at the same time.

When Should Brands Start Their Back-to-School Marketing Campaign?

Timing is one of the most common questions marketers ask heading into the school season. 

Back-to-school planning clearly starts well before the first day of class: the interest clusters we identified span everything from early supply shopping to major sales moments, with events like Black Friday, Cyber, and Prime Day appearing within the same shopping conversations.

This overlap between back-to-school shopping and broader seasonal discount periods suggests that families are planning and comparing prices across an extended window, not making a single last-minute purchase. School marketing campaigns built around one moment risk missing the earlier stages of that planning process.

Who Are Today's Back-to-School Shoppers?

Back-to-school shoppers are not a single audience. The season breaks into six core interest areas, each shaped by different motivations and content habits:

  1. Books and Study: Families researching test prep (ACT, PSAT, college admission), elementary reading tools, and classic books and authors.
  2. Supplies and Shopping: Parents focused on preschool learning materials, seasonal crafts, classroom tools, and teacher appreciation gifts.
  3. Snacking and Food: Households planning lunchbox staples, homemade cookie recipes, and weekly grocery prep tied to the new routine.
  4. Community: Families engaging with school sports, school trips and events, and school support topics like PTA and staffing.
  5. Technology: Shoppers exploring online learning tools, college and career paths, teacher digital resources, and homeschooling programs.
  6. Gear and Fashion: Consumers shopping for school day essentials, trusted clothing brands, and smart shopping strategies around sales.

This range shows why a single back-to-school marketing message rarely works across the board. School shoppers move between these interest areas depending on their household needs.

What Surprising Behaviors Are Shaping Back-to-School Shopping?

Some of the most interesting back-to-school trends come from where these categories unexpectedly connect. Within the Books and Study neighborhood, we identified conversations blending literature curriculum mapping with classic authors like Jane Austen, meaning academic test prep and nostalgic reading discussions live side by side.

Homeschooling shows a similar pattern. A neighborhood cluster where homeschooling intersects directly with technology interests, particularly among parents sharing digital learning resources with one another.

Within the Community pillar, school sports conversations sit closely alongside smaller school milestones like book fairs, showing that the same emotional energy fueling student athletics also extends to everyday school events.

These overlaps matter because they reveal opportunities that a single-category campaign would miss entirely.

Back-to-School Marketing Tips for Brands

Based on these patterns, a few principles stand out for building a stronger school marketing campaign this year:

Speak to more than one interest area at once. Since families move fluidly between categories like Books and Study, Snacking and Food, and Gear and Fashion, campaigns that reflect more than one of these moments tend to feel more relevant than single-category messaging.

Recognize that back-to-school shopping overlaps with sales culture. Because gear and fashion conversations already connect with major discount periods, back-to-school promotions can align naturally with broader seasonal sale moments rather than competing against them.

Don't overlook homeschooling and technology audiences. This growing segment blends digital learning tools with community-driven resource sharing, representing a distinct content environment from traditional classroom shopping.

Match tone to the moment within each pillar, whether that's the practical urgency of school supplies, the routine-driven nature of lunch planning, or the community spirit around school events and sports.

From Supplies to Sentiment: Why Context Matters More Than Ever

As back-to-school shopping spreads across six distinct interest areas and 14 contextual neighborhoods, relevance becomes harder to achieve through guesswork alone. 

This is where our Neuro-Contextual approach becomes valuable. Liz, Seedtag’s proprietary Neuro-Contextual AI, reads signals of interest, emotion, and intent within content itself, identifying these clusters by both definitional meaning and how topics naturally occur together on the page.

Rather than targeting a generic "parent" profile, this approach allows advertising to align with the specific moment a shopper is in, whether that's researching test prep, planning lunches, or browsing backpacks ahead of a sale. And it does this without relying on individual tracking, keeping the experience privacy-first while still feeling personal.

The Bigger Opportunity for Back-to-School Marketing

Back-to-school marketing isn't about reaching one type of shopper. It's about understanding the many overlapping moments that make up the season, from test prep stress to lunchbox planning to Friday night games.

Brands that recognize these connections, rather than treating back-to-school as a single retail event, are better positioned to build campaigns that feel relevant at every stage of the school season.

Want to see the full range of interests, content clusters, and behaviors shaping this year's back-to-school season? Download our Back-to-School Insights report to explore the data behind these trends.

Evidenziato

Publisher monetization has entered a new phase. As streaming consumption officially surpasses linear television, advertising budgets are following audience attention into Connected TV (CTV), FAST channels, mobile apps, and other emerging digital environments. That shift is reshaping where publishers generate revenue and how they build sustainable monetization strategies.

For publishers, this is one of the biggest stories in publisher ad revenue news today. Revenue growth no longer depends on expanding inventory alone. It depends on creating advertising experiences that are transparent, measurable, and connected across multiple channels.

At Cannes Lions 2026, Mike and I sat down with Chandra Cirulnick, VP of Global Supply Partnerships at Yahoo DSP, for The Pub Way Podcast to explore what this evolution means for publisher ad management. Our conversation covered everything from CTV and FAST channel monetization to in-app growth, programmatic advertising, and the increasing importance of omnichannel strategies.

While we discussed several emerging formats, one idea connected them all. Publishers that diversify their revenue streams while giving advertisers greater transparency into performance are building stronger foundations for long-term publisher monetization.

Key Takeaways

  • Streaming has overtaken linear TV, shifting publisher ad revenue toward CTV and FAST channels.
  • New programmatic advertising formats are expanding monetization beyond traditional commercial breaks.
  • CTV and FAST support different publisher monetization strategies, each serving unique advertiser needs.
  • Transparency around inventory and campaign performance is becoming a competitive advantage.
  • Omnichannel ad revenue strategies for digital publishers are creating stronger, more sustainable revenue growth.
Publisher Ad Revenue News

How Are Publishers Monetizing CTV and FAST Channels in 2026?

Streaming has fundamentally expanded the number of ways publishers can generate advertising revenue. Instead of relying solely on traditional commercial breaks, publishers now have access to a growing mix of premium formats that can be packaged for different buyers, campaign objectives, and budgets.

Pause ads, home screen placements, shoppable experiences, and live sports sponsorships have all become available through programmatic advertising over the past year. These formats create new opportunities for publishers to diversify revenue streams while giving advertisers more flexible ways to reach audiences.

This evolution is also changing how inventory is sold.

Historically, television advertising centered around large upfront commitments, where buyers purchased broad audience reach months in advance. While those agreements remain important, they now exist alongside a growing programmatic marketplace that allows advertisers to buy inventory with far greater precision.

Instead of purchasing an entire market, brands can target audiences based on household counts and campaign objectives. That means advertisers that may not have the budgets for traditional national television campaigns can now reach highly relevant audiences through CTV, making premium inventory accessible to a much broader range of buyers.

For publishers, this creates far greater flexibility in publisher ad management.

Rather than relying on a single sales model, they can package premium inventory for large brand advertisers while simultaneously making additional inventory available through programmatic channels. This balance allows publishers to maximize advertising revenue without sacrificing the premium value of their content.

More importantly, it reflects a broader shift taking place across the industry.

Publisher monetization is no longer built around individual channels. It is increasingly built around connected audience experiences, where CTV, FAST channels, mobile apps, and other digital environments work together to create more valuable opportunities for both publishers and advertisers.

The Difference Between CTV and FAST Channel Monetization

Although they are often grouped together, CTV and FAST channel monetization solve different challenges for publishers.

Connected TV, particularly across premium streaming services, is typically valued for its broad reach, premium content, and household-level addressability. Advertisers use CTV to build large-scale awareness while benefiting from more precise targeting and measurement than traditional television has historically offered.

FAST channels, on the other hand, create value in a different way.

Rather than competing on audience size alone, they allow publishers to build highly engaged communities around specific interests, genres, or cultural moments. Whether it's motorsports, entertainment, news, or lifestyle programming, FAST channels give advertisers the opportunity to reach audiences who have intentionally chosen that content.

During our conversation, Formula 1 emerged as a great example of this shift. While traditional broadcast inventory around the sport may be limited, dedicated FAST programming creates entirely new opportunities for publishers to monetize highly engaged viewers who are actively seeking that content.

That distinction matters.

CTV often delivers scale and premium reach. FAST channels deliver contextual relevance and deeper audience engagement. Together, they give publishers more flexibility to package inventory based on different advertiser objectives instead of relying on a single monetization model.

As streaming ecosystems continue to evolve, understanding the difference between CTV and FAST channel monetization will become increasingly important for publishers looking to diversify advertising revenue while maximizing the value of every impression.

CTV and FAST

Why Transparency Is the New Currency of Ad Revenue Growth

As new inventory becomes available, advertisers are asking for something beyond scale. They want transparency.

Today, publishers are expected to answer two fundamental questions before media budgets are committed: 

  1. Where will my ads appear?
  2. How did the campaign actually perform?

The first question is about content transparency. Buyers want to understand the environments where their ads will run before activation, whether that's a premium streaming service, a specific FAST channel, or a curated portfolio of content.

The second is about performance transparency. Advertisers increasingly expect clear measurement that demonstrates how campaigns contributed to business outcomes, not simply how many impressions were delivered.

Publishers are responding by offering different levels of transparency based on campaign objectives.

Portfolio-based or genre-based packages provide advertisers with greater flexibility and broader reach, often at more accessible price points. Show-level sponsorships, live events, and premium programming offer greater certainty around placement, allowing publishers to command higher premiums for inventory that delivers stronger contextual alignment.

This approach creates opportunities across multiple buyer types.

Brands focused on efficiency can access quality inventory through broader packages, while advertisers seeking highly controlled environments can invest in premium placements with full visibility into where their campaigns appear.

For publisher ad management teams, transparency is no longer simply a reporting feature. It has become an important driver of publisher monetization, helping strengthen advertiser confidence while supporting long-term revenue growth.

Omnichannel Ad Revenue Strategies for Digital Publishers

Perhaps the biggest takeaway from our conversation was that publisher monetization is no longer defined by individual channels.

The next stage of growth is being built around connected audience experiences.

Instead of viewing CTV, FAST, mobile apps, podcasts, and streaming as separate revenue opportunities, publishers are beginning to package them as complementary environments that reflect how audiences actually consume media throughout the day.

These omnichannel ad revenue strategies for digital publishers create more consistent experiences for advertisers while opening additional revenue streams for publishers.

Mobile apps are a good example.

For years, app advertising was largely associated with gaming. Today, non-gaming publishers are increasingly extending their brands into mobile experiences, creating new inventory that keeps audiences engaged beyond the browser while attracting advertisers looking to diversify their media-buying strategies.

Audio is evolving in much the same way.

Dynamic ad insertion has transformed podcast advertising from a largely manual process into a scalable programmatic channel. At the same time, advances in contextual intelligence allow campaigns to align with individual episode topics instead of entire shows, giving advertisers greater flexibility without sacrificing relevance.

The boundaries between formats are also becoming less defined.

Streaming platforms continue to experiment with video-first podcasts, while traditional audio content increasingly incorporates visual elements. Rather than thinking about video, audio, or mobile as separate channels, publishers are beginning to organize inventory around audience attention and content consumption.

This shift reflects a broader evolution across digital advertising.

Successful publisher monetization no longer depends on maximizing one channel at a time. It depends on creating connected advertising experiences that allow advertisers to engage audiences wherever they choose to consume content.

Understanding the Moment Behind Every Ad Dollar

One theme kept resurfacing throughout our conversation with Chandra.

The future of publisher monetization isn't being shaped by new channels alone. It's being shaped by a better understanding of audience attention.

Whether someone is watching a live sporting event on CTV, exploring a niche FAST channel, listening to a podcast during their commute, or engaging with content in a mobile app, the opportunity isn't simply to place another ad. It's to understand what that person is interested in at that specific moment and deliver advertising that complements the experience.

As media consumption becomes increasingly fragmented, context becomes the common thread connecting every environment. Publishers that understand not only where audiences are spending time, but also the interests, emotions, and intent behind that attention, are better positioned to create advertising experiences that feel relevant for consumers and valuable for advertisers.

This is where AI is beginning to play an increasingly important role.

Rather than relying solely on historical performance or broad audience segments, AI-powered contextual intelligence helps identify the environments where audiences are most receptive to a brand's message. That creates opportunities for publishers to strengthen monetization while helping advertisers make more informed media-buying decisions across multiple channels.

At Seedtag, this philosophy sits at the core of our Neuro-Contextual approach.

Powered by Liz, our proprietary AI built on more than a decade of content understanding at scale, Neuro-Contextual intelligence interprets signals of interest, emotion, and intent directly from content. Instead of relying on personal identifiers, it helps advertisers understand when audiences are most receptive to a message, creating more relevant advertising experiences across CTV, premium publisher environments, mobile, and other emerging formats.

As omnichannel strategies continue to evolve, this deeper understanding of context will become increasingly valuable for both publishers and advertisers looking to build sustainable, privacy-first revenue growth.

The Next Chapter of Publisher Monetization

Publisher ad revenue is no longer being shaped by a single channel or a single transaction. It's being built across connected experiences.

CTV continues to expand premium video opportunities. FAST channels are creating new ways to engage highly passionate communities. Mobile apps and digital audio are opening additional revenue streams that complement traditional web inventory. Together, these environments are transforming how publishers package, measure, and monetize advertising.

The publishers that succeed won't simply add more inventory. They'll create connected strategies that reflect how audiences actually consume media, while giving advertisers greater transparency, stronger measurement, and more meaningful ways to engage consumers across every touchpoint.

For advertisers, that means moving beyond isolated media buys and embracing omnichannel planning that prioritizes relevance alongside reach.

For publishers, it means recognizing that the future of publisher monetization isn't about choosing between CTV, FAST, mobile, or audio. It's about connecting those environments into a strategy that delivers long-term value for both buyers and audiences.

As attention continues to shift, the publishers that thrive will be the ones that understand not just where audiences are, but what captures their attention in the moments that matter most.

If you're exploring new ways to grow publisher ad revenue across CTV, FAST channels, mobile, and other digital environments, our conversation with Chandra Cirulnick offers valuable perspectives on where the industry is heading.

Listen to the full episode of The Pub Way Podcast for the complete discussion.

Il nostro blog

The UK automotive market has never been more complex. Stricter privacy regulations, economic headwinds and the surge of electric-vehicle challengers have rewritten the rules for automotive brands. Today’s car buyers move seamlessly between devices and researching family SUVs during morning coffee, comparing EV range at lunch, then exploring finance deals after work. To win their business, brands and agencies must understand not just who is in the market but why, when and how their intentions evolve.

Seedtag’s contextual AI platform Liz has analysed over 10,000 automotive-related articles and webpages to decode the audiences driving new cars home. In this post, we share the strategic insights that will help UK automotive marketers reach each segment precisely capturing fleeting purchase moments in a privacy-first environment.

Who’s Buying: A Deeper Dive into UK Car-Buyer Segments?

Moving beyond broad demographics, our research identifies five high-value audience cohorts, each defined by motivations, content habits and media touchpoints. Understanding these profiles enables brands to tailor creative, media and messaging for maximum relevance and efficiency.

1. First-Time Buyers: Cautious Digital Natives

Profile

  • Age: 24–35, early career or young families.
  • Priorities: Affordability, reliability, ease of ownership.
  • Values: Financial prudence, wellness and work-life balance.

Media Habits

  • Start with “best first car” articles, obsess over budget calculators
  • Compare user forums and video reviews of entry-level models
  • Search “PCP vs. hire purchase” and “insurance cost by age”

2. Young Urbans: Trendsetters on the Move

Profile

  • Age: 25–40, professionals in metropolitan areas.
  • Priorities: Sustainability, connectivity, compact-city practicality.
  • Values: Social currency, experience-driven purchases.

Media Habits

  • Read urban-mobility think-pieces; watch “EV for city living” video explainers.
  • Scroll social feeds for trending EV scooter or compact car content.
  • Engage with lifestyle influencers showcasing tech-integrated dashboards.

Insights for Automotive Advertising

3. Family Upgraders: Space, Safety and Stability

Profile

  • Age: 35–50, growing families upgrading from compact cars.
  • Priorities: Interior room, safety tech, running costs.
  • Values: Reliability, long-term value, lifestyle consistency.

Media Habits

  • Binge-read “top seven-seater SUVs” and “best electric family car” comparisons.
  • Click through to “family car maintenance” and “insurance discounts for minivans”.
  • Watch sponsored test drives by family vloggers.

4. Luxury Seekers: Prestige and Performance

Profile

  • Age: 40+, affluent professionals and executives.
  • Priorities: Brand heritage, driving experience, exclusivity.
  • Values: Craftsmanship, bespoke options, peer recognition.

Media Habits

  • Digest in-depth features on Nürburgring lap times, bespoke customisation options.
  • Follow automotive journalists and fine-living platforms.
  • Engage with virtual reality showrooms and high-res imagery.

5. Technophiles: Innovators Embracing Tomorrow

Profile

  • Age: 25–45, tech industry professionals and early adopters.
  • Priorities: Autonomous features, AI-driven safety, seamless connectivity.
  • Values: Cutting-edge innovation, data-driven performance.

Media Habits

  • Read “Tesla software updates” and “AI co-pilot reviews”.
  • Watch footage of self-parking demos and LIDAR tests.
  • Participate in online forums about OTA updates and app integrations.

Insights for Automotive Advertising

Aligning Media to Moment: Seizing Intent-Driven Windows

Effective automotive advertising hinges on matching each audience’s mindset with the right content at the right stage of their journey. Whether you’re speaking to cautious First-Time Buyers or tech-obsessed Technophiles, recognising the moments that trigger purchase intent (and embedding your message in those contexts) is critical.

At the Awareness & Discovery stage, consumers encounter broad research queries and inspirational editorial. First-Time Buyers often begin by searching “best starter cars under £10 000,” while Young Urbans look for “EVs for city commuting.” Family Upgraders binge on “top seven-seater SUVs” lists, Luxury Seekers digest “luxury performance SUV design trends,” and Technophiles stream “latest autonomous driving demos.” To capture attention here, brands should place high-impact, value-driven creative such as eco-credentials or design innovations, in think-pieces and first-look videos that these segments naturally explore.

As buyers move to the Consideration & Interest phase, their queries become more focused on direct comparison and evaluation. First-Time Buyers compare PCP versus hire-purchase finance guides, Young Urbans review charging-app comparisons, and Family Upgraders read seven-seat crash-test results. Luxury Seekers investigate bespoke trim options, and Technophiles delve into technical whitepapers on AI safety systems. Serving calculators, detailed spec sheets, and interactive configurators alongside these articles helps nudge evaluators toward enquiry, bridging the gap between page view and test-drive booking.

In the Conversion & Action stage, transactional signals dominate. First-Time Buyers click “book first-time test drive” buttons, Young Urbans reserve subscription services, and Family Upgraders schedule showroom visits. Luxury Seekers RSVP to VIP launch events, while Technophiles sign up for beta tests of self-parking features. By detecting surges in content that indicates these final steps (dealer locators, “click to reserve” features or exclusive invites) brands can deploy geo-targeted offers, rapid-response chat prompts and dynamic call-to-action banners that turn interest into action. Seasonality further sharpens these windows: EV interest peaks in Q1 and Q4 around tax deadlines and New-Year resolutions, while SUV and hybrid demand stays robust year-round. Sports and off-road vehicle searches climb ahead of summer, underscoring the value of real-time bid adjustments whenever intent signals spike.

Three New Rules for Privacy-First Automotive Advertising

Context, Not Cookies

With third-party cookies crumbling, contextual signals are the new currency. Liz analyses page text, imagery and metadata without user data, to infer purchase intent in real time. This respects ICO guidelines while pinpointing engaged audiences.

Intent-Weighted Bidding

Allocate higher CPMs to content with strong transactional cues (e.g., finance breakdowns, dealer locators) and lower bids on general news or lifestyle reads. Intent scoring automates this process, ensuring spend follows real demand.

Agile Campaign Activation

Automotive trends shift with model launches, fiscal events and seasonality. Liz’s continuous intent recalculation enables brands to adapt budgets within hours of content consumption spikes rather than waiting weeks for manual reports.

Insights for Automotive Advertising Success

A Roadmap for Brands and Agencies

  1. Deep-Dive into Audience Profiles
    Use Seedtag’s segment definitions to audit current campaigns. Are you reaching Family Upgraders on finance comparison pages? Are Young Urbans seeing your ads during city-mobility reviews?
  2. Tailor Creative to Context
    Develop distinct creative sets for each segment: pragmatic messaging for First-Time Buyers, aspirational aesthetics for Luxury Seekers and tech demos for Technophiles.
  3. Secure Premium Contextual Inventory
    Partner via private marketplaces to place ads on specialist blogs, enthusiast forums and lifestyle verticals that ensure brand-safe, high-intent environments.
  4. Automate Bid Adjustments
    Configure your DSP to ingest Liz’s intent scores, automatically raising bids on high-value pages and suppressing low-relevance inventory.
  5. Measure Full-Funnel Impact
    Track downstream engagement metrics such as enquiry submissions, test-drive bookings, dealer visits…to validate that contextual campaigns drive real-world sales.

The Road Ahead: From Reach to Relevance

The UK automotive sector will see increased competition as EV incumbents, startup disruptors and subscription models accelerate. Consumer values, from sustainability to seamless digital experiences, will continue evolving. In this landscape, automotive advertising that focuses on when and why audiences act rather than who they are will outperform legacy approaches centred on broad demographics.

Contextual AI, anchored by real-time intent analysis, empowers brands to:

  • Pivot Quickly in response to seasonal spikes and new model launches.
  • Speak Directly to each segment’s core motivations, boosting relevance.
  • Respect Privacy while maintaining precision in media targeting.

By adopting these strategies, UK automotive brands can shift from mass reach to micro-moments that steer budgets toward the content that truly drives consumer decisions and delivers measurable growth in an increasingly privacy-first world.

Discover the Full Contextual Insights Report

For a comprehensive breakdown of segments, seasonal intent curves and competitive benchmarks, download Seedtag’s Q2 2025 Automotive Contextual Insights: Access the report here.

When you understand who your buyers are, why they choose your brand, and when they’re ready to act, every impression moves them closer to the driver’s seat.

In a rapidly shifting digital landscape, publishers face mounting pressure to boost revenue while preserving audience trust. In Episode 16 of The Pub Way podcast, hosts Tina Iannacchino (Seedtag’s VP Publisher Partnerships, North America) and Mike Villalobos (Seedtag’s SVP Stratey & Success) sit down with Dan Benyamin, founder and CEO of Aeon, to explore AI in publishing - from adtech hurdles to creator collaborations, emerging AI influencers, and practical strategies for AI monetization. Below, we unpack the episode’s key moments, demonstrating how publishers can harness AI responsibly, keep the human touch, and unlock new revenue streams.

From Hardware to Headlines: Dan’s Journey

Dan Benyamin is no stranger to disruption. Over a career spanning chip design, social-media platforms, and data products at Condé Nast, he has seen technologies reshape audiences and ad models. At Aeon, his fourth startup, Dan is charting the next wave: helping media owners use AI to automate video production, personalize experiences, and optimize yield.

His adtech origin story selling the first Facebook beta ads by email underscores one constant truth: publishers succeed when they remain user-centric.

Facing Adtech’s Growing Complexity

The User as North Star

Dan recalls the early days of Facebook advertising with no targeting, no placements, just a postage-stamp ad sold for a day. Fast forward, and the adtech stack has ballooned: multiple platforms, countless measurement standards, opaque programmatic flows. Yet publishers often fall into two traps:

  1. Tech First: Investing heavily in bespoke data platforms and complicated pipelines, losing sight of editorial quality and brand loyalty.
  2. Platform Dependence: Relying on Google or a handful of ad networks for revenue, ceding control over user relationships.

Dan’s prescription is straightforward: prioritize your readers above all else. Every algorithm tweak, dashboard rollout, or content experiment should answer one question: does this create a better experience for our audience? If not, it risks becoming an expensive dead end.

The Value of Agility

Publishers that treat adtech as an ever-evolving toolkit, rather than a monolithic fortress, will outpace their peers. Dan highlights how rapidly user behaviors can pivot, whether due to a new video format on TikTok or shifting reading habits during major news events. By pairing AI for publishers with nimble workflows, media owners can test new formats, measure engagement in real time, and iterate before budgets are wasted.

AI in Publishing: How Publishers Can Unlock Growth Through Audience-Centered Innovation

Bridging Traditional Publishing and the Creator Economy

A Two-Front Battle

Publishers today are squeezed from both sides. On one hand, the major social platforms (Facebook, Instagram, TikTok) consolidate huge swaths of attention. On the other, a flourishing creator economy has turned individuals into media companies: micro-brands that build dedicated audiences on YouTube, Twitch, or Substack, often with minimal overhead.

Dan warns that consistent collaboration between legacy publishers and independent creators remains uneven. While a handful of partnerships, such as Vogue enlisting YouTube stars for the Met Gala, capture headlines, most publishers have yet to forge sustainable models to co-create content, share revenue, and cross-promote audiences.

Turning Creators into Partners

Yet the potential is immense. Traditional media houses boast seasoned editors, photographers, and brand equity. Creators bring agility, authenticity, and built-in fanbases. Smart alliances can combine those strengths:

  • Content Repurposing: Use AI-powered video engines to transform written features or photo essays into engaging short-form clips.
  • Co-Branded Sponsorships: Bundle creator channels with publisher sites for advertisers seeking both scale and niche community buy-in.
  • Revenue-Share Models: Offer creators a slice of subscription or ad revenue in exchange for exclusive or early-access content.

By leveraging AI for content creation, from automated editing to dynamic personalization, publishers can scale these partnerships without ballooning production costs.

The Rise of AI Influencers and the Case for Transparency

When Bots Become Brand

Dan describes the phenomenon of AI influencers: digital personas designed to engage audiences on social platforms, often without any real human behind the account. Early adopters, such as fashion houses casting AI models, demonstrate AI’s capacity for high-volume, on-brand content. Yet the technology also raises red flags around authenticity, trust, and intellectual property.

Publishers must decide how far to embrace synthetic personalities. Dan suggests two guiding principles:

  1. Be Transparent: Clearly label AI-generated content or personas. Readers value honesty; misleading them risks reputational damage.
  2. Focus on Value: If an AI persona informs, entertains, or inspires better than a standard post (without pretending to be human) then it has earned its place. The goal is to enhance, not replace, genuine human connection.

Regulation on the Horizon

As AI content proliferates, regulators and platform owners are racing to define standards. Dan points to spam filters as an early example of automation policing automation: publishers that watermark AI-crafted imagery or sign API agreements with chatbot providers can ensure their content remains discoverable and compliant. Publishers that proactively engage with emerging policies will avoid last-minute compliance headaches.

AI in Publishing: How Publishers Can Unlock Growth Through Audience-Centered Innovation

AI as a Force Multiplier for Monetization

Beyond “Build vs. Buy”

Publishers often wrestle with whether to build in-house AI solutions or license third-party tools. While engineering teams may relish crafting bespoke pipelines, Dan cautions that such projects can distract from core editorial missions. Instead, he recommends:

  • Evaluate ROI: Will a custom model truly outperform a commercial offering?
  • Partner with Specialists: Use AI for publishers platforms that integrate seamlessly with existing CMS and ad stacks.
  • Modular Adoption: Begin with high-impact use cases (automated video summaries, headline generators, or ad yield forecasting) before extending capabilities.

Five Low-Hanging Fruits for AI-Driven Revenue

  1. Automated Content Tagging & Personalization
    Natural language processing can instantly categorize articles by topic, sentiment, and reader intent, fueling on-site personalization and boosting subscription conversions.
  2. Video Production at Scale
    Leverage AI video editors to turn long-form interviews or articles into short social teasers, generating new ad inventory and ancillary sponsorship opportunities.
  3. Dynamic Ad Creative
    Implement responsive banners or video ads that adapt messaging, call-to-action, and imagery based on real-time page context, raising click-through rates and CPMs.
  4. Yield Optimization Tools
    AI algorithms can forecast demand, identify under-monetized ad slots, and recommend price floors - putting publishers in control of their programmatic outcomes.
  5. Rights Management Automation
    Automated scans can detect copyright flags in submissions or user-generated content, protecting intellectual property and avoiding legal pitfalls.

Data-Driven Decision Making, Powered by AI

From Dashboards to Decisions

Publishers generate vast troves of behavioral data (pageviews, scroll depth, engagement time) but insights often remain locked behind manual reports. AI offers a leap forward:

  • Anomaly Detection: Instant alerts when traffic patterns or ad performance deviate, so teams can respond to banner blockers or viral spikes in real time.
  • Predictive Churn Models: Early warnings when subscribers show signs of disengagement, triggering targeted retention campaigns.
  • Cross-Channel Attribution: A unified view across articles, newsletters, social posts, and podcasts - revealing which touchpoints truly drive ad revenue or subscriptions.

By embedding AI into the publishing process, editorial and commercial teams alike move from gut instinct to evidence-based strategies.

Balancing Automation with the Human Touch

The Perils of Overreliance

While AI can draft news articles or produce quick video summaries, Dan emphasizes that publishers’ most enduring asset is editorial credibility. Over-automation risks diluting brand voice, undermining trust, and scaling errors. Instead, he advocates:

  • Human-In-The-Loop: Any AI-generated draft or creative asset should undergo editorial review for accuracy and tone.
  • Ethical Guardrails: Establish internal guidelines on which content types (breaking news, investigative features, expert analysis) remain strictly handcrafted.
  • Continuous Training: Use feedback loops where editorial teams flag AI missteps, refining models for better performance over time.

In this way, generative AI becomes a collaborator, not a replacement, empowering journalists and marketers to focus on high-value work.

Preparing for AI’s Next Chapter

AI for Publishers: A Mindset Shift

Dan’s closing advice is to treat AI not as a magic bullet but as a performance-enhancing tool. Publishers that:

  • Stay Curious about emerging models and platforms
  • Invest in Data Literacy across their teams
  • Foster Cross-Functional Collaboration between editorial, technology, and sales
    will build the resilience to adapt when the next big disruption arrives, be it voice interfaces, immersive media, or new regulations.

Six Months to Action

  1. Audit your current AI and data projects.
  2. Pilot one AI-powered tool in content creation or ad yield.
  3. Measure its impact on engagement, revenue, or efficiency.
  4. Scale successful experiments and sunset low-impact efforts.
  5. Document ethical guidelines and compliance checkpoints.
  6. Communicate wins and lessons to all stakeholders, building momentum for further AI adoption.

Tune In and Take the Wheel

AI-driven innovation is reshaping the publishing industry at every corner, from automated content creation and video automation to real-time yield optimization and personalized experiences. The Pub Way episode with Dan Benyamin offers a masterclass in how AI in publishing can become a catalyst for growth, not a source of distraction.

Ready for more actionable insights? Subscribe to The Pub Way and explore the full conversation with Aeon’s Dan Benyamin.
Discover more episodes and dive into the discussion

Modern advertising has always revolved around securing consumer attention. Yet, merely capturing eyes on a screen no longer guarantees real outcomes. In our initial blog, From Attention to Intention: Redefining Performance with Intent Based Marketing, we introduced the idea that intent—not viewability metrics alone—truly drives conversions.

Let’s now dive deeper into intent based targeting and AI intention models as a strategic solution for advertisers looking to connect with high-intent audiences at precisely the right moment.

Why Attention Alone Isn’t Enough

Attention metrics evolved because advertisers grew dissatisfied with superficial measurement. An ad might be “viewable,” but viewers often skip right past it if they lack genuine interest. Publishers sometimes exploit such metrics by overcrowding pages with ads, resulting in wasted budgets.

Conventional targeting often focuses on broad user traits or simple viewability. But these approaches overlook user intent, the critical indicator of someone’s motivation or readiness to act. If a consumer is in the research stage for a product or service, they’re more receptive to detailed information.

Conversely, a customer comparing prices might respond best to promotional offers. Recognizing these nuances reduces mid-funnel waste and ensures ad spend goes where it matters most.

Where attention is fleeting, intention signals a deeper commitment, whether that’s learning about a category or actively preparing to purchase.

By identifying high-intent users, you increase the likelihood of conversion and substantially improve performance metrics—all while respecting user privacy. This shift from mere visibility to meaning helps advertisers trim waste and realign marketing budgets with real outcomes.

Understanding Context and User Intent

Contextual advertising traditionally relied on keywords or broad topics, but it didn’t always capture a user’s mindset. Intent based targeting digs deeper, distinguishing casual curiosity from a genuine readiness to buy. Whether the user is checking detailed reviews, comparing costs, or seeking a product’s pros and cons, these actions highlight how far along they are in the buying journey.

What sets intent based marketing apart is its respect for user privacy. Rather than tracking personal data, you focus on the “why” behind a user’s content choice. For instance, if someone consistently reads about eco-friendly travel, an ad for renewable energy solutions hits closer to genuine customer intent than a random pop-up. By aligning messages with user motivation, advertisers see higher relevance, stronger engagement, and a more refined marketing approach overall.

Intention Based Targeting and AI Intention Models

AI Intention Models: Precision Targeting at Scale

Early contextual methods only scanned for keywords, missing the deeper meaning. AI intention models take it further by examining page structure, sentiment, and engagement signals in real time. Two similar-looking pages about electric cars may differ dramatically in tone—one might celebrate them; the other might criticize them. AI interprets these nuances, ensuring ads appear where the buying intent is highest.

Such AI models require vast amounts of labeled data to differentiate between purely informational content and content signaling purchasing decision readiness. Over time, the system refines its accuracy, quickly learning from which ad placements yield stronger results. This self-improving loop makes intent based targeting more flexible and immediate than any static keyword approach.

From Mid-Funnel Wasteland to Action

The mid-funnel often swallows large chunks of marketing budgets without delivering conversions. People might be curious but not quite ready to act. Intent based targeting, powered by AI intention models, helps filter out half-hearted browsers. Advertisers engage those who exhibit genuine interest—like searching for specific features or actively comparing reviews—rather than wasting impressions on visitors who remain on the fence.

With intent based marketing, brand messaging syncs up with the user’s stage in the buying journey, nudging them further along the funnel. In B2B marketing, for example, identifying a prospect who’s actively evaluating solutions can significantly improve lead generation efforts. You’re no longer yelling into the void; you’re helping potential clients finalize their choices.

Intention Based Targeting and AI Intention Models

Balancing Conversion Goals with User Respect

Regulations such as GDPR and CCPA demand a privacy-first approach, complicating how advertisers gather data. Intent based marketing meets this challenge by relying on context signals within content rather than personal identifiers. Advertisers stay compliant while still honing in on high intent audiences who genuinely match the product or service being promoted.

Unlike retargeting that follows a user around the web, intent based targeting zeroes in on immediate signals within content.

Ads feel relevant rather than invasive, boosting user intent to click. Freed from heavy tracking scripts, brands can build trust by delivering more respectful, better-timed ads that align with the user’s actual interests.

Performance, Privacy, and the Value of Intent

Seedtag’s proprietary contextual AI Liz, interprets language, visuals, and engagement signals to determine real-time intent. Traditional approaches might label a page simply “travel” or “health,” but Liz detects whether the content indicates a user casually browsing or actively evaluating a product or service. The result is a more refined approach that resonates with potential customers on the verge of making a decision.

Many brands, from automotive to consumer goods, have cut costs and increased conversions by using Liz’s AI intention models. Instead of blanketing broad categories, ads appear in contexts that reflect actionable customer intent. This fosters an environment of higher relevance, fewer wasted impressions, and stronger ROI.

From Mere Attention To Meaningful Intention

As machine learning grows more sophisticated, expect ongoing improvements in how systems interpret language and user signals. Advertisers will adapt in real time, recognizing subtle shifts in consumer interest. The upshot: a more agile marketing approach ready to pivot fast when trends or consumer preferences evolve.

The essence of intent based targeting is giving consumers ads they welcome at the moment they seek answers. With AI-driven insights, advertisers deliver messaging that stands out as helpful rather than intrusive. The result is a mutually beneficial ecosystem, where performance goals align naturally with user needs.

Gone are the days when superficial measures like viewability or broad-based targeting sufficed. Today’s advertisers must connect with real user intent, ensuring each impression lands in front of a high-intent audience ready to engage or convert. By integrating advanced AI intention models, the gap between vague browsing and concrete action narrows, helping brands cut through the noise.


Ready to meet your consumer right where they are with the power of intent based targeting with AI-driven precision?
Learn how Seedtag’s proprietary AI, Liz, can transform your strategy

While the term artificial intelligence has been around for decades, recent AI trends are ushering in a wave of cutting edge approaches that surpass anything we could have imagined just a few years ago. At Seedtag, we believe this AI revolution marks the biggest shift in modern advertising since the rise of programmatic buying.

By integrating advanced machine learning, Large Language Models (LLMs), Agentic AI, and Cognitive AI techniques, we’re opening new possibilities that promise not only greater performance for advertisers but also more respectful, relevant experiences for consumers.

Below, we’ll explore how these AI models transcend basic automation and why Seedtag’s ongoing commitment to technological superiority, fueled by over a decade of dedicated R&D, is propelling the future of AI-driven contextual advertising forward.

What Is a Large Language Model?

No discussion of the AI revolution is complete without addressing Large Language Models, or LLMs. In simple terms, LLMs are AI models trained on massive volumes of text often gleaned from books, websites, and various digital sources. These models learn the underlying patterns in language, enabling them to process text, generate human-like responses, and understand context far beyond simple keyword matching.

An LLM is not limited to short sentences or rote tasks: it can summarize articles, create coherent narratives, answer questions, and even transform the marketing function through advanced language comprehension. These models have become essential in modern embedded systems that power chatbots, language translators, and dynamic content generation engines. For advertisers, an LLM can refine messaging in real time, adapting creative elements to different user mindsets, often with minimal human guidance.

Blog_In-Article-Image-1_Pushing the Boundaries of the AI Revolution in Advertising Digital Advertising

Embeddings and the Power of Meaningful Connections

Understanding language at a human intelligence level goes hand in hand with another crucial technology: embeddings. But what are embedded systems or, more precisely, embedded representations? In essence, embedding technology converts words or phrases into numerical vectors (coordinates in a multi-dimensional space) that capture their conceptual relationships.

Picture the difference between two pages mentioning “fitness.” One might address the challenges of post-injury workouts, while another focuses on group yoga sessions. Both share a fitness keyword, yet they differ in tone and context. With embeddings, an AI system can instantly recognize these nuances, clustering content by semantic similarity rather than just surface words.

For advertisers, these vectors unlock the ability to match campaigns to the actual meaning behind pages. Instead of placing ads for running shoes anywhere the word “fitness” appears, an embedding-based approach can position those ads next to genuinely aligned topics such as rehabilitative exercise or mindfulness routines. This approach ensures better audience alignment and fosters a more positive brand interaction.

Agentic AI: When Machines Step In to Help

Another key concept in the future of AI is Agentic AI. Unlike simpler algorithms that simply make suggestions, agentic AI has the capacity to carry out actions in pursuit of a goal. Think of a tool that not only identifies optimal ad placements but autonomously changes campaign parameters and redeploying budgets, revising targeting clusters, or refining creative assets based on real-time data. This is a giant leap from conventional automation, which depends on continuous human input.

The implications for advertisers are immense. A brand could launch a marketing campaign, then have an AI “agent” dynamically improve performance based on fresh insights in order to minimize wasted spend, boost engagement, and adjust to new trends on the fly. This adaptive quality is especially powerful in volatile markets where consumer preferences shift quickly. One might liken it to having a nuclear power plant that continuously optimizes its output to maintain efficiency and safety, only in this case, the “plant” is an AI system that generates maximum advertiser ROI with minimal oversight.

Cognitive AI: Going Beyond Surface Context

Where agentic ai enables action, Cognitive AI adds the capacity for deeper comprehension. Traditional contextual solutions rely heavily on keywords: see a certain word, place an ad. By contrast, Cognitive AI evaluates the sentiment, tone, structure, and even emotional resonance of content. It’s an evolution from standard keyword matching to a more holistic, human level method of understanding.

Consider the difference between an upbeat product review and a scathing critique. Both may reference the same item, but the emotional weight is entirely different. Cognitive AI discerns this difference immediately, ensuring the brand’s ads appear in places that truly reflect its values. Advertisers thus gain more robust brand safety while also enjoying greater impact when content synergy is genuinely positive.

A Decade of Innovation at Seedtag

While many companies are racing to incorporate new AI features, Seedtag has been honing proprietary technology for 10+ years, pushing the boundaries of AI revolution long before it became a buzzword. Our technology stack has grown from straightforward contextual algorithms to integrated systems featuring embeddings, LLMs, agentic AI, and cognition ai capabilities.

This ongoing R&D effort is not about following trends; it’s about ensuring we remain at the cutting edge of applied AI. Over the years, we’ve amassed unique experience in analyzing massive datasets, refining our embedding methodology, and building an AI system that can scale across global markets. As a result, our solutions stand out in their precision, speed, and adaptability, allowing advertisers to harness advanced targeting without compromising user privacy or brand safety.

“All this innovation is not coming from competing with others - it’s about competing with ourselves. We're working to become the best version of Seedtag we can be.”, Jorge Poyatos, Seedtag Founder & Co-CEO.

Blog_In-Article-Image-2_ Pushing the Boundaries of the AI Revolution in Advertising

Leading the Charge Into Tomorrow

The potential of AI is immense, and the current AI trends are just the beginning. We anticipate further breakthroughs in LLMs, deeper integration of cognition AI, and more sophisticated forms of agentic AI that will revolutionize how brands strategize and connect with audiences. By combining big data insights with nuanced language understanding, we’re poised to reshape everything from real-time creative optimization to predictive consumer intent forecasting.

Yet, this AI revolution demands responsibility. While these technologies can unlock unprecedented relevance, trust remains paramount. At Seedtag, we ensure our solutions respect user boundaries, deliver fair outcomes, and reflect modern privacy standards. AI might be the driving force, but it’s applied with a conscientious mindset that recognizes the line between helpful automation and intrusive overreach.

Whether you’re eager to enhance performance, strengthen brand safety, or simply future-proof your marketing strategies, harnessing these innovations is the next logical step. By embracing the synergy of agentic AI, cognition AI, embeddings, and Large Language Models, advertisers can thrive in a world where deeper, more authentic user engagement becomes the gold standard for digital success.

Ready to explore the full potential of AI-driven contextual advertising? Discover more about how Seedtag is leading the AI revolution in contextual advertising

The British automotive landscape is travelling through unfamiliar territory. Economic caution, stricter privacy rules, and a surge of EV‑focused challengers have reshaped how automotive brands reach and persuade car buyers. Car buyers start a search on their phone during a Sunday coffee, watch an EV review on their tablet that evening, and compare finance rates on a work laptop the next morning.

To stay ahead, advertisers must understand not only who is in market but why, when and how their intentions change along the route to purchase.

Seedtag’s latest UK analysis, powered by our contextual AI platform Liz, unpacks more than 10,000 automotive‑related URLs, combining third‑party research (GWI, Kantar) with real‑time content signals. The result is a clear map of consumer motivations, seasonal peaks and digital touchpoints that matter most for growth.

Below we highlight the new rules of automotive marketing, the media hurdles brands face, and how contextual targeting helps steer campaigns toward high‑value moments without relying on personal data.

From ‘Who’ to ‘Why’: Reframing the British Car Buyer

Traditional demographic slices like “men 25‑44” or “families in the Midlands” no longer tell the full story. Our research shows that:

  • Intent‑driven moments govern decisions. Buyers zig‑zag through reviews, price calculators, EV incentives and lifestyle articles before contacting a dealer.
  • Attitudes trump loyalty. Only 2 in 10 UK buyers cite brand loyalty as a deciding factor. Environmental concern (60 % of adults) and lifestyle fit weigh more heavily.
  • Content choices signal readiness. Reading a financing guide is low‑intent; comparing trim levels or booking a test drive indicates high intent.

Marketing implication: Segmentation must include attitudes, values and stage‑specific needs. By recognising intent signals in content, brands can speak with relevance boosting lead generation and cutting media waste.

Blog_In-Article-Image-2_ digital marketing for publishers_ - Strategic Insights for Automotive Marketing Success

Navigating the Funnel: Common Roadblocks and Media Fixes

Awareness & Discovery

When a new model launches or a brand refreshes its EV range, noise is intense. Advertisers often default to broad reach, yet buyers here gravitate toward editorial rundowns, sustainability think‑pieces and first‑look videos. Without matching message to mindset, brands blur together. The fix? Position creative around bigger themes like eco credentials, tech innovation, and design leadership, so that early explorers remember your unique value.

Consideration & Interest

At this mid‑phase, car shoppers compare specs, watch long‑form reviews and price‑check across dealer sites. Competition for qualified traffic is fierce; misaligned ads bleed budgets. Contextual signals, such as an article contrasting leasing and PCP finance, reveal that the reader is weighing affordability. Serving calculators, configurator links or transparent monthly cost breakdowns here nudges prospects toward enquiry forms rather than another Google search.

Conversion & Actions

Plate‑change months (March and September) and bank‑holiday weekends still anchor the registration cycle, driving last‑mile urgency. Buyers dig into dealer ratings, click for real‑world range stats or book showroom slots. Yet many campaigns continue with broad awareness messaging, missing the chance to trigger “book now” intent. By detecting these calendar‑led spikes in transactional content, brands can deploy geo‑targeted offers, rapid‑response chat and booking widgets that translate clicks into test‑drive appointments.

Seasonality magnifies these patterns. EV content peaks in Q1 and Q4, aligned with tax deadlines and New‑Year eco resolutions. SUV and hybrid interest remains steady, ideal for always‑on prospecting. Sports and off‑road vehicles ramp up ahead of summer road trips. Each curve hints at when to push big‑ticket hero models versus down‑payment incentives or accessory bundles.

Three New Rules for UK Automotive Marketing

1. Context Is Your Compass

See content through the buyer’s lens. A parent reading “best seven‑seat SUVs” is evaluating practicality; an enthusiast dissecting Nürburgring lap times seeks performance proof points. Align copy and creative to these distinct needs and watch engagement metrics climb.

2. Treat Intent Like Currency

High‑intent environments (dealer comparisons, finance‑offer pages) deserve higher bids than broad lifestyle blogs. Liz scores each URL for intent on the fly, letting budgets rise or fall in milliseconds, so spend follows genuine purchase signals.

3. Act in the Moment, Honour Privacy

Retargeting cookies already fail on Safari and Firefox. Contextual AI delivers relevance without personal data, meeting ICO expectations while still spotting the right eyeballs in real time.

Blog_In-Article-Image-1_ digital marketing for publishers_ - Strategic Insights for Automotive Marketing Success

Liz Under the Bonnet: Turning Insight into Action

Seedtag’s contextual engine breaks automotive content into nuanced themes such as Luxury & Competition, Everyday Vehicles and Fuel Efficiency & CO₂. Within each impression, Liz assesses language, imagery and placement to assign one of three intent tiers:

  1. Explorers – broad curiosity about trends, lifestyle fit
  2. Evaluators – detailed side‑by‑side research, feature debates
  3. Deciders – finance, dealer locator, insurance queries

Campaign logic then adjusts: high‑level brand storytelling for Explorers, granular offers for Evaluators, and strong calls‑to‑action for Deciders. Because Liz recalculates intention every time a user lands on new content, ads stay as fluid as the journey itself - no shelf‑worn segments, no wasted impressions.

Real‑World Mileage: Ford and Nissan

Ford | Visibility That Converts

Launching an updated SUV line, Ford needed to stand out without ballooning spend. Liz prioritised pages heavy in transactional cues (leasing FAQs, “best family haulers” lists) while down‑weighting generic news reads. Viewability climbed 32 % above benchmark and click‑through rates rose 10 %, translating visibility into site visits and data‑capture submissions.

Nissan | Turning Interest Into Leads

For Qashqai, Nissan’s brief was straightforward: fill dealer pipelines. Seedtag isolated high‑intent content clusters (range calculators, ownership cost breakdowns) and dynamically inserted location‑based banners. Cost per visit fell 57 %, cost per lead 35 %, and average on‑site time hit 77 seconds, demonstrating genuine shopper engagement.

Roadmap for Automotive Brands and Agencies

  1. Audit Content Signals – List the triggers (e.g., “EV charge cost,” “used car depreciation”) that reveal stage and emotion.
  2. Mirror Motivations – Craft bespoke messages for eco‑first, tech‑obsessed or budget‑sensitive segments. One‑size banners are relics.
  3. Leverage PMPs – Use private marketplace deals to access premium review sites, enthusiast forums or EV‑news hubs, safeguarding brand fit.
  4. Optimise Quickly – Plate‑season interest spikes last weeks, not months. Shift weight as soon as Liz flags rising intent.
  5. Measure Beyond CTR – Track viewability, dwell time, booking completions and downstream showroom visits for a complete sightline to sale.

The Road Ahead for Automotive Marketing

Competition will intensify as legacy makers, EV specialists and subscription models tussle for share. Environmental concerns and flexible ownership plans will keep reshaping criteria. In this clutter, brands that decode when to nudge, rather than blanket who to target, will capture attention cost‑efficiently. Contextual AI, honed by intent signals, offers that navigational edge while respecting the UK’s privacy framework.

The road ahead may feature sharp bends, but with real‑time intent analysis guiding creative, media and timing, brands can move from guesswork to precision and from passive reach to profitable growth.

Discover the Full Deep Dive into the UK Automotive Industry

Learn all about segments, seasonal curves and competitor share in Seedtag’s contextual insights, Access it here

From binge-worthy boxsets to live linear channels, the way we watch TV has changed. The rise of Connected TV (CTV) and Free Ad-Supported Streaming Television (FAST) is transforming not only how audiences consume content but also how marketers reach them.

As consumers grow weary of high subscription costs and subscription fatigue sets in, more viewers are turning to free alternatives like FAST channels.

  • Two in three (66%) TV content viewers in the US are using free, ad-supported streaming TV (FAST) platforms in a typical month, according to Horowitz Research
  • Over 7 in 10 (73%) FAST users agree that TV is more enjoyable now that they can turn on these free services and watch whatever is on.

For marketers, this means access to large, diverse audiences across smart TVs and streaming devices, with the added bonus of granular ad targeting, measurable outcomes, and a lower barrier to entry than traditional TV buys.

CTV Is the New Prime Time

CTV refers to any television that can stream content over the internet. This includes smart TVs and devices like Roku, Fire TV, and gaming consoles. It provides users with access to both on-demand video and live programming through apps and services that operate outside the traditional broadcast and cable boundaries.

CTV has rapidly become a dominant force in the media landscape. With 88% of U.S. households owning at least one connected TV device and streaming becoming the default mode of viewing for younger audiences, marketers are quickly shifting their budgets to meet audiences where they are. CTV allows advertisers to combine the immersive storytelling of television with the precision of digital targeting.

Unlike linear TV, CTV supports interactive formats, dynamic ad insertion, and performance tracking. This opens up a new era for video advertising, where brands can serve tailored messages across premium inventory, all while optimizing for reach, frequency, and performance.

Blog_In-Article-Image-1_ what is fast tv - contextual advertising ctv advertising

FAST Channels: The Return of Linear TV, Reimagined

FAST stands for Free Ad-Supported Streaming Television. These channels mimic traditional linear TV with scheduled programming but are delivered via the internet, without any subscription fees. The trade-off? Ads. But unlike traditional cable, FAST channels are flexible, free, and often highly specialized by genre, interest, or audience.

Platforms like Tubi, Pluto TV, Roku Channel, Freevee, and Samsung TV Plus have made FAST channels widely accessible, offering content that ranges from classic sitcoms and cult favorites to live news and niche verticals. This retro-meets-modern format appeals to audiences seeking background entertainment or a curated, low-key experience.

For advertisers, FAST provides a scalable, brand-safe, and measurable video environment. Audiences are not just growing, they are engaged.

A recent study found that only 7% of viewers skip ads on FAST channels, and more than half of millennial and Gen X viewers tune in each month. This makes FAST a prime space for awareness, consideration, and even conversion campaigns.

A Performance-Driven Ecosystem for Advertisers

CTV and FAST platforms bring together the best of both worlds. Advertisers can leverage the storytelling potential of TV with the targeting and measurement of digital. Key benefits include:

  • High-quality inventory in brand-safe environments.
  • Granular targeting based on content, geography, and device.
  • Real-time performance metrics like impressions, completion rates, and conversions.
  • Lower CPMs compared to traditional TV spots.

Because these platforms are digital-first, they enable seamless integration with broader omnichannel strategies. For example, a campaign might target viewers of a specific FAST cooking channel with a video ad and then retarget them with native or display ads on the open web.

Content Libraries and the Evolution of FAST

One of the early value propositions of FAST was access to vast content libraries. Many services built their offerings on classic shows and older programming, giving dormant IP new life. However, as those libraries become saturated, the next phase of FAST growth will depend on innovation.

Some platforms are beginning to invest in original content, while others explore partnerships and content swaps. Well-funded services may lead with fresh programming, while others will focus on curating genre-specific channels or mining niche interests.

The bottom line: FAST is evolving, and so are viewer expectations. Marketers who adapt quickly will be those who understand how to pair the right creative with the right context at the right time.

Blog_In-Article-Image-2_ what is fast tv - contextual advertising ctv advertising

Why Now: The Strategic Value of CTV & FAST

Marketers are under pressure to do more with less. Rising acquisition costs, data restrictions, and shifting consumer behaviors make it essential to invest in channels that deliver attention and performance. CTV and FAST check all the boxes:

  • Growing audiences and screen time.
  • Better targeting and measurement.
  • Brand-safe environments.
  • Inventory diversity and creative flexibility.
  • Cost-effective compared to traditional broadcast buys

Whether it’s a national brand looking to replace linear TV spend or a challenger brand exploring high-impact video, the CTV and FAST ecosystem offers solutions for upper-, mid-, and lower-funnel goals.

Looking Ahead: Sustainable Growth in CTV & FAST

The expansion of CTV and FAST is not without challenges. Measurement standardization, content licensing, and viewer fragmentation are hurdles that the industry is still working to overcome. Yet, the demand for accessible, ad-supported streaming continues to grow, and advertisers are responding accordingly.

As more platforms refine their offerings and invest in better ad experiences, marketers will gain even greater control over how they connect with audiences. From tailored content alignment to contextual targeting powered by AI, the future of CTV and FAST is about relevance at scale.

Discover Seedtag's Solutions for CTV

As the CTV and FAST landscape continues to evolve, brands that align their messaging with the right context and deliver it at the right moment, will rise above the noise. That’s where contextual intelligence makes the difference.

At Seedtag, we help marketers unlock the full potential of video advertising through privacy-first, AI-powered targeting that goes beyond demographics. Whether you're launching on a FAST channel or scaling CTV reach, our solutions are built to deliver attention, relevance, and results - all without relying on personal data.

Curious how it works? Let’s talk about how Seedtag can elevate your next video campaign.

Brand safety is often considered an advertiser’s priority. Yet in today’s complex ecosystem, digital marketing for publishers cannot thrive without robust brand safety measures of its own. In an era marked by privacy concerns, misinformation, and intensifying competition, publishers must ensure that their advertising environments protect both their reputation and the trust of premium advertisers.

In a landscape where 67% of advertisers prioritise brand safety and where brands risk losing two-thirds of their customers if their ads appear next to misinformation, publishers must take a proactive approach to ensuring a brand-safe environment.

Below, we explore the crucial role of brand safety for publishers, highlighting how advanced AI-driven solutions and contextual advertising can secure revenue streams and safeguard a publisher’s standing in the digital landscape.

Why Brand Safety Matters More Than Ever

In recent years, brand safety has surged in importance, following high-profile incidents where prominent advertisers discovered their content next to inappropriate or harmful material. While brand safety has traditionally been seen as an advertiser concern, publishers are finding themselves under similar scrutiny. Potential partners want assurances that their ads will not appear alongside questionable or damaging content, and any reputational risk is now a two-way street.

Publishers are brands in their own right, entities with values, reputations, and long-term visions. A single brand-unsafe association can weaken a publisher’s credibility, especially among advertisers who are increasingly selective about where they place their spend. Failure to address brand safety can also erode the loyalty of readers who expect a consistent, trustworthy environment.

digital marketing for publishers - monetization with brand safety

Is Brand Safety the Missing Link?

When looking at digital marketing for publishers, brand safety often surfaces as the missing piece in achieving sustainable revenue growth. Without effective safeguards in place, publishers risk:

  • Losing Premium Advertisers: Many advertisers simply refuse to partner with publishers lacking clear brand safety protocols.
  • Damaging User Trust: Consumers notice mismatched or inappropriate ads and may question the editorial standards of the publisher.
  • Jeopardising Future Growth: If your site gains a reputation for lax oversight, it becomes far harder to secure robust partnerships down the line.

How Brand Safety Affects Digital Marketing Campaigns

In practical terms, brand safety impacts everything from marketing strategies and marketing campaign planning to audience perception. Advertisers want to ensure that each campaign reaches the right target audience in a context that aligns with their brand. Publishers who fail to offer such security may see fewer bids, reduced eCPMs, and lower overall ad inventory value.

Are Your Brand Safety Practices Holding You Back?

Some publishers adopt overly broad keyword blocking or blanket restrictions, hoping to avoid risk entirely. While this can address the immediate concern, it often inadvertently blocks legitimate content, resulting in lower monetisation. In effect, too many marketing efforts get choked off before reaching audiences who would otherwise be receptive.

Balancing safety and scale is key. Relying on outdated or simplistic “malgorithm” keyword approaches can inadvertently eliminate entire verticals of content (think legitimate articles on health, travel, or politics) where an advertiser could have effectively engaged potential readers or prospective customers.

Common Brand Safety Pitfalls for Publishers

  1. Malgorithm Misalignments
    When automated systems match ads to content based purely on surface-level keywords, they often disregard tone, sentiment, or context. For instance, a brand promoting healthy lifestyles might inadvertently appear next to articles discussing controversial or negative health claims. This mismatch not only diminishes ad impact but can also erode advertiser trust.
  2. Inappropriate Content Conflicts
    The “Dirty Dozen” (topics like violence, terrorism, and hate speech) may not always be relevant to every publisher. However, it is crucial to identify where your site stands on such themes. Publishers covering sensitive news topics, for example, must clearly differentiate between factual reporting and sensationalised content so advertisers can decide whether it matches their comfort level.
  3. Bot Traffic and Fake Impressions
    Advertisers are wary of spending budgets on non-human or fraudulent traffic. By ignoring ad fraud protection, publishers risk a situation where large segments of ad inventory are served to bots, wasting advertiser spend and sabotaging genuine engagement. Publishers who fail to address this will find high-quality advertisers less willing to invest.

Blog_In-Article-Image-3_ digital marketing for publishers_ - Digital Marketing Musts for Publishers Locking in Monetisation with Brand Safety

The Strategic Role of AI-Driven Contextual Solutions

Publishers often struggle with brand safety because older systems rely on simplistic rules. However, advanced AI-driven technology interprets both text and visual signals, distinguishing fact-based journalism from sensational content. This nuance is especially critical in today’s climate, where news is sometimes automatically flagged for controversial topics even though it may be high-quality reporting.

By employing AI to read sentiment, identify subtle context, and filter out truly risky placements, publishers can prove that ads next to factual news need not harm brand perception. Indeed, premium journalism outlets that adopt these strategies tend to retain top-tier advertisers by ensuring a controlled environment without sacrificing editorial integrity.

As brand safety standards evolve, so too must publisher strategies. Overly cautious content blocking will deprive legitimate journalism of advertising revenue, leading to a vicious cycle of reduced funding for high-quality reporting. Conversely, ignoring brand safety leaves you vulnerable to misplaced adverts, reputational damage, and lost business.

A nuanced approach to brand safety, backed by AI-driven contextual advertising, allows publishers to present a consistent, secure, and valuable environment. Advertisers, reassured by these measures, are likely to invest more in your inventory. Readers, seeing carefully moderated content, trust your platform and return for informed engagement.

Building a Sustainable Brand Safety Approach

Brand safety is not an optional add-on; it is now integral to digital marketing for publishers. Whether you run a niche blog, a national news site, a CTV publisher, or an industry-specific portal, adopting a proactive stance on brand safety pays dividends in trust and monetisation. A robust brand safety framework underscores your commitment to editorial quality, premium partnerships, and user experience.

Publishers who embrace AI solutions that go beyond keyword-based filtering can strike the perfect balance between protecting brand interests and supporting crucial topics, even those that are challenging or sensitive.

By safeguarding your advertising space and creating an environment where brands feel truly secure, you position your publication at the forefront of digital marketing for publishers and proving that brand safety is not just an advertiser concern but a key to sustainable success for everyone involved.

Curious about how contextual AI can strengthen your brand safety strategy and maximise monetisation opportunities? Discover more about how contextual works for publishers

Advertising is continually reinventing itself in the face of new technology and changing consumer expectations. Many advertisers already see the possibilities of generative AI in improving efficiency and increasing sales. Yet there’s an even bigger shift on the horizon that goes beyond creating marketing copy or predicting audience segments.

That shift is agentic AI - but what is agentic AI, and why does it matter for advertising?

Agentic AI refers to AI-driven “agents” that can operate independently to achieve specific goals, carry out multi step tasks, and respond to real time data without constant human oversight.

Think of an AI assistant that does far more than generate content; it can plan, optimize, and autonomously tweak campaigns based on performance signals. For brands and publishers, these AI agents open new doors for reaching the right audiences in ways that respect user privacy while achieving tangible outcomes.

Below, we’ll explore how agentic AI is reshaping digital advertising, particularly how it elevates contextual advertising to a new level of relevance and effectiveness, and how real-time decision-making, continuous learning, and privacy-friendly design combine into a framework that marketers can use to solve complex challenges with minimal friction. Most importantly, we’ll show how advertisers can integrate these AI powered agents to stay ahead of industry shifts and future-proof their campaigns in an era that demands intelligence and trust in equal measure.

A Snapshot of an Evolving Advertising Landscape

More than ever, the advertising world finds itself grappling with consumer privacy concerns, new regulations, and an explosion of AI-driven tools. According to industry data from Forrester, about 91% of advertisers are already using or considering using generative AI. Of those adopters, nearly 81% believe it has the potential to boost sales. These figures reflect a real desire in the market: brands want flexible technology that can maximize results while respecting user boundaries.

Yet generative AI is only one piece of the puzzle. While generative models excel at producing text or visuals, advertisers need broader capabilities to plan and execute campaigns end-to-end. This is where agentic AI steps in, linking advanced analytics, optimization, and action to create seamless marketing flows.

Key Market Signals Driving Agentic AI Adoption

  • Desire for Efficiency: Advertisers want to cut down on manual tasks and launch campaigns quickly.
  • Increased Need for Personalization: Brands aim to deliver more relevant messages without violating privacy.
  • Privacy Regulations: With cookies and user tracking under constant scrutiny, advertisers look to contextual methods that don’t rely on personal data.
  • Competitive Advantage: Companies that experiment with AI-driven tactics early can adapt rapidly to new consumer behaviors.

Blog_In-Article-Image-1_Pushing the Boundaries of the AI Revolution in Advertising

When AI Takes the Wheel: The Essence of Agentic AI

So, what is agentic AI at a practical level? It’s a type of artificial intelligence AI that doesn’t just follow static rules or churn out one-time suggestions. Instead, agentic AI operates autonomously, gathering data, making informed decisions, and carrying out specific tasks with minimal human intervention. The technology stems from large language model innovations and other advanced ai models that support reasoning and problem solving steps.

By design, agentic AI systems can integrate with multiple data sources. This means they can scan real-time signals such as user engagement metrics or content trends, and immediately adjust campaign settings. Instead of waiting days for a human to interpret data and push new creative, the AI agent can optimize placements, budget allocations, or even messaging on a specific campaign. If customer queries spike around a particular product feature, the AI agent can serve relevant ads highlighting that exact feature with no lengthy lag time required.

A big question arises: If AI is handling so much, what’s the role of human experts? In practice, advertisers provide the strategic vision, define success metrics, and ensure human intervention when needed.

The AI focuses on executing tasks, optimizing campaigns, and learning from continuous feedback loops. This collaboration preserves creativity while reducing repetitive tasks.

Agentic AI and the Changing Web

Recent forecasts suggest a rapidly changing internet, where a significant portion of website visits could be carried out by AI-based tools. These automated systems might scan pages to compare prices or gather product details, all tasks once done only by humans. This shift might sound like a threat to traditional ad-supported sites, yet many see it as an opportunity to refocus on human engagement.

When bots handle the purely transactional side, websites can become more immersive spaces that truly capture user attention such as places for brand storytelling, vivid content, and genuine community interaction. This is especially vital for publishers who want to maintain audience loyalty. If a growing share of “visitors” are actually AI assistants, the real people who do visit will expect more than just product specs or quick checkouts; they’ll want meaningful experiences.

For advertisers, agentic AI can help identify these high-intent human visitors in real time, serving well-placed ads that speak to genuine user interests. By pairing agentic AI with contextual advertising, marketers ensure they’re not running ads solely aimed at personal data. Instead, they focus on the page itself (its theme, tone, even sentiment) automatically matched to user intent.

Blog_In-Article-Image-2_ What is Agentic AI And How is Transforming Digital Advertising

Unlocking Intention in the Mid-Funnel

For years, the mid-funnel in digital advertising has been a place where leads show interest but often drop off before converting. Many marketers find themselves spending on click-throughs that never lead to a purchase or deeper brand relationship. With AI intention models and agentic AI, this mid-funnel gap narrows dramatically.

  1. Immediate Adaptation:
    If a user spends time reading about a particular product category, an AI powered agent can respond by showing a short case study or targeted promotional offer right then and there. It detects the shift from casual interest to deeper consideration and aligns ad content accordingly.
  2. Smarter Sequencing:
    Instead of bombarding users with repetitive messages, agentic AI can sequence content in logical steps. A person who has already read an introductory piece might see more specific insights or success stories that guide them toward a conversion.
  3. Real-Time Reallocation:
    If budgets are misaligned or if mid-funnel ads aren’t resonating, agentic AI can immediately adjust. It can allocate extra funds to more impactful messages or channels, ensuring advertisers don’t waste impressions on audiences that aren’t ready to act.

By turning attention into action at these crucial in-between stages, agentic AI doesn’t just capture leads; it nurtures them with timely content. As a result, advertisers can reduce mid-funnel drop-off and see stronger returns on every impression served.

The Contextual Connection: Privacy, Relevance, and Performance

While traditional audience-based targeting is under pressure from data regulations, contextual advertising provides a natural alternative that respects user privacy. Instead of profiling individuals, contextual approaches analyze the environment (a web page’s text, sentiment, or imagery) and serve relevant ads accordingly so brands can remain both effective and compliant.

When agentic AI meets contextual AI, the result is a marketing strategy that feels less like guesswork and more like continuous learning in motion:

  • Faster Optimization: Campaigns can be recalibrated on the fly, aligning ad creatives with emerging trends or breaking news that resonates with the page’s content.
  • Multi-Level Relevance: Agentic AI doesn’t only match ads to the surface-level topic; it can interpret subtext, user engagement signals, and real-time metrics.
  • Future-Ready Model: As regulations tighten, contextual strategies anchored by AI agents stay a step ahead by minimizing reliance on personal data.

In essence, advertisers get a double benefit: data-driven insights without invasive practices, and real-time performance boosts courtesy of an AI that never sleeps.

Embracing an Agentic Future in Digital Advertising

Agentic AI isn’t a passing trend; it’s a new standard for how digital campaigns are planned, launched, and optimized. By tapping into decisions based on real-time content signals, advertisers gain agility and scalability that manual processes can’t match. Publishers, meanwhile, can refine their content and user experiences to attract both human visitors and AI-driven workflows.

In a landscape where “set-and-forget” strategies quickly become outdated, agentic AI offers a proactive, real time data–driven approach. It helps advertisers transform fleeting attention into meaningful engagement and drives publishers to create deeper connections with their human readers.

The convergence of agentic AI with contextual advertising elevates digital marketing to a place where ads are timely, relevant, and respectful of user privacy.

By automating the routine and accelerating the complex, these AI powered agents free up human teams to focus on creativity, strategy, and ethical innovation. The result? Campaigns that deliver consistent outcomes and adapt to market shifts faster than ever before.

If you’re looking to align your brand with the future of advertising, now is the time to explore the advantages of agentic AI. Its ability to solve complex tasks, deliver informed decisions, and power the next generation of contextual AI experiences will define how brands connect with consumers in the years to come.

Want to dig deeper into how advanced contextual advertising can elevate your campaigns? Explore more about Contextual AI here.

In the competitive world of advertising, sports continue to stand out as one of the most culturally resonant and emotionally charged arenas for brands to connect with consumers. And in 2025, this power intensifies, driven by a packed calendar of summer sports events, surging multi-screen consumption, and shifting audience behaviors.

The insights are clear: consumer interest in sports spikes by 34% during major summer events, and brands aligned with summer sports see a 21% increase in brand recall. This isn’t just a seasonal opportunity but a strategic imperative.

This blog post explores how sports marketing trends are evolving in 2025, and how Seedtag’s contextual AI, Liz, is powering the ability to align marketing strategies with the exact moments, athletes, and fan passions that matter most.

The Rise of Real-Time Sports Marketing

Sports are inherently contextual. Every game, match, or tournament unfolds in real time, and so does audience attention. What’s trending before kickoff might shift entirely by halftime. In this environment, traditional media plans are no longer enough. Advertisers need agility, anchored in intelligence.

Seedtag’s contextual insights, powered by Liz, its proprietary AI, reveal a dynamic, multidimensional map of what sports fans are truly engaging with. Across platforms and formats, Liz processes the full context of sports content, allowing advertisers to activate brand messaging in perfect alignment with fan moments.

And this isn’t speculation: 79% of consumers engage across multiple screens during sports events, and 62% of sports enthusiasts consume content primarily on mobile. The opportunity to deliver contextually relevant messaging that follows the rhythm of the fan journey has never been greater.

Golf: Precision Targeting Meets Prestige

Golf audiences represent a blend of tradition and tech-savviness. With iconic events like The Masters, PGA Championship, Ryder Cup, and British Open dominating the summer sports calendar, interest spikes around both players and venues.

The most engaged players (Rickie Fowler, Jordan Spieth, Tiger Woods, Jon Rahm, and Xander Schauffele) attract consistent media attention, while legendary venues like Pebble Beach and Augusta National create deep emotional resonance for fans.

Golf engagement is also evolving. Conversations around LIV Golf, streaming coverage across Peacock, ESPN, CBS, and Amazon, and PGA-LIV merger dynamics have introduced new narratives. Brands aligned with golf can activate around luxury travel, fashion, sportswear, wellness, and financial services - all within premium content environments.

Using Liz, advertisers can insert campaigns into contextually relevant golf content that spans from swing technique tutorials to pre-tournament speculation, tailoring messaging to the mindset of the moment.

summer sports marketing trends

Hockey and the Stanley Cup: Local Loyalty, International Reach

Ice hockey delivers one of the most engaged fan bases of any summer sport. The Stanley Cup playoffs bring together regional pride, historic rivalries, and fast-paced gameplay, fueling engagement across the U.S., Canada, and Europe.

The most talked-about teams include the Vancouver Canucks, Boston Bruins, Vegas Golden Knights, and Colorado Avalanche, while player-driven stories dominate fan interest. Sidney Crosby, Connor McDavid, Brad Marchand, and Auston Matthews are frequent media magnets.

What makes hockey especially valuable to marketers is the depth of context: fans aren’t just following scores, they're engaged with penalty box drama, draft class speculation, and international team stories. This creates an expansive contextual graph ideal for advertisers aiming to align with real-time fan energy.

Brands can activate across CTV, digital sports analysis, and fantasy platforms, reaching audiences where they’re comparing stats, discussing trades, or reliving game highlights.

FIFA Club World Cup 2025: Global Football, Local Activation

The 2025 FIFA Club World Cup, hosted by the United States, marks a significant evolution in the global football calendar and a pivotal moment for brands.

With games set in high-capacity stadiums like MetLife, Hard Rock, and Mercedes-Benz, this edition of the tournament brings together football’s global powerhouses and American audience reach. Real Madrid, FC Barcelona, Manchester United, Bayern Munich, and Inter Miami are already dominating mentions, with players like Haaland, Neymar, Modric, Vinicius Jr., and Messi attracting cross-continental attention.

Fan conversations overlap with Copa America, UEFA qualifiers, and national leagues, creating a rich and multilingual content ecosystem. Liz can identify where each club or player intersects with fan conversations whether it’s on team strategy, training regimens, or pre-game predictions.

For advertisers, this is a prime opportunity to connect with travelers, multicultural communities, sports bettors, and lifestyle consumers across premium content and multiple languages, all within privacy-first environments.

Tennis: Personalities That Power Year-Round Relevance

Few sports offer as much one-on-one narrative potential as tennis. With the Grand Slam season in full swing (Wimbledon, Roland Garros, the US Open, and Australian Open) players become storylines, and every match is a micro-drama.

On the women’s side, Coco Gauff, Iga Swiatek, Aryna Sabalenka, and Madison Keys headline engagement. For the men, Djokovic, Alcaraz, Nadal, Federer, and Medvedev lead digital conversations, alongside emerging names like Jack Draper and Ben Shelton.

Contextual interest goes beyond match scores. Fans are drawn to training insights, player rivalries, off-court personalities, and health routines, opening up powerful adjacency for brands in skincare, performance nutrition, fashion, and fitness tech.

Seedtag’s contextual AI enables brands to align with specific storylines - be it Gauff’s rise, Federer’s legacy, or Alcaraz’s next challenge, creating relevance at the exact moment it matters most.

summer sports marketing trends

Formula 1: A Global Platform Accelerating Fan Attention

Formula 1 continues to gain momentum as a high-engagement, multi-market platform. Its summer races in Monaco, Silverstone, Monza, Suzuka, Las Vegas, and Mexico City pull in viewers not only for speed and spectacle, but for stories of engineering, rivalry, and innovation.

Fans closely follow top drivers like Max Verstappen, Lewis Hamilton, Charles Leclerc, and Lando Norris, as well as rising stars such as Oscar Piastri and Andrea Kimi Antonelli. Team narratives (Red Bull, Ferrari, McLaren, and Mercedes) add depth to every race week.

F1’s audience overlaps with tech enthusiasts, travel buffs, and high-net-worth consumers, making it ideal for automotive, luxury, and electronics brands looking to deliver message precision.

With Liz, advertisers can target content where fans are exploring driver telemetry, race predictions, and post-race analysis in order to contextually sync ads with moments of high emotional investment.

Baseball: Multi-Generational Appeal and Cultural Identity

Baseball’s place in summer is unmatched for its consistency and cultural nostalgia. From Little League to the World Series, baseball threads through American life, offering long-form, habit-driven content engagement.

Teams like the Yankees, Dodgers, Astros, Braves, and Cubs dominate mentions, while star players like Shohei Ohtani, Juan Soto, Freddie Freeman, and Mookie Betts remain at the heart of fan conversations.

Importantly, baseball’s multi-generational appeal means brands can engage across age groups and interests. From stats-based storytelling to family traditions, it’s an environment where QSR, FMCG, education, and Americana-themed brands can deliver highly relevant creative.

Seedtag’s contextual tools allow advertisers to seamlessly insert messaging into game recaps, player interviews, historical comparisons, and fan prediction content, all while respecting user privacy.

Strategic Implications for Brands

Across all of these sports, one thing is clear: audiences are not passive. They’re active, informed, multi-screening, and emotionally invested. And as consumer interest in sports rises by 34% during summer, marketing strategies must evolve to meet the moment.

Contextual targeting offers brands a solution that’s real-time, privacy-first, and precisely aligned with the stories fans care about.

For advertisers, this means:

  • Moving away from static media planning and toward real-time contextual planning.
  • Using contextual insights to shape messaging that adapts to match in-the-moment fan attention.
  • Activating across CTV, mobile, and publisher environments where sports conversations actually happen.
  • Replacing reliance on outdated third-party data with AI-driven contextual relevance.

Sports Marketing Trends: From Audience to Impact

Summer 2025 will be defined by more than warm weather. It’s a season filled with high-impact sports moments, each representing a chance to do more than place an ad, but to resonate with fans, to deliver immersive experiences, and to create long-term brand affinity.

By aligning with sports marketing trends, understanding fan behavior through contextual insights, and activating through Seedtag’s AI-powered solutions, advertisers have the tools to make every impression matter.

Advertising today demands more than just reach. As digital consumption evolves and regulations tighten, advertisers face a dual challenge: deliver meaningful results while respecting user privacy. The days of passive impressions and overreliance on personal data are fading fast.

Intent-based marketing is gaining more traction than ever as a strategic approach that targets audiences based on real-time context and content signals that suggest purchase readiness or interest.

Unlike traditional models that follow users around the web based on past behavior, intent based strategies look at what truly matters: what a user is actively engaging with in the moment.

At the core of this shift is intentionality: the ability to understand user purpose without personal identifiers. It's not just a workaround for privacy laws; it's a better way to market.

From Guesswork to Precision: Understanding Intent Based Marketing

Intent-based marketing focuses on users' real-time content consumption to determine their mindset. Instead of profiling users by demographics or historical browsing behavior, it aligns ads with the type of product or service the user is actively exploring. The goal: increase the likelihood of conversion by targeting based on intention, not identity.

This approach eliminates a major flaw in traditional digital marketing: mid-funnel waste. Many marketing teams struggle with lead generation that never materializes into action. Users click, scroll, and bounce. Why? Because they weren’t ready to buy.

With intention-based targeting, advertisers can:

  • Minimize wasted impressions.
  • Boost conversion rates.
  • Align messaging with where users are in the buying journey.
  • Stay compliant with privacy regulations.

It’s about precision over presence - reaching fewer users, but reaching them at the right moment.

For years, marketers have used keyword and category targeting to serve ads on pages aligned with certain topics. But this method has its limits. A page tagged "automotive" doesn’t reveal whether the reader is casually browsing or actively comparing models.

The difference between browsing and buying is the gap intent based marketing seeks to close. Without identifying user behavior or storing personal data, AI models can now infer intent directly from the content being consumed.

How AI Models Drive Intention Based Targeting

The backbone of modern intent based marketing is artificial intelligence. Advanced AI models, trained on intent-labeled data sets, allow marketers to distinguish between users who are simply curious and those who are ready to act.

These AI models evaluate more than keywords. They analyze structure, language, tone, sentiment, and visuals within digital content to assess intent signals in real time. For example:

  • Informational content such as "What are hybrid car benefits?" signals research-phase interest.
  • Transactional content like "Best lease offers for hybrid SUVs" signals readiness to purchase.

These nuances are invisible to basic contextual methods but they are critical to outcomes. AI models trained in intention modeling don’t just react to content, they interpret it. And because they continuously learn from performance data, they improve over time, enabling advertisers to fine-tune campaigns based on evolving user behavior.

Seedtag’s proprietary Contextual AI, Liz, brings this to life. Liz doesn’t just parse keywords but understands content with human-like depth. Powered by Natural Language Processing, machine learning, and computer vision, Liz can:

  • Analyze textual and visual content in parallel.
  • Score intent signals dynamically.
  • Adapt targeting logic based on campaign goals.

What sets Liz apart is the ability to model intent across campaigns, meaning the same AI framework can flex to suit the conversion path of an automotive client one day and a consumer tech brand the next. Every page impression is scored and optimized for intent, aligning ad delivery with readiness, not randomness.

These AI-powered systems take into account where a piece of content ranks on search engines, how it’s written, and how audiences engage with it while creating a more robust view of user mindset than historical behavior ever could.

By combining AI’s real-time analysis with privacy-first design, intention modeling transforms digital marketing from reactive to proactive. And it does so without invading users’ personal space.

intention based marketing

Real Outcomes Across the Marketing Funnel

Intent-based marketing isn’t just theory. It's already delivering stronger outcomes for brands looking to maximize every impression.

In a recent campaign, automotive leader Nissan used intention models to optimize vehicle consideration and lead generation. The results:

  • 34% reduction in Cost Per Lead (CPL).
  • 67% drop in Cost Per Qualified Visit (CPQV).
  • Improved performance across every stage of the conversion funnel.

By identifying users who were further along the buying journey, Nissan engaged prospects who were ready to act and saw real return on their digital marketing investment.

These results highlight a key advantage of intent marketing: it turns attention into action.

"Our challenge was to optimize Nissan’s full-funnel strategy, improving consideration without compromising efficiency in the lower funnel. These results confirm that contextual AI is key to driving brand performance," said José Manuel Muries, Cluster Director, Nissan United.

Beyond the Funnel: Ethical, Efficient, and Future-Ready

In an era where users demand transparency and regulators demand compliance, intent based strategies offer a sustainable solution. There’s no need to trade relevance for responsibility.

Intention modeling does not collect personal data or track users across the web. Instead, it interprets signals within the environment a user has already chosen to engage with. That means brands can:

  • Protect user privacy.
  • Avoid data-driven bias.
  • Reduce reliance on third-party cookies.
  • Deliver messages that feel timely, not intrusive.

And because intent modeling is dynamic, it continues optimizing in real time, helping advertisers stay agile as market behavior evolves.

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Reimagining the Mid-Funnel with Intent Based Strategies

For too long, the mid-funnel has been a blind spot in digital marketing - too broad for performance metrics, too narrow for brand awareness. But with the rise of intent modeling, marketers can now:

  • Identify when users shift from awareness to consideration.
  • Serve tailored content that matches their stage in the buying journey.
  • Optimize marketing tools to drive higher value actions, not just clicks.

This shift transforms marketing efforts from static exposure to strategic activation, maximizing the value of each touchpoint.

Intentionality in Action: A New Standard for Performance

Performance marketing has long relied on short-term KPIs. But a privacy-first world requires more thoughtful planning. Intent-based marketing introduces a framework where long-term brand value and short-term results aren’t in conflict.

It enables advertisers to:

  • Understand online behavior in real time
  • Predict potential customers’ needs without invasive data
  • Create high-performance campaigns rooted in trust and transparency

By aligning marketing approaches with real user purpose, brands can build relationships that last beyond a single click, closing the gap between strategy and signal.

But intent based strategies are not plug-and-play. They require:

  • Clear alignment between business goals and user actions
  • Campaigns built around relevance, not reach
  • Investment in AI-powered platforms that understand content the way humans do

But the payoff is measurable. When brands stop chasing users and start meeting them in moments of intent, they turn uncertainty into opportunity.

The advertising ecosystem is evolving fast. Privacy-first doesn’t mean performance-second.

With intent based marketing, advertisers can reclaim efficiency, improve outcomes, and meet growing expectations for ethical, effective digital marketing.

To see this in action, explore Liz, the Contextual AI behind Seedtag’s intention models, designed to predict and act on real-time intent across the open web.

To mark International Women’s Month, Seedtag brought together a powerhouse group of industry leaders for a special episode of The Pub Way Podcast hosted by Tina Iannacchino, VP of Publisher Partnerships North America at Seedtag. She was joined for a dynamic conversation that brought forward honest, bold, and deeply human insights from women who are shaping the future of advertising and media.

This special panel featured:

  • Jackelyn Keller, CMO at Comscore
  • Natasha Byrne, Global Business Lead at Omnicom Media Group
  • Samantha Skey, CEO at SHEMedia
  • Luisa Izquierdo, CHRO at Seedtag

With this year’s International Women’s Day theme Accelerate Action as a guide, they explored leadership, representation, and the tangible steps needed to create more inclusive, impactful environments.

  1. From Imposter Syndrome to Imposter Awareness.
  2. Redefining What Leadership Looks Like.
  3. Why Context Matters In Advertising and Leadership.
  4. Taking Action That Moves the Needle.
  5. What Comes Next.

From Imposter Syndrome to Imposter Awareness

“I kept saying, ‘What if I’m not good at what I do?’” said Natasha Byrne, reflecting on a major career shift. “Even at my level, I had that imposter syndrome.”

But what many women label as internal insecurity is often a reaction to external dynamics. Samantha Skey challenged the very term: “Imposter syndrome was created by the patriarchy. It’s not that we’re broken, it’s that we’re made to feel like we don’t belong.”

Jackelyn Keller added, “We need to change the stories we tell ourselves. Instead of saying, ‘I’m quitting smoking,’ say, ‘I’m not a smoker.’ That shift in identity and self-talk is powerful.”

Across the board, the takeaway was clear: what we call self-doubt is often a response to environments that haven’t been built with us in mind. Changing the narrative starts with recognizing that - and speaking up anyway.

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Redefining What Leadership Looks Like

“I was the only woman in the room and the youngest,” said Luisa Izquierdo, recalling her early years as an HR director. “I had to coach and guide people decades older than me. What helped was preparation. That’s how I built my confidence.”

For others, it was about redefining the qualities often negatively labeled as ‘feminine.’

“In the beginning, I thought empathy and emotion made me weak,” said Natasha Byrne. “Now, I see them as my superpowers.”

And leadership doesn’t just show up in boardrooms. Jackelyn Keller shared a moment of pride when her young daughter challenged her school’s curriculum for reinforcing outdated gender roles. “She raised her hand and said, ‘We don’t read that in my family.’ She changed the book for the whole class.”

These stories highlight how leadership today is rooted in authenticity, emotional intelligence, and a willingness to challenge the status quo, whether that’s in the workplace or the classroom.

Why Context Matters In Advertising and Leadership

Throughout the episode, the panel returned to a shared belief: that the future of advertising, and leadership, is personal.

Luisa Izquierdo emphasized the need to encourage women to take risks and aim higher, saying, “We raise the bar for ourselves constantly. It’s painful to see brilliant women still doubting their worth.”

And when discussing the evolution of advertising, personalization and relevance took center stage. But not at the expense of empathy or privacy.

The message? Advertising doesn’t need to follow users around. It can meet them where they are through meaningful, real-time context. That’s where contextual advertising has a role to play: making relevance possible without sacrificing respect.

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Taking Action That Moves the Needle

Our panelists did not just reflect on challenges but also shared the concrete actions that can help change the system.

Samantha Skey spoke about the importance of transparency, explaining how her company reports compensation by gender and race and creates space for open conversations on topics that are often overlooked, like caregiving. “There’s power in visibility,” she said. “We can’t fix what we don’t acknowledge.”

Jackelyn Keller emphasized the value of starting before everything is perfect. “Let’s treat change like a product roadmap. Build the MVP, launch it, learn from it,” she said. “Progress doesn’t need to be perfect - it just needs to keep moving.”

The message across the board was clear: meaningful change doesn’t happen in one sweeping moment. It’s built through everyday decisions, intentional policies, and a willingness to speak up and show up, even (or maybe especially) when it’s uncomfortable.

What Comes After Women's History Month

This conversation offered a forward-looking view of what leadership can and should look like in today’s advertising world. Whether it was calling out outdated systems, rethinking how we support women at every life stage, or encouraging the next generation to lead with confidence, reinforcing that change starts with action, not intention.

At Seedtag, we’re committed to building the kind of workplace and advertising ecosystem where inclusion, authenticity, and context drive every decision. Because real relevance isn’t just about what people are watching or reading but about who they are, what they value, and how they want to be seen.

Want to discover the full conversation? Tune in to this special episode of The Pub Way Podcast and explore how women in advertising and media are leading change from the inside out.

The SXSW 2025 Conference and Festivals once again turned Austin, Texas into a dynamic hub of technology, creativity, and cultural convergence. Known for its eclectic mix of interactive media, film premieres, and featured sessions, this year’s event pushed boundaries beyond just what’s new, focusing instead on how tech can meaningfully serve people.
Seedtag brought together leading voices from the industry into the Wild Wild Land of Advertising for an unforgettable experience about connecting, learning, and exploring how contextual advertising can evolve in a world defined by data, privacy, and personalization.

A Seedtag Experience to Remember

In the middle of the buzzing South by Southwest, Seedtag hosted top-tier brand and agency leaders in immersive settings to encourage meaningful conversations, building stronger partnerships, discussing strategic insights, and exploring how our contextual AI Liz is reshaping the advertising ecosystem.

Our SXSW presence reflected Seedtag’s mission to deepen the connection between brands and audiences by helping advertisers and publishers deliver relevant, privacy-compliant, and engaging content at scale.

With an audience of marketers navigating increasingly complex media landscapes, we focused on what matters most: helping our clients understand how Seedtag’s solutions fit into a privacy-first, performance-driven, and attention-led future of advertising.

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Personalization, Privacy, and AI: What Dominated the SXSW Conversation

Amid art installations and experiential activations, the conversations inside SXSW were grounded in practical insights. The event highlighted a growing industry focus on hyper-personalization. But the nuance lies in how that personalization is achieved. The call was clear: marketers want to move beyond static demographic profiles and understand what motivates their audiences in the moment. Contextual advertising answers that by meeting users where they are, based on what they’re engaging with rather than who they are.

Equally important was the topic of scale through AI-driven strategies, which are becoming increasingly essential for sorting and interpreting massive amounts of content and behavioral signals. However, speakers across the conference emphasized the importance of human oversight to ensure accuracy, transparency, and ethical application. This aligns with Seedtag’s approach to contextual AI: blending machine learning with human-like semantic understanding to deliver content suitability and brand safety.

Personalization also came up in discussions about content curation. Attendees explored how empowering users to shape their content environments results in deeper engagement and better advertising outcomes. For advertisers, this means more than programmatic efficiency; it means delivering messaging that feels natural, timely, and aligned with a user’s interests in that exact moment.

SXSW also highlighted the rising pressure on advertisers to shift toward privacy-forward solutions. With traditional identifiers fading and the industry moving beyond cookies, contextual targeting emerged repeatedly as a necessary, scalable alternative. Not only does it enable compliant, data-conscious ad delivery, it also enhances relevance and user experience.

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See You Next: Where to Connect with Seedtag

If you missed us at SXSW 2025, don’t worry. Seedtag will be at POSSIBLE, the Digiday Programmatic Summit, and of course, Cannes. Catch up with us to continue the conversation on how contextual advertising is helping brands adapt, evolve, and thrive in the ever-changing digital ecosystem.

A Context-First Vision for the Road Ahead

At Seedtag, we believe in solutions that balance innovation with responsibility. That means designing advertising strategies that work for everyone: advertisers, publishers, and consumers.

Want to explore how contextual advertising can reshape your digital strategy? Let’s connect.

Television is undergoing one of the most significant transformations in its history. As viewers shift from traditional cable to streaming services, Connected TV (CTV) has become the new frontier for both brands and publishers.

By 2025, 86.3 million US households are expected to be CTV viewers, surpassing the reach of traditional TV. This shift presents an unparalleled opportunity for advertisers to engage with audiences in more personalized, measurable, and data-driven ways.

However, for CTV to reach its full potential, the industry must overcome challenges related to data fragmentation, standardization, and transparency. The future of CTV is about unlocking efficiencies, optimizing targeting, and fostering collaboration between advertisers and publishers.

CTV 101: What It Is and How It Works

CTV advertising refers to video ads delivered through internet-connected TV devices, such as Smart TVs, streaming sticks (Apple TV, Roku, Fire Stick), gaming consoles, and set-top boxes.

Unlike traditional TV ads, CTV advertising is highly targeted, using demographic, behavioral, and contextual signals to deliver relevant ads to viewers.

CTV ads can be inserted dynamically into streaming content and measured using real-time performance metrics, giving advertisers insights into:

  • Who saw the ad.
  • How they interacted with it.
  • Whether they took an action after viewing.

"Household adoption of Smart TVs is set to exceed 80% in the U.S. within the next five years."

As more consumers shift to ad-supported streaming models, brands and publishers must rethink their ad strategies to capitalize on this expanding ecosystem.

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Why CTV Is Winning Over Advertisers and Publishers

The shift toward CTV advertising is not just a response to changing consumer behavior, it’s a strategic move toward more efficient, measurable, and cost-effective advertising.

For Advertisers: A Smarter Way to Engage Consumers

"Studies show that CTV achieves an attention rate of 82% vs. 69% for linear TV."

This increased engagement makes CTV one of the most powerful digital advertising platforms available today. For brands looking to advertise on CTV, key advantages and additional benefits include:

  • Precision Targeting – Unlike traditional TV, CTV enables granular audience segmentation, reaching consumers based on interests, viewing history, and demographics.
  • Cost Efficiency – With programmatic buying, advertisers optimize their ad spend, reaching the right audience without excessive waste.
  • Measurable Performance – Brands can track impressions, engagement, and conversions, ensuring their ads deliver tangible business results.

For Publishers: Unlocking Revenue Opportunities

With ad-supported streaming models growing, publishers have more ways to monetize premium content. Streaming giants like Netflix, Amazon Prime Video, and Disney+ have introduced ad-supported tiers, while over two-thirds of viewers on Peacock, Paramount+, and Hulu are expected to opt for ad-supported plans next year.

For publishers, CTV presents a way to maximize ad inventory and drive higher CPMs, thanks to:

  • A more engaged audience – Streaming viewers are actively selecting content, leading to higher ad retention rates.
  • Diverse revenue models – Publishers can monetize through pre-roll, mid-roll, and post-roll ads, ensuring a flexible ad strategy.
  • Cross-device opportunities – CTV ads can integrate with mobile and desktop campaigns, providing an omnichannel advertising experience.

“By 2028, CTV is projected to grow at a compound annual growth rate (CAGR) of 13%, reinforcing the importance of this format for publishers looking to future-proof their business models.”

Solving CTV’s Biggest Challenges: Data, Measurement, and Standardization

Despite its advantages, CTV still faces hurdles that advertisers and publishers must navigate to fully unlock its potential.

Data Fragmentation and Standardization

One of the biggest challenges in CTV advertising is the lack of uniform data-sharing practices. Log-level data—which provides granular insights into user behavior—remains fragmented across different platforms.

This fragmentation leads to:

  • Ad repetition issues – Viewers often see the same ad multiple times in succession, creating negative brand sentiment.
  • Limited transparency – Advertisers struggle to track where their ads appear, impacting brand safety and performance measurement.

The industry must work toward standardized data-sharing models that give advertisers and publishers a clearer view of ad performance.

The Role of First-Party Data to advertise on CTV

As third-party cookies continue to decline, first-party data has become the most valuable asset in CTV advertising strategies.

  • Better audience insights – First-party data enables precise targeting without infringing on user privacy.
  • Privacy-compliant solutions – Cookieless advertising ensures compliance with evolving data regulations.
  • Improved ad relevance – Personalized ad experiences lead to higher engagement and conversion rates.

"More than half of the open web and all CTV inventory have already been cookieless for some time."

By harnessing first-party data, brands and publishers can optimize ad placements, reduce waste, and improve targeting accuracy.

Advertise on CTV - ctv advertising

What’s Next for CTV Advertising?

The future of CTV advertising is being driven by emerging technologies and new industry standards that improve efficiency and measurement.

1. Programmatic TV & AI-Driven Targeting

Programmatic CTV advertising allows brands to buy ad inventory in real time, ensuring maximum efficiency and reach. AI-driven targeting enhances personalization and performance optimization.

2. New Ad Formats to advertise on CTV

New ad formats specifically designed for CTV are creating more immersive ad experiences, helping brands connect with audiences in meaningful ways.

3. Cross-Device Advertising for Seamless Engagement

CTV will become a seamless part of omnichannel campaigns, integrating with mobile, desktop, and social advertising strategies to enhance user engagement.

“CTV ad revenue is projected to reach $42.5 billion by 2028."

Why CTV Is the Future of Advertising

CTV is no longer an emerging trend—it is the present and future of television advertising. With higher engagement, precise targeting, and measurable performance, it offers a compelling alternative to traditional TV.

For publishers, it provides new monetization opportunities through ad-supported streaming models, maximizing revenue while maintaining a seamless viewing experience. As CTV viewership continues to grow and regulatory restrictions make other channels less effective, CTV campaigns will become an even more powerful way for advertisers to reach their target audiences and brands that advertise on CTV today will gain a long-term competitive advantage.

The industry’s next step is clear: addressing data-sharing challenges and embracing first-party data to improve measurement, targeting, and campaign effectiveness. The brands and publishers that invest in CTV today will gain a long-term competitive advantage.

At Seedtag, we help brands and publishers unlock the full potential of CTV advertising by providing contextual AI solutions that drive performance, ensure brand safety, and optimize targeting strategies. Our technology empowers advertisers to deliver privacy-first, engaging campaigns that reach the right audience at the right time. As CTV continues to grow, our solutions help advertisers maximize impact by refining placements, improving engagement, and enhancing measurement strategies.

Ready to take your CTV advertising strategy to the next level? Contact Seedtag today to explore how our contextual AI solutions can drive results for your brand.

For years, advertisers have debated whether their budgets should be concentrated within walled gardens or expanded across the open web. As consumer behaviors shift and privacy regulations reshape the advertising landscape, the conversation has become more relevant than ever. The dominance of closed ecosystems, such as Facebook, Instagram, Google, and Amazon, has led many brands to rely heavily on these platforms. However, growing concerns around lack of transparency, limited audience segmentation, and rising costs have pushed advertisers to explore alternatives.

Instead of viewing this as a binary choice, advertisers must recognize the need for a balanced approach—one that leverages the advantages of walled gardens while capitalizing on the transparency, scale, and contextual intelligence offered by the open web.

Where Are Users Spending Their Time?

The way people interact with digital content is changing, and advertisers need to follow the audience. While walled gardens continue to attract logged-in users, research indicates a growing shift toward the open web.

This shift is driven by consumer preference for quality content, greater control over privacy, and dissatisfaction with the experience in closed ecosystems. Users browsing the open web are often more engaged, actively seeking information, news, and entertainment—creating valuable moments for advertisers to connect with them.

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Walled Gardens vs Open Web: What Advertisers Need to Know

Both walled gardens and the open web play a vital role in digital advertising. However, understanding their strengths and weaknesses is key to optimizing campaign performance.

The Appeal and Challenges of Walled Gardens

  • High user engagement: Walled gardens benefit from logged-in users, allowing for better audience segmentation.
  • First-party data access: Brands can leverage structured data for precise targeting.
  • Seamless ad experiences: Advertisers can optimize for in-platform engagement within a controlled environment.

However, these platforms also present significant challenges:

  • Lack of transparency: Advertisers have limited insight into ad performance beyond platform metrics.
  • Higher costs: Competition for ad inventory in closed ecosystems drives up prices.
  • Brand safety risks: As content moderation policies shift, advertisers face uncertainty about where their ads appear.

Advertising on the Open Web: Strengths and Challenges

  • Greater transparency: Advertisers have full visibility into where ads are placed and how they perform.
  • Expansive reach: Consumers spend most of their total online time on the open web, creating more opportunities for engagement.
  • Privacy-first advertising: The open web enables contextual targeting without relying on third-party data.

However, challenges include:

  • Fragmentation: The open web consists of thousands of websites, apps, and connected TV platforms, requiring robust ad strategies.
  • Variable content quality: Ensuring ad placements appear alongside trusted, premium content requires advanced contextual intelligence.

A balanced digital ad strategy should integrate both ecosystems, leveraging the structured targeting of walled gardens while taking advantage of the transparency and reach of the open web.

Brand Safety in Walled Gardens: A Growing Concern for Advertisers

Recent changes in content moderation policies on platforms like Meta have raised brand safety concerns for advertisers. The relaxation of fact-checking programs and shifts in hate speech policies could increase the risk of brand exposure to controversial or harmful content.

Additionally, reliance on a black box model—where advertisers have minimal control over ad placements and audience data—adds to the challenge. The demand for more control over brand safety and ad transparency has led many advertisers to diversify their spending across trusted media outlets on the open web.

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Contextual Advertising: A Key Strategy for the Open Web

With the decline of third-party cookies and increasing concerns over data privacy, contextual advertising has emerged as a powerful solution for targeting audiences effectively—without tracking personal information.

  • No reliance on third-party cookies: Contextual AI analyzes content relevance instead of user behavior.
  • Enhanced user experience: Ads appear in relevant, brand-safe environments, increasing engagement.
  • Higher ad performance: Research shows that contextual ads achieve a 70% view rate, compared to 64% for cookie-based ads.

Brands that invest in contextual intelligence gain a privacy-compliant alternative that ensures effective targeting and brand suitability across the open web.

Why Advertisers Need an Omnichannel Strategy

Rather than viewing walled gardens vs open web as opposing forces, advertisers should adopt an omnichannel approach that leverages both ecosystems strategically:

  • Use walled gardens for structured audience segmentation and conversion-driven campaigns—where first-party data plays a strong role.
  • Capitalize on the open web for reach, brand safety, and contextual targeting—ensuring engagement in premium, high-quality content environments.
  • Integrate contextual AI solutions to enhance relevance, improve audience targeting, and maintain compliance with privacy regulations.

Where Should Advertisers Invest?

The debate over open web vs walled gardens is no longer about choosing one over the other. A successful digital advertising strategy requires a hybrid approach that balances precision with scale, targeting with transparency, and brand safety with performance.

  • Consumer habits are evolving—users are spending more time on the open web while walled gardens remain important for structured targeting.
  • Brand safety concerns are rising—advertisers need control over where their ads appear.
  • Privacy-first strategies are the future—contextual AI provides a sustainable, high-performing solution.

By combining targeted engagement from walled gardens with contextual intelligence on the open web, brands can future-proof their strategies while maximizing ad performance.

At Seedtag, we empower advertisers with cutting-edge contextual AI solutions that enhance targeting, ensure brand safety, and optimize campaign performance in a privacy-first world. Contact us today to explore how our technology can drive measurable results for your brand.

Each year, March Madness takes center stage as one of the most thrilling and unpredictable tournaments in sports. With bracket-busting upsets, rising college stars, and national title hopes on the line, the NCAA Tournament is more than just basketball—it’s a cultural phenomenon. But, When is March Madness 2025? The 86th annual edition of the tournament will begin on March 18, and will conclude with the championship game on April 7.

For advertisers, March Madness 2025 offers a golden opportunity to connect with engaged audiences through sports betting trends, brand sponsorships, and multi-platform fan interactions. Let’s dive into the top March Madness trends and the strategies brands can use to capitalize on the madness.

  1. March Madness Takes Over: How Fans Are Engaging.
  2. Brackets, Bets, and Big Wins: The Betting Boom.
  3. Rising Stars: The Players Defining March Madness 2025.
  4. Sponsorships That Score: How Brands Are Winning Big.
  5. Beyond the Court: March Madness as a Cultural Event.
  6. How Advertisers Can Maximize March Madness 2025.
  7. The Playbook for March Madness Success.

March Madness Takes Over: How Fans Are Engaging

College Basketball’s Biggest Stage Dominates the Conversation

"With 97% of sports-related discussions centered on March Madness, the tournament generates non-stop buzz across multiple media channels. Whether analyzing top seeds, predicting upsets, or debating NCAA tournament odds, fans are deeply invested in every game."

Key Insights:

  • March Madness ranks as the most discussed sporting event, surpassing even the World Series and Bowl Season in cross-sport engagement.
  • North Carolina, Notre Dame, and Iowa State are among the most talked-about programs, presenting regional engagement opportunities.
  • Bracketology and sports betting discussions are skyrocketing, making March Madness a must-watch for advertisers looking to tap into fan excitement.

Why This Matters for Brands:
Companies that integrate their campaigns into the most engaging conversations around March Madness can maximize visibility and audience connection.

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Brackets, Bets, and Big Wins: The Betting Boom

Bracket-building and sports betting have become March Madness staples. Fans are not only tuning in to watch but also placing wagers on point spreads, tournament game outcomes, and Cinderella story upsets.

Key Insights:

  • Bracket predictions and NCAA tournament odds dominate engagement, with analysts like Joe Lunardi and Ken Pomeroy leading the discussion.
  • Platforms like CBS Sports, ESPN, and DraftKings are at the forefront of sports betting and NCAA tournament odds coverage.
  • The legalization of sports betting across more states has increased participation, with fans placing bets on everything from 16 seed upsets to national championships.

Why This Matters for Brands:
Companies in sports betting, analytics, and gaming can benefit from contextual advertising strategies that align with real-time betting trends and fan predictions.

Rising Stars: The Players Defining March Madness 2025

March Madness always produces breakout stars. Some will lead their teams to national titles, while others will cement their legacies with unforgettable performances. Tracking player momentum can help advertisers tap into real-time fan engagement.

Key Insights:

  • Cooper Flagg (Duke) is the most mentioned player, with over 1,100 articles discussing his performance.
  • Johni Broome (Auburn) leads in total visits per article, indicating high levels of fan engagement.
  • Paige Bueckers (UConn) and JuJu Watkins (USC) are among the most-discussed women’s players, reflecting the growing media spotlight on women’s college basketball.

Why This Matters for Brands:
Advertisers can increase engagement by aligning with high-profile players, leveraging real-time highlights, and integrating contextual AI-driven ad placements during peak game moments.

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Sponsorships That Score: How Brands Are Winning Big

Sponsorships remain one of the most powerful tools for brands looking to gain visibility during March Madness 2025. Leading sponsors are making waves with integrated campaigns, in-game activations, and digital-first advertising strategies.

Key Insights:

  • AT&T leads all sponsorship discussions, appearing in 5,000+ articles.
  • Capital One and Coca-Cola remain dominant sponsors, leveraging TV spots and digital activations.
  • Buffalo Wild Wings and Reese’s are driving strong fan engagement, with Reese’s content receiving 64 visits per article.

Why This Matters for Brands:
Sponsors who integrate their messaging into game-day experiences, bracket challenges, and multi-platform activations will see the most impact.

Beyond the Court: March Madness as a Cultural Event

March Madness is bigger than basketball—it influences fashion, social media, and global sports discussions. Its reach extends far beyond the U.S., making it a key moment for international engagement and cross-industry collaborations.

Key Insights:

  • International interest in March Madness is growing, particularly in Europe, Canada, and Australia.
  • Basketball legends like Michael Jordan, Kobe Bryant, and LeBron James continue to shape NCAA tournament conversations.
  • Social media engagement surges during the tournament, creating multi-screen advertising opportunities.

Why This Matters for Brands:
Companies that blend sports, culture, and digital trends into their March Madness marketing will connect with a broader, more engaged audience.

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How Advertisers Can Maximize March Madness 2025

Key takeaways of March Madness Trends

Align with Bracketology & Betting Trends

  • Place ads around bracket predictions, betting insights, and NCAA tournament odds.
  • Partner with platforms like ESPN and CBS Sports to reach the most engaged audiences.

Tap Into Rising Stars & Team Storylines

  • Focus on top-ranked seeds, standout players, and dramatic matchups.
  • Use real-time highlights and AI-driven ad placements to stay relevant.

Capitalize on Women’s College Basketball Momentum

  • Feature high-performing female athletes in campaigns.
  • Support gender equity initiatives with strategic sponsorships.

Invest in High-Impact Sponsorships

  • Leverage AT&T, Coca-Cola, and Capital One’s sponsorship visibility.
  • Create March Madness-themed activations and promotions.

Expand Across International & Multi-Platform Audiences

  • Adapt messaging for global audiences engaging with March Madness.
  • Use CTV, mobile, and social media integration to maximize reach.

The Playbook for March Madness Success

March Madness is unpredictable, thrilling, and a dream opportunity for advertisers. As the tournament unfolds, seeds will fall, legends will rise, and millions of fans will stay glued to their screens.

Brands that align with bracket fever, top player narratives, betting trends, and cross-platform engagement will dominate the conversation and drive real impact.

Learn how Seedtag’s contextual AI solutions are ready to craft data-driven, contextual campaigns that capitalize on the excitement and unpredictability of March Madness.

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