Brand safety has always been one of the most persistent challenges for publishers. The issue has never been the concept itself. The real problem is that many tools shaping brand safety in advertising were not created with the publisher perspective in mind. When outdated blocklists, blunt keyword filters and legacy workflows decide what is safe, publishers lose access to revenue they should have earned. These systems cannot interpret nuance which is why so much valuable inventory is mislabeled and excluded from campaigns.

In this episode of The Pub Way Podcast Mike and I sat down with Heather Carver, Chief Customer Officer at tvScientific, formerly Chief Revenue Officer at Freestar, to talk about how AI and modern curation are transforming the way publishers protect and monetize their content. I speak with publishers every day and hear the same pattern. High quality content is being misread by tools that were never designed to understand context. Our conversation with Heather helped clarify why this happens and where real progress is finally taking place.

1. Reframing Brand Safety for a New Era
2. Why This Shift Matters for Publishers
3. Curation With Intention
4. Preparing for the Shifts in Search and AI Discovery
5. How Freestar Uses AI to Support Publisher Growth
6. What Publishers Should Expect From Curation Partners
7. Looking Ahead
8. Listen to the Full Episode

Reframing Brand Safety for a New Era

Heather has worked across multiple sides of the industry for more than fifteen years. She began on the publisher side, moved into the SSP world and later joined a major tech platform. That range gives her a rare understanding of how brand safety in advertising has evolved and where the blind spots remain.

One of the biggest issues she raised is how deeply legacy tools are embedded within agency workflows. Keyword blocklists once felt like the safest and simplest option, but today they often create more harm than protection. A single word can trigger a block even when the surrounding context is positive or neutral. Articles about sports get flagged because the word shoot appears. Entire news sections are treated as unsafe even when they are accurate and balanced.

This is particularly damaging for publishers because quality journalism still drives audience trust. It also supports the wider digital ecosystem. AI models, search engines and recommendation systems all rely on credible content. When brand safety tools over block the open web, they reduce the quality of the very signals powering modern information systems.

This is where AI creates opportunity. Modern suitability models can interpret tone, sentiment and meaning rather than relying on isolated terms. AI allows brand safety in advertising for publishers to be far more precise. Nuanced content is recognized for what it actually communicates. High quality reporting is not penalized simply for covering real events. Publishers gain access to demand that should have always been available to them.

Why This Shift Matters for Publishers

The shift from blocking to suitability is not only a technological improvement. It is a reset in how we understand publisher value. When legacy tools miscategorize content they erase context that is essential for advertisers. They also create a distorted picture of what publishers actually produce.

Heather emphasized that publishers should be part of the conversation. They have a unique understanding of their editorial standards, their audience and the true nature of their content. When these nuances are lost, publishers are pushed into a defensive posture even when their environments are completely suitable.

Suitability frameworks give publishers a way to demonstrate that their content is relevant, trustworthy and aligned with advertiser goals. They also create pathways to recover monetization that legacy systems have blocked.

Curation With Intention

Curation has existed in ssp advertising for years, but Heather explained that the latest evolution of curation is far more valuable for publishers. Older curation models grouped thousands of sites into broad categories and rarely adapted. They did not showcase what made each publisher unique and they did not help buyers understand the context behind impressions.

Modern curation is dynamic and intelligent. AI evaluates context, tone and performance signals in real time. Packages reflect quality rather than volume. Buyers can see how curated segments are built and which publishers contribute to them. This transparency makes it easier for advertisers to invest with confidence.

For publishers this matters because intentional curation helps correct misclassification. It brings premium inventory back into circulation and connects it with campaigns where it naturally performs well. It also gives publishers without large direct sales teams a meaningful way to reach premium budgets.

This shift in curation also highlights how much innovation is happening on the sell side. SSPs are no longer simply pipes for demand, they are becoming intelligence layers that help publishers surface the true value of their inventory. If you want to understand how this evolution is shaping monetization and ad quality, we covered it in more detail in an earlier episode about how supply side platforms are driving smarter ad experiences.

These changes in suitability and curation run parallel to shifts on the buy side. DSPs continue to refine how they evaluate context, quality signals and performance across formats like CTV, which ultimately shapes how publisher inventory is valued. For publishers who want a deeper look at what this means in practice, we explored it in a recent episode focused on how demand side platforms are reshaping CTV strategies.

Learn more about Brand Safety in Advertising

1. How Publishers Can Future-Proof Brand Safety and Revenue with the Right Advertising Supply Side Platform
2. How Publishers Can Use AI to Monetize Content and Audience Attention - AI for Publishers
3. Digital Marketing Musts for Publishers: Locking in Monetization with Brand Safety

Preparing for the Shifts in Search and AI Discovery

Our conversation then moved to search traffic and the rise of AI generated results. Publishers are already seeing changes as users engage with zero click answers and LLM summaries. Heather’s view is that publishers cannot rely on a single traffic source. Instead they need to build editorial brands that readers return to directly.

That means investing in quality content, improving user experience and strengthening newsletters and owned channels. While these strategies take longer, they create dependable traffic patterns and reduce exposure to algorithmic shifts.

We also discussed upcoming models around AI scraping. Large publishers have begun negotiating deals with AI companies, but the mid and long tail need collective solutions. Ideas like pay per crawl or pay per query may emerge as sustainable models. What remains clear is that AI systems depend on publisher content. Publishers deserve to be compensated for the value they provide.

How Freestar Uses AI to Support Publisher Growth

Heather shared how Freestar uses AI inside their own stack. Their dynamic ad system processes billions of impressions and adjusts floors, timeouts and wrapper behavior automatically. The goal is to maximize monetization while protecting user experience.

Freestar also relies on AI agents across their teams to automate research, data ingestion and internal workflows. This allows teams to focus on strategic guidance rather than manual operations. For publishers without large technical resources these efficiencies create a real competitive advantage.

What Publishers Should Expect From Curation Partners

Before closing the episode I asked Heather what publishers should look for when evaluating partners. She highlighted transparency, performance and flexibility. Partners should explain how segments are curated, who is buying them and what results they drive. They should reflect the strengths of the publisher rather than grouping sites into generic categories. They should use real technology that enhances outcomes rather than relabeling existing inventory.

Looking Ahead: Brand safety in advertising

If there is one message to take from this conversation it is that publishers finally have a pathway forward. With better suitability models, more advanced curation and meaningful AI applications, the industry can move away from outdated systems and toward a model that truly recognizes and rewards quality content. Brand safety in advertising can become a tool that supports publishers, not a barrier that undermines them.

Listen to the Full Episode

For a deeper look at suitability models, curation frameworks, AI adoption and the future of monetization for publishers listen to the full conversation with Heather Carver on The Pub Way Podcast.

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As the digital marketing industry moves beyond the volatility of recent years, one thing is clear: the marketing trends of 2025 set the stage for a much deeper transformation ahead. By 2026, brands and marketers will no longer be optimizing around isolated signals, legacy identifiers, or fragmented channels. Instead, the next era of advertising will be defined by intelligence, adaptability, and a more human understanding of audiences.

Economic pressure, regulatory change, and rapid advances in AI are forcing marketers to rethink how they plan, execute, and measure campaigns. These shifts are not incremental. They signal a fundamental change in how value is created across digital marketing, content marketing, and media activation.

Below, we explore the most important marketing trends shaping 2026 and what they mean for brands planning long-term growth.

Key Takeaways: Marketing Trends

1. Marketing in 2026 moves beyond identity, as declining addressable signals push brands toward privacy-first, contextual, and emotion-driven approaches.
2. Contextual advertising evolves into emotional understanding, enabling marketers to align messages with interest, emotion, and intent rather than demographics.
3. CTV precision comes from content, not households, making contextual targeting essential for reducing waste and improving performance in streaming environments.
4. Agentic AI reshapes how marketing decisions are made, shifting AI from execution support to strategic collaboration across creative, media, and measurement.
5. Regulation accelerates better advertising, rewarding explainable, transparent, and privacy-first models rather than limiting innovation.
6. The future of marketing is more human, combining AI-powered intelligence with a neuro-contextual approach to deliver relevance, efficiency, and long-term growth.
   

From the Marketing Trends of 2025 to a New Advertising Reality

The biggest marketing trends of 2025 were driven by constraints. Marketers faced tightening budgets, growing regulatory complexity, and the accelerating decline of third-party cookies and traditional identity signals. These pressures reshaped priorities across the industry.

Efficiency, automation, and measurable ROI became non-negotiable. At the same time, privacy regulations across Europe and beyond increased the cost and complexity of compliance for adtech platforms, agencies, and brands alike. Consolidation accelerated, as larger players acquired data and technology companies to gain scale, simplify operations, and control more of the marketing stack.

These trends in marketing exposed a deeper issue. Many of the systems advertisers relied on were no longer fit for purpose. Reach and impressions alone could not justify investment. What mattered was outcome, relevance, and the ability to adapt quickly in an increasingly complex ecosystem.

By 2026, those pressures will converge into a clear demand for smarter, more resilient marketing strategies.

The Biggest Marketing Trend: The Collapse of Traditional Addressability

One of the most significant advertising trends heading into 2026 is the erosion of addressable signals. Third-party cookies, household IDs, and IP-based targeting are no longer able to deliver reliable scale or accuracy, especially across premium environments like streaming and connected TV.

This shift is not just regulatory. It is structural. Signals designed to approximate people through devices or households were always inaccurate. As restrictions increase and signal quality declines, marketers are being forced to confront a new reality. Identity-based targeting cannot sustain the next phase of digital marketing.

As a result, brands are moving toward privacy-first alternatives that do not rely on personal data. First-party data, contextual signals, and consent-driven systems are becoming central to modern marketing strategy. Ownership and control of data infrastructure are now strategic advantages, not technical considerations.

For marketers planning for 2026, the question is no longer how to preserve legacy identifiers, but how to replace them with approaches that are durable, compliant, and effective in the long term.

Contextual Advertising Evolves Into Emotional Understanding

Among current marketing trends, contextual advertising is undergoing one of the most important transformations. Once viewed as a category-based or keyword-driven tactic, contextual targeting is evolving into a far more sophisticated approach, one that understands interest, emotion, and intent. It’s what we call here at Seedtag as the neuro-contextual approach.

Advances in AI now allow platforms to analyze content holistically, across text, visuals, video, and audio. By 2026, this capability will expand further, enabling marketers to decode how people feel as they engage with content, not just what they consume.

This emotional layer changes how audiences are understood. Instead of relying on demographic or behavioral proxies, brands can align their messaging with moments of curiosity, excitement, aspiration, or readiness to act. In this model, relevance is driven by context and emotion, not identity.

This evolution positions contextual advertising as both a privacy-first solution and a performance driver. Matching creative to the mood, genre, and narrative of content has been shown to lift attention, recall, and brand favorability. This makes it one of the most powerful digital marketing trends heading into 2026.

Learn More

1. How Neuromarketing Is Redefining Ad Relevance Today
2. What’s Powering Travel Marketing in 2026
3. AI Agent Platforms and the Future of Agentic Commerce: Insights for Marketers
   
   

CTV and Video Content: From Household Targeting to True Precision

Video content remains central to top marketing strategies, but one of the most misunderstood advertising trends is the role of connected TV. Despite growing investment, CTV is still often treated as a person-level medium, when in reality most signals are aggregated at the household level.

This creates inefficiency. In a single home, viewers may have entirely different preferences, viewing habits, and interests. Targeting the household alone risks delivering impressions to the wrong viewer at the right time.

Contextual intelligence changes that equation. By targeting the content itself, rather than the household, marketers can reach viewers based on what they are watching in the moment. Sports fans, reality TV viewers, news audiences, and children’s programming viewers can each be addressed with relevance and precision.

As ad-supported streaming tiers expand, more households become accessible to advertisers. At the same time, years of investment in programmatic infrastructure are making CTV more transparent, more addressable, and more comparable to other digital channels.

In this environment, contextual CTV emerges as one of the most effective ways to extend reach, reduce waste, and improve performance across video advertising.

How Agentic AI Will Influence Marketing Trends in 2026

Perhaps the most transformative adtech trend for 2026 is the rise of agentic AI. While AI-powered tools have already improved optimization and efficiency, the next phase goes much further. AI agents will move from assisting marketers to actively executing and orchestrating strategy.

Instead of manually managing workflows, marketers will collaborate with intelligent agents capable of analyzing massive data sets, building audience frameworks, optimizing media in real time, and recommending next steps proactively. These agents will operate across creative generation, campaign execution, and measurement, reducing complexity while increasing speed and precision.

This shift fundamentally changes how marketing teams work. Strategy becomes conversational. Optimization becomes predictive. Decision-making moves from reactive to anticipatory.

In this new model, human creativity and machine intelligence work together. Marketers focus on vision, storytelling, and brand direction, while AI agents handle scale, adaptation, and execution. By 2026, this collaboration will define how high-quality digital marketing operates across channels.

Regulation as a Catalyst for Better Marketing

Regulation continues to shape digital marketing industry trends, but its role is evolving. Policies such as the EU AI Act, the Digital Markets Act, and the Digital Services Act are raising standards around transparency, explainability, and accountability, particularly for generative AI and automated systems.

While some adtech models struggle under these requirements, platforms built on explainable AI and privacy-first principles are better positioned to adapt. Mandatory labeling of AI-generated content, documentation of models, and clearer data practices will push the industry toward higher quality and greater trust.

For brands, this shift reinforces the importance of choosing partners that can operate responsibly at scale. In 2026, regulatory resilience becomes a competitive advantage, not just a compliance exercise.

Major Moments and Smarter Media Planning in 2026

Global events such as the FIFA World Cup, major elections, and large-scale sporting competitions will continue to drive spikes in attention. However, one of the emerging marketing trends is how brands activate around these moments.

Rather than competing solely for expensive sponsorships, marketers can use AI-powered neuro-contextual insights to identify adjacent content that attracts similarly engaged audiences. This approach allows brands to capture attention in relevant environments at a fraction of the cost, extending impact beyond the event itself.

For 2026 brands planning long-term strategies, this represents a smarter way to balance scale, efficiency, and relevance across media investments.

Looking Ahead: The Most Human Era of Marketing

The defining marketing trends of 2026 point toward a more intelligent, more adaptive, and more human advertising ecosystem. As traditional identifiers fade and complexity increases, success will depend on understanding people through context, interest, emotion, and intent, rather than outdated demographics.

Agentic AI, privacy-first design, and neuro-contextual intelligence are not separate trends. Together, they form the foundation of a new marketing strategy built for resilience and growth. Brands that embrace these shifts will be better equipped to create meaningful connections, deliver measurable outcomes, and navigate the digital marketing landscape for years to come.

2026 marks the beginning of advertising’s most transformative era: one where understanding feelings becomes the key to understanding audiences.

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Digital advertising is entering a period of transformation. After years of optimizing for automation, reach, and performance metrics, the industry faces a challenging limitation. Efficient delivery does not guarantee meaningful engagement, and the signals that once guided traditional marketing and targeting are fading because of changes in consumer behavior and privacy regulations.

Our new neuroscience research, conducted with Prof. Moran Cerf of Columbia University, shows that the way people respond to advertising is shaped by the emotional and cognitive state activated by the content they consume in the moment. The results demonstrate that when an ad appears in an environment that aligns with a person’s interest, emotional tone, and intent, the brain produces stronger attention, emotional response, and neural activity.

Neuromarketing, also known as consumer neuroscience, offers a deeper understanding of these reactions. As a discipline, it uses neuromarketing techniques such as eye tracking, heart rate monitoring, pupil dilation, facial coding, brain scans, functional magnetic resonance imaging, and electroencephalogram (EEG) to measure brain activity to observe emotional reaction and attention. These methods reveal signals that traditional market research or focus groups cannot capture because they measure reactions that occur before conscious awareness.

Even with this strength, traditional neuromarketing usually examines the ad in isolation. It asks how a person responds to a specific creative asset. What it does not fully examine is the environment that shapes the emotional and cognitive state a person brings into the moment. People switch between devices, topics, and formats throughout the day. Their intentions, motivations, and emotions shift as they engage with different types of content. The moment before the ad appears plays a major role in determining how the brain receives it.

Using EEG brainwave technology, our neuroscience study measured how people responded to ads placed within different types of content environments. Participants viewed non-contextual ads, standard IAB contextual ads, and Neuro-Contextual ads while neural responses were recorded.

Our research found that Neuro-Contextual Advertising generates significantly stronger neural responses when it aligns with the interest, emotion, and intent expressed in the surrounding content. This insight reflects a core principle of neuromarketing and supports the neuromarketing definition that emphasizes how emotional engagement and attention shape consumer decisions.

Neuro-Contextual Advertising builds on this foundation. Neuromarketing explains how the brain reacts, while Neuro-Contextual Advertising identifies where those reactions can be amplified. It connects neuroscience with the role of AI to interpret the meaning of the content people choose to engage with. This includes the emotional tone, cognitive load, and motivational state reflected in that content. These insights support media planning decisions that reveal how people naturally think and feel.

1. A New Perspective on Neuromarketing
2. How Neuro-Contextual Advertising Works
3. Deep dive into the Research
4. What Brands Can Learn From the Study
   
   

Neuromarketing Highlights

• Advertising becomes more effective when it aligns with the interest, emotional tone, and intent expressed in the surrounding content.
• Neuro-Contextual Ads produce significantly stronger neural engagement, reaching up to 3.5x higher than non-contextual ads.
• Neuro-contextual ads offer 26% stronger emotional response than standard contextual ads.
• Mobile environments intensify attention and emotional resonance, which makes neuro-contextual alignment even more impactful on mobile devices.
• The strongest predictors of relevance come from Neuro-Contextual signals rather than identity-based data, supporting a more human and privacy-safe approach to advertising.

A New Perspective on Neuromarketing

Neuromarketing helps advertisers understand how people react to ads by measuring emotional response, attention, and cognitive load. The emotional state and motivation of the user are shaped by the content they choose to watch or read. These factors influence how open the brain is to the advertising that follows.

When an ad appears in an environment that matches their mindset, the brain responds more positively, processing becomes easier, emotional response increases, attention increases, and the ad feels more natural and less disruptive. This broadens the role of neuromarketing. Instead of evaluating only the creative, it now includes the context that surrounds it.

This shift also reflects the rise of AI in media planning. To capture real consumer behavior, neuromarketing must consider both the ad and the environment framing it. Neuro-Contextual Advertising brings these two elements together and creates a more human understanding of relevance.

How Neuro-Contextual Advertising Works

Neuro-Contextual Advertising aligns ads with the interest, emotion, and intent expressed by the surrounding content of an article or video. It reflects how the brain processes content in real time. This approach goes beyond traditional contextual advertising, which matches ads to topics or keywords. Instead, Neuro-Contextual Advertising takes into account emotional tone and intentions, which influence how open the brain is to receiving information.

People bring an emotional and motivational state into every moment of digital consumption. Some content evokes curiosity. Some build trust. Some sparks excitement. Some demand deeper cognitive effort. These states influence how receptive the brain is to new messages.

Our research shows that when ads align with these cues, the brain processes the message with less effort. Relevance becomes a function of the moment itself. AI supports this alignment by interpreting signals found directly in the content instead of relying on identity-based data. This protects privacy while supporting a more human understanding of attention and emotion. This is where the broader AI revolution is reshaping the planning phase for advertising.

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Learn more about Neuro-Contextual

1. How is Neuroscience Transforming the Digital Advertising Landscape
2. Neuro-Contextual Advertising: Winning Audiences Through Interests, Emotions and Intentions
   
3. Neuro-Contextual Advertising: From Industry Innovation to eMarketer’s Number One Trend
   
   

Deep dive into the Research

Three core signals were measured by using EEG brainwave technology: attention, emotional resonance, and neural engagement. Together, these indicators reveal how receptive and emotionally open people become when viewing different types of advertising.

Participants viewed non-contextual ads, standard IAB contextual ads, and neuro-contextual ads while their neural responses were analyzed. The results were clear:

Neuro-Contextual placements generated up to 3.5x higher neural engagement compared with non-contextual ads. This is meaningful because Cross-Brain Correlation is closely associated with memory formation and collective emotional processing.

The study also found a 26% stronger emotional response than standard contextual ads. This was shown through brain left side frontal activity linked to approach motivation. Signals related to trust, excitement, and approval appeared more strongly when the ad aligned with the emotional tone of the content.

Mobile environments amplified these effects. The research revealed that mobile consumption intensified both attention and emotional resonance, likely because mobile is a more personal and immersive setting. Across all indicators, the brain favored the moment that felt most coherent.

What Brands Can Learn From the Study

To build relevance, brands should consider how emotional tone, intention, and cognitive processing influence the moment in which an ad appears. When planning reflects these human signals, advertising becomes more intuitive and easier for the brain to receive.

AI systems that interpret interest, emotion, and intent without using personal data become valuable tools in this process. They help brands align with the mindset of the moment instead of the identity of the user. This reflects the brain’s natural processing style and supports a more privacy-safe understanding of relevance.

Liz, our proprietary neuro-contextual AI, interprets deeper signals of interest, emotion, and intent within content. This supports a more intuitive, privacy-first, and human-centered approach and reflects the promise of Artificial Intelligence Advertising for more human understanding.

If you want to explore the complete findings, including the full methodology and EEG framework, download the full research report here:

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The travel industry is entering 2026 with a surge of renewed demand and a rapidly evolving set of traveller expectations. Across the UK, people are planning earlier, researching more deeply, and making decisions based on emotional context as much as practical needs. In this scenario, brands cannot rely on old patterns. They must understand what captures attention in the moments that matter.

Our Travel Insights Report for H1 2026 presents a clear view of how UK audiences behave across the open web during the first half of the year. This period is crucial because H1 is when most travellers begin thinking about where to go, how much to spend, and what experiences matter most.

The analysis outlines the motivations, seasonal dynamics, and neuro-contextual signals shaping travel behaviour, and these insights reveal what effective travel marketing must look like in 2026.

Keep reading to explore the most important travel trends for H1 2026, based solely on our report findings, and understand how advertisers, travel brands, tour operators, and travel businesses can transform these insights into stronger, more relevant travel advertising strategies.

1. A Critical Shift: Travel Planning Starts Early in H1 2026.
2. The Most Important Travel Trends for H1 2026.
3. Where Neuro-Contextual Advertising Strengthens H1 Strategy.
4. A Travel Marketing Future Built on Context and Timing.
   
   

Blog Post Highlights

1. Understanding the marketing funnel reveals clear brand opportunities. Traveller behaviour in H1 maps directly to the full funnel, from inspiration to booking. Recognising these shifts helps brands build awareness early, support mid-journey decision making, and drive bookings when intent peaks.
2. Travellers begin planning early in H1. In January and February, audiences start researching and budgeting for summer holidays, festivals, concerts, and key seasonal events, well before the season arrives. This early surge in inspiration and planning makes early-season awareness crucial for brands looking to influence decisions long before bookings peak.
3. Local travel demand is shaped by convenience, culture, and food, with travellers seeking short breaks, mobility updates, and authentic regional experiences.
4. International motivations shift from value to experiences. In Q1, travellers focus on saving money. By Q2, they turn their attention to the activities they plan to enjoy on arrival, from festivals to cultural experiences, driving a clear shift towards experience-led decision making.
5. Cultural moments spark real travel movement throughout H1. Events such as Easter, St Patrick’s Day, and VE Day do more than influence mood. They create clear spikes in travel interest and mobility, with people actively planning trips, celebrations, and long-weekend getaways around these moments. These cultural pulses offer high-value opportunities for brands to reach audiences who are primed to travel.
   
   

A Critical Shift: Travel Planning Starts Early in H1 2026

Our report shows that travellers begin researching and planning long before peak holiday seasons. In early Q1, behaviours such as budget checking, inspiration gathering, and destination comparisons are already visible across the open web.

Travellers in H1 2026 are:

• Monitoring travel news, airport updates, and weather alerts,
• Exploring seasonal activities, including concerts, festivals, and sporting events,
• Gravitating towards either low-cost options or premium experiences,
• Planning around significant holidays such as Easter, St Patrick's Day, and VE Day.

This behaviour highlights an important shift. Travellers begin shaping their decisions much earlier in H1, which means brands should plan for earlier campaign activation that aligns with the topics people are already exploring. By connecting creative and messaging to the seasonal moments, events, and motivations shaping early research, brands can build awareness sooner and guide consideration more effectively throughout H1.

The Most Important Travel Trends for H1 2026

Below, we highlight the five biggest travel trends emerging from our analysis. These insights uncover how travellers think and act, and where the best opportunities lie for data-driven travel marketing.

1. Early Planning in H1 is Intent Led, Not Impulsive

Travellers begin preparing for summer as early as January. They start building lists, comparing destinations, and checking budget-friendly options. In Q1, the data shows that saving money is the top motivation and represents 44.8% of analysed visits.

H1 is a season of preparation. Travellers are aspirational, but also cautious, looking for practical guidance that supports better decision-making.

Why this matters for travel marketing

Brands should activate awareness early in H1 and appear in the contexts where planning takes place. These moments include deal content, seasonal previews, weather insights, and early inspiration pieces. By showing up early, brands increase the likelihood of becoming part of the traveller's long-term consideration set.

2. Local Travel is Motivated by Convenience, Culture, and Food

Domestic travel plays a major role throughout H1. UK audiences are influenced by:

• Rail and subway updates, especially changes, closures, or disruptions.
• Weekend city break content, often driven by geographic proximity.
• Culinary experiences, which remain a major pull factor.
• Strong interest in arts and cultural hubs across regions.

What this means for travel businesses

Campaigns should focus on short-form itineraries, cultural discovery, mobility ease, and food-led experiences. Local travel is rarely driven by price alone. It is shaped by what enhances time, enjoyment, and convenience.

Learn More about UK Insights

1. Consumer Trends: What’s Driving Shopping Fever This Season
2. Consumer Trends in the Automotive Industry: What’s Driving Change
3. Revving Up Growth: Deep Audience Insights for Automotive Advertising Success

3. International Travel in H1 Splits into Two Distinct Motivations

Across outbound destinations, the report identifies four consistent drivers:

• Saving money, the strongest motivator across all countries analysed.
• Airport transfer convenience, a major mobility pain point.
• Luxury experiences, visible in select destinations.
• Sun and beach holidays, the most consistently preferred type.

Destinations shift across H1:

January to March

• Spain leads with affordable sun and beach options
• France attracts interest due to transport links and cruise demand
• Italy captures travellers seeking food, drink, and higher-end experiences

April to June

• France rises to the top with beaches, food, and cultural appeal
• Spain remains strong for budget-conscious travellers
• Ireland appeals to cultural explorers

Why this matters for your travel marketing strategy

Messaging must shift as the season progresses. Q1 requires value-led creative that supports budgeting and planning. Q2 requires experience-led storytelling focusing on culture, exploration, and outdoor activities.

H1 is not a uniform season. The audience mindset evolves quickly, and brands should adapt in real time.

4. Cultural and Emotional Moments Drive High Engagement

Our report also highlights several cultural pulses that shape attention in H1 2026:

• Easter
• St Patrick’s Day
• VE Day
• Chinese New Year
• Valentine’s Day

Not all moments carry equal impact. For example, St Patrick’s Day generates a 56% engagement rate and significantly outperforms Valentine’s Day because it reflects a stronger cultural connection.

Why this matters

Travel brands should align advertising with emotionally relevant cultural events. Contextually placed creative around these moments can strengthen brand association, improve attention, and help guide traveller decisions during H1.

5. Travellers Want Supportive Guidance, Not Disruptive Ads

Throughout H1, travellers consistently search for practical help such as:

• Travel advice
• Mobility guidance
• Curated cultural experiences
• Culinary tips
• Insight into the best seasonal activities
• Clear explanations of routes, logistics, and timing

What this means for travel advertising

Ads should provide clarity, value, and relevance. Creatives that support decision making outperform ads that interrupt or distract. This includes interactive formats, explorable visuals, and value-led storytelling that helps travellers make confident choices.

Where Neuro-Contextual Advertising Strengthens H1 Strategy

Liz, our proprietary neuro-contextual AI, plays a central role in helping brands connect with travellers throughout H1. Built to mirror the nuance of human thought, she interprets deeper signals of interest, emotion, and intent in real time. This allows brands to understand not only what people are reading, but why they are engaging with that content at that particular moment.

These capabilities ensure that travel campaigns reach audiences when they are most receptive and support them as they move from early inspiration to active research and, ultimately, booking. Liz brings together human-like understanding and real-time neuro-contextual insight, giving brands a measurable advantage throughout the H1 travel journey.

A Travel Marketing Future Built on Context and Timing

H1 2026 is a period defined by early planning, cultural influence, and shifting motivations. Brands that succeed will be those that: show up early, understand seasonal behaviour changes, align with emotional and cultural moments, use data-driven insights to shape communication, and activate creative that provides genuine value.

To explore all insights in depth, download the full H1 2026 Travel Insights Report and plan smarter for the year ahead.

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Connected TV advertising now plays a central role in modern media planning, offering scale, premium content environments and measurable impact. As investment grows, the question advertisers need to answer with precision is: How do you measure the performance of connected TV advertising campaigns?

Unlike linear television, CTV delivers a broader and richer set of signals. But extracting value from those signals requires a structured measurement framework and consistent methodologies. The following approach reflects industry-standard practices applied by leading media owners, platforms and measurement providers across the CTV ecosystem.

Key Highlights: Connected TV advertising  

1. CTV needs a structured, consistent measurement framework to understand performance, optimize campaigns, and detect invalid activity.
2. Key CTV KPIs include reach, impressions, viewability, completion rate, conversions, CPCV, VTR, and incrementality to assess goal alignment.
3. Technology unifies fragmented signals, enriches metadata, detects suspicious activity, and links exposure to cross-device behavior for more accurate CTV measurement.

Understanding the Importance of Measuring CTV

A strong measurement foundation is essential for understanding how CTV campaigns perform and for generating insights that drive ongoing optimization.

Unlike traditional TV, where viewers can easily change channels during ad breaks, CTV environments typically reduce skipping and create more immersive ad experiences, often resulting in higher view-through rates.

Marketers plan their CTV initiatives around specific objectives. Clear definitions of measurement and ad exposure allow them to evaluate whether those objectives are being met. Accurate measurement helps determine if the investment is reaching the right audiences, quantifies the value of CTV as a format, and enables ROI analysis through metrics such as conversions and onsite engagement. It also plays a key role in identifying invalid activity and ensuring budgets reach real viewers.

CTV measurement involves tracking exposure across platforms, analyzing delivery accuracy, and assessing performance indicators at scale. It reveals incremental impact, highlights optimization opportunities, and ensures advertisers can benchmark results against campaign goals.

How CTV measurement differs from linear TV

Linear TV relies on panel-based estimates and broad demographic projections. By contrast, connected TV advertising provides:

• Impression-level data.
• Household-level reach and frequency.
• Precise completion and engagement indicators.
• Stronger attribution models linking exposure to digital outcomes.

This contrast is central to understanding the value of CTV measurement. It moves evaluation from estimated exposure to verifiable, behavior-based insight.

Key metrics to watch

To evaluate CTV campaign performance, advertisers typically rely on a set of core KPIs:
Reach: The number of unique viewers who were exposed to the ad.

• Impressions: The total count of times the ad was served on a screen.
• Viewability: The share of impressions that met standard viewability criteria. Given that CTV ads usually display full-screen, viewability tends to be high.
• Completion Rate: The percentage of viewers who watched the ad all the way through.
• Conversions: Actions taken after exposure, such as purchases or sign-ups.
• Cost per Completed View (CPCV): The average cost paid when a viewer finishes the full ad.
• View-Through Rate (VTR): The percentage of impressions that completed on screen. 100% complete pixels / impression pixels = VTR
  Incrementality: The incremental reach or lift generated by the campaign.

These KPIs help determine whether performance aligns with campaign goals, whether messaging resonates, and where adjustments may be needed.

Learn More about Connected TV advertising  

1. CTV Ads and the New Standard for Smarter Audience Targeting
2. How Streaming Viewers Broke the Old Rules of TV Measurement
3. Closing the CTV Measurement Gap: Data Quality & Performance Talks

How is CTV advertising success measured?

Measuring CTV performance involves evaluating exposure, frequency, unique reach, and post-exposure actions. In addition to the core engagement KPIs, advertisers monitor the broader ripple effects that CTV campaigns create.

CTV activity often influences several downstream metrics, including website visits, time spent on site, bounce rate, lead generation, share of voice, and overall brand awareness. These indicators help demonstrate how CTV contributes to both short-term outcomes and long-term brand impact.

A comprehensive analysis of these KPIs provides visibility into who saw the ads, how frequently they were exposed, and what they did afterward. This allows advertisers to directly connect results to campaign objectives.

One of CTV’s biggest strengths is the ability to deliver video ads to precise audience segments at the most relevant moment. Unlike linear TV’s broad demographic assumptions, CTV supports real-time optimizations and delivers insights that help fine-tune targeting strategies.

How technology supports accurate CTV measurement

Within industry standards, technology plays a critical role by improving data consistency and strengthening attribution models. The most common applications include:

• Unifying signals across disparate apps, devices, and publishers.
• Generating richer content-level metadata, including tone and thematic classification.
• Detecting invalid or suspicious activity to protect media investment.
• Improving the linkage between ad exposure and cross-device behavior.
• Enabling near real-time adjustments based on observed performance.

These capabilities help advertisers address fragmentation and maintain a clear, consistent measurement structure at scale.

Strengthening CTV’s Role in a Measurable Media Future

Measuring the performance of connected TV advertising campaigns requires a disciplined framework that links delivery, engagement, and outcomes. When these components are combined with consistent data practices and reliable attribution, CTV becomes a channel that can be evaluated with clarity and optimized with confidence.

This approach allows advertisers to capture the full connected tv advertising benefits and integrate CTV as a measurable, performance-ready component of their broader marketing strategy.

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Every November, Black Friday advertising takes the stage. A moment of excitement, anticipation, and exclusive, limited-time offers that signal the start of the holiday shopping season. Yet in 2025, it’s no longer just about discounts and doorbusters.

Black Friday has evolved into a full-scale retail experience where entertainment, technology, and emotion intersect. Shoppers aren’t only hunting for deals, they’re engaging with stories, content, and brands that feel relevant to their world.

For advertisers, this transformation has created a new era of retail media, one powered by context, emotion, and precision.

According to Seedtag’s latest insights, Black Friday advertising trends are now driven by the convergence of tech innovation, consumer intention, and neuro-contextual advertising. From streaming and gaming to sports and shopping, audiences are interacting across digital environments that reveal what captures their attention, inspires emotion, and motivates action.

The result? Unprecedented opportunities for brands to connect meaningfully and make every impression count.

1. The Context Behind the Click: What People Really Do on Black Friday
2. Beyond Discounts: Why Emotion and Context Drive Sales
3. How Brands Use Black Friday Ads to Drive Sales
4. The Rise of AI in Black Friday Advertising
5. What Publishers Can Learn from Black Friday Advertising
6. The Shift Toward Intentional Shopping
7. The Emotional Economics of the Holiday Shopping Season
8. Smarter Context, Stronger Impact
   

Black Friday Advertising Trends Takeaways

• Black Friday has evolved from discounts to discovery: It’s no longer just about price, it’s about emotional connection, entertainment, and contextual relevance across the holiday shopping season.
• Technology dominates consumer attention: Over 31% of Black Friday content revolves around technology and computing, with audiences engaging heavily in AI-powered deal trackers, gaming devices, and smart home tech.
• Emotion drives engagement and sales: Successful Black Friday ads go beyond “limited-time offers”. They align with consumer emotions such as excitement, nostalgia, and anticipation to build lasting brand affinity.
• Publishers can win through contextual intelligence: By matching content like reviews, streaming line-ups, or gaming guides with contextually aligned Black Friday ads, publishers can boost CPMs, monetise high-intent traffic, and even earn affiliate commissions.
• Early access defines success: The pre–Black Friday period is now crucial. Consumers research and plan weeks ahead, meaning early storytelling and contextual engagement are key to conversion.
• Black Friday and Cyber Monday form a connected ecosystem: While Black Friday triggers emotional, in-store, and lifestyle-led buying, Cyber Monday amplifies online conversions — both are powered by content-rich, AI-driven experiences.
  
  

The Context Behind the Click: What People Really Do on Black Friday

Black Friday advertising isn’t about offering the biggest discount anymore. It’s about understanding what people are doing, watching, and feeling when they shop. Our analysis of 8,655 articles and over 1.6 million total visits shows that conversations around Black Fridayextend far beyond e-commerce. They flow through entertainment, sports, and lifestyle, the digital equivalent of a buzzing shopping mall where every moment tells a story.

At the center sits technology and computing, representing 31.3% of all Black Friday-related content. Consumers are drawn to gaming laptops, consoles, smartphones, VR headsets, and TVs, but just as important are the price-tracking tools and AI-powered deal finders helping them make smarter choices. This year, AI isn’t just powering ads; it’s shaping how consumers compare, decide, and buy.

Engagement intensity also varies across categories, with technology and gaming articles generating the highest average visits per article, showing where consumer curiosity peaks during Black Friday.

Next comes shopping, accounting for 12.4% of the conversation. Audiences are diving into comparisons between Black Friday and Cyber Monday, tracking early access deals from major retailers like Walmart and Dyson, and planning purchases with precision.

The data shows that pre-Black Friday engagement spikes earlier each year, proving that timing and contextual presence drive conversion.

Sports also play an unexpected role. With 11% of content linked to sports gear, fan apparel, and NFL promotions, advertisers are aligning their Black Friday advertising with cultural events, turning fandom into commerce.

Beyond Discounts: Why Emotion and Context Drive Sales

The biggest Black Friday advertising wins aren’t necessarily the loudest. They’re the ones that tap into emotion, grabbing consumers' attention by the heart. This season’s data shows how brands like Sony, Fender, and Xiaomi leverage nostalgia and exclusivity with limited-edition guitars, collector devices, and premium bundles to turn products into experiences.

That emotional connection is what makes contextual advertising so powerful. Imagine a smart TV promotion appearing beside a Netflix review or a PS5 bundle ad within a gaming walkthrough. When the environment reflects the user’s mindset, engagement rises naturally.

In Seedtag’s data, entertainment and streaming categories, including Netflix, Disney+, and Paramount+, dominate attention during the holiday season, underscoring how Black Friday advertising thrives where people feel most inspired.

How Brands Use Black Friday Ads to Drive Sales

So how do brands translate interest, intent, and emotion into action? Through retail media, the new powerhouse of Black Friday advertising.

In 2025, retail media networks have become more than conversion platforms; they’re contextual ecosystems connecting audiences at the moment of consideration. During Black Friday and Cyber Monday, these ecosystems merge first-party retail data with AI-driven contextual signals, helping brands deliver ads that feel timely, relevant, and human.

For example:

• Microsoft, Samsung, and Apple lead with tech-focused campaigns tied to early-access launches.
• PlayStation and Alienware dominate gaming spaces, aligning Black Friday ads with entertainment content long before consumers reach retailer sites.
• Disney+ and Hulu use exclusive bundle promotions to merge content consumption with retail conversion.
  
  

The result: advertising that aligns emotion with availability, creating authentic connections during the most competitive retail moment of the year.

Learn More

1. Consumer Trends: What’s Driving Shopping Fever This Season
2. Consumer Trends in the Automotive Industry: What’s Driving Change
3. How to Advertise on CTV: Streaming Into the Future for Brands and Publishers
4. Digital Marketing Musts for Publishers: Locking in Monetization with Brand Safety
   
   

The Rise of AI in Black Friday Advertising

The next chapter in Black Friday advertising trends is powered by AI, not as a buzzword, but as a bridge between data and human behaviour.

From dynamic creative optimisation to neuro-contextual advertising, AI helps brands interpret not just what consumers read, but why they engage.

Our proprietary Neuro-Contextual AI, Liz, decodes interests, emotions, and intent in real time, ensuring Black Friday ads appear where users are most receptive. When a reader browses gaming setups or smart-home articles, Liz detects emotional cues like curiosity or anticipation; then it delivers matching creatives, such as a limited-time TV offer or early-access console deal.

This approach transforms advertising from interruption to interpretation. It’s not about pushing harder. It’s about understanding better.

What Publishers Can Learn from Black Friday Advertising

Publishers are essential to the success of Black Friday advertising. With audiences seeking inspiration, recommendations, and deal insights, content environments become prime retail media real estate.

By combining editorial content with AI-powered context, publishers can:

• Align Black Friday ads with high-intent moments.
• Increase CPMs through relevance and engagement.
• Turn review articles, gift guides, and product comparisons into interactive purchase journeys.
• Leverage affiliate programs to earn an affiliate commission from Black Friday sales, maximising the value of high-intent content.

The Shift Toward Intentional Shopping

One of the defining patterns of Black Friday advertising 2025 is the rise of intentional shoppers. Today’s consumers plan earlier, compare smarter, and buy faster once they identify the right deal.

Our data reveals that planning behaviour starts weeks before the Black Friday season, driven by curiosity around exclusive offers, free gifts, and early-access sales. Brands that engage during this pre-period, through emotional storytelling and contextual alignment, can build familiarity and trust that pay off once purchase decisions peak.

If you wanna know more about how brands are adapting, explore our blog article new marketing trends.

The Emotional Economics of the Holiday Shopping Season

Even as Cyber Monday extends the momentum online, the heart of Black Friday advertisingremains emotional. It’s about belonging, celebration, and the thrill of discovery. Categories such as music tech, streaming, and gaming consistently outperform because they offer participation, not just promotion.

Campaigns like Spotify Wrapped, Netflix holiday premieres, and Disney+ bundles show that the most successful Black Friday marketing campaigns combine storytelling with utility, a reflection of how modern retail media turns attention into intention.

While Cyber Monday drives significant online traffic, with 1,446 related articles and over 320,000 visits, its focus remains largely on tech and streaming deals, complementing the broader, more emotional narrative of Black Friday.

Smarter Context, Stronger Impact

Black Friday advertising is evolving into something far more sophisticated than a weekend of markdowns. It’s becoming the pulse of modern brand strategy — where interest, intent, emotion, data, and AI converge to drive measurable impact.

Seedtag’s neuro-contextual approach, powered by Liz, helps brands understand audiences more humanly, connecting messages to mindsets across every stage of the journey.

Because in 2025, the brands that win won’t be those shouting the loudest, but those that understand the moment best.

That’s the power (and promise!) of Black Friday advertising in the new era of contextual connection.

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Season four of the AdTech Heroes podcast opens with a forward-looking conversation about the next phase of digital commerce (Episode 52: Reimagining Commerce for the Agentic Era). I sat down with Amie Owen, Global Chief Commerce Officer at IPG Mediabrands, to explore how AI agents, consumer behavior, and cultural signals are converging to reshape buying and selling in real time.

Before we started the conversation, one thing was already clear to me: the industry is entering a new phase of AI adoption, one that goes far beyond generative tools.

We are now working with AI agents, autonomous systems that can analyze data, plan actions, complete multi-step tasks, and adapt in real time. These agents do not wait for human instruction. They connect information across platforms, respond instantly to performance signals, and optimize campaigns as they learn.

For marketers, this shift marks a move from simple automation to intelligent decision-making that operates continuously and at scale. This is why I believe agentic AI represents the next meaningful step in AI-powered commerce.

It connects analytics, optimization, and execution in a way that removes friction and unlocks a level of speed and responsiveness that was not possible before.

With that context in mind, my conversation with Amie felt perfectly timed. This episode offers one of the clearest explanations I have heard of how agentic AI, intelligent automation, and retail transformation are evolving together.

AI Agent Platforms - Key takeaways

• AI agent platforms mark a major shift from traditional AI tools, moving commerce from isolated task execution to fully connected, intelligent systems that automate, analyse, and improve in real time.
• AI agent platforms help brands shift from reactive to proactive decision-making, bridging artificial intelligence, creative needs, retail signals, and human oversight
• Consumer adoption of AI varies significantly by generation, which means customer AI agents will need adaptive behaviors. Gen X and Millennials want visibility, Gen Z wants selective assistance, and Gen Alpha is already voice-first.
• Synchronized commerce is the new operating model, where brand campaigns, shoppable experiences, content, and data all work together through managed AI agents and automated orchestration.
• Agent platforms are central to the next phase of the AI revolution, acting as orchestrators that unify data, automation, and creativity into a single, intelligent commerce engine.
  
  

Commerce Has Been Here All Along, But It Has Entered a New Era

Amie Owen's career began with in-store media, selling signage placements that many now consider to be the earliest form of retail media. Although commerce feels newly elevated, its foundations stretch back decades. What has changed is the pace at which the space is accelerating.

COVID marked the turning point. Online grocery shopping, BOPIS behavior, and digital exploration pushed retailers and brands to rethink how products are discovered. Wider adoption of delivery services and marketplace shopping created an entirely new ecosystem for commercial strategy.

“Commerce used to be the extra. Now it is the centrepiece, and clients expect it”, Owen explains.

Today, I see commerce not as a channel, but an organisational strategy.

How AI Agent Platforms Reshape the Next Phase of Agentic AI

One of the strongest themes in the episode is the explanation of how an AI agent platform vs traditional AI tools has become a defining shift. Traditional AI tools tend to perform a single function, usually in isolation. An AI agent platform works very differently. It enables brands to:

• Connect systems that previously worked independently.
• Deploy and manage multiple AI agents inside one environment.
• Automate tasks that slow down teams.
• Expand agent capabilities based on real-time goals.
• Oversee and refine outcomes through a human-in-the-loop model.
  
  

This is the foundation of what is agentic AI, where autonomous systems can evaluate information, execute multi-step tasks, and learn from the results.

IPG Mediabrands already uses an internal platform that scans PDPs, detects seasonality shifts, compares competitors, evaluates reviews, and produces a complete optimization brief in a matter of seconds. Previously, teams executed all of this manually.

Our guest noted that these improvements are not simply productivity gains. They drive measurable revenue, since pre-built workflows and intelligent agents can optimize hundreds of pages far faster than any human team.

Generational Shifts in How Consumers Use AI

The episode also takes a deep look into the behavioral side of agentic commerce. According to Amie, Millennials and Gen X want to see the steps an agent takes because they grew up in both physical and digital worlds.

Gen Z, on the other hand, welcomes AI for utility tasks but wants more personal involvementin categories tied to identity, such as fashion or beauty. Gen Alpha views voice-driven interactions as normal, and they often use assistants to search or shop without hesitation.

This variation matters. A future customer AI agent will need to adjust its behavior depending on who it serves. For commerce leaders, these patterns are early signals of how artificial intelligence will shape long-term engagement.

Learn More

1. What is Agentic AI And How is Transforming Digital Advertising
2. Pushing the Boundaries of the AI Revolution in Advertising
3. Passions Over Profiles: AI for Advertising
   
   

From Total Commerce to Synchronized Commerce, Enabled by Agent Platforms

Commerce strategy has expanded from simple media activation to a four-pillar model that includes retail readiness, data, technology, media, and content.

Amie believes we have now entered the phase of synchronized commerce, where everything works together through intelligent automation. In this model, brand campaigns must connect to retail outcomes; shoppable formats bridge media, store, and product pages; data informs creative decisions, and agent platforms help teams manage AI agents and coordinate all elements in real time

This shift positions commerce as the connective tissue between brand building and performance, rather than a siloed discipline.

The Emotional Layer of Commerce and the Rise of Cultural Signals

We also explored the emotional side of commerce. Amie described how IPG has experimented with emotion-tracking technology, eye-tracking, and sentiment tools that identify what customers feel before they make a choice.

At the cultural level, she explains how major pop-culture moments, such as Taylor Swift album releases, create immediate waves in online behavior. Intelligent agents can monitor these moments and highlight where brands can participate.

The opportunity lies in speed. Many brands want to react to culture but struggle with internal processes. Agent platforms can help teams automate tasks, filter signals, and surface strategic recommendations faster than traditional methods.

Do Brands Still Matter in an AI-Driven Commerce Environment?

The short answer is yes. Even with the rise of automation and intelligent agents, brands remain the source of emotional connection, trust, and cultural relevance.

Brand equity influences purchase decisions, social engagement, sustainability expectations, and consumer loyalty. AI can optimize the journey, but the story, identity, and value of the brand still drive meaning.

Industries That Benefit Most From AI Agent Platforms

Although agent platforms can support nearly any category, the industries primed for the greatest transformation include:

• Retail and e-commerce, where thousands of SKUs (Stock-Keeping Units) require constant optimization.
• Consumer packaged goods, because each retailer requires custom PDP alignment.
• Media and advertising, where creative, context, and placement can now be coordinated through agents.
• Travel and hospitality, where personalisation and automation go hand in hand.
• Financial services that depend on accuracy, compliance, and intelligent workflows.
  
  

These categories generate large volumes of data and require agility at scale. This makes them ideal environments for agentic AI and coordinated agent platforms.

Listen to the Full Episode about the Agentic Era

For a deeper look into agentic commerce, AI agent platforms, and the future of automated decision-making, I invite you to listen to the full conversation with Amie Owen on AdTech Heroes, Season 4, Episode 1.

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The digital advertising landscape is at a crossroads. After years of optimizing for impressions, reach, and automation, the industry has drifted away from what matters most: human connection and understanding what drives people's motivations in the moments that matter most. An ad may have high visibility, yet fail to ignite the emotional or cognitive connection required to move someone to act.

This raises a critical question: What is the current digital advertising landscape really optimizing for, performance metrics or human relevance?

Our new research, developed in partnership with Prof. Moran Cerf, a leading neuroscientist at Columbia University, provides scientific evidence that the brain naturally prefers information that feels intuitive, emotionally aligned, and easy to process. When advertising aligns with the moment someone is in, how they think, feel, and intend to act, the ad resonates more naturally and becomes far more impactful.

This is the foundation of neuro-contextual advertising, a more human-centered approach that enables brands to build genuine connections in real-time.

Access The Report

1. The Limits of Behavioral Targeting
2. First Things First: What Is Contextual Advertising?
3. Introducing the Neuro-Contextual Advertising Approach
4. The Brain Sets the Standard for Real Relevance
5. A Human-Centered Future Built on Neuro-Contextual Understanding
   

Key Takeaways: Digital Advetising Landscape

• Advertising focuses too heavily on automation and KPIs that don’t reflect real human impact, losing sight of the emotional and cognitive connection.
• Behavioral targeting is declining in accuracy and scale, capturing past behavior instead of present intent.
• The brain prefers information that feels intuitive, emotionally aligned, and easy to process, making people more receptive to advertising.
• Neuro-contextual advertising interprets the context of an article or video to decode deeper user signals of interest, emotion, and intent to match the cognitive and emotional state of the moment.
• Liz, our proprietary neuro-contextual AI, enables privacy-first, human-centered relevance, without using personal data.
  
  

The Limits of Behavioral Targeting

For more than a decade, behavioral targeting promised precision by tracking where people went and what they did online. What it captured were digital traces, not genuine human understanding. It relied on demographics and past behavior, placing people into fixed categories that did not reflect the real motivations or emotional context shaping their decisions.

It is not a small disruption. It is a structural failure that has revealed long-standing gaps in how audiences are understood, which has drained budgets and weakened performance across the funnel.

At the same time, people have changed. Loyalty is declining, attention is fragmented, and users are increasingly uncomfortable with the idea of their personal data being used without their permission. Decisions are shaped by emotional context rather than broad demographic labels. Someone’s age or gender cannot explain why they are searching, what motivates them, or how they're likely feeling in the moment an ad appears.

Neuroscience has validated what the industry is only now rediscovering. Human readiness is contextual. Emotion is what first signals relevance and opens the door. Interest is what draws attention and keeps someone engaged. Intention transforms that engagement into action, whether it’s a conversion or a purchase.

Our study reveals that these signals come from the content people are actively engaging with. Emotional tone, cognitive state, and intent expressed in the surrounding environment influence how the brain receives an ad. These patterns appear in the EEG brainwave technology results through stronger attention, emotional resonance, and neural engagement when ads align with the mindset activated by the content.

To connect in a privacy-first world, advertisers need to understand the moment itself. Our research shows that alignment with interest, emotion, and intent present in the content strongly impacts people's receptiveness to ads. These signals come from the context of the moment, not from personal identifiers or historical tracking.

In this sense, context is not a fallback. It is simply where the study recorded the strongest neural and emotional responses. When advertising matches the mindset a person is already in, the brain processes the message more fluently. This is the foundation of Neuro-Contextual advertising and the relevance observed in the research.

First Things First: What Is Contextual Advertising?

As behavioral data declines, many marketers are revisiting contextual advertising and rethinking how they can create relevance without personal data. This shift has renewed a long-running debate between behavioral and contextual approaches. Behavioral data looks backward, capturing what someone once did, while contextual aims to understand the environment a person is in right now. To understand why the landscape needed to evolve, it is helpful to start with a simple question: What is contextual advertising?

In practical terms, standard contextual targeting places ads based on page topics, usually identified through keywords or broad IAB categories. While this approach is privacy-safe, it often lacks the nuance needed to capture real human intent. Contextual systems may classify content correctly but still miss the motivation behind it. For example, a wellness retreat ad might appear on a fitness site simply because both are tagged as “health.” The match is technically correct, yet contextually off, because they do not share the same intent or emotional state.

This limitation becomes even more apparent as consumer behavior grows more fluid and emotionally driven. Traditional contextual targeting can recognize what someone is reading, but not why they are there, how they are likely feeling, or what they may be preparing to do after reading that content.

This is exactly where standard contextual advertising reaches its limit and where neuro-contextual advertising begins to set a new standard for human relevance.‍

Introducing the Neuro-Contextual Advertising Approach

Neuro-contextual advertising represents the next evolution of contextual advertising. Built at the intersection of neuroscience and artificial intelligence, it interprets deeper signals of interest, emotion, and intent from the content people are reading or watching

At the heart of this approach is Liz, our proprietary neuro-contextual AI. Liz mirrors the sophistication of human thought by interpreting these deeper signals in real time and delivering privacy-first,full-funnel advertising across premium CTV, video, and the open web.

The evidence is clear: the report confirmed that aligning ads to these cognitive and emotional signals produces significantly stronger effects:

• 3.5x higher neural engagement than non-contextual ads.
• 26% stronger emotional response than standard contextual ads.

Stronger neural responses indicate a higher likelihood of recall and downstream impact, meaning ads are not only noticed but also remembered and acted on.

Using EEG brainwave technology, the main outcomes demonstrate that neuro-contextual ads generate higher shared neural response, deeper emotional resonance, and stronger attention

Neuro-Contextual Advertising is a part of the experience rather than an interruption.

The Brain Sets the Standard for Real Relevance

Our neuroscience study explains that the brain instinctively prefers information that feels intuitive, emotionally aligned, and easy to process. This comes from our reliance on fast, automatic thinking to navigate daily decisions.

Three core signals shape how people respond to content:

• Emotion — signals immediate relevance
• Interest — sustains attention
• Intention — drives action

Together, they form the natural sequence that underpins effective advertising. When the environment aligns with the right emotional and cognitive tone, people become more open, more engaged, and more likely to connect with the message.

A Human-Centered Future Built on Neuro-Contextual Understanding

The research makes one insight clear: people process content emotionally, not only semantically. The emotional tone of the environment shapes how someone feels about the message they see, and how likely they are to remember it.

Neuro-contextual advertising is designed for this reality. It interprets why someone is consuming content and how the surrounding environment shapes their emotional and cognitive state. Neuro-Contextual AI, powered by embedding technology, analyzes the context of a piece of content to decode deeper user signals of interest, emotion, and intent in real time. It moves beyond simple content classification to create a more human-like understanding of how people think, feel, and decide.

This deeper alignment reduces cognitive effort, increases attention, and strengthens connection.

Download the full study to explore the scientific framework behind neuro-contextual advertising and learn how brands can build deeper relevance across today’s digital environments.

UK consumers are entering the shopping season with sharper expectations, stronger intent, and a smarter approach to spending. The traditional shopping calendar still matters, but the motivations behind every purchase are evolving.

From social commerce to sustainability, the way Britons discover, evaluate, and buy products has become more complex, yet more predictable.

Seedtag’s Shopping Season Insights 2025 reveals how understanding consumer behaviourthrough real-time signals of interest, emotion, and intent is key to connecting with audiences in moments that matter most. Between November and January, the UK’s most influential shopping season unfolds, where millions of digital interactions translate into long-term loyalty.

For marketers, success isn’t just about recognising consumer trends. It’s about understanding how UK consumers are shopping in 2025, when they convert, and what emotional cues drive their decisions.

1. The Rise of the Intentional Shopper
2. When UK Shoppers Convert Most
3. Sectors Shaping Consumer Demand
4. Gen Z and the New Age of Influence
5. The Emotional Economy: Why Feelings Still Fuel Conversions
6. From Insight to Action: A Playbook for 2025 and Beyond
7. The Neuro-Contextual Advantage
8. Context Is the New Conversion
   

Consumer Trends Takeaways:

• Shoppers buy with intent: UK consumers plan earlier, compare more, and expect brands to align with their values, not just offer discounts.
• Search and social drive discovery: From Google to TikTok, consumers rely on digital platforms for product recommendations and purchase validation.
• Sustainability shapes expectations: Eco-conscious decisions and transparent practices are now standard, influencing how and where people spend.
• Timing meets emotion: Conversions peak from November to January, led by logic during Black Friday and emotion at Christmas.
• Gen Z rewrites influence: Authenticity and peer recommendations matter more than traditional advertising or celebrity endorsements.
• Context is the new conversion: With Seedtag’s neuro-contextual AI, brands can connect at the exact moment consumers are most receptive.
  
  

The Rise of the Intentional Shopper

Across the UK, consumers continue to balance practicality with emotion. They’re driven by convenience and comfort, but increasingly expect brands to deliver value with purpose, from sustainable products to authentic storytelling and meaningful engagement.

Seedtag’s analysis shows that audiences begin their shopping journey earlier than ever, searching for deal previews, product comparisons, and digital exclusives well before Black Friday and Christmas. The shift reflects how early planning and emotional intent now shape consumer behaviour, revealing an audience that values preparation, not impulse.

What Defines Consumer Trends in 2025

• Search-first shopping: Search engines play a central role in discovery. Shoppers compare prices, read reviews, and bookmark pages weeks before purchase.
• Social commerce at scale: Social media has evolved from inspiration to conversion. Gen Zers in particular turn to platforms such as TikTok, Instagram, and YouTube for authentic product recommendations.
• Sustainability and accountability: Environmental impact continues to shape consumer behaviour. Shoppers expect sustainable choices and brands that demonstrate responsibility in both products and communications.
• Hybrid retail experiences: The boundary between digital and physical shopping is fading. Consumers browse online, explore in store, and complete purchases across multiple channels.
• Long-term value: From home upgrades to durable fashion and ethical beauty, buyers are focusing on products that align with lifestyle and longevity.
  
  

This more mature, mindful audience demands that brands move beyond demographic assumptions towards intent-led, contextual engagement rooted in emotion and timing.

When UK Shoppers Convert Most

One thing hasn’t changed: timing is everything, and still drives performance. But in 2025, the conversion curve is more nuanced.

Seedtag’s analysis highlights two key peaks in UK shopping behaviour:

• Black Friday & Cyber Monday (early November to early December): A longer window of engagement led by technology and entertainment, where discounts trigger functional value and rational decision-making.
• Christmas (mid to late December): A second peak driven by emotion, gifting, and convenience, as consumers prioritise availability and speed to secure last-minute purchases.
  
  

Notably, 24% of Christmas-related content mentions Black Friday, showing that shoppers now treat both events as part of one connected journey. This overlap provides brands with an extended opportunity to build awareness early and convert later.

Where Black Friday activations appeal to logic, focusing on price and performance, Christmas conversions are fuelled by emotion and urgency. As Seedtag’s insights confirm, understanding these emotional triggers ensures brands connect at the right moment to maximise results.

Sectors Shaping Consumer Demand

Every vertical tells a different story of intent, interest, and emotion. From tech to consumer packaged goods, Seedtag’s data shows that relevance and timing consistently outperform volume.

Technology

Smart devices, audio tech, and gaming dominate the season. Meta and Dyson lead in engagement due to exciting product launches, with fewer but more focused campaigns, while Samsung generates more content but lower impact.

Beauty

Luxury skincare and high-end cosmetics continue to engage audiences, while accessible gifting options and seasonal sets gain strong traction. Interest peaks in November and December, blending self-care with gift-giving sentiment.

Home and Interiors

Functionality and aesthetic products to liven up the home drive this category. From coffee innovation to smart appliances, engagement is highest in December and January, when audiences shift from gifting to personal lifestyle upgrades. DFS and Kärcher achieve strong results despite publishing less, proving that contextual timing matters more than frequency.

Supermarkets and FMCG

The focus on festive food, comfort, and family moments reinforces the emotional nature of this season. Tesco leads in visibility, while Lidl delivers the strongest engagement. Consumers spend more time seeking recipes and inspiration for gatherings, a great reminder that storytelling anchored in warmth and community wins attention.

Fashion

The fashion landscape blends luxury aspiration with affordability. Consumers are exploring both designer labels and accessible alternatives, from seasonal gift sets to wearable tech. Demand reflects self-expression and identity rather than price alone.

Gen Z and the New Age of Influence

Gen Z is reshaping how consumers engage with brands. They don’t just consume; they create and curate.

This generation merges shopping with entertainment, scrolling through social media for hauls, tutorials, and real-time reviews. Their purchase decisions are influenced by social proof and authenticity rather than traditional advertising.

While Millennials followed influencers, Gen Zers value peer discovery and contextual relevance. They expect brands to appear organically in the spaces they already inhabit, from editorial environments to livestream shopping experiences.

For marketers, this means shifting focus from who the consumer is to how they feel and interact. Social commerce and contextual targeting now work together to enhance the customer experience, shaping consumer demand and emotional connection.

The Emotional Economy: Why Feelings Still Fuel Conversions

While technology has simplified the path to purchase, emotion remains the most powerful consumer behavioural driver. Seedtag’s Shopping Season Insights 2025 shows that emotions influence each vertical differently:

• Tech succeeds through logic: functionality, utility, and innovation.
• Alcohol dominates Christmas due to its emotional and social associations.
• Fashion and beauty connect through identity and self-expression.
  
  

This proves that shopping is no longer transactional; it’s experiential. Every click and conversion is tied to anticipation, reward, or ritual. Brands that recognise these cues can shape moments of resonance that move audiences from awareness to action.

From Insight to Action: A Playbook for 2025 and Beyond

The shopping season may be short, but its lessons extend far beyond the holidays. As consumer trends 2025 continue to evolve, success depends on a brand’s ability to combine empathy with precision, to understand not only what people buy, but why, when, and how they decide.

This playbook turns data into direction, with six actions to help marketers connect with intent, inspire trust, and deliver lasting impact.

1. Activate Early, Retarget Later
   Audiences start engaging in early November. Build intent before peak moments, and retarget after to convert undecided shoppers.
2. Prioritise Emotion over Exposure
   Focus on storytelling that mirrors real motivations, like gifting, comfort, renewal, rather than noise.
3. Target Context, Not Categories
   Consumers connect through experiences. Blend lifestyle, tech, and culture to reflect how people actually shop.
4. Embed Sustainability Authentically
   Transparency earns trust. Make your environmental commitments visible and credible throughout communications.
5. Embrace Social Commerce and Search Synergy
   Social media drives discovery while search engines validate intent. Together, they shape a seamless omnichannel journey.
6. Optimise for Experience, Not Just Reach
   Engagement depth, dwell time, and emotional impact matter more than volume, the true indicators of consumer expectations and satisfaction.

The Neuro-Contextual Advantage

As attention fragments across devices and platforms, relevance has become the strongest form of performance.

Seedtag’s Neuro-Contextual AI, Liz, decodes how people think, feel, and decide. By aligning creative messaging with audience interest, intent and emotion, Liz ensures campaigns appear in premium, privacy-first environments, precisely when audiences are most receptive.

Through UK insights and neuro-contextual approach, brands can transform seasonal activations into lasting connections, predicting when shoppers will act and why they’ll care.

Learn more about Neuro-Contextual

1. Pioneering Neuro-Contextual: The Next Evolution in Artificial Intelligence Advertising
2. Neuro-Contextual Advertising: Winning Audiences Through Interests, Emotions and Intentions
3. Passions Over Profiles: AI for Advertising
4. Neuro-Contextual Advertising: From Industry Innovation to eMarketer’s Number One Trend
   
   

Context Is the New Conversion

UK consumers are more conscious, sustainable, and emotionally attuned than ever. They’re guided by discovery, validation, and value, but ultimately, by relevance.

The brands that thrive will be those that look beyond demographics, harness real-time intent, interest, and emotion, and respect the aim behind every click.

In 2025, conversion doesn’t start at checkout. It starts the moment a consumer feels understood. And in that moment, Seedtag’s neuro-contextual advertising isn't just an advantage, it’s the difference between visibility and genuine impact.

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CTV vs Linear TV: What is the Difference of Connected TV and traditional?

Linear or traditional TV refers to the conventional television broadcasting model where content is delivered via satellite or cable. Content is programmed and displayed on particular channels at specific times and dates.

Connected TV (CTV), on the other hand, refers to any television set with an internet connection, offering viewers the freedom to watch content on-demand. Viewers can use smart TVs, gaming consoles, and streaming devices to access streamed content from platforms like Netflix, Hulu, and Amazon Prime Video, choosing from a wide range of programming, live events, and viewing options.

Key differences

• On traditional cable, content is broadcast at specific times and dates, while connected TV allows viewers to watch content on their own schedule.
• Typically, TV viewers watch programs in real-time on cable, and the content is delivered through broadcast channels. Connected TVs require an internet connection and provide content through streaming services, giving advertisers new ways to reach their target audience.
• While linear TV ad placements depend on specific times and scheduled programming, connected TV advertising offers more precision targeting. Advertisers can reach niche audiences based on demographics, interests, and viewing habits, making CTV advertising a more data-driven approach to ad spending.
• Additionally, CTV platforms allow users to interact with advertisements, creating a more engaging experience compared to linear TV. This interactive capability is a significant advantage of linear TV advertising’s digital counterpart, as it encourages higher conversion rates.

CTV vs Linear TV Advertising

Linear TV Advertising

Traditional television advertising involves placing commercials within programs by buying time slots or pods during specific commercial breaks to reach the target audience. The Designated Market Area (DMA) refers to a group of territories considered the primary television viewing area for a particular city or metropolitan region. The DMA defines the television markets, and everyone within a DMA viewing a specific channel where a brand purchases ad space will see the same commercial.

Linear TV ad placements are effective for broad audience reach but lack the precise targeting capabilities of connected TV vs. linear TV approaches. Advertisers must rely on DMA-based targeting, which can limit the effectiveness of ad spending since many viewers may fall outside the desired demographic.

CTV Advertising

CTV advertising is a form of digital advertising that involves placing ads on connected TVs like smart TVs and streaming devices. Advertisers buy ad inventory through ad exchanges or directly from CTV platforms and then place the ads within the content viewers watch on their connected TVs. This approach allows advertisers to reach their target audience with greater precision targeting by analyzing viewing habits and engagement data.

With the rising number of cord-cutters and increasing CTV viewership, advertisers are shifting their focus from traditional television advertising to connected TV advertising. CTV enables advertisers to reach highly specific demographics, ensuring that ads are delivered to relevant viewers. This capability contrasts sharply with traditional broadcast advertising, which cannot offer the same level of addressable TV precision.

While linear advertising enables advertisers to reach a wider audience base, the targeting capabilities are more limited. Advertisers cannot target niche audience segments making it difficult to target specific demographics or interests precisely. Since targeting is primarily based on DMAs, advertisers have restricted capabilities and could target segments where many viewers fall outside the desired target group.

Bagging prime-time slots for ads on traditional TV is also expensive when compared to CTV ads, and measuring campaign effectiveness is also difficult on cable as there is no access to ​​detailed data and analytics. Advertisers only rely on traditional measurement methods like Nielsen ratings that provide a general overview of viewership.

Furthermore, CTV advertising provides real-time data and analytics, allowing advertisers to measure impressions, engagement rates, and conversions. Unlike linear TV, where success is measured through Nielsen ratings and broad estimates, connected TV advertising allows for more accurate and trackable results. This makes it easier to adjust advertising strategies and optimize campaigns in real-time.

The CTV advertising era

Unlike traditional television advertising, which broadcasts all ads to a general audience, CTV advertising enables personalization and relevance by targeting based on audience interests and viewing habits. CTV targeting focuses on an interest-based approach to effectively capture audience attention and engage them by showing viewers ads that are relevant to their preferences.

Since the ads align with a viewer’s real-time interests and you can now engage with the ads, CTV ad placements tend to lead to higher engagement and conversion rates. The ability to track key metrics like impressions, viewability, engagement rates, and conversions, makes it easier to measure the effectiveness of campaigns, optimize ads, and measure ROI.

Linear TV viewing is often passive, the engagement rates are lower, and viewers are less likely to interact with ads or take immediate action. CTV ads offer interactive capabilities that allow viewers to take action with an ad to learn more about the product or service, leading to higher levels of engagement and brand recall. The ability to target specific audiences reduces ad budget wastage on viewers who are not relevant, thus making CTV more cost-effective than traditional advertising.

CTV advertising is emerging as a preferred choice among advertisers as it empowers them with a more targeted, measurable, and engaging way to reach audiences compared to traditional advertising. CTV advertising can help maximize the effectiveness of campaigns by aligning ads with the current genre or show being watched by viewers. The ads appeal to the audience as they find them more relevant and engaging.

• Learn more about CTV advertising capabilities with Contextual TV by Seedtag.
• Additionally, register for Seedtag Academy to become an expert in all things CTV!

CTV vs Linear TV – Which is the Future of Advertising?

CTV and linear TV both have their strengths, but as consumer preferences shift towards streamed content, advertisers must adapt to these changes. While the advantages of linear TV advertising include broad audience reach and familiarity, CTV advertising offers better targeting, measurable engagement, and cost efficiency.

Additionally, comparisons highlight how CTV reduces ad budget wastage. Traditional TV ads often reach broad audiences, including many viewers who may not be interested in the product or service being advertised. In contrast, CTV’s addressable TV capabilities ensure ads are shown to the most relevant viewers, improving conversion rates and campaign effectiveness.

The growing adoption of smart TVs, gaming consoles, and streaming services like Netflix and Hulu further solidifies the dominance of connected TV in modern advertising strategies. As more TV viewers transition to digital platforms, advertisers who leverage CTV advertising will benefit from improved precision targeting, higher engagement, and a more effective return on investment. The future of advertising lies in the evolving landscape of CTV vs. linear TV, with connected TV leading the way in delivering personalized, data-driven ad experiences.

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The automotive sector is entering one of its most transformative decades yet. From the rapid rise of EVs (electric vehicles) to new patterns in digital car buying, the landscape is being reshaped by evolving consumer expectations and smarter marketing technology.

But how is the automotive industry changing, and what does this mean for brands trying to connect with today’s drivers?

In the UK, the stakes have never been higher. With almost two million new cars registered in 2024 and the automotive sector forecast to double in value by 2035, opportunity is growing fast, but so is competition.

Seedtag’s latest white paper, How to Drive Marketing Success in the UK Automotive Industry, powered by our neuro-contextual AI platform Liz, analyses over 10,000 automotive-related web pages to map out the motivations, values, and intent signals shaping the next wave of automotive consumers.

Download the report to discover the up-to-date consumer trends in the automotive industry, and how neuro-contextual insights can put your brand in the driver's seat.

Key Takeaways

• Consumer expectations are reshaping the automotive industry. UK buyers are more value-driven, eco-conscious, and digitally connected, demanding vehicles that align with their lifestyles and ethics.
• Digital discovery leads to physical purchase. While 83% of buyers still close in-person deals, online research, reviews, and contextual content shape every decision.
• Marketing must move from “who” to “why.” Intent-driven insights and contextual advertising outperform demographic targeting, revealing why consumers act, not just who they are.
• Agility is essential. Seasonal intent peaks — such as EV interest in Q1 and Q4 — require real-time campaign optimisation to stay competitive.
• Privacy-first targeting is the future. Contextual AI enables precision advertising without cookies, aligning with new data regulations and consumer trust standards.
• The road ahead demands adaptability. Brands that leverage AI and neuro-contextual insights to anticipate emerging automotive consumer trends will lead the next era of marketing success.
  
  

From ‘Who’ to ‘Why’: A New Blueprint for the Car Buyer

Traditional targeting based on demographics is losing traction. The modern automotive consumer is no longer defined by who they are, but by why they buy, and when they’re ready to act.

According to the research, brand loyalty is fading fast, with only 2 in 10 UK buyers citing it as a decisive factor. Instead, environmental awareness and lifestyle alignment now play leading roles, influencing both brand choice and vehicle type.

Today’s car buyers move seamlessly between screens and moments of intent: watching EV reviews at lunch, comparing finance calculators after work, and booking test drives at the weekend.

Understanding why they engage—whether for status, practicality, or sustainability—allows brands to connect more meaningfully and time their messaging to perfection.

What’s Driving Automotive Conversations in 2025

By analysing the content people engage with, we uncover key themes across the web, revealing the shifting priorities, values, and motivations of today’s car buyers. Here are some examples:

• Luxury redefined: Innovation, personalisation, and tech integration are now as desirable as prestige.
• Everyday practicality: Cost-efficiency, reliability, and maintenance remain top of mind for mainstream buyers.
• Efficiency and control: Consumers are increasingly motivated by running costs, insurance rates, and tax savings.
• Sustainability as standard: With 60% of UK adults concerned about CO₂ emissions, environmental responsibility has become a key purchasing factor.

These themes reflect a broader shift across the global automotive industry, where consumers are demanding relevance, authenticity, and alignment with their personal values.

Learn More about how to win audiences

1. Neuro-Contextual Advertising: Winning Audiences Through Interests, Emotions and Intentions
2. Pioneering Neuro-Contextual: The Next Evolution in Artificial Intelligence Advertising
3. Passions Over Profiles: AI for Advertising

Digital Journeys, Real Decisions

Car buying has become an omnichannel experience, but digital discovery is now firmly in the driver’s seat. Seedtag’s latest report identifies five key audience mindsets—each shaped by distinct motivations and online behaviours—that reveal how automotive advertising should evolve to drive success.

• First-Time Buyers: cautious and cost-conscious, rely heavily on forums, calculators, and user reviews.
• Young Urbans: dynamic city-living professionals, explore sustainability and connected EVs.
• Family Upgraders: focused on safety and practicality, engaging with comparison articles and test-drive videos.
• Luxury Seekers: guided by refinement and innovation, explore bespoke options and digital showrooms.
• Technophiles: early adopters, actively seek out autonomous features and AI-powered enhancements.

By aligning creative and media placement with these intent signals, brands can ensure that every impression lands at precisely the right moment in the car buyer’s journey.

How Is the Automotive Industry Changing?

The shift from traditional cars to electric and autonomous vehicles is more than technological. It's behavioural. Consumers now expect brands to deliver:

• Performance with purpose: EVs and hybrids are chosen not just for innovation, but for the statement they make.
• Intelligence and safety: Interest in autonomous driving and in-car AI systems is growing as trust builds.
• Seamless omnichannel experiences: 83% of car sales still close in person, but most of the decision-making happens online.
• Privacy-first engagement: As cookies disappear, contextual AI is redefining how brands reach audiences responsibly.

In short, automotive marketing is evolving from static messaging to real-time contextual storytelling. Driven by data, powered by emotion.

What to Expect From the Road Ahead

The future of automotive marketing will belong to brands that blend data intelligence with creative agility. The next era of success will not be about reaching everyone, it will be about reaching the right someone at the right time, with the right message.

Seedtag’s neuro-contextual AI approach helps marketers decode these micro-moments of intent, ensuring every campaign resonates with both head and heart.

To uncover the full insights: from seasonal intent curves to segment breakdowns and actionable recommendations, download Seedtag’s UK Automotive White Paper and put your brand in the driver’s seat.

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The publishing industry is going through one of its most defining transformations. Attention is fragmented, competition is fierce, and artificial intelligence is reshaping how publishers create, distribute, and monetize content. Yet, amid all this disruption, one constant remains: the most successful publishers are the ones who understand their audience best.

In this episode of The Pub Way Podcast, Mike Villalobos and I spoke with Dan Benyamin, founder and CEO of Ion, about how AI is reshaping publishing, the impact of the creator economy, and what it really means to build a sustainable business model around attention.

What Matters Most — AI for publishers highlights

• Audiences still come first and publishers build a sustainable business model around attention.
• Smarter yield optimization, contextual and emotional intelligence, and predictive insights drive monetization.
• Automated video creation turns written stories into short-form videos and new ad inventory.
• The creator economy can be both competition and opportunity and repurposing long-form journalism into short videos helps publishers stay relevant.
• Build or buy combines specialized AI platforms with creative control and data ownership, and transparency is essential.

A Changing Landscape for Publishers

Dan’s career tells the story of modern adtech. As a four-time entrepreneur and former VP of Data Products at Condé Nast, he has seen the digital industry evolve from simple banner placements to data-driven ecosystems powered by artificial intelligence.

His takeaway is simple but powerful: audiences still come first. Everything else, from data pipelines to monetization tools, should revolve around creating meaningful experiences for readers. Publishers who lose sight of that connection risk being left behind, no matter how advanced their technology stack is.

Competing for Attention in a Fragmented Landscape

Publishers now find themselves in the middle of a new attention economy. On one side are the major social platforms that dominate reach. On the other, a generation of independent creators has become powerful competitors, building loyal audiences with minimal resources.

For traditional publishers, this shift can feel like a threat, but it also opens new doors. AI allows them to move faster, personalize experiences, and compete on equal terms with the creators who set the tone of online culture.

By analyzing what readers care about and how they behave, publishers can turn insights into action, adapting both content and monetization strategies in real time.

Turning AI into a Monetization Engine

Artificial intelligence is helping publishers grow revenue in ways that were unthinkable just a few years ago. Instead of relying solely on historical performance data, AI models identify trends, forecast demand, and optimize yield before opportunities are lost.

Here are some of the most impactful ways publishers are using AI to drive monetization:

Smarter yield optimization

AI analyzes traffic and engagement patterns to recommend pricing adjustments and increase the value of underperforming inventory.

Contextual and emotional intelligence

AI understands not just what a story is about but how it makes readers feel. This helps match ads that align with the emotional tone of the content, improving both performance and user experience.

Automated video creation

Platforms like Ion transform written stories or photo features into short-form videos, creating new ad inventory and sponsorship opportunities.

Predictive insights

Machine learning anticipates which readers are most likely to subscribe, engage, or leave, enabling faster and more personalized responses.

Through these applications, AI does not replace human creativity but amplifies it. The result is a smarter, more efficient monetization ecosystem built around audience understanding.

Learn more about AI for publishers & Monetization

1. AI in Publishing: How Publishers Can Unlock Growth Through Audience-Centered Innovation
2. Digital Marketing Musts for Publishers: Locking in Monetization with Brand Safety
3. How Publishers Can Future-Proof Brand Safety and Revenue with the Right Advertising Supply Side Platform
   

Collaboration in the Creator Economy

The creator economy has redefined what it means to be a publisher. Individual creators now function as media brands, often capturing the cultural pulse faster than traditional outlets. For established publishers, this can be both competition and opportunity.

Dan believes collaboration is the key. Publishers already have trusted brands, strong editorial voices, and access to advertisers. Creators bring authenticity, community, and agility. AI can bridge the two worlds by making it easier to produce, adapt, and distribute content at scale.

Repurposing long-form journalism into short videos or co-branded pieces helps publishers stay relevant across formats while giving creators access to higher-quality storytelling. When powered by AI, this type of partnership can unlock entirely new revenue models.

Trust, Transparency, and the Rise of AI-Generated Influencers

As AI becomes part of the creative process, questions around authenticity naturally arise. We’re already seeing the emergence of AI-generated influencers, digital personalities capable of producing endless content. While these tools can be efficient, they also challenge the foundations of trust that publishers have built with their audiences.

Dan’s view is clear: transparency is essential. Audiences appreciate honesty about how technology is used. Publishers who clearly disclose AI-generated elements preserve credibility and maintain control over how their brands are perceived.

AI should enhance creativity, not disguise it. It should amplify human talent, not replace it.

Build or Buy: AI for publishers

As AI becomes more integrated into publishing, many organizations are asking whether to build their own solutions or partner with external providers. Dan’s answer is pragmatic.

Publishers are not technology companies; their true strength lies in culture, storytelling, and audience relationships. Building everything from scratch can distract from that mission. Partnering with specialized AI platforms allows teams to focus on what they do best while gaining access to innovation and scale.

The smartest approach often combines both: outsourcing infrastructure and automation while maintaining creative control and data ownership. This balance lets publishers innovate without losing their identity.

Practical Ways to Apply AI

Adopting AI does not have to mean overhauling every workflow. Many publishers start with small, high-impact projects that deliver quick results.

Some of the most effective examples include:

• Automated content tagging to improve ad targeting and user experience
• Personalized recommendations that increase engagement and session time
• Dynamic ad creatives that adapt to context and audience mood
• Predictive analytics that help forecast trends and performance
• Automated video summaries that repurpose existing assets for social media

Each of these applications generates incremental value. Together, they build a foundation for long-term, scalable monetization.

Why AI Matters for Publishers

AI is transforming how content is produced, delivered, and monetized. But beyond efficiency, it’s redefining how publishers connect with their readers and partners.

It enables privacy-first monetization models that respect user data while maximizing ad performance. It replaces manual reporting with predictive insights, helping teams anticipate trends instead of reacting to them. And it empowers publishers to offer advertisers something invaluable—relevance rooted in context rather than personal identifiers.

In a world where attention is scarce, understanding audience emotion and intent in real time has become a competitive advantage. AI gives publishers the ability to act on that understanding at scale.

As Dan summed up in our conversation, “It’s a battle for attention. You have a thousand companies fighting for a few minutes of someone’s day. Make sure you know what you’re fighting for.”

Listen to the Full Conversation

Artificial intelligence is redefining how publishers grow, compete, and connect with audiences. But technology alone is not the answer. The winners will be those who combine data, creativity, and authenticity to build stronger relationships with readers and advertisers alike.

Listen to the full episode ofThe Pub Way featuring Dan Benyamin, founder and CEO of Ion, to learn how publishers can use AI to improve monetization and stay ahead in a rapidly changing digital landscape.

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Television has entered a new chapter. What was once a one-way medium is now one of the most dynamic and data-driven channels in the marketing mix. As viewers move from traditional TV to streaming, CTV ads are reshaping how audiences are reached and how content is monetized.

The numbers tell the story. As of 2024, over 115 million U.S. households consume television through connected devices, representing nearly 88 percent of all homes. That is not a trend; it is a complete redefinition of attention.

CTV Ads: Highlights

• CTV advertising blends TV impact with digital precision: targetable, measurable, and optimizable in real time.
• Reach the right viewers using demographics, interests, and content-viewing behavior to reduce guesswork and waste.
• Spend smarter with programmatic buying that optimizes price, location, co-viewing, relevance, and cross-screen ROI.
• Measure what matters with real-time analytics—impressions, completion rates, conversions—and benefit from higher attention than linear TV.
• Tackle fragmentation with first-party data, unified identity and measurement, and contextual targeting for privacy-safe relevance.
  
  

From Cable to Connection

For years, television revolved around reach. Brands bought airtime, crossed their fingers, and measured success with broad estimates. But the streaming era changed everything.

CTV advertising brings together two worlds that once lived apart: the impact of television and the precision of digital. With internet-connected TVs, ads can be targeted, measured, and optimized in real time.

This means advertisers can finally understand who saw their ad, how they engaged, and whether that exposure led to real action. It is still TV, but it behaves like digital.

Why Advertisers Are Moving to CTV

Let’s be honest. It is not just about following the audience. It is about efficiency, accountability, and more thoughtful engagement.

CTV ads allow brands to:

Reach the right viewers

Unlike traditional TV, CTV uses audience signals, such as demographics, interests, and content-viewing behavior. Advertisers can deliver messages that make sense in the moment rather than relying on guesswork or broadstroke targeting.

Spend smarter

Programmatic buying makes every impression count by optimizing signals for price, location, high-intention, co-viewing, audience relevance, and cross-screen ROI

Measure what matters

With real-time analytics, advertisers track impressions, completion rates, and conversions. The gap between storytelling and measurable outcomes is finally closing.

And there is another layer. Attention on CTV is higher than on linear TV. Viewers actively choose what to watch, making ads more likely to be noticed and remembered.

Learn More about CTV Ads

1. How to Advertise on CTV: Streaming Into the Future for Brands and Publishers
2. CTV vs Linear TV​: How is CTV advertising different from Linear TV?
3. A “Break” Down of Ad Breaks: Understanding CTV Ad Pods
4. Closing the CTV Measurement Gap: Data Quality & Performance Talks
   

What CTV Means for Publishers

If CTV is a revolution for advertisers, it is a lifeline for publishers.

As streaming consumption grows, ad-supported models are generating new, sustainable revenue streams. Major platforms like Netflix, Disney+, and Amazon Prime Video now include ad tiers, and viewers are embracing them.

For publishers, CTV advertising unlocks:

More monetization opportunities

Pre-rolls, mid-rolls, post-rolls, homescreen spots, and pause ads offer flexibility, while premium ad-supported tiers generate recurring revenue without relying on subscriptions.

Premium value for premium content

Streaming viewers are intentional about what they watch. This attention translates into higher retention and stronger CPMs for publishers who can offer brand-safe, high-quality environments.

Cross-device consistency

With identity spines that include HHIDs, CTV can integrate with mobile and desktop campaigns, giving publishers a unified, omnichannel narrative that keeps audiences engaged across screens.

The result is a more balanced ecosystem where publishers are not only storytellers but strategic partners in delivering measurable, relevant advertising.

The Data Challenge Everyone Is Talking About

Still, growth brings complexity. The CTV advertising ecosystem faces its biggest challenge in one word: fragmentation.

Data lives across multiple platforms, formats are not standardized, and measurement practices vary widely. This leads to ad repetition, limited transparency, and difficulties in tracking performance across devices.

But there is good news. The industry is moving fast to fix it.

Collaboration among advertisers, publishers, and tech partners is leading to unified measurement and identity frameworks.
Contextual targeting is making a comeback, using content signals rather than personal data to reach audiences with relevance and respect.

These advances are not just technical upgrades. They are the foundation of a healthier advertising ecosystem.

From Streaming to Strategy

CTV is no longer just a way to deliver video content. It has become a strategic platform where brands compete for attention, measure performance in real time, and optimize investment with precision. It is the place where storytelling and outcomes finally come together, where reach gains relevance, and where media buying starts with the audience and ends with measurable impact.

For advertisers, this means campaigns that perform and connect without wasting impressions. For publishers, it means monetizing intentional viewing with more control and higher value. And for audiences, it means seeing ads that feel timely, respectful, and worth watching.

CTV is not just a continuation of television. It is a new model for how advertising works and where it is headed.

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

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

This evolution presents advertisers with unprecedented opportunities:

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

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

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

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

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

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

TV Measurement at a Crossroads

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

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

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

From IP Delivered Viewing to IP Delivered Data

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

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

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

When TV Drives Outcomes

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

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

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

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

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Learn More

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

Linear’s Incremental Reach Problem

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

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

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

Where Ad Tiers Fit Today

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

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

The CTV KPI Toolkit

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

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

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

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

Omnichannel Reach Extension with Context

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

This is where Contextual TV plays a key role:

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

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

Looking Ahead: TV measurement

Three shifts will define it's next phase :

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

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

Tune In to the Full Episode

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

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

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From scanning pages to understanding people

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

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

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

Winning Audiences: Key Highlights

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

Why passions matter more than profiles

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

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

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

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

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

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

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

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

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

The role of Agentic AI

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

With an intuitive, conversational interface, Agentic AI dynamically:

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

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

Learn more about winning audiences

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

Why this matters for advertisers

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

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

A smarter, more human era of advertising

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

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

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

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

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

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