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Actualités, tendances et informations en matière de publicité numérique
Every week, the internet tells you what's trending. It rarely tells you how any of it felt.
Open any trends page, any weekly recap, any "most talked about" list, and the logic is the same. Volume wins. Whatever generated the most clicks, shares, or mentions gets ranked first, regardless of what that attention actually meant. A blockbuster movie premiere and a last-minute playoff upset can sit side by side on the same list, indistinguishable by the metric used to rank them.
But attention and emotion are not the same thing. A story can dominate headlines and still leave people cold. Another can spike quietly in wonder, anger, or admiration without ever cracking the top of a trends page. Volume tells you where people looked. It says nothing about what they felt while looking.
That gap between the content people consume and how they actually feel about it is exactly where Neuro-Contextual advertising begins.
From Signal to Spotlight: Introducing the Seedtag Emotion Quotient
Today, we're putting Liz, our Neuro-Contextual AI, to work with the launch of the Seedtag Emotion Quotient, a weekly ranking of the five cultural moments that generated the strongest measured emotional response, not the ones simply generating the most volume.
Each moment is scored against its own emotional baseline. Take The Odyssey: admiration and anticipation for Nolan's epic were real, but off-screen romance between its stars ended up generating the strongest emotional signal of all, stronger than the film itself. And sometimes, what stands out is how differently the same event can be felt. At this year’s US Open, coverage around Carlos Alcaraz drove admiration to 3.93x its usual baseline, while stories around Novak Djokovic's early exit pushed sadness to 2.37x. Same tournament, same week, but two very different ways of experiencing it. For advertisers, that's an important distinction. Knowing that the US Open is capturing attention is one thing. Understanding whether that attention is being shaped by admiration or sadness gives brands a much more precise read on the moment and how their message can fit within it.
That's the point of the Emotion Quotient. It's the same intelligence behind Liz, our Neuro-Contextual AI, made visible: reading not just what a moment is about, but how it's genuinely felt.
Key Takeaways
- The Seedtag Emotion Quotient turns that same Neuro-Contextual analysis into a public, weekly view of the five cultural moments the internet felt the most.
- Liz, our Neuro-Contextual AI, reads interest, emotion, and intent across content in real time, without relying on personal data.
- Emotional signals rarely appear alone. Liz identifies the multiple emotions layered within a single piece of content.
- Traditional contextual targeting can identify what a piece of content is about. Neuro-Contextual advertising reads why it matters, understanding what sets one piece of content apart from another and how it's likely to land with the person engaging with it.
- Understanding why, not just what, is what makes Neuro-Contextual advertising fully resonant, and it's the foundation of full-funnel outcomes across the open web and CTV.
It's Not About Who Someone Is. It's About What They're Passionate About, In This Moment.
What Is Neuro-Contextual Advertising?
Contextual targeting has been part of digital advertising for years. At its most basic, it matches ads to content using keywords and categories. A travel article gets travel ads. A sports recap gets sports ads. It works, but it reaches its limit there. Classification is as far as it goes.
More advanced systems now use vector embeddings, numerical representations that place related concepts closer together in meaning, even when they share no keywords at all. That's a real improvement in how machines read content. But embeddings alone only summarize meaning. They don't explain why a moment matters to the person reading it.
That's the gap Neuro-Contextual advertising is built to close.
Neuro-Contextual Advertising, our approach at Seedtag, adds a purpose-built layer of business logic on top of that foundation, one built to interpret interest, emotion, and intent within content itself.
Two articles can sit in the exact same category and still mean entirely different things. Someone reading a spoiler-filled recap of a finale and someone reading a spoiler-free review are both talking about the same show, but their intent runs in opposite directions: one wants closure, the other wants to be convinced to watch. Knowing what the content is about can't tell them apart. Understanding why each reader is there can.
The same holds for emotion. A product launch event and a product recall story can both sit under "tech news," yet one carries excitement and anticipation, the other frustration and concern. That same underlying intelligence, reading interest, emotion, and intent together, is what powers everything we build, the Seedtag Emotion Quotient included.
The same logic applies to people, not just pages. Two readers can share every demographic box, same age, same income, same zip code, and still care about completely different things. Demographics describe who someone is on paper. They say nothing about what actually moves that person in the moment. Neuro-Contextual advertising shifts the question from "who is this person?" to "what are they passionate about right now?", and content itself is where that answer shows up first.
The Tech Behind the Ranking
Behind every score in the ranking is Liz, our Neuro-Contextual AI, reading content at scale and in real time. Liz scans more than 100 million URLs every day, with native understanding across 10+ languages and access to inventory from more than 30,000 premium media publishers globally, spanning the open web, video, and CTV.
That scale matters because the Seedtag Emotion Quotient isn't built from isolated pieces of content. Liz understands the connections between content across this broader ecosystem, identifying signals of interest, emotion, and intent as they emerge. The result is a view of cultural moments grounded not in a snapshot, but in what is happening across the content universe around us.
From there, understanding goes deeper than keywords. Liz maps the relationships between topics using vector embeddings grounded in neuroscience, which is how the ranking can isolate the specific terms driving a spike, not just name the general subject behind it.
Because human reactions are rarely singular, Liz reads emotion in layers rather than assigning one flat label. A single moment can carry curiosity and excitement at once, or admiration alongside real tension, and the ranking is built to reflect that complexity.
All of this happens without relying on personal data. Liz reads the content environment itself, not the individual people engaging with it, which is what keeps the ranking privacy-first by design.
Each week, the Seedtag Emotion Quotient publishes a new read on the five moments that generated the strongest measured emotional response over the week prior. It's built to be explored, not just read: every entry breaks down the specific emotions behind it, the story driving the spike, and how that moment's emotional profile compares to its usual baseline, a starting point for thinking through which emotional signals are worth aligning a campaign with, and when.
Why Does Measuring Emotion Matter for Advertisers?
The Seedtag Emotion Quotient makes something visible that advertisers should care about directly: emotion is measurable, and it predicts performance.
That's not just true for the moments in this ranking. It holds inside real campaigns too.
The same Neuro-Contextual intelligence behind the ranking already drives stronger performance where it counts most: inside live campaigns. Liz, our Neuro-Contextual AI, is the same engine behind Seedtag NeuroX, our Neuro-Contextual Exchange, powering both from the same underlying intelligence. NeuroX connects that intelligence at scale across 30,000+ premium publishers and broadcasters, making every impression understood whether or not identity is present in the bidstream.
Working with Professor Moran Cerf from Columbia University, our neuroscience research measured real-time brain responses and found that Neuro-Contextual ads drive 3.5 times higher neural engagement than non-contextual ads, and a 26% stronger emotional response than standard contextual advertising. Full-funnel outcomes, from awareness to conversion, are consistently stronger when a message aligns with the emotional state of the moment it appears in.
Is Neuro-Contextual advertising the future of targeting? As identity signals keep fragmenting across the open web, understanding the moment becomes the only foundation that holds.
It's not about knowing what content people consume. It's about understanding how that content makes them feel.
The Seedtag Emotion Quotient is live now. Explore this week's ranking.
The industry has always chased one promise: delivering the right message to the right person at the right time. The surprising part of advertising automation in 2026 is that the creative side of that promise is largely solved. Dynamic creative platforms, modern ad servers, and workflow automation have brought the industry much closer to making personalization at scale a reality.
What hasn't caught up is measurement.
That gap between what advertising automation can execute and what teams can actually measure is where many agencies still struggle. Closing it requires more than adopting another AI tool. It demands smarter workflows, disciplined testing, and connected data that turns execution into measurable business outcomes.
In this episode of AdTech Heroes, I sat down with Lisa Markou, Executive Vice President, Platforms at Publicis Collective, to explore what advertising automation actually looks like inside a modern agency, why measurement remains the industry's biggest challenge, and how leading teams are deciding what to automate first.
Key Takeaways
- Creative automation has made personalized advertising at scale possible, but measurement and attribution have yet to keep pace.
- Advertising automation in 2026 is less about adding new AI tools and more about simplifying technology stacks and eliminating inefficient workflows.
- The biggest advertising automation benefits often come from workflow automation, replacing manual processes that slow teams down and introduce errors.
- The most successful automation strategies begin with small, focused tests before expanding across larger marketing campaigns.
- Connected data—not disconnected platforms—is what allows automation to deliver meaningful business outcomes.
Creative Automation Has Solved What Measurement Still Can't
Creative technology has advanced rapidly over the past few years. According to Markou, the technology behind creative automation, including dynamic creative platforms and modern ad-serving capabilities, has finally reached a point where that vision is achievable.
Measurement, however, remains the missing piece.
Connecting metadata, taxonomy, creative assets, and media signals across multiple platforms continues to be one of advertising's biggest operational challenges. While renewed attention on brand metrics and engagement signals can help marketers understand campaign performance sooner, accurately attributing business outcomes still requires significant work behind the scenes.
For marketers, this means the next competitive advantage won't come from delivering more personalized creative alone. It will come from proving which creative actually drives results.
What Is Advertising Automation, and How Are Agencies Using It in 2026?
Ask five people to define advertising automation, and you'll probably get five different answers. For Markou, the definition extends far beyond AI or generative tools.
Her teams apply workflow automation to the tasks that historically consumed the most time, from dashboard creation and reporting to media planning and operational processes that once relied on manual spreadsheets. The objective isn't simply greater efficiency. It's freeing the marketing team to focus on strategy instead of repetitive work.
At the same time, not every legacy system needs replacing. Sometimes a manual workaround is more effective than forcing a new marketing automation platform into an existing workflow. The real challenge is knowing when consolidation genuinely improves performance, and when it simply adds complexity.
Rather than asking, "What new tool should we adopt?", agencies are increasingly asking, "Which process no longer deserves to exist?"
The Best Way to Test AI-Driven Automation Before Scaling
One of the biggest mistakes organizations make is trying to automate everything at once.
Markou advocates for a different approach: start small. Whether it's a single campaign, a tentpole event, or one portion of the media budget, focused testing allows teams to understand the trade-offs before investing in a broader rollout.
Just as importantly, every test needs a clear objective. Without defining what success looks like upfront, even promising automation pilots generate little actionable learning.
Breaking automation into smaller experiments reduces risk, builds internal confidence, and gives leadership the evidence needed to scale successful initiatives across future marketing campaigns.
The Biggest Advertising Automation Benefits Start With Better Workflows
Throughout the conversation, one theme kept resurfacing: agencies often overcomplicate automation by focusing on what new technology to add rather than what unnecessary process they can remove.
Markou described how outdated spreadsheets, redundant platforms, and legacy approvals frequently remain in place simply because replacing them feels disruptive. Yet the long-term cost of maintaining inefficient processes often outweighs the temporary effort required to redesign them.
The biggest advertising automation benefits rarely come from the newest AI feature. They come from reducing manual work, improving collaboration, and building automated workflows that help teams move faster with fewer errors.
Connected Data Is the Foundation of Modern Advertising Automation
Even the most sophisticated automation depends on one thing: connected data.
Markou explained that aligning taxonomy, naming conventions, customer data, and measurement across vendors and platforms remains one of the industry's most complex challenges. Add evolving privacy regulations, regional differences in first-party data onboarding, and increasingly fragmented marketing channels, and it's easy to see why automation alone isn't enough.
As the saying goes: good data in leads to good decisions out. Without a strong data foundation, even the most advanced marketing automation software struggles to deliver meaningful results.
For marketers, success increasingly depends on connecting systems, not simply adding more of them.
Where Advertising Automation Goes From Here
Advertising automation is no longer a side experiment. It is quickly becoming the operating standard for modern media organizations.
The agencies moving ahead aren't necessarily the ones adopting every new AI capability first. They're the ones willing to rethink outdated workflows, test new approaches deliberately, and build connected systems that turn data into better decisions.
As automation continues to evolve, competitive advantage won't come from adding more technology. It will come from understanding which processes to simplify, which experiments to scale, and how to connect every part of the marketing process into a more measurable, efficient whole.
For a deeper look at how leading agencies are approaching automation, connected data, and modern media operations, watch the full conversation with Lisa Markou in AdTech Heroes, Episode 60.
Every summer, the back-to-school season sneaks up faster than expected. Families start planning while the last day of school is still weeks away, and by the time September arrives, most of the shopping decisions have already been made.
For marketers, this creates a familiar challenge: the back-to-school marketing window opens earlier every year, and audiences are far more layered than a simple parent-buying-supplies narrative suggests.
This season is no longer just about pencils and backpacks. It stretches across education, food, community, technology, and fashion, often overlapping in ways brands don't expect. Understanding that complexity is the real key to a stronger back-to-school ad strategy.
Below, we break down the trends, timing, and audience behaviors shaping back-to-school marketing this year, along with what these shifts mean for seasonal marketing overall.
Key Takeaways
- Back-to-school marketing now spans far more than school supplies, touching food, technology, sports, and fashion content.
- Education-related content leads the conversation, with food and lunch prep following close behind.
- Liz, our Neuro-Contextual AI, uncovered 14 distinct contextual neighborhoods within the season, each reflecting a different shopper motivation.
- Shoppers fall into distinct interest groups, from test prep researchers to homeschooling parents to sports families.
- Some of the most valuable back-to-school trends this year come from unexpected overlaps between categories.
What Are the Key Back-to-School Marketing Trends for This Year?
One of the clearest back-to-school trends this year is just how education-driven the season has become. Education leads the back-to-school content universe at 67% of mentions, covering everything from test prep to classroom learning tools.
Food and drink content follows as the second biggest driver, with a strong focus on lunchbox packaging and baking. This shows how deeply back-to-school planning is tied to daily routines rather than a single shopping trip.
Beyond these two leading categories, Liz, our Neuro-Contextual AI, uncovered 14 custom contextual neighborhoods within the back-to-school content universe, connecting topics like homeschooling, online learning, athletics, and craft making.
This fragmentation is exactly why generic back-to-school advertising ideas tend to underperform. The audience isn't one shopper. It's many shoppers with very different needs happening at the same time.
When Should Brands Start Their Back-to-School Marketing Campaign?
Timing is one of the most common questions marketers ask heading into the school season.
Back-to-school planning clearly starts well before the first day of class: the interest clusters we identified span everything from early supply shopping to major sales moments, with events like Black Friday, Cyber, and Prime Day appearing within the same shopping conversations.
This overlap between back-to-school shopping and broader seasonal discount periods suggests that families are planning and comparing prices across an extended window, not making a single last-minute purchase. School marketing campaigns built around one moment risk missing the earlier stages of that planning process.
Who Are Today's Back-to-School Shoppers?
Back-to-school shoppers are not a single audience. The season breaks into six core interest areas, each shaped by different motivations and content habits:
- Books and Study: Families researching test prep (ACT, PSAT, college admission), elementary reading tools, and classic books and authors.
- Supplies and Shopping: Parents focused on preschool learning materials, seasonal crafts, classroom tools, and teacher appreciation gifts.
- Snacking and Food: Households planning lunchbox staples, homemade cookie recipes, and weekly grocery prep tied to the new routine.
- Community: Families engaging with school sports, school trips and events, and school support topics like PTA and staffing.
- Technology: Shoppers exploring online learning tools, college and career paths, teacher digital resources, and homeschooling programs.
- Gear and Fashion: Consumers shopping for school day essentials, trusted clothing brands, and smart shopping strategies around sales.
This range shows why a single back-to-school marketing message rarely works across the board. School shoppers move between these interest areas depending on their household needs.
What Surprising Behaviors Are Shaping Back-to-School Shopping?
Some of the most interesting back-to-school trends come from where these categories unexpectedly connect. Within the Books and Study neighborhood, we identified conversations blending literature curriculum mapping with classic authors like Jane Austen, meaning academic test prep and nostalgic reading discussions live side by side.
Homeschooling shows a similar pattern. A neighborhood cluster where homeschooling intersects directly with technology interests, particularly among parents sharing digital learning resources with one another.
Within the Community pillar, school sports conversations sit closely alongside smaller school milestones like book fairs, showing that the same emotional energy fueling student athletics also extends to everyday school events.
These overlaps matter because they reveal opportunities that a single-category campaign would miss entirely.
Back-to-School Marketing Tips for Brands
Based on these patterns, a few principles stand out for building a stronger school marketing campaign this year:
Speak to more than one interest area at once. Since families move fluidly between categories like Books and Study, Snacking and Food, and Gear and Fashion, campaigns that reflect more than one of these moments tend to feel more relevant than single-category messaging.
Recognize that back-to-school shopping overlaps with sales culture. Because gear and fashion conversations already connect with major discount periods, back-to-school promotions can align naturally with broader seasonal sale moments rather than competing against them.
Don't overlook homeschooling and technology audiences. This growing segment blends digital learning tools with community-driven resource sharing, representing a distinct content environment from traditional classroom shopping.
Match tone to the moment within each pillar, whether that's the practical urgency of school supplies, the routine-driven nature of lunch planning, or the community spirit around school events and sports.
From Supplies to Sentiment: Why Context Matters More Than Ever
As back-to-school shopping spreads across six distinct interest areas and 14 contextual neighborhoods, relevance becomes harder to achieve through guesswork alone.
This is where our Neuro-Contextual approach becomes valuable. Liz, Seedtag’s proprietary Neuro-Contextual AI, reads signals of interest, emotion, and intent within content itself, identifying these clusters by both definitional meaning and how topics naturally occur together on the page.
Rather than targeting a generic "parent" profile, this approach allows advertising to align with the specific moment a shopper is in, whether that's researching test prep, planning lunches, or browsing backpacks ahead of a sale. And it does this without relying on individual tracking, keeping the experience privacy-first while still feeling personal.
The Bigger Opportunity for Back-to-School Marketing
Back-to-school marketing isn't about reaching one type of shopper. It's about understanding the many overlapping moments that make up the season, from test prep stress to lunchbox planning to Friday night games.
Brands that recognize these connections, rather than treating back-to-school as a single retail event, are better positioned to build campaigns that feel relevant at every stage of the school season.
Want to see the full range of interests, content clusters, and behaviors shaping this year's back-to-school season? Download our Back-to-School Insights report to explore the data behind these trends.
Publisher monetization has entered a new phase. As streaming consumption officially surpasses linear television, advertising budgets are following audience attention into Connected TV (CTV), FAST channels, mobile apps, and other emerging digital environments. That shift is reshaping where publishers generate revenue and how they build sustainable monetization strategies.
For publishers, this is one of the biggest stories in publisher ad revenue news today. Revenue growth no longer depends on expanding inventory alone. It depends on creating advertising experiences that are transparent, measurable, and connected across multiple channels.
At Cannes Lions 2026, Mike and I sat down with Chandra Cirulnick, VP of Global Supply Partnerships at Yahoo DSP, for The Pub Way Podcast to explore what this evolution means for publisher ad management. Our conversation covered everything from CTV and FAST channel monetization to in-app growth, programmatic advertising, and the increasing importance of omnichannel strategies.
While we discussed several emerging formats, one idea connected them all. Publishers that diversify their revenue streams while giving advertisers greater transparency into performance are building stronger foundations for long-term publisher monetization.
Key Takeaways
- Streaming has overtaken linear TV, shifting publisher ad revenue toward CTV and FAST channels.
- New programmatic advertising formats are expanding monetization beyond traditional commercial breaks.
- CTV and FAST support different publisher monetization strategies, each serving unique advertiser needs.
- Transparency around inventory and campaign performance is becoming a competitive advantage.
- Omnichannel ad revenue strategies for digital publishers are creating stronger, more sustainable revenue growth.
How Are Publishers Monetizing CTV and FAST Channels in 2026?
Streaming has fundamentally expanded the number of ways publishers can generate advertising revenue. Instead of relying solely on traditional commercial breaks, publishers now have access to a growing mix of premium formats that can be packaged for different buyers, campaign objectives, and budgets.
Pause ads, home screen placements, shoppable experiences, and live sports sponsorships have all become available through programmatic advertising over the past year. These formats create new opportunities for publishers to diversify revenue streams while giving advertisers more flexible ways to reach audiences.
This evolution is also changing how inventory is sold.
Historically, television advertising centered around large upfront commitments, where buyers purchased broad audience reach months in advance. While those agreements remain important, they now exist alongside a growing programmatic marketplace that allows advertisers to buy inventory with far greater precision.
Instead of purchasing an entire market, brands can target audiences based on household counts and campaign objectives. That means advertisers that may not have the budgets for traditional national television campaigns can now reach highly relevant audiences through CTV, making premium inventory accessible to a much broader range of buyers.
For publishers, this creates far greater flexibility in publisher ad management.
Rather than relying on a single sales model, they can package premium inventory for large brand advertisers while simultaneously making additional inventory available through programmatic channels. This balance allows publishers to maximize advertising revenue without sacrificing the premium value of their content.
More importantly, it reflects a broader shift taking place across the industry.
Publisher monetization is no longer built around individual channels. It is increasingly built around connected audience experiences, where CTV, FAST channels, mobile apps, and other digital environments work together to create more valuable opportunities for both publishers and advertisers.
The Difference Between CTV and FAST Channel Monetization
Although they are often grouped together, CTV and FAST channel monetization solve different challenges for publishers.
Connected TV, particularly across premium streaming services, is typically valued for its broad reach, premium content, and household-level addressability. Advertisers use CTV to build large-scale awareness while benefiting from more precise targeting and measurement than traditional television has historically offered.
FAST channels, on the other hand, create value in a different way.
Rather than competing on audience size alone, they allow publishers to build highly engaged communities around specific interests, genres, or cultural moments. Whether it's motorsports, entertainment, news, or lifestyle programming, FAST channels give advertisers the opportunity to reach audiences who have intentionally chosen that content.
During our conversation, Formula 1 emerged as a great example of this shift. While traditional broadcast inventory around the sport may be limited, dedicated FAST programming creates entirely new opportunities for publishers to monetize highly engaged viewers who are actively seeking that content.
That distinction matters.
CTV often delivers scale and premium reach. FAST channels deliver contextual relevance and deeper audience engagement. Together, they give publishers more flexibility to package inventory based on different advertiser objectives instead of relying on a single monetization model.
As streaming ecosystems continue to evolve, understanding the difference between CTV and FAST channel monetization will become increasingly important for publishers looking to diversify advertising revenue while maximizing the value of every impression.
Why Transparency Is the New Currency of Ad Revenue Growth
As new inventory becomes available, advertisers are asking for something beyond scale. They want transparency.
Today, publishers are expected to answer two fundamental questions before media budgets are committed:
- Where will my ads appear?
- How did the campaign actually perform?
The first question is about content transparency. Buyers want to understand the environments where their ads will run before activation, whether that's a premium streaming service, a specific FAST channel, or a curated portfolio of content.
The second is about performance transparency. Advertisers increasingly expect clear measurement that demonstrates how campaigns contributed to business outcomes, not simply how many impressions were delivered.
Publishers are responding by offering different levels of transparency based on campaign objectives.
Portfolio-based or genre-based packages provide advertisers with greater flexibility and broader reach, often at more accessible price points. Show-level sponsorships, live events, and premium programming offer greater certainty around placement, allowing publishers to command higher premiums for inventory that delivers stronger contextual alignment.
This approach creates opportunities across multiple buyer types.
Brands focused on efficiency can access quality inventory through broader packages, while advertisers seeking highly controlled environments can invest in premium placements with full visibility into where their campaigns appear.
For publisher ad management teams, transparency is no longer simply a reporting feature. It has become an important driver of publisher monetization, helping strengthen advertiser confidence while supporting long-term revenue growth.
Omnichannel Ad Revenue Strategies for Digital Publishers
Perhaps the biggest takeaway from our conversation was that publisher monetization is no longer defined by individual channels.
The next stage of growth is being built around connected audience experiences.
Instead of viewing CTV, FAST, mobile apps, podcasts, and streaming as separate revenue opportunities, publishers are beginning to package them as complementary environments that reflect how audiences actually consume media throughout the day.
These omnichannel ad revenue strategies for digital publishers create more consistent experiences for advertisers while opening additional revenue streams for publishers.
Mobile apps are a good example.
For years, app advertising was largely associated with gaming. Today, non-gaming publishers are increasingly extending their brands into mobile experiences, creating new inventory that keeps audiences engaged beyond the browser while attracting advertisers looking to diversify their media-buying strategies.
Audio is evolving in much the same way.
Dynamic ad insertion has transformed podcast advertising from a largely manual process into a scalable programmatic channel. At the same time, advances in contextual intelligence allow campaigns to align with individual episode topics instead of entire shows, giving advertisers greater flexibility without sacrificing relevance.
The boundaries between formats are also becoming less defined.
Streaming platforms continue to experiment with video-first podcasts, while traditional audio content increasingly incorporates visual elements. Rather than thinking about video, audio, or mobile as separate channels, publishers are beginning to organize inventory around audience attention and content consumption.
This shift reflects a broader evolution across digital advertising.
Successful publisher monetization no longer depends on maximizing one channel at a time. It depends on creating connected advertising experiences that allow advertisers to engage audiences wherever they choose to consume content.
Understanding the Moment Behind Every Ad Dollar
One theme kept resurfacing throughout our conversation with Chandra.
The future of publisher monetization isn't being shaped by new channels alone. It's being shaped by a better understanding of audience attention.
Whether someone is watching a live sporting event on CTV, exploring a niche FAST channel, listening to a podcast during their commute, or engaging with content in a mobile app, the opportunity isn't simply to place another ad. It's to understand what that person is interested in at that specific moment and deliver advertising that complements the experience.
As media consumption becomes increasingly fragmented, context becomes the common thread connecting every environment. Publishers that understand not only where audiences are spending time, but also the interests, emotions, and intent behind that attention, are better positioned to create advertising experiences that feel relevant for consumers and valuable for advertisers.
This is where AI is beginning to play an increasingly important role.
Rather than relying solely on historical performance or broad audience segments, AI-powered contextual intelligence helps identify the environments where audiences are most receptive to a brand's message. That creates opportunities for publishers to strengthen monetization while helping advertisers make more informed media-buying decisions across multiple channels.
At Seedtag, this philosophy sits at the core of our Neuro-Contextual approach.
Powered by Liz, our proprietary AI built on more than a decade of content understanding at scale, Neuro-Contextual intelligence interprets signals of interest, emotion, and intent directly from content. Instead of relying on personal identifiers, it helps advertisers understand when audiences are most receptive to a message, creating more relevant advertising experiences across CTV, premium publisher environments, mobile, and other emerging formats.
As omnichannel strategies continue to evolve, this deeper understanding of context will become increasingly valuable for both publishers and advertisers looking to build sustainable, privacy-first revenue growth.
The Next Chapter of Publisher Monetization
Publisher ad revenue is no longer being shaped by a single channel or a single transaction. It's being built across connected experiences.
CTV continues to expand premium video opportunities. FAST channels are creating new ways to engage highly passionate communities. Mobile apps and digital audio are opening additional revenue streams that complement traditional web inventory. Together, these environments are transforming how publishers package, measure, and monetize advertising.
The publishers that succeed won't simply add more inventory. They'll create connected strategies that reflect how audiences actually consume media, while giving advertisers greater transparency, stronger measurement, and more meaningful ways to engage consumers across every touchpoint.
For advertisers, that means moving beyond isolated media buys and embracing omnichannel planning that prioritizes relevance alongside reach.
For publishers, it means recognizing that the future of publisher monetization isn't about choosing between CTV, FAST, mobile, or audio. It's about connecting those environments into a strategy that delivers long-term value for both buyers and audiences.
As attention continues to shift, the publishers that thrive will be the ones that understand not just where audiences are, but what captures their attention in the moments that matter most.
If you're exploring new ways to grow publisher ad revenue across CTV, FAST channels, mobile, and other digital environments, our conversation with Chandra Cirulnick offers valuable perspectives on where the industry is heading.
Listen to the full episode of The Pub Way Podcast for the complete discussion.
Notre blog
Connected TV, or CTV, no longer requires an introduction. The digital era has enabled hyper-connectivity and access to the internet which made information readily accessible anytime, anywhere. With CTV, the Internet was brought to the world of television, and any television set that can connect to the Internet can now stream video content, welcome to the future of Connected TV.
CTV has become increasingly popular as it offers a wider range of content than traditional television, and viewers can watch content of their choice, whenever they want.
This evolving landscape presents opportunities for advertisers to enhance the ad experience through interactive ads and advanced targeting capabilities.
On-demand viewing, flexibility, and access to a vast library of content make CTV the favored choice among viewers. These numbers will only continue to grow as more people switch to streaming services and internet-connected devices. The seismic shift in audience base has revolutionized advertising by paving the way for hyper-targeted CTV advertising with enhanced audience targeting capabilities and precise targeting methods.
What is Connected TV advertising?
CTV advertising has overcome the limitations of traditional TV ads where all ads are broadcast to a general audience. It focuses on personalized ads and relevant targeting based on audience interests and viewing habits. This interest-based targeting approach increases engagement and potentially boosts conversion rates for advertisers.
CTV advertising allows viewers to see ads that are relevant to them and helps measure campaign effectiveness, beating the limited tracking capabilities of traditional TV advertising. Access to key metrics like impressions, completion rates, and attribution of ad exposure to website visits or in-store purchases enables better measurement, campaign optimization, and ROI on CTV ad spend.
Navigating CTV advertising
A new channel that advertisers are actively tapping into, CTV advertising presents a massive opportunity for advertisers to effectively capture and engage with their target audience at the right time. However, similar to other channels of advertising, CTV advertising also has its limitations. Advertisers need to be mindful of poor inventory, quality concerns, ad fraud, and limited campaign measurement.
Contextual advertising has been garnering a lot of traction ever since the cookie phase-out announcement. Contextual targeting practices are emerging as a preferred solution among advertisers because of its hyper-personalization capabilities and the potential to measure campaign effectiveness through relevant and accurate metrics.
Contextual-connected TV advertising is bringing the magic of contextual targeting to CTV, allowing advertisers to target viewers based on the content they are currently watching. Contextual CTV targeting goes beyond generic demographics or browsing history and dives into the details of a viewer’s current channel, show, or genre. To determine what genres and programs work best for them, advertisers leverage information like descriptions, keywords, and genre classifications.
Post-analysis, the ads are aligned with the content being watched, thus improving the chances of ads appealing to the audience as they find them relevant and engaging. By analyzing the specifics, Contextual CTV goes beyond broad genre targeting and focuses on analyzing specific themes, topics, and emotions of programs to ensure a good fit for the ad. This evolving landscape of advertising is reshaping how brands connect with audiences through connected TV advertising.
Seedtag Contextual TV
We’ve been closely observing market trends and decided to bring our Open Web expertise to the CTV landscape. For 10+ years, we have been partnering with businesses and helping them connect with their audiences using technology we developed in-house for user understanding and targeting.
At Seedtag, we analyzed the CTV advertising space and uncovered the limitations around targeting precision. We aimed to empower advertisers to overcome the most traditional challenges:
- Targeting: Going beyond generic categories and genres with precise targeting capabilities.
- Reporting - Accessing valuable attention metrics and gauging the effectiveness of campaigns.
- Ad creatives - Creating ads that capture attention through an objective-led creative strategy .
Our objective was to explore how we could transfer all the possibilities and learnings from the open web campaigns to CTV, and we mapped topics between the two ecosystems. With Contextual TV, we are identifying audiences in the open web and bringing the benefits and granularity that we offer to CTV advertising through programmatic advertising:
- Comprehensive reporting to truly measure success.
- Engaging creatives that get attention.
- Targeting beyond genres.
- Maximize viewer attention.
How to manage the future of Connected TV
With Contextual TV by Seedtag, we are taking the learnings from our open web analysis and transferring that knowledge to find users in the CTV space. This allows more precision as we go beyond the genres and limitations of traditional CTV targeting methods.
Leverage our unmatched targeting capabilities, powered by the data extracted from the open web, to discover untapped opportunities and engage with the right audience at the right time, with the right message. These campaigns can reach a more targeted audience base and improve overall engagement. With the rise of smart TVs, advertisers must stay ahead by leveraging innovative solutions that enhance the ad experience.
Want to learn more about CTV and our exclusive contextual approach to CTV? Register to Seedtag Academy and become an expert on all things CTV!
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At this point, Google’s intentions to phase out third-party cookies from Chrome are no surprise to anyone. But how has this transition actually played out, and why does the deadline keep getting extended? Google Q1 2024 report, published by The UK’s Competition and Markets Authority (CMA) and Google, shared the latest update on the timeline for the phase-out of third-party cookies on Chrome. In the report, Google recognized ongoing challenges related to reconciling divergent feedback from the industry, regulators, and developers, and said they will continue to engage closely with the entire ecosystem. Google also said that the CMA must have sufficient time to review all evidence including results from industry tests, which the CMA has asked market participants to provide by the end of June.
Citing these reasons, Google revealed that they will not be able to complete the phase-out of third-party cookies during the second half of Q4. However, the news doesn’t come as a complete surprise to those who have been following the cookie phase-out space.
Google Chrome third-party cookie depreciation: A timeline
As a part of its broader initiative to improve user privacy and create a more sustainable web ecosystem, Google first announced its intention to deprecate third-party cookies in January 2020.
- After announcing its intention to phase out support for third-party cookies in Chrome, Google worked with the web community and engaged with various industry stakeholders to gather feedback, as part of a larger initiative called the Privacy Sandbox, and explore alternative solutions to third-party cookies.
- The Privacy Sandbox initiative introduced a set of proposals for privacy-preserving advertising and measurement solutions.
- Google provided an update on the Privacy Sandbox, outlining potential solutions like Federated Learning of Cohorts (FLoC) for interest-based advertising while preserving user privacy.
- From the original deadline of 2020, Google shifted the phase-out to mid-2023.
- However, Google acknowledged the need for more testing and refinement of Privacy Sandbox APIs before complete removal, pushing back the date again to 2024.
- In late 2023, the testing phase began, and in early 2024, third-party cookies were restricted for 1% of Chrome users. Later that year, Google further expanded the test group to 20% of Chrome users.
- In April 2024, Google announced another delay, pushing back the full phase-out to early 2025, citing ongoing discussions with regulators and the need for further testing.
As it stands today, third-party cookies remain restricted for a portion of Chrome users as testing continues. However, the official phase-out is expected to be completed in early 2025.
You can view the latest update report on the implementation of Google’s Privacy Sandbox here.
The future of advertising
While Google’s plan to phase out third-party cookies will not be complete in 2024; it is merely a delay but imminent. Brands and agencies have already begun opting out of legacy, audience-based targeting practices and embracing privacy-compliant and effective alternatives like contextual advertising.
Leading global brands are using this time to test newer alternatives, better understand them, quantify the value created by these solutions, and how they can be incorporated into targeting playbooks to ensure a smooth transition once cookies inevitably disappear.
Contextual advertising is quickly emerging as one of the most sought-after alternatives to cookie-based targeting practices as it offers a privacy-compliant and non-intrusive way to reach the desired target audience. Powered by next-gen tech like AI, ML, and NLP, contextual advertising analyzes both the written and visual content of a web page, enabling brands to deliver ads on relevant websites that target relevant audiences without the use of cookies.
Powered by Liz, our pioneering AI technology, we at Seedtag offer future-proof, thoroughly tested contextual targeting solutions that find and engage with nuanced audiences and capture their attention by aligning with their current line of interest. Popular brands like KIA, Pedigree, LG, and Garnier have partnered with us to implement a superior AI-powered contextual advertising strategy to achieve higher accuracy and better ROI.
The results?
- KIA saw a 43% increase in brand awareness for contextual ads versus 18% for cookie-based ads
- Pedigree noticed a 61% increase in messaging association
- LG observed a 53% uplift in CTR
Want to learn more about our contextual advertising solutions?
For many years, brands were able to leverage the benefits of third-party cookies to help them identify consumer behavior and target them online with ads. Consumers were not particularly pleased with this approach and considered it an intrusion of privacy. This focus on data privacy became especially relevant in 2020 as online activity sky-rocketed, with most people staying home.
Companies like Apple have already moved to phase out third-party cookies, with Google looking to complete the same by 2024. With acts like GDPR and CCPA put in place by governments, the death of third-party cookies and other means to identify online behavior was welcomed by consumers; advertisers did not share the same enthusiasm.
The marketing and advertising industry has again looked to technology to solve the same challenges technology has created.
Contextual advertising emerged as one of the relatively easy options for companies to adopt and ensure they could still target consumers with some degree of certainty. It showed more significant benefits in targeting, increased sales, improved adherence to brand safety and suitability, and much more.
Reports estimate that the global market for contextual advertising will reach a size of US$335.1 Billion by 2026, growing at a CAGR of 13.3% over the analysis period.
Contextual advertising is all about analyzing the web page's content and context to determine whether an advertisement is relevant and suitable to that page. The tools in the market today allow brands to study a variety of parameters including keywords, page type,media channel, positive or negative connotations and more, without the use of third-party cookies.
Brands are able to optimize ad positions and deliver relevant and engaging communications with the target audience. The goal of contextual advertising is to make the ads as relevant as possible to the user to increase their chances of clicking on the ad. For example, someone reading a webpage on golf is more likely to buy golfing equipment and related apparel than possibly place an order for fast food.
Contextual advertising is continuously being refined by technologies like AI, machine learning, natural language processing and more. For the longest time, AI was confined to the realms of science fiction, books and movies. However, the science fiction of yesterday has become the reality of today. The advertising world got its first taste of the power of AI when Lexus released an advertisement entirely scripted by AI. By studying over a decade of award-winning car advertisements, Watson from IBM identified the winning elements and put them together in a single ad.
With AI, brands are able to gain actionable insights with regard to context behind digital content beyond just keywords and user behavior. AI is helping brands determine suitability of an ad in correlation to a webpage with greater accuracy, determine optimal spots for ad placement to yield higher returns on ad spend, enhance targeting through real-time analytics, deliver more relevant and personalized experiences to readers and much more.
Marketers and advertisers prefer to leverage AI to palace contextual ads than third-party cookies for various reasons. Some of the top reasons include the following –
- Adherence to data privacy - Third-party cookies have been under scrutiny for their potential impact on consumer privacy. Cookieless advertising methods, such as AI-powered contextual advertising, do not rely on personal data from users to target ads. AI can analyze data from first-party sources to create a complete picture of the user. This includes demographics, first-party customer data, interests, and behavior, which can be used to target ads more accurately.
- Improved targeting – AI algorithms can analyze and understand the context of a webpage or app beyond just text and keywords. These algorithms can optimize ad campaigns by adjusting targeting by studying performance metrics such as click-through and conversion rates to know what ads work in the page's context. AI-based NLP is even able to understand the intent behind a search query, allowing for more accurate ad targeting. AI is also helping brands locate the optimal spots for ad placements so as to ensure maximum return on advertising investments
- Enhanced personalization - Consumers today find most digital ads to be disruptive to their online experience. AI is helping address this challenge by not only finding the best spot to place the ad, but deliver the ability to blend ads into images or video more seamlessly into the larger webpage content, that is more attractive and interesting to readers and enabling a higher quality experience and subsequently returns
- Increased brand safety and suitability – AI algorithms can also identify negative articles, fake news, fraudulent articles, etc., and avoid placing content there to enhance favorability with audiences and avoid financial losses. When going beyond browsing data, AI allows brands to ensure that users see ads in the proper context. AI can also detect and prevent fraud, such as bots clicking on ads, making the advertising ecosystem more secure.
The market spending for AI in marketing is expected to grow significantly in the coming years. According to a report by Markets and Markets, the global market size of AI in marketing is expected to reach USD 40.09 billion by 2025. AI constantly improves, learns, and adapts as needed to make better decisions. This will allow brands to future-proof their targeting efforts and advertising spending as the market evolves. Cookie-less advertising is the future of digital advertising, and AI is set to usher in a new era of contextual advertising. If you are yet to adopt contextual advertising and technologies like AI to improve the return on your marketing investments, contact us at Seedtag today.
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The privacy era will reshape the ad tech landscape, and contextual advertising is set to emerge as a lynchpin for brands looking to adopt effective, privacy-first ad strategies.
According to research, the global digital advertising market is projected to reach 562 billion USD by 2030, growing at a CAGR of 13.8%.
With the progressive loss of effectiveness of third-party cookies and the introduction of data privacy laws, brands must explore privacy-first, future-proof alternatives. Contextual advertising is emerging as a frontrunner as it bridges the gap between privacy and targeting. The traditional practice of relying on personal information will not make the cut going forward.
How Contextual Advertising is Shaping the Future of Advertising
The shift in focus: Quality over Quantity
For the longest time, both advertisers and publishers have relied on data collected through profiling to attract audiences and make ad-buying decisions. The focus has always been on bringing in a large number of general audiences and never on what truly interests them. These traditional methods solely rely on the intrusive collection of personal data not backed by any other privacy-first approach.
This method of automated or programmatic ad buying has had a significant impact on the quality of content online. Programmatic advertising focuses on reaching a broad audience, thus incentivizing publishers to prioritize the volume game and diluting the emphasis on catering to specific audience interests.
But with the spotlight on data privacy laws and the progressive loss of reach of third-party cookies, the emphasis is back on content quality over engaging with generic audience pools. Contextual advertising offers a privacy-compliant alternative to display ads on relevant websites that target relevant audiences beyond just using cookies.
The rise of contextual advertising
Artificial Intelligence (AI) and Machine Learning (ML) have already made their way into various walks of life, and the advertising industry is no exception. AI-powered contextual advertising has the ability to analyze the written and visual content on a web page and display relevant ads that reach the desired targeted audience.
With rising privacy concerns and the progressive loss of reach of third-party cookies, contextual advertising is poised for significant growth in the coming years. It offers a more privacy-compliant and relevant way to target consumers compared to traditional methods by providing a solution that balances user privacy with effective targeting.
The Role of AI in Contextual Advertising
AI and machine learning are transforming the way digital ads are placed in the advertising industry. By analyzing consumer behavior and the content of web pages in real time, AI-driven ad campaigns ensure that ads are displayed in the most relevant ad space. Evolving at a rapid pace, and brands must adapt to the new reality where third-party data is no longer the gold standard. This method not only increases engagement but also prevents ads from being placed near inappropriate content, ensuring brand safety.
By leveraging first-party data and AI-powered contextual advertising, advertisers can make data-driven decisions without compromising consumer privacy. This privacy-first approach aligns with data protection regulations like GDPR and CCPA, ensuring brands remain compliant while still delivering highly relevant online ads.
A Privacy-First Future of Advertising
Privacy-first marketing strategies will shape the future of advertising as consumers demand more control over their data. As regulations tighten and consumers become more aware of their personal data, businesses that adopt contextual advertising will stay ahead in the digital advertising landscape. Those who fail to embrace it, risks falling behind as the industry shifts towards a more secure, transparent, and ethical future.
Additionally, linear TV is losing its dominance to Connected TV (CTV) and digital platforms, making programmatic advertising and contextual targeting the best strategies for brands looking to maximize ad spending while adhering to data privacy laws. Building niche audience segments, leveraging first-party data, and exploring new-age strategies like CTV advertising are a few among the myriad opportunities contextual advertising offers.
Contextual advertising is not just an alternative to cookie-based tracking; it is the foundation of the future of advertising. By focusing on real-time analysis, AI-powered targeting, and privacy-first approaches, brands can build trust and loyalty with their audiences. Interested to learn more about how you can benefit from contextual advertising?
As the number of consumers moving online grows at a meteoric pace, brands today are doubling down on the effort spent to understand and control what kind of online content their ads run along with. Growing consumer focus on brand reputation and data privacy have every brand treating ad placement with kid gloves.
Until 2019, brands defined their own rules and strategies of what was considered appropriate in the online space. It was in 2019 that the focus on brand safety and brand suitability saw a concrete direction with GARM.
For the uninitiated, GARM stands for the Global Alliance for Responsible Media. It is an industry-led initiative founded in 2019 that aims to improve the safety and sustainability of digital advertising, reduce harmful content online, and promote integrity and accountability in the digital media ecosystem.
Since the standard procedures and guidelines have been defined by representatives of agencies, advertisers, media platforms, and industry bodies, GARM is widely regarded as having set the brand safety and suitability standard for all to follow.
Despite the standards being defined, a report featured in The Guardian in 2020 found that over 100 big brands like Samsung, Decathlon, Audi, L'oreal were unknowingly running their advertisements on YouTube videos on the site that were actively promoting climate misinformation. These incidents highlighted the need for greater transparency and responsibility in digital advertising practices and underscored the importance of initiatives like GARM.
Brands can demonstrate their commitment to responsible advertising practices by aligning with the practice set forth by GARM in the following manner –
- Understand the GARM Framework - A comprehensive grasp of the brand safety floor and suitability framework enables organizations to identify hazardous content and convey an incorrect message about brand values, which can significantly affect consumer perception. Without knowing the tools that one is working with, building a successful concrete campaign would be improbable.
- Audit existing brand campaigns and partners – Once you know what the playing field looks like, you must audit your brand's advertising practices and make changes as necessary to ensure compliance with GARM standards. This is not limited to just the company that owns the brand itself but needs to extend into the larger ecosystem to ensure partners, including media platforms and agencies, and everyone responsible for developing and implementing brand campaigns understands and implements the standards thoroughly. For example, in 2020, Unilever announced that it would stop advertising on Facebook, Instagram, and Twitter in the United States until at least the end of the year, citing concerns over hate speech and divisive content on the platforms.
- Leverage relevant tools and technologies to monitor the brand: Leverage available technologies and tools, such as brand safety verification services, to monitor where your ads are being placed and ensure that they do not appear next to harmful content. With the growing focus on contextual advertising, brands can leverage advanced tools like AI to determine brand suitability and contextual fit. Brands like P&G and Nestle are already experimenting with AI in market analysis and product development, analyzing ad placements in real-time and ensuring that ads are not appearing next to inappropriate content.
- Given the pace of change in the digital advertising landscape, the renewed interest in contextual advertising, and the bright spotlight focused on brand suitability, it is essential for brands to continuously engage with the GARM community and work with partners who understand how brands can thrive in the digital space.
We at Seedtag understand the digital advertising landscape and possess the relevant technical knowledge to ensure that brands can grow in today's world. Do write to us to know how we can audit and help your brand stay safe by adopting the latest GARM standards.
The cord-cutting era is here! We’re officially in the age where streaming services have changed the course of television and how content is delivered worldwide. As a result, the shift from traditional TV (Linear TV) to Connected TV (CTV) is also impacting the landscape of online ads, making them more dynamic, interactive, and personalized for viewers.
According to a survey, 2023 was the first year non-pay TV households stood at 68.7 million vs. traditional cable at 62.8 million, outnumbering cable connections for the first time in the United States. Broadcast and cable fell below 50% of all TV usage, and Statista revealed that in 2023, 88% of U.S. households owned at least one internet-connected TV device. The number of CTV users totalled more than 110 million among Gen Z and Millennials.
What is CTV? Laying the Foundations for CTV advertising
Connected TV refers to the device that delivers streaming content, a rapidly growing market with increasing popularity. The past years have seen a growing cord-cutting trend, as people are canceling traditional cable and switching to streaming services. Connected TVs have become the most sought-after and popular choice among the masses as they offer a vast library of content beyond traditional channels, the freedom to browse in one's own time, and choose content that aligns with one’s interests.
Connected TVs give users on-demand access to streaming services like Netflix, Hulu, Disney+, and HBO Max which stream movies, TV shows, documentaries, and even live programs. Flexibility, content diversity, convenience, and overall experience are among the top reasons why people increasingly turn to Connected TV.
The change in trend and massive viewership have naturally garnered the attention of advertisers too. Brands want to display their ads where their audiences are, and today, CTV advertising has gained a top spot. CTV advertising allows brands to reach this growing audience base by offering far superior audience targeting capabilities, higher engagement rates, deeper insights, and measurable results.
CTV advertising is transforming the digital ad landscape, allowing brands to reach highly engaged audiences with more precise targeting. Unlike traditional display ads, CTV ads offer immersive, full-screen experiences that drive higher engagement and brand recall.
Advertising tips: How to choose the right CTV partner for your brand
A strong CTV partner should offer advanced ad tech solutions, including programmatic ad buying, to optimize placements and maximize reach. This ensures advertisers can automate their media buying processes efficiently while targeting the right audiences at the right time.
Inventory quality
Advertisers need to be mindful of the quality of the inventory and its relevance to their brand and audience. Brands need to target their audience effectively and avoid irrelevant placements. Rather than choosing any CTV partner based on demographics or audience types, the focus should be contextual relevance. Placing ads that align with the content audiences are engaging which ensures better engagement.
Brands must also know what type of content will accompany the CTV ads. While CTV ads can be placed across various platforms, the inventory must comprise premium and professionally produced content to attract the right audience and capture their attention. The right CTV partner helps advertisers place ads alongside content the audience trusts, thus going beyond just engagement, elevating brand credibility, and increasing brand loyalty.
Brand safety and brand suitability
As advertisers unlock CTV inventory, it is important to ensure ad messaging and placement are optimal. Ads appearing alongside content that is offensive or harmful can have a negative impact on a brand's reputation. Advertisers must pick CTV partners who provide tried and tested brand safety expertise and contextual relevance to suit the brand’s values, messaging, and positioning.
Many CTV partners leverage AI in advertising, using AI-powered tools and AI and machine learning algorithms to analyze metadata and ensure brand safety. They analyze metadata like the descriptions of CTV videos and titles to determine safety and relevance. It’s crucial to go beyond just metadata and analyze the full content of a video to assess safety and suitability. Brands must gain a complete understanding of a video’s suitability before finalizing a campaign or any ad placement.
This approach goes beyond simple keyword scanning, allowing advertisers to understand the full context of video content and make informed decisions on ad placements."
Reporting capabilities
Like any advertising campaign, understanding performance in-depth for attribution measurement is critical for advertisers. Beyond real-time metrics, brands can analyze search results to evaluate audience interest after exposure to CTV ads. The effectiveness of CTV campaigns relies on analyzing party data and other data collected from audience interactions to better understand consumer behavior.
By tracking how often users search for a brand or product after seeing an ad, advertisers can gain deeper insights into brand recall and effectiveness. When picking a CTV partner, brands must analyze what metrics will be accessible to measure the impact of CTV ads. Transparency of campaign performance and reporting is critical to evaluate ROI.
How did the target audience engage with the brand after viewing an ad, what was the viewer intent and how did the ad impact this journey, what action did they take after viewing the ad, etc. are key metrics that advertisers must have access to. Brands must ensure real-time reporting and insights into metrics like impressions, reach, completion rates, and frequency for transparency.
Enhancing CTV Campaigns with Effective Advertising Tips
To maximize the effectiveness of CTV advertising, brands should adopt advertising tips that enhance their overall campaign strategy. Incorporating eye-catching creatives ensures that ads capture audience attention and leave a lasting impression. Additionally, brands should integrate email marketing strategies such as email newsletters to complement CTV ad campaigns and maintain ongoing engagement with their audience.
Using programmatic ad buying can also improve efficiency by automating ad placements, ensuring that brands reach the right audience at the right time. By leveraging AI-driven insights, advertisers can fine-tune their CTV advertising efforts and optimize results.
Introducing Contextual TV by Seedtag
Seedtag’s latest offering for the Connected TV ecosystem, Contextual TV aims to extend our contextual expertise to enable brands to activate strong CTV campaigns with precise targeting capabilities that go beyond the standard targeting practices.
CTV has now become one of the most effective ways to target audiences, especially the new generations like the Millenials and Gen Z, who have cut the cord. For over a decade, we at Seedtag have been empowering brands to effectively connect with their audiences using our unmatched technology that provides superior targeting capabilities and user understanding.
With Contextual TV, we’re not just adapting to trends, but actively helping to shape the future of advertising in the CTV space. Brands can now leverage open web benefits for the big screen, eliminating today’s limitations of targeting precision and reporting in the CTV advertising landscape.
- Combining the Open Web with Connected TV empowers brands to explore, uncover untapped opportunities, and engage with the right audience at the right time with the right message.
- Comprehensive reporting options to ensure you truly understand the effectiveness of your campaigns.
- Engaging creatives that garner audience attention.
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Trust, reputation, review, and recommendations play a critical role among consumers today, during any decision-making process. Customers want to purchase from a reputed brand. Thus, brands invest significant budget and workforce to ensure their image and reputation are built and safeguarded at all times.
The public's overall perception of a brand is forged over a period based on the brand’s values, messaging, reviews, and the customer’s interactions and experiences with the brand. The brand image focuses on the messages a business intends to convey through marketing, design, and communication efforts. Brand reputation reflects trustworthiness, ethics, reliability, the quality of their products or services, and the high-quality advertising content they create and place.
Advertising plays a key role in making or breaking a brand’s image and reputation: The messaging and creatives floated by brands through their ads are a direct reflection of their ideas and values. So, the ads a brand creates and where it chooses to place them have a crucial impact on consumer perception. Effective ad campaigns should take into consideration brand safety, ensuring that the messaging aligns with the company’s values and avoids harmful contexts.
For example, a children's toy company running ads on a website or article that features explicit language or violent content can negatively impact how they are perceived. Similarly, a brand that sells vitamins or fitness products placing ads on a platform that promotes unhealthy lifestyle choices and dangerous behaviors such as extreme dieting or risky physical activities, it goes against its fundamental values.
Brand safety: The need of the hour
Today, there is an ever-increasing need to be mindful of the advertising content created and where they are showcased, making way for the implementation of brand safety and suitability measures. These advertising practices aim to shield a brand's image and reputation from being negatively impacted by online advertising placements.
Whether it is social media or the web universe, ad placement plays a critical role in ensuring brands avoid content that may harm their image, maintain trust with consumers, and build their reputation. To protect your brand’s image, it is essential to ensure that your ads do not appear in inappropriate contexts or next to harmful content. So, the focus lies in making sure brand ads do not show up next to content that could be considered harmful or inappropriate.
Factors pose a threat to brand safety in today’s digital landscape
- Placing ads in inappropriate or controversial contexts using exclusion lists, etc.
- Ad placement alongside unrelated or conflicting content.
- Brand presence besides fake news or misinformation, preventing ads from showing alongside unrelated or harmful content.
- Losing precious advertising dollars to ad fraud on dubious websites set up to generate false clicks.
- Data breaches or data privacy violations of precious consumer information.
The deprecation of third-party cookies has already put contextual advertising as a front runner in the digital landscape. However, contextual AI’s ability to ensure the highest levels of brand safety and suitability is another reason that makes contextual ads an ideal alternative to cookie-based advertising practices. Contextual advertising and AI advertising enable a brand to target relevant audiences while ensuring the ads align with its values, thus protecting its reputation.
The spotlight on brand safety and brand suitability
Contextual advertising relies on Artificial Intelligence (AI) to deliver ads on relevant websites that target relevant audiences without the use of cookies. Contextual advertising’s Machine Learning (ML) and Natural Language Processing (NLP) capabilities go a step further and have the ability to understand nuances in language and semantically interpret editorial content.
By analyzing the written and visual content of a page, contextual advertising offers brands an environment where the values and ideas seamlessly fit with their image and values, thus ensuring the highest levels of brand safety. Additionally, brand suitability helps bridge the divide between risk and opportunity and provides context-based protections.
The merge of brand safety and suitability
It helps brands elevate their targeting strategy:
- Shields your brand image and reputation from any negative impact
- Prevents your ads from appearing alongside harmful or inappropriate content
- Aligns ad placement with content that reflects brand identity and values .
- Places ads where they resonate with the right audience.
What can we expect of the future of brand safety and suitability
With brand safety and suitability, brands can navigate tricky spaces where there is a risk of exposure to controversial and harmful content. For instance, a website that focuses on financial news might cover some topics that brands might deem unsafe. However, websites that cover topics like finance or the stock market might be a great bet for a luxury watch brand. Therefore, strategic ad placement plays an important role in maximizing opportunity and impact.
As we venture into the future of digital marketing, the combination of brand safety and suitability emerges as a guiding light for brands seeking to safeguard their reputation while maximizing their reach. By embracing contextual advertising and its contextual AI capabilities, brands can confidently navigate the complexities of online advertising, secure in the knowledge that their message is not just heard, but heard in the right place, at the right time, by the right audience.
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Connected TV or CTV advertising is swiftly becoming a core advertising strategy as internet-connected televisions take over households and the interest shifts towards content streaming platforms. Leichtman Research Group reported that 88% of US households own at least one Internet-connected TV device. The number of adults in the United States households who watch videos on a TV via a connected device daily rose from 6% in 2013 to a staggering 49% in 2023.
Audience inclination toward CTV from traditional television has shifted the spotlight to CTV advertising, making it the next big thing in the ad tech space for brands seeking to reach their target audiences. Brands need to be where their audiences are and make their presence felt. With the audience behavior shifting toward streaming platforms, understanding consumer behavior is essential for brands to adapt their advertising strategies accordingly. Likewise, dedicating a significant amount of time in their day-to-day to spend on streaming platforms like Netflix, Amazon Prime Video, Disney+, and Hulu; it is only obvious that brands are changing gears in their ad strategies and allocating more more advertising budgets to CTV ads.
Beyond just the viewership
While the rising viewership numbers are an important factor that is shining the light on CTV advertising, another critical aspect is brand safety. Maintaining brand reputation is imperative in today’s chaotic digital landscape where there are myriad stories, news pieces, opinions, and debates. As a more regulated and transparent medium, Connected TV offers a safer space for brands to engage with the audience in the digital age.
Brand safety refers to the practice of protecting a brand's online reputation and image by taking steps to prevent its ads from appearing alongside inappropriate or harmful content. For example, no brand would want its ads to appear next to content about hate speech or terrorism. Similarly, a fast food chain will not want ads to appear in an article about heart attacks or a travel company’s ad next to news around layoffs or economic downturns.
Tackling Ad Fraud and Viewability in the CTV Advertising Landscape
As CTV advertising continues to shape the modern advertising landscape, brands must also consider the impact of ad fraud and viewability challenges. Unlike traditional TV, where ad placements are predetermined, CTV operates in a dynamic digital environment where fraudsters exploit loopholes through practices like device spoofing and invalid traffic.
To ensure both brand safety and budget efficiency, advertisers must leverage advanced verification tools and collaborate with trusted ad tech partners. Implementing AI-driven fraud detection and adopting programmatic transparency measures will help brands safeguard their campaigns from wasted ad spend and reputational damage.
Brand safety and Connected TV (CTV)
A survey revealed that 70% of advertisers felt brand safety incidents impacted their campaigns. It also showed that 67% of brands said they believe they are taking a serious financial risk by not addressing brand safety online. 37% of brands have experienced a brand safety issue and the worldwide advertising dollars wasted due to a lack of brand safety in 2019 was estimated to be $14.8 billion.
While there is transparency in the inventory and regulations in the space, CTV advertising is still a struggle for brands and advertisers when it comes to a buying environment. They need a more in-depth understanding of the inventory and where their ads will appear. With no industry-wide protocols in place yet and a lack of transparency on what marketers are buying, the need of the hour is visibility. Brands and marketers need real-time visibility of ad placement to prevent their ads from appearing in inappropriate or harmful environments and requiere to be watchful of ad placement to prevent their ads from appearing in inappropriate or harmful environments.
A mix of reputable inventory sources and contextual relevance is a tactic many brands are opting for to overcome the brand safety issues that the sought-after CTV advertising currently poses. Analyzing and reviewing media buying at a content level can help alleviate brand safety concerns by ensuring the content is not just safe but relevant too.
With contextual advertising-backed CTV targeting, brands can address both brand safety and brand suitability. By analyzing the content and context of shows, contextual targeting empowers brands to place their ads alongside the most brand-safe and relevant content. Users are more likely to engage with an ad that aligns with the content they are currently viewing, thus driving engagement and ad recall by garnering more impactful consumer attention.
Relevant and engaging content creates a great connection with the user, increases the time users spend on an ad, and goes beyond just visibility to deliver meaningful engagement. CTV ads bolstered by contextual targeting help brands better navigate the relatively new ad space, improve ad targeting, deliver more impactful outcomes, and enhance the overall brand impression.
The Future of Brand Safety in CTV Advertising
n today’s evolving advertising landscape, winning brand safety in CTV advertising requires a multi-faceted approach that combines transparency, technology, and strategic media buying. As brands continue to shift budgets toward CTV, adopting proactive safety measures, such as contextual targeting, premium inventory selection, and third-party verification, will be key to maintaining brand integrity. By staying ahead of industry developments and investing in secure advertising practices, brands can maximize the potential of CTV advertising while ensuring their message reaches the right audience in a safe and suitable environment.
In today’s privacy-first world, , cookie-based targeting has been a central pillar that both advertisers and publishers have relied on heavily for decades. According to a Deloitte survey, the average projected revenue risk ranged from around $91 million to $203 million per year, with some companies risking upward of $300 million in revenue. A Google study showed that for the top 500 global publishers, the average publisher revenue decreased by 52% with a median per-publisher decline of 64%.
Publishers who have exclusively relied on third-party cookies have begun to feel the heat. Much like advertisers, publishers have been evaluating other strategies to help them grow their revenue while remaining privacy-compliant. Beyond business-as-usual, the progressive loss of signal and reach of cookies presents publishers an opportunity to future-proof their business and generate new revenue streams. This approach is not just a short-term fix, but a sustainable, long-term strategy to future-proof the business against privacy changes.
How are publishers riding the Data Privacy-First World wave?
Publishers are looking to continue to expand their readership and audience trust and audience trust in a privacy-first world, where privacy compliance and transparent data usage are becoming paramount. While large tech companies have traditionally dominated the advertising space, publishers are now taking more control over their ad inventories through privacy-compliant solutions.
Topics API is the Privacy Sandbox entrant that was initially introduced as an alternative to third-party cookies, to enable privacy-first, interest-based advertising. To make the most out of Topics, publishers and advertisers must use them with other tools to develop more innovative marketing strategies that cater to the new-age audiences.
Leveraging First-Party Data for Better Targeting
While third-party data has been a staple for targeting, publishers are increasingly focusing on first-party data, which is more reliable and privacy-compliant. Information that audiences willingly share can be used alongside Topics for a more tailored and relevant targeting approach. First-party data is a gold mine that publishers can leverage to monetize audiences and boost revenue numbers. Secure collation of first-party data is essential to collate privacy-safe media that can be monetized by publishers, but they must be cautious with personal data, ensuring that they only use it with user consent and in accordance with privacy regulations with the General Data Protection Regulation (GDPR) to avoid potential legal risks.
"The amount of data publishers can collect from first-party sources is growing, allowing for more personalized and relevant ad targeting".
Evaluating and Upgrading Tech Stacks to Enable Privacy-Safe Data Collaboration
Publishers are working towards evaluating their current tech stacks and upgrading them to create more data clean rooms that enable privacy-safe media collaboration. Publishers can collaborate with advertisers and monetize the data by giving them access to the valuable repository. Effective consent management is crucial for publishers to ensure that the data they collect is used appropriately and in compliance with privacy regulations.
AI-Powered Contextual Advertising: Boosting Monetization and User Experience
AI-powered contextual advertising offers publishers a cookie-free solution that aces targeting and better utilizes first-party data. Contextual ads are proving to be a game-changer for publishers by enabling them to navigate privacy regulations and create a sustainable monetization strategy.
- Contextual AI analyzes the written content of a page and empowers publishers to provide advertisers with an environment that offers the highest levels of brand safety and suitability. Machine Learning (ML) and Natural Language Processing (NLP) capabilities of contextual advertising enable understanding of nuances in language and the ability to semantically interpret editorial content. Brand suitability bridges the divide between risk and opportunity and provides context-based protections for advertisers and publishers. Brand safety ensures they steer clear of any negative or harmful content that can impact user perception and damage the reputation of publishers or advertisers.
- With contextual ads, publishers can have a higher impact on users as they are relevant ads displayed alongside high-quality content. The ads are more relevant and impactful as they speak more directly and personally with the readers, increasing the likelihood of users paying attention and engaging with contextual ads. Publishers who host contextual ads unlock a new, steady revenue stream as the relevance to the content users are currently consuming increases brand recall. Better brand recall and ROI on dollars spent increase the chances of advertisers continuing to buy inventory. By using AI-powered contextual advertising, publishers can expect higher conversion rates as ads are more relevant to the audience’s interests.
- Contextual advertising also enables publishers to enhance the overall user experience. Contextual ads are more relevant to the real-time interests of users, are less intrusive, and do not hamper their browsing experience. A more pleasant overall experience will help publishers grow their readership as users are more likely to come back and recommend them to other readers. It allows publishers to focus on reaching and engaging the right audience, ensuring that the ads displayed are highly relevant and impactful.
Collaborating with a contextual partner will help publishers unearth new monetization opportunities and provide a superior user experience. Engaging creatives, content alignment, and intelligent ad placement ensure contextual ads are seamlessly integrated with the on-page content, thus maximizing visibility, impact, and revenue potential.
Embracing a Privacy-First World for Sustainable Growth
We have partnered with over 11,900+ digital publishers across the globe, and our combination of relevant data and new-age technology helps them make the most out of every ad placement in a privacy-first world. 80% higher viewability, 15% longer in-view time, and 1.3% more click-throughs; our unique, data-backed targeting strategies and innovative methods like custom AI, backed by our in-house contextual AI solution, Liz, have delivered exceptional results when compared to exclusively relying on cookie-based targeting practices.
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The ad tech world is steadily shifting to more inclusive and privacy-centric advertising practices that align with the requisites of consumers and data privacy regulations. Fundamentally, audience categorization has largely been based on the demographics and past behavior patterns of users. This practice is based on assumptions and stereotypes that are limiting, not always accurate, and relies on third-party cookies.
The audience selection and classification process plays a crucial role in determining the success of an ad campaign. By collecting data from various sources, advertisers leverage data to display ads to users based on their assumed interests, hobbies, and browsing activities. The main data points include -
- The websites and apps a user chooses to visit, browsing patterns and interactions, and what kind of content they engage with
- Demographics like age, gender, and location
- Interests listed by the user on platforms like social media
- Third-party data
Using this data, marketers profile potential customers who are most likely to buy their product or service and target their ads to those individuals.
What is interest-based targeting?
Consumers have become increasingly apprised of digital advertising practices and are well-informed about their data and personal information being collected whenever they are online. The increase in awareness and rising frustration of consumers around data privacy resulted in the decision to phase out third-party cookies and governments implementing more stringent data privacy regulations. Marketers are facing several restrictions today and the conventional audience categorization and targeting practices will result ineffective as they are built on stereotypes and assumptions, and are not privacy compliant.
While traditional advertising practices reach a broader audience, they are not necessarily effective as everyone who views the ad might not be interested in the product/service, leading to wasted ad spend. Consumers have access to a plethora of information and are bombarded with hundreds of ads daily. A blanket targeting approach sans any personalization or relevance is not just ineffective but could have a negative impact as it disrupts the user journey. Additionally, consumers are also using ad blockers to avoid traditional ads while streaming services give them the option to skip ads.
New-age targeting goes well beyond the conventional, identity-based targeting approach and focuses on a user’s current areas of interest and the context of the content they consume. Breaking away from stereotypes, interest-based targeting is held as a more effective, non-intrusive, and privacy-centric alternative.
The rise of interest-based targeting in the cookieless world
Contextual targeting is a strategy that focuses on categorizing consumers based on what they are interested in at present, by displaying ads that align with the content they are consuming on a web page or app. When the on-page content and context align with the ads, it ensures a seamless, privacy-centric, and non-intrusive customer experience. Interest-based targeting enables personalization and allows marketers to tailor ads to individual preferences, thus enhancing relevance and engagement. Users are more likely to engage and resonate with the ad because it aligns with what they are looking for in the moment and since the ads blend with the content they are reading, the ads don’t hamper their browsing experience.
Seedtag Contextual Audiences help brands go beyond conventional targeting practices and engage with users based on what they are looking for or interested in at the moment. Powered by Liz©, our pioneering AI technology, custom AI, contextual categories, images, and cookieless sociodemographic models, allows brands to target an audience base that’s diverse, inclusive, and relevant. Our Contextual Audiences evolve from customer input and diverse market research enabling brands to build unique and dynamic audience categories to suit specific business needs.
Interest-based targeting practices like contextual targeting empower marketers to appeal to a more relevant customer base with ads that align with their real-time interests. Contextual ads appear at the most optimal time and place with tailored messaging without violating privacy, thus helping brands reach the desired audiences with a targeting capability that is more flexible and accurate. With interest-based targeting, brands can capture user attention at the ideal moment without relying on cookies, and overcome the limitations of rigid taxonomies and stereotypes.
With Seedtag Contextual Audiences, brands can build a hyper-personalized target group. Backed by AI, this unique targeting capability provides flexibility, scale, and higher accuracy. To know more about the exclusive offering and types of contextual audiences, contact us.
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With the demise of the third-party tracking cookie just months away for Chrome users, digital advertisers who have yet to begin preparations need to catch up swiftly to navigate the transition successfully.
One of the primary alternatives to the deterministic data enabled by cookies is Google’s Privacy Sandbox, which the company describes as “a series of proposals to satisfy cross-site use cases without third-party cookies or other tracking mechanisms.” Initially composed to include audience models like Google’s Federated Learning of Cohorts (FLOC), which was sunsetted in 2022, the Privacy Sandbox includes Protected Audiences (formally known as FLEDGE or “First Locally-Executed Decision over Groups Experiment”) and other APIs that will undoubtedly dictate the contours of the market to come. Businesses across the ecosystem should consider the following details when preparing.
Reevaluating The Focus: Beyond IP Addresses
In the past, digital advertising heavily relied on tracking users through cookies and IP addresses. Protected Audiences and Google Topics moves away from this practice, emphasizing a more privacy-focused approach. It presents a challenge and an opportunity for marketers to improve performance on a device level without resorting to invasive tracking methods.
A crucial aspect of working with Google Topics is to integrate contextual information with situational and device-specific data provided by Google Topics signals. The zip code, for instance, can be a valuable contextual signal. By combining these data sources, advertisers can gain a better understanding of users' preferences and needs, all while respecting their privacy. This approach opens the door to a new world where the cohort can contribute to a more nuanced contextual understanding.
The Evolution Of Performance Marketing
As Protected Audiences and Topics contextual models become increasingly relevant, performance marketers need to adapt to the changing landscape. This transformation involves elongating the marketing funnel and focusing on strategies beyond traditional last-click attribution.
- First-Click Strategies. Performance marketers can adopt first-click strategies to recapture email addresses for retargeting or directly upload data from CRM systems. This shift might result in a longer turnaround time, possibly extending from a six-day window to 10-15 days. However, the potential benefits in terms of privacy and engagement could make it worthwhile.
- Dynamic Creative Optimization (DCO). With privacy concerns taking center stage, it's essential to shift from audience-centric advertising to context-centric advertising. DCO allows advertisers to tailor content to the context of the page rather than focusing solely on the audience. This approach ensures that ads remain relevant while respecting user privacy.
- Redefining Retargeting. Retargeting is evolving. Instead of relying solely on traditional methods, marketers can explore new avenues like email retargeting and mobile site optimizations. These practices add value for the user, offering content, discount codes, tips and trends. It's a broader approach to content marketing, where the emphasis is on reengaging with users in a more meaningful way. Loyalty programs can also play a significant role in this transformation, allowing users to choose their preferred engagement strategies.
- Contextual Lookalikes. One exciting development in this landscape is the emergence of contextual lookalikes. This approach leverages first-party data, whether it's cookie-based or segmentation data, to identify commonalities among users. Instead of relying on tracking and personal data, contextual lookalikes provide a privacy-friendly way to find users with similar interests and behaviors.
In the coming transition, choosing the right partners is crucial. Marketers should seek out tech-forward partners who are committed to responsible and privacy-conscious advertising practices. It's important to avoid partners engaged in arbitrage or those who use "AI" as a copout without a genuine commitment to user privacy.
The Importance Of Retooling Analytics
As performance marketing evolves, it's crucial to retool analytics. Media mix modeling remains essential, even if it's probabilistic. Marketers should look closely at unit economics that can lead to conversion metrics. For instance, understanding the return on ad spend (ROAS) as a "three to one" ratio requires a deep understanding of the step functions involved. This level of analysis is more critical now than ever as privacy and user consent become paramount.
The era of the Privacy Sandbox and its two main APIs, Protected Audience and Topics, signals a significant shift in the world of digital advertising. Performance marketers must adapt to these changes by embracing contextual models, moving away from invasive tracking methods and respecting user privacy. Strategies that elongate the marketing funnel, focus on context over audience and leverage first-party data offer a path forward. By selecting tech-forward partners and retooling analytics, marketers can navigate this evolving landscape successfully, ensuring both effective advertising and user privacy.
By Mike Villalobos, VP of Strategy and Partnerships at Seedtag.
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From browsers like Firefox, Safari, and Opera completely banning third-party cookies to their complete demise in 2024 with Google’s phase-out of cookies; all eyes are on privacy and global regulations. The end of third-party cookies marks the beginning of a new era in advertising as the go-to targeting practice worldwide will become obsolete.
In a survey conducted by Statista, 75% of marketers revealed that they heavily relied on third-party cookies. 45% of respondents stated spending at least half of their marketing budgets on cookie-based advertising. With the fundamentals of audience tracking, targeting, and personalization becoming obsolete, there is a lot of debate around what will be the next best approach for audience targeting that will give marketers a competitive edge.
How are marketers preparing for the cookieless world?
Among the options marketers are evaluating, contextual advertising has been one effective stand-out targeting alternative that has gotten the nod from leading global brands. Contextual advertising is backed by new-age tech like AI, ML, and NLP, paving the way for personalized and impactful advertising in the privacy-first world.
Another alternative that has been around for a while but has garnered more importance ever since the deprecation of third-party cookies is first-party data. First-party data is collected with the knowledge and consent of users when they interact with a brand’s website or advertisement, or purchase a product. However, first-party data is not a magic formula. When utilized individually, first-party data lacks the ability to scale, enhance the precision of audience segmentation, or improve ad placement.
Contextual advertising is scalable and allows marketers to create custom audiences. This opens doors to never-seen-before opportunities and delivers advertising strategies that go beyond traditional metrics like impressions and CTRs. Contextual ads rank high across impactful attention metrics that provide insights into more quantifiable data like the quality of user engagement and campaign efficacy. Contextual advertising aces granularity, accuracy, and relevance by placing ads based on the content and context of web pages, thus helping marketers go beyond stereotypical audience segmentation practices that rely on audience demographics, past browsing patterns, and assumptions.
It also ensures enhanced levels of brand safety and brand suitability. Its ability to understand nuances in language and interpret the meaning of content used within a given context empowers brands to avoid harmful or negative content and maximize opportunities. With AI-powered contextual targeting, marketers can display ads in environments where the messaging aligns with a brand’s values and positioning.
Maximizing impact with the duo
What if marketers could take contextual advertising up a couple more notches? By utilizing precious first-party data repositories along with contextual advertising, marketers can further fine-tune their strategy and maximize the impact of a campaign. Based on the audience information derived from first-party data, audiences can be further segmented based on factors like age group, gender, or location. Since this data is collated with user consent, it is compliant with all privacy regulations. With first-party data-backed audience categorization, marketers can tailor messaging to suit very specific audience segments.
For example, with the combination of intel from first-party data with contextual advertising, a brand can target its repeat customer base with a new product launch or launch an exclusive privé members-only sale. Campaigns and messaging are more tailored and relevant to the target audience, driving more impact and ROI. It can also be used to create geo-specific campaigns during a particular time of the year or during festivals that are more prominent in a particular location. For celebrations like Valentine’s Week, curated gifting ideas or product collections can be showcased to specific genders and age groups to drive more engagement.
Fueling contextual advertising with first-party data will empower marketers to strengthen their strategies and create high-impact campaigns that connect with the desired audiences. The duo ensures seamless, privacy-centric, and non-intrusive experiences that customers love.
Interested to learn more about contextual advertising and its capabilities?
Cue Lover by Taylor Swift…It’s Cupid’s time of the year and the hearts are all afloat. From roses to teddy bears, cards, and jewelry, romance is brewing strong. Couples are on the lookout for the perfect date nights and the ideal gifts to present their loved ones. World over, Valentine’s Day is one of the highlights of February.
In today’s rapidly changing environment, seasonal events like Valentine’s unfold every other day. It is important for brands to not just track, but truly understand these special occasions to capitalize on them. We analyzed the evolution of content creation and its consumption to show how this day impacts the open web. In 2023, Valentine's Day was an engaging and relevant topic, with a particular interest in high-profile couples and commercial promotions. The data showed a steady increase in the number of views as Valentine's Day approached, peaking on February 20th, with the top articles indicating a mix of celebrity news, product promotions, and romantic rumors.
So what’s trending this Valentine’s?
According to our 2024 analysis, the interest in content is mirroring a pattern very similar to that of the previous year. However, we are experiencing a higher viewership when compared to the same time period last year. As a result, we anticipate a substantial increase in views, with the peak expected to reach a staggering 500,000 views on the most prominent days!
The top category with over 15% article distribution is events and attractions, followed by pop culture and family and relationships hovering over 10%. Travel, music and audio, food and drink, and movies are the next set of categories with a 5 - 10% distribution. The last 3 in the top 10 are television, home and garden, and sports.
What are the areas of interest of the Valentine's Day-focused audience?
- Garnering over 2.82M impressions, Love Life is a key interest area where the content centers on the romantic journeys of individuals. The content interest ranges from finding a partner to tying the knot and building a family. The top keywords include power couple, baby son, beautiful family, heartfelt message, closeness, life together, and happy marriage.
- Love life is followed by Celebrities Relationships with 2.4M impressions. The content shines the spotlight on well-known celebrities and public figures, delving into the intricacies of their breakups, romantic escapes, and the elaborate ways in which they celebrate Valentine's Day. Some prominent keywords are relationship timeline, Georgina, Kardashians, Gigi, Love Island, couple, Taylor Swift, celebrity news, and daily celebrity.
- Up next is the much-talked-about Valentine’s Day Plans with 2.32M impressions. This genre places the importance on enhancing the celebration of love and connection through activities and arrangements that couples can enjoy together. This includes keywords like a romantic date, hotel, romantic stroll, romantic dinner, laser tag, authentic Italian, night sky, and outdoor adventure.
- With 2.05M impressions, Rom-Coms are next in line, emphasizing the charm of romantic comedy films and the relaxed, comforting atmosphere they provide. Some trending keywords are Ryan Gosling, Love Actually, Dicaprio, Cameron Diaz, Jennifer Aniston, comedy film, streaming platform, and pride.
- Valentine’s Day Presents come in fifth, gathering 1.53M + impressions by throwing light on the importance of thoughtful presents as a tangible expression of love and appreciation, thus enhancing the romantic connection. The top keywords are gift box, wishlist, Etsy, gift card, pet shop, spa treatment, happy valentine, chocolate, and jewelry.
These areas of interest and keywords are unique to this Valentine’s season. Seasonal audiences have a high affinity for particular environments within the content universe. Brands must engage with this audience pool by sharing the right messaging within their realm of interest at the most optimal time. This requires a shift from the ordinary.
Move beyond traditional audience segmentation based on stereotypes and go contextual to deliver a scalable strategy for the open web. With Seasonal Audiences powered by Liz, brands can engage audiences with a privacy-centric strategy during the peak of specific global seasonal events like Valentine’s Day.
As the phase-out of third-party cookies begins, marketers worldwide are pondering over ideal alternatives and weighing in on what could be the ideal replacement solutions. The DoubleVerify report, Post-Cookie Questions: The Evolution of Advertising Strategies and Sentiments revealed that publishers and advertisers are divided on which solutions they believe hold the greatest promise in replacing cookie-dependent solutions. 47.3% of publishers said publisher first-party data activation was their top choice while 49% of advertisers picked advertiser first-party data activation. Social media targeting, Google Topics, Attention-based metrics, and contextual advertising were among the other solutions.
Interestingly, the report also found that 96% of publishers surveyed said that contextual advertising capabilities will be important for their businesses in 2023. 94% of advertisers stated they were planning to rely on contextual advertising for some or most of their buys in 2023. However, contextual targeting has significantly evolved over the past few years, transforming from a mere cookie-replacement alternative to a must-have strategy for future-proof, privacy-first advertising.
The magic of AI-powered contextual targeting
Today, contextual targeting is backed by AI, ML, and NLP capabilities that enable the possibility to go beyond just keywords, understand nuances in language, and semantically interpret content. Contextual targeting’s ability to understand the meaning and sentiment of full pages of content with their complete context is opening doors to several new targeting possibilities.
For example, let’s take an article titled Makeup for Everyone: Organic products for all skin tones and types. Earlier, contextual targeting’s capability was limited to identifying that it is an article on makeup products in a lifestyle publication. The new and enhanced contextual targeting understands and interprets that it is an article on organic beauty products for people of different skin types and colors.
Contextual targeting’s ability to derive that level of granular detail about an article ergo means a heightened understanding of the readership, their mindset, and interests; fundamentally changing the way audiences are segmented and targeted. Advertisers can leverage pre-defined contextual audiences, modify them, or even build their own personalized audience segments based on who they want to reach with a particular message.
Displaying a vegan beauty product ad to women who are interested in premium beauty products that are cruelty-free, vegan, and suitable for acne-prone skin; that’s the level of granularity, accuracy, and relevance contextual targeting brings to the table. It presents an opportunity for advertisers to look beyond conventional, stereotypical audience segmentation and targeting practices that are not very detailed or precise.
Contextual targeting: More than just a cookie deprecation alternative
Contextual targeting fueled by AI is not just an option or alternative but a door to a whole new world of possibilities in digital advertising. Advertisers and publishers can finally look beyond standard taxonomies, demographics, traditional cohorts, or off-the-shelf audience segments. It’s a chance to finally break free from the ordinary and meet users within their realm of current interests, at the right time. Contextual targeting empowers advertisers to unearth new opportunities and capitalize on those that were overlooked or never even considered before. While zero and first-party data gain more importance, contextual targeting can help brands maximize the impact they can create using this data repository.
Contextual targeting’s ability to understand the meaning of content within a set context significantly boosts brand safety and brand suitability as it avoids any negative or harmful content and provides brands an environment where the values and ideas fit seamlessly with their own. In the ever-evolving digital landscape, contextual targeting presents an opportunity for advertisers to level up their strategy and win big. The difference lies in the approach; marketers who look at contextual targeting as just an option to overcome the privacy limitations won’t reap much when compared to those who go all in to make the most out of it.
Ready to shift gears and embrace new-age contextual targeting?
It’s 2024, the year of privacy is finally here. Google announced the deprecation of third-party cookies back in 2019 and the world has been abuzz ever since. The countdown has finally begun. January 4th marked the pivotal change as Google Chrome began the third-party cookie phase-out by initiating its restriction for 1% of users. Google also revealed that it plans to ramp up third-party cookie restrictions to 100% of users from Q3 2024. However, it was finally announced that the cookie deprecation would not take place as such.
With this, the digital advertising world marks a fundamental change in ad strategies and the go-to source of user targeting will soon cease to exist. Now publishers and advertisers must look for alternative approaches to reach users with tailored content that matches their preferences. As traditional, cookie-dependent practices become obsolete, the need to transition is inevitably clear. In a survey conducted in late 2022, 59% of respondents stated that they were either accelerating their readiness for a cookieless future or keeping it a high priority.
In anticipation of the cookieless future, Google introduces Privacy Sandbox. The Privacy Sandbox is Google’s initiative that aims to provide phase-out support for third-party cookies when new solutions are in place. It plays a crucial role in enabling advertisers and publishers to continue offering content online by ensuring a balance between user privacy and the sustainability of online services, reducing cross-site and cross-app tracking.
Digital marketing in the privacy-first world
Beyond Google’s Privacy Sandbox, advertisers are also exploring other alternatives to third-party cookies to make a seamless transition and create effective privacy-first ad strategies. One of the more obvious emphasis has fallen on first-party data. Data collected with the knowledge and consent of users, first-party data refers to the information that a brand collates from users when they interact with the brand’s website and marketing/advertising literature or make a purchase. This data gives advertisers insights into user preferences that help them segment audiences and deliver ads that align with their interests.
Zero-party data is always a great option as the data is directly and intentionally shared by the user to receive personalized communications from the brand. Both zero and first-party data are collected with the user’s consent and are authentic sources of information that brands can rely on as they are accurate and compliant with data privacy regulations.
Other options of programmatic advertising include demographic, geographic, or device-based targeting but these don’t offer the ability to create and share relevant content to users. Zero and First-party targeting practices are also limiting as advertisers are restricted to their existing audience base. Advertisers and publishers need a privacy-safe solution that combines relevance with scale.
Contextual targeting has emerged as a front-runner in the transition to the cookieless world as it bridges the gap between relevance and scale and offers a new-age, non-intrusive solution. Looking at data beyond a user’s browsing history or leveraging third-party cookie data, contextual targeting focuses on a user’s current interests based on the content they are consuming. Without tracking a user’s browsing patterns or using alternative IDs, contextual advertising powered by AI goes beyond stereotypes and enables precise targeting. Network Level Analysis (NLA) provides real-time insights and recognizes trends that power more effective strategies by reaching the right audiences where they are.
Contextual advertising is pushing the boundaries by transcending conventional, stereotypical, and invasive practices of categorizing users based on interests and past browsing patterns that are not always accurate. Instead, the focus lies on placing ads on web pages where the on-page content and context align with the ads. This ensures the ads match the content a user is currently consuming, maximizing relevance without violating their privacy.
Built for scale, contextual targeting empowers advertisers to create custom audience categories that align with their brand based on contextual cues. It presents an opportunity to elevate to a future-proof strategy that embraces diversity and inclusivity through a more in-depth understanding of audience preferences. Contextual targeting’s ability to understand nuances and semantically interpret content also enhances brand safety and brand suitability by eliminating the display of ads beside negative or harmful content and ensuring ad placement falls in line with the overall message and tonality of the brand.
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