AdTech Collective by Seedtag
News, trends, and insights in Digital Advertising
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.
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Phasing out of third-party cookies, brand safety and brand suitability, privacy laws, and changing customer preferences are among the top factors that have brought the spotlight back on contextual advertising in the global ad tech landscape. Contextual ads are increasingly becoming the preferred choice among advertisers, publishers, and customers today.
A factor that plays a key role in helping brands reach their desired target audience is the audience selection process. An audience refers to a group of people with similar interests and shared characteristics. This crucial element helps brands reach the right individuals who are most likely to be interested in their product or service.
Traditionally, audience categorization is a process where people are grouped based on their interests and past behavior patterns. This method is limiting because it tends to group individuals based on stereotypes, and relies on third-party cookies. Poor categorization of personas can have a negative impact on marketing efforts and campaigns as the categories are not 100% accurate, resulting in incorrect targeting and wasted ad dollars.
We live in a world that is embracing diversity and inclusivity with open arms and actively steering away from stereotypes. Brands looking to level up their advertising game need to keep up with the changing times and better understand audience preferences.
What if they could go a step further with their targeting strategies?
What are Contextual Audiences?
Contextual advertising focuses on placing ads on web pages where the on-page content and context align with the ads. Contextual audiences refer to individuals who are identified and grouped based on their online behavior and the context of the content they are currently engaging with.
At first glance, contextual audiences may seem very similar to the traditional audience categorization process where people are grouped based on their interests. However, the key differentiator is that contextual audiences do not leverage any personal data, and create audience groups solely based on contextual cues.
Instead of using the most common and typical way of grouping individuals based on personal information, contextual audiences use the power of context to group people. Contextual audiences ensure scalability, privacy adherence, and greater precision, making it a method ideal for the post-cookie world.
What challenges do Contextual Audiences solve for customers?
Contextual audiences are a targeting capability that enables brands to ace audience segmentation and targeting by displaying ads that are most relevant to them.
- With the deprecation of third-party cookies and the implementation of tighter data privacy laws, brands need a solution that empowers them to reach the desired target audience.
- Consumers have raised concerns about data privacy and do not want to be tracked or are already untrackable. In a world that puts data privacy on the front seat, this targeting capability is a great way to deliver relevant ads without violating privacy.
- It is also a great way to reach out to the most relevant customers with ads that better align with their real-time interests, using the right message, and displaying them at the right time.
Go a step further with Seedtag Contextual Audiences
The conventional way brands understand their audience does not work anymore as they are built on stereotypes, clichés, and non-privacy-compliant strategies. Contextual audiences can help brands find a diverse, inclusive, and relevant audience base using privacy-first technology.
Seedtag Contextual Audiences can help customers do all of that and more! Crafted using Custom AI, contextual categories, images, and cookieless sociodemographic models, our contextual audiences evolve from customer input and diverse market research.
Powered by Liz, our pioneering AI technology, Seedtag Contextual Audiences are built to deliver audiences that are unique and dynamic to suit specific business needs. Using AI models, our contextual audiences create a comprehensive network that generates audience categorizations that are relevant to a brand, whilst respecting consumer privacy.
Types of Contextual Audiences
To empower brands with our unique, AI-powered targeting capabilities, Seedtag offers three types of audiences:
- Signature Audiences: These are audiences defined by Seedtag and backed by insights provided by Liz, panelists, and research data. Brands can seamlessly activate pre-defined and tested audiences with clear interests and attitudes toward their products. Signature Audiences provide very accurate results with room for a certain degree of customization to better suit brand needs.
Examples: Luxury Car Enthusiasts, Adventure and Outdoor Enthusiasts, and Environmentally Conscious Consumers.
- Off-the-shelf Seasonal Audiences: Similar to contextual audiences but more focused on a particular event in time, this type has a clear start and end date for activations, and takes advantage of interest spikes throughout the year.
Examples: Black Friday sale, Earth Day awareness, and F1 Grand Prix season. - Custom Audiences: These are one-of-a-kind audiences engineered to help brands solve specific challenges. As the name suggests, this goes beyond the pre-set audiences, leverages the targeting capabilities of Liz, finds exactly where the users are, and creates a tailor-made audience targeting strategy.
What sets Seedtag´s Contextual Audiences apart from regular audiences?
Traditional audience targeting methods typically leverage cookies, and the audience categorization is based on stereotypes. This contributed to the increase in the popularity of contextual targeting methods which are interest-based. It targets the most relevant users at the right time with content that aligns with their current mindset.
However, even contextual targeting cannot solve every challenge and it has its limitations when it comes to scale. Seedtag contextual audiences go beyond these limitations and provide a targeting capability that is cookie-free, flexible, accurate, and precise.
Seedtag's contextual audiences are future-proof, thoroughly tested, built for scale, and backed by advanced AI models. The audiences are constantly updated using our network analysis capabilities to optimize targeting precision and meet KPIs. With Custom AI, our targeting capability offers unique audience definitions and real-time improvements.
We partnered with Metrix Lab to evaluate the effectiveness of our custom AI in delivering precision at scale to unique target audiences. The research revealed that using custom AI, which is the backbone of our contextual audiences, affinity went up by 92%.
- Seedtag’s Custom AI model allows brands to craft unique contextual territories based on the audiences’ interests.
- Our technology goes well beyond classic contextual technologies. We leverage external and internal innovation in the AI ecosystem to bring new capabilities like contextual audiences that go beyond standard taxonomies. For example, curating a campaign targeting automotive enthusiasts or city drivers and urban commuters.
- Brands can create unique, tailored audiences without any dependencies on cookies.
- Our targeting capability is constantly evolving and improving as it is based on real-time data from our network.
- It enables brands to engage with users at the most optimal time by effectively delivering personalized and optimized experiences.
Contextual audiences by Seedtag are advanced and garner users by capturing their attention at the ideal moment, without relying on cookies. It also addresses the reach and scalability issues that many brands currently face and is a flexible solution that goes beyond rigid taxonomies or stereotypes. The unique targeting capability fueled by AI offers greater precision and helps achieve higher accuracy when compared to traditional targeting practices.
Get in touch with us to know more about our latest targeting capabilities powered by AI models.
Phasing out of third-party cookies, brand safety and brand suitability, privacy laws, and changing customer preferences are among the top factors that have brought the spotlight back on contextual advertising in the global ad tech landscape. Contextual ads are increasingly becoming the preferred choice among advertisers, publishers, and customers today.
A factor that plays a key role in helping brands reach their desired target audience is the audience selection process. An audience refers to a group of people with similar interests and shared characteristics. This crucial element helps brands reach the right individuals who are most likely to be interested in their product or service.
Traditionally, audience categorization is a process where people are grouped based on their interests and past behavior patterns. This method is limiting because it tends to group individuals based on stereotypes, and relies on third-party cookies. Poor categorization of personas can have a negative impact on marketing efforts and campaigns as the categories are not 100% accurate, resulting in incorrect targeting and wasted ad dollars.
We live in a world that is embracing diversity and inclusivity with open arms and actively steering away from stereotypes. Brands looking to level up their advertising game need to keep up with the changing times and better understand audience preferences.
What if they could go a step further with their targeting strategies?
What are Contextual Audiences?
Contextual advertising focuses on placing ads on web pages where the on-page content and context align with the ads. Contextual audiences refer to individuals who are identified and grouped based on their online behavior and the context of the content they are currently engaging with.
At first glance, contextual audiences may seem very similar to the traditional audience categorization process where people are grouped based on their interests. However, the key differentiator is that contextual audiences do not leverage any personal data, and create audience groups solely based on contextual cues.
Instead of using the most common and typical way of grouping individuals based on personal information, contextual audiences use the power of context to group people. Contextual audiences ensure scalability, privacy adherence, and greater precision, making it a method ideal for the post-cookie world.
What challenges do Contextual Audiences solve for customers?
Contextual audiences are a targeting capability that enables brands to ace audience segmentation and targeting by displaying ads that are most relevant to them.
- With the deprecation of third-party cookies and the implementation of tighter data privacy laws, brands need a solution that empowers them to reach the desired target audience.
- Consumers have raised concerns about data privacy and do not want to be tracked or are already untrackable. In a world that puts data privacy on the front seat, this targeting capability is a great way to deliver relevant ads without violating privacy.
- It is also a great way to reach out to the most relevant customers with ads that better align with their real-time interests, using the right message, and displaying them at the right time.
Go a step further with Seedtag Contextual Audiences
The conventional way brands understand their audience does not work anymore as they are built on stereotypes, clichés, and non-privacy-compliant strategies. Contextual audiences can help brands find a diverse, inclusive, and relevant audience base using privacy-first technology.
Seedtag Contextual Audiences can help customers do all of that and more! Crafted using Custom AI, contextual categories, images, and cookieless sociodemographic models, our contextual audiences evolve from customer input and diverse market research.
Powered by Liz, our pioneering AI technology, Seedtag Contextual Audiences are built to deliver audiences that are unique and dynamic to suit specific business needs. Using AI models, our contextual audiences create a comprehensive network that generates audience categorizations that are relevant to a brand, whilst respecting consumer privacy.
Types of Contextual Audiences
To empower brands with our unique, AI-powered targeting capabilities, Seedtag offers three types of audiences:
- Signature Audiences: These are audiences defined by Seedtag and backed by insights provided by Liz, panelists, and research data. Brands can seamlessly activate pre-defined and tested audiences with clear interests and attitudes toward their products. Signature Audiences provide very accurate results with room for a certain degree of customization to better suit brand needs.
Examples: Luxury Car Enthusiasts, Adventure and Outdoor Enthusiasts, and Environmentally Conscious Consumers.
- Off-the-shelf Seasonal Audiences: Similar to contextual audiences but more focused on a particular event in time, this type has a clear start and end date for activations, and takes advantage of interest spikes throughout the year.
Examples: Black Friday sale, Earth Day awareness, and F1 Grand Prix season. - Custom Audiences: These are one-of-a-kind audiences engineered to help brands solve specific challenges. As the name suggests, this goes beyond the pre-set audiences, leverages the targeting capabilities of Liz, finds exactly where the users are, and creates a tailor-made audience targeting strategy.
What sets Seedtag´s Contextual Audiences apart from regular audiences?
Traditional audience targeting methods typically leverage cookies, and the audience categorization is based on stereotypes. This contributed to the increase in the popularity of contextual targeting methods which are interest-based. It targets the most relevant users at the right time with content that aligns with their current mindset.
However, even contextual targeting cannot solve every challenge and it has its limitations when it comes to scale. Seedtag contextual audiences go beyond these limitations and provide a targeting capability that is cookie-free, flexible, accurate, and precise.
Seedtag's contextual audiences are future-proof, thoroughly tested, built for scale, and backed by advanced AI models. The audiences are constantly updated using our network analysis capabilities to optimize targeting precision and meet KPIs. With Custom AI, our targeting capability offers unique audience definitions and real-time improvements.
We partnered with Metrix Lab to evaluate the effectiveness of our custom AI in delivering precision at scale to unique target audiences. The research revealed that using custom AI, which is the backbone of our contextual audiences, affinity went up by 92%.
- Seedtag’s Custom AI model allows brands to craft unique contextual territories based on the audiences’ interests.
- Our technology goes well beyond classic contextual technologies. We leverage external and internal innovation in the AI ecosystem to bring new capabilities like contextual audiences that go beyond standard taxonomies. For example, curating a campaign targeting automotive enthusiasts or city drivers and urban commuters.
- Brands can create unique, tailored audiences without any dependencies on cookies.
- Our targeting capability is constantly evolving and improving as it is based on real-time data from our network.
- It enables brands to engage with users at the most optimal time by effectively delivering personalized and optimized experiences.
Contextual audiences by Seedtag are advanced and garner users by capturing their attention at the ideal moment, without relying on cookies. It also addresses the reach and scalability issues that many brands currently face and is a flexible solution that goes beyond rigid taxonomies or stereotypes. The unique targeting capability fueled by AI offers greater precision and helps achieve higher accuracy when compared to traditional targeting practices.
Get in touch with us to know more about our latest targeting capabilities powered by AI models.
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Connected TV (CTV) gained popularity in the mid-2010s as internet-enabled smart TVs and streaming devices became commonplace. With the growth of platforms like Hulu, Roku, Disney and more, the spending on ads for CTV has also been rising quite steadily. According to e-marketer, CTV is one of the fastest-growing channels in digital advertising and is projected to reach $29.5 billion in 2024. Companies are seeing significant benefits from this channel, with Hulu making over $3 billion and YouTube making over $2.5 billion in ad revenues from CTV.
CTV has become an increasingly important part of the TV landscape, as viewers have increasingly turned to internet-connected devices to consume content. Like all things relatively new, this growth in the popularity of CTV as a medium for advertising has come with its own share of misconceptions and assumptions. Even the term CTV is ambiguous to many given the number of devices one can stream content on these days. Some of the common misconceptions about CTV advertising are as follows –
- CTV is only for younger audiences
While CTV has traditionally been associated with younger audiences, we saw a change in the demographics over the last couple of years. During the pandemic, there was a notable increase in not just the viewership of Gen-Z and millennial audiences, but also an increase in the number of baby boomers. CTV viewership is becoming increasingly mainstream, with a growing number of households disconnecting traditional cable TV in favor of streaming services. As a result, CTV offers a valuable opportunity for advertisers to reach a wide range of demographics, from youngsters to families to seniors, who are using CTV devices to consume content. Advertisers find the extensive demographic coverage of CTV valuable because CTV viewers are deeply invested in the content they choose to watch and are less likely to skip ads.
- There’s no difference between CTV advertising and Linear TV advertising
Numerous traditional businesses still feel that there’s a large overlap between CTV and Linear TV advertising. The reality is that the biggest difference between advertising on CTV and linear TV is the audience. Linear TV advertising tends to have a broad reach while CTV advertising can be more targeted, allowing advertisers to reach specific audiences based on demographics, interests, and behavior. Advertising on CTV allows better personalization and ensures TV viewers are more engaged and receptive to ads that are relevant to their interests. Today’s CTV advertising even allows audiences to interact with the ad, changing the very nature of advertising. Brands like Chevrolet, Pepsi, IKEA are already rolling out interactive ads.
- CTV and OTT are not the same, though they are related
Marketers continue to use the terms CTV and OTT (Over-The-Top) interchangeably. While the two are related, they are not the same. OTT is a category that includes apps and services for streaming video content, independent of traditional cable or pay-TV subscriptions. Connected TV (CTV), on the other hand, refers to the device used by the viewer to access OTT content. In other words, CTV is a subset of OTT and is the platform on which viewers watch streaming video content without requiring traditional subscriptions.
- CTV ads cannot be skipped
If we look at a platform like YouTube, for those of us not looking to pay for ad-free subscription, YouTube offers a variety of options to skip or not skip ads. Some ads can be skipped after a certain amount of time has passed, while some ads need to be viewed entirely before you can access the content. Quite similarly, CTV ads can be skipped depending on the ad format and platform used. Some CTV platforms may offer non-skippable ads that require viewers to watch them in full before returning to their content. Meanwhile, other platforms may offer skippable ads that can be skipped after a set amount of time has passed. As discussed above, some CTV ad formats may also include interactive elements that allow viewers to engage with the ad and receive a more personalized experience. It is up to the advertiser to define how to engage with the consumer using the platform on CTV.
- CTV provides only high-quality inventory
Various types of CTV inventory are available, ranging from remnants to high-quality opportunities.Advertisers can access premium inventory opportunities to showcase their ads during popular TV shows and movies, and reach engaged audiences during prime hours. The quality of CTV inventory can vary significantly depending on multiple factors such as content providers, geographic locations, ad placements, and type of content.
- Measuring ROI from CTV advertising is difficult, hence not worth it
While it is true that measuring the effectiveness of CTV advertising can be more complex than traditional linear TV, advertising on CTV is measured with very similar digital advertising metrics like impressions delivered, click-through rate, cost per acquisition, performance by creative, geo and much more. CTV advertising also covers all the relevant metrics around brand safety to ensure audiences stay engaged. Using AI technology in programmatic CTV ad campaigns is expected to enhance their efficiency and effectiveness. Marketing firms will be able to offer clients performance-based pricing models using AI, thereby increasing the attractiveness of CTV advertising.
CTV presents brands with a tremendous opportunity to address the growing number of users switching from traditional cable TV or liner TV to a more digital-friendly option. CTV advertising is quickly emerging as another powerful channel to successfully target and meaningfully engage with audiences. The ability to provide higher ROI, experiences to consumers and enhanced targeting makes CTV advertising a compelling investment for those seeking to diversify their advertising strategies and stay competitive in the dynamic advertising landscape. Write to us at Seedtag to understand how we’re helping leading brands across the globe foray into advertising on CTV and explore how we can help your business make the jump.
In 2017, technology giant Google came under extreme fire from large brands like Coca-Cola, Procter & Gamble, Microsoft and others for placing ads on YouTube videos promoting racist and anti-Semitic content . This resulted in other brands like Starbucks, PepsiCo and General Motors immediately pulling their ads from YouTube. Google also saw brands ramp down the spending on all Google advertising except targeted ads.
According to a 2020 study, 75% of global executives have experienced a recent reputational crisis that could have been prevented. Before online advertising became integral to brands, advertising campaigns were crafted based on viewability and subsequently ROI. The more places you saw the ad, the higher the recall with a direct impact on sales. As online avenues grew, brands too leveraged technology to maximize their reach.
When it came to digital advertising, it was no longer just about how many times the target audiences saw the ad, but also where the ad was presented, adjacent content, context where the consumer saw the ad and more. This shift gave rise to two frequently used terms – ‘Brand Safety’ and ‘Brand Suitability’.
‘Brand safety’ was the first major focus area for brands in the online world. ‘Brand safety’ is defined as the steps a brand takes to keep its reputation safe when advertising online. This ensures that
all the brand elements deliver a positive message, do not appear in unsafe environments or seem confrontational with other brands in the market. The lack of focus on this foundational element will result in financial losses and reputational backlash. In 2017, brand safety cost YouTube 5% of their top North American advertisers.
While ‘brand safety’ covered the basic premise of ensuring that an ad does not show up at inappropriate places or videos, it largely relies on primitive techniques like keyword-ban lists and URL block listing. The techniques used did miss out on one big component – ‘context’. This does not cover sites with fake news, extremist content, fraud sites and even relevant sites purely based on keywords. This is where ‘brand suitability’ comes in.
Brand suitability determines if the context in which an ad or piece of content appears is an appropriate fit for the brand that is advertising. Brand suitability is the logical next step in the evolution of brand safety that ensures displaying advertising in the right environment to the right audience based not on keywords, but on context. For example, an ad for a new car would not be suitable for a news article about a car crash. Very recently, CNN was criticized for an ill-timed ad placement of Applebee’s along with the announcement of the Russian invasion of Ukraine. This is where brand suitability leads the way.
As consumers become more aware of online privacy, and governments stepping in with acts like the GDPR and the California Consumer Privacy Act to protect consumer’s private data rights, we’re seeing a shift towards privacy-first advertising. Personal data-driven tools, like third-party cookies, while effective, are viewed as invasive and are being phased out of use. Brands are leveraging technologies like AI to discover new ways to place ads in a way that meet the expectations of consumers while ticking off the checklist for brand safety and brand suitability.
As we move ahead, ‘context’ along with high quality creatives will be the foundation of every ad strategy. Contextual advertising has proven to be the way forward for brands looking to maximize returns while ensuring the brand is perceived positively. The targeting mechanisms have proven to be more advanced allowing brands to focus on creating compelling marketing content. We at Seedtag have been helping brands craft effective advertising campaigns that maximize ROI while ensuring positive brand recall and association.
As the amount of time consumers spent online exponentially grew over the last few years, brands began investing more and more in online advertising. Brands resorted to using all the means available to fight for the diminishing attention spans of their target audiences. However, consumers became increasingly aware of how they were being targeted and the perceptions of online advertising significantly worsened. It no longer became acceptable to collect personal data for advertising purposes without the explicit consent of the consumer. Tools like third-party cookies which were initially designed to enhance the consumer experience soon became the enemy. Tech giants like Apple and Google soon decided to do away with cookies altogether.
With challenges around data privacy and how brands were using personal information becoming one of the biggest concerns, governments stepped in with legislation such as the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) to define how a business needed to be transparent about the way data was collected, stored and used. This resulted in all of us being subject to the cookie-consent pop up whenever we’ve visited a website. While most pop-ups try to define what data is being tracked and how it is being used, it’s done little to help consumer perception.
Most consumers continue to be bombarded with ads for a product or service they looked up online well after they’ve either lost interest or have already purchased. Despite the wealth of information in a cookie, consumers today continue to feel they aren’t getting value in return for the information they are giving up.
We at Seedtag collaborated with the international internet-based data analysis and market research firm YouGov to survey 3.000 adults across 6 European countries to understand how consumers perceive online advertising, their preferences for funding editorial content and the value they feel they get from the ads they encounter online. According to the survey, 84% of respondents feel the ads they are served online lack personal relevance. This is further backed up by nearly a third of all respondents stating that they deny all cookies on the sites they visit while 12% stating that they provide false information while filling out cookie forms. Clearly, there’s no love lost when it comes to consumers of today and online cookies. The survey generated three key insights:
- Data Privacy benefits both consumers and brands – Data privacy is a key concern for consumers. 82% of participants felt positive or very positive about brands ending their use of personal data for targeting. Brands that want to continue to be trusted need to have a robust data privacy policy in place and be transparent with their consumers. Companies that move away from leveraging third-party data or are more mindful about what consumer data they are collecting and why, will continue to be perceived positively in the online world.
- Consumers don’t mind being served advertising in exchange for free content – It’s not all bad news for advertisers. There is still a large section of users who are on-board with being served ads, provided they get value in terms of free editorial content tailored to their interests. 58% of participants chose hybrid or ad supported methods for funding the journalistic content they consume. Advertisers need to go back to the drawing board to evaluate how they can add more value to consumers seeing their ads.
- Relevant ads attract attention when placed in the right context – Context and creativity continue to lead the way in the online advertising world. 53% of users responded that ads embedded within high quality content were more likely to grab their attention. Consumers who spend a large part of their day on digital media place a high value on the context in which they see the ad. The survey indicates that “dedicated” readers, ie. those participants who spend time reading digital media multiple times a day, are 177% more likely to feel positive about a brand if the ad is shown to them alongside content that is relevant to them. This is where ‘context’ would play a large role in a post-cookie world for brands.
The market is at a very interesting inflection point when it comes to online advertising. Consumer expectations when it comes to data privacy swing between those who are completely against any use of personal data and those who are willing to share it as long as they get something of fair value in exchange. Advertisers and brands need to juggle with meeting these expectations and changes in the way they’ve been doing business. However, the challenges setby current data privacy acts are creating new opportunities for brands to innovate by leveraging new technologies. Early results do indicate that brands are able to target audiences better and see significantly higher returns on their investment, allowing them to focus on creativity rather than just inventory.
Brands that can successfully craft a privacy-first approach and are able to leverage new-age tools like Contextual AI, will be able to strike the perfect balance between personalization and privacy, and eventually thrive. To further understand the various perceptions consumers have towards online advertising, and subsequently build a strategy to effectively engage with them, download our research report today.
Topics API is the new Privacy Sandbox entrant that is replacing Google’s previous Federated Learning of Cohorts (FLoC) proposal. There has been a huge buzz around Google’s decision to phase out third-party cookies and the Privacy Sandbox initiative was a step in that direction.
Globally, the focus today lies on data privacy. Consumers have made it abundantly clear that third-party cookies are violating their data privacy and thus began the motion to phase them out. FLoC was a part of the larger Privacy Sandbox initiative, a privacy-first web tracking technology. Google faced a lot of backlash ever since the announcement, and after collating feedback from the trials decided to drop the FLoC and replace it with a new initiative, Topics API.
The FLoC model revolved around the concept of grouping people into cohorts based on their browsing patterns. This idea did not fly well among privacy advocates as they believed the algorithm could be reverse-engineered, giving rise to new privacy concerns. Replacing FLoC is Topics API, the new initiative for privacy-first, interest-based advertising, created keeping in mind the learnings and community feedback on the earlier proposal.
What is the Topics API Privacy Sandbox proposal?
Topics API aims to provide a highly secure browsing experience for users:
- The API labels every website within one of the high-level topics
- It enables the browsers to determine your top interests for the week based on your browsing history.
- Shared as one new topic per week, the topics are stored only for three weeks and all old topics are deleted.
- There are no external servers (not even Google servers) involved as all the topics are selected on the user’s device.
- Only 3 topics, one from each of the past three weeks are picked and shared with websites and its advertising partners.
- The main list of Topics is a human-curated list that is visible to the public and capped at 350 topics to prevent any risk of fingerprinting.
That’s not all. Topics also excludes sensitive categories like gender or race, and extends more control to users as it is powered by their browser. Google aims to further facilitate transparency and data control by also giving users access to disable this feature entirely, or remove any topic they choose to.
Let’s take an example to better understand Topics API – Say you search for something related to automobiles, the API will label the website under the topic ‘Automobiles & Vehicles’. Similarly, based on your browsing history, your browser will collect your most recent topics of interest and share it with advertisers to show you ads that are relevant, without knowing any specifics about your browsing history. For more details about the API and how it works, click here.
With this, users have more visibility and control over their data unlike third-party cookies, while also enabling advertisers to serve relevant ads without involving any technique that invades user privacy.
How will Topics API impact the advertising industry?
This initiative will give advertisers access to topics users have been interested in recently, keeping the possibility of interest levels high as the topics are fresh and updated on a tri-weekly basis. However, this has been the latest worry factor for advertisers and marketers as it could dilute their targeting capabilities.
With cookies phasing out and Topics API still in its testing phase, without any clarity about its effectiveness or regulatory compliance, it is about time advertisers expand their horizons and explore other avenues they can leverage for successful interest-based advertising strategies.
A strategy that has been gaining popularity among global brands today is contextual advertising. An ideal solution for the cookieless era, contextual advertising analyzes both content and context of a website to determine if it will be the right fit. Contextual ads are compliant with all data protection standards and do not leverage any personal information of users. With contextual targeting, ads are non-intrusive and rendered only within the user’s area of interest.
Contextual advertising rates high on brand safety and suitability as the strategy incorporates the GARM framework. It traverses a vast ocean of content and picks only those websites and categories that are relevant to a brand’s products and services, while ensuring all sensitive and harmful content is avoided and also creating an apt balance between risk and opportunity. Additionally, with Seedtag’s contextual AI technology, advertisers are also able to leverage the power of machine learning to get a human-like understanding of content to deliver ads that not only capture audience attention but also retain it longer.
For instance, the global technology giant, LG, leveraged contextual advertising to spread its campaign dynamically and creatively. They saw a +53% rise in CTR and +24% increase in viewability. Levis, one of America’s most loved clothing brands, opted for contextual ads to raise brand awareness and increase its association with sustainability. The results? 79.4%viewabilityand 66.5% VTR.
Get in touch with us and learn more about how our Contextual AI is helping global brands lead the way in the cookieless world.
Pursuit of excellence is what keeps great men moving and the pursuit of perfection is what keeps great brands exploring!
Seedtag’s contextual creativity has been focused on creating efficient and pro-privacy advertising solutions for brands in the cookieless era. In a strategic move towards strengthening its product portfolio, Seedtag, the leading contextual advertiser in EMEA and LATAM, recently acquired KMTX (previously Keymantics), a French company dedicated to building AI models to optimise and automate performance campaigns. This addition will further empower Seedtag to provide a full-funnel cookieless solution to advertisers that helps them achieve exceptional results in their ad campaigns.
KMTX, is a key French company centered on building the most transparent and data-driven approach to programmatic advertising that helps marketers improve their ad spend efficiency with a special attention on keyword and semantic audiences. With the focus on delivering mid and low funnel KPIs to advertisers, since 2019 they have consistently helped over 150 clients improve more than 500 campaigns and grown to become one of the most reliable digital media partners.
At Seedtag, as we help organizations prosper in the upcoming cookieless era, this acquisition is a logical expansion towards understanding audience insights more accurately and refining targeting strategies better to identify relevant contexts and place ads where they will matter the most.
Jorge Poyatos and Albert Nieto, Co-CEOs and Co-Founders of Seedtag, state: “Over the last few years, we have seen a strong correlation between contextual signals and performance results although we have not had the technology to predict post-click behaviours at scale. The acquisition of KMTX brings AI based predictive models into our stack that combined with our proprietary contextual data will constitute a leading solution for achieving performance results in a cookieless world”.
Arthur Querou, CEO and Co-Founder of KMTX, adds: “Over the past 5 years, we have built a successful business based on helping advertisers make better media buying decisions. With Seedtag we share a common vision of making advertising on the open web simpler through data-driven media investment. By combining KMTX’s technology with Seedtag’s, the industry will be able to avail of a full-funnel contextual AI solution that will help advertisers make accurate targeting decisions in a privacy-first world.”
Gone are the days when advertisers used to piggy-ride on cookies to track consumers anywhere and everywhere on the net. With concerns around data privacy growing by the day, governments and regulating agencies all over the world have strengthened the data privacy laws and brands are now obligated to tweak their strategies to incorporate pro-privacy measures and come up with ways to add to the user experience online and not interrupt it.
With data privacy on the rise and consumers’ attention span in the fall, it makes more sense for brands to invest in measures that are in sync with consumer’s evolving preferences. Such approaches not only garner better views and engagement but also amplify the trust in a brand. The more conscious your consumers become, the more enriching digital experience would they demand. Do your ad campaigns incorporate this gradual shift towards relevance and interest or are they still going the cookies way? Talk to us today and improve to thrive better than your competition.
With the eventual phasing out of third-party cookies and the implementation of various regulatory compliances like CCPA and GDPR, audience targeting is getting tougher than ever in today’s privacy-first world. As the competition skyrockets in the advertising world, leading advertisers are leveraging what is believed to be the future of audience targeting – Contextual Intelligence.
From an estimated global market valuation of US$157.4 billion in the year 2020, today the contextual advertising market is growing at a CAGR of 13.3% and is projected to reach a whopping US$335.1 billion by 2026.
So, what is contextual intelligence? It has been a topic of interest for a long time in the advertising space and is closely associated with contextual advertising today, as this form of advertising has been developed on the same principles. Contextual intelligence involves a deep and thorough analysis of a webpage to determine if it will make a good fit based on various factors like its content, context, relevance, brand safety, and brand suitability. This analysis helps brands enhance their understanding of consumer interests, enables automation, and provides proof points that fuel confident, data-driven decision making.
Contextual advertising, as the name suggests, gives advertisers the power to leverage one of the biggest impact factors – context. With its Artificial Intelligence (AI) capabilities, contextual advertising delivers ads on relevant websites that target suitable audiences, without the use of cookies.
With context, advertisers and brands can better understand what customers are browsing, their areas of interest, and how they engage and interact with content. By analyzing both the written and visual content of a page, contextual AI offers advertisers the perfect environment where the values and ideas fit seamlessly with their own, thus ensuring the highest levels of brand safety.
Contextual intelligence does not analyze just the text but takes into account all visual elements as well to establish relevance between the text, visuals, and the webpage as a whole. With a complete understanding of customer interests, it is also highly capable of providing contextual creatives that resonate with consumers.
A superior understanding of user behavior coupled with purchase intent and consumer interests helps in serving ads to the right audience by rendering them in optimal places, besides relevant content. Contextual creatives have higher engagement rates and have proven to deliver better impressions, empowering brands to build a memorable and consistent brand identity.
Here’s what a study conducted on contextual targeting revealed:
- 63% higher purchase intent
- 83% higher recommendation of the product advertised
- 40% higher brand favorability
- 73% of consumers said contextual ads rendered alongside video content complemented their overall video experience
Better brand perception, improved sentiment analysis, a stronger connection between the ad and content, and a higher brand valuation on the whole – contextual targeting is paving the way for the future of advertising strategies that put customers and their data privacy first.
What are the top 5 factors that make contextual intelligence the best bet for audience targeting in the era of data privacy?
- Greater ROI: Contextual intelligence-based targeting goes far beyond just keyword research and analyses the content and context of a page to draw customer insights that are leveraged for customer targeting. This has proven to be a more effective targeting strategy as the ads are non-intrusive, more relevant, and resonate better with the audiences, thereby increasing ROI on ad spending. Businesses are constantly on the lookout for cost-effective solutions that fit the modern advertising landscape. Contextual AI makes a great fit as it is an effective, affordable, and scalable solution unlike alternatives such as behavioral advertising. Behavioral ad strategies are heavily reliant on data and need large volumes of data to deliver successful campaigns. Collation, analysis, and reporting of data, and then leveraging it is far more expensive and time-consuming.
- Superior accuracy and personalization capabilities: Since the ad strategies are created based on data-driven insights, advertisers have access to all the information they need to narrow down their lists and target the right people who are looking for that particular product or service. Leveraging new-age tech like AI/ML, contextual intelligence ensures highly accurate targeting by performing a human-like analysis of the content. Contextual AI’s ability to build personalized segments at scale helps advertisers reach their desired target audience by building contextual segments beyond the standard IAB taxonomy. With this, advertisers can deliver ads at a highly granular level, eliminating impression wastage. Brands can create ads that speak more directly and personally with their online consumers. Since the ads are contextual and relevant, consumers are more likely to pay attention and engage better.
- Ensuring brand safety: The human-like analysis of content and context executed using AI/ML capabilities helps identify and avoid any harmful content. Contextual intelligence integrates the GARM framework, implementing universal brand safety standards. This helps avoid sensitive content that could potentially harm brands like sexual content, hate speech, spam, and terrorism.
- Assuring brand suitability: Brand suitability is built atop the brand safety standards. While safety is universal, brand suitability needs are unique to each brand. Contextual intelligence helps focus on brand suitability along with the GARM framework. This intelligent targeting technique picks only those categories that are relevant to and resonate with the brand’s products, services, and unique positioning. The combination of safety and suitability helps brands strike the perfect balance between reach and security, by focusing on brand niches and nuances. This thoughtful mix helps reach the right audiences without missing out on potential high-value customers that could have otherwise been lost if the focus remained only on brand safety measures like block lists or exclusion lists.
- Privacy-focused: An ideal fit for the cookieless future, contextual intelligence does not leverage any third-party data. The audience targeting is solely based on the analysis of webpage content and context to determine all factors from user intent and relevance to brand safety and suitability.
As businesses traverse through the post-cookie era, they need to find ways to adapt to the privacy-first world. Contextual AI is here to stay as it fits the bill. It does not depend on any third-party cookies and enables brands to reach specific customer segments while being respectful of their privacy, and mindful of brand safety, and suitability.
Brand engagement just isn’t what it used to be. In “the good old days”, with TV, it was easy to identify which commercial break of which soap opera, cartoon or sporting event to place ads in, to drive brand recall. It is no wonder that brands are still willing to pay upwards of $6 million to reach 110 million viewers of the Super Bowl.
We’re not even factoring the cost of production of the ad at this point. Outside of the Super Bowl, the story is different.
Marketers world over will agree that with people consuming a mind boggling amount of content across a steadily growing number of devices, screens, platforms, channels, consumer attention has become extremely fragmented. With the average human having a relatively finite attention span, the battle to grab a slice of that pie has fiercely intensified.
Over the last few years, we’ve been seeing the word ‘Attention Economy’ popping up often. The attention economy treats attention as a scarce commodity, which everyone from brands, big businesses, politicians and numerous other entities are fighting for.
In today’s digital age, the very real fight for this limited resource is shaking up the way marketers are measuring success. Human attention has quickly become the key measure of ad or content success.
It’s important to note that ‘attention’ is not the holy grail of content performance. It is, however, the next big step and builds on traditional metrics of success. At Seedtag, we see three key components that need to be in place to ensure attention is grabbed at every possible opportunity.
Context drives impact
As we move towards a privacy-first world, measuring whether the right audience saw their ad has become quite the task for marketers. The end of the cookie, industry regulations such as GDPR and CCPA are impacting the ability to target and measure success.
This is where context plays a key role for marketers. With the average consumer seeing anywhere between 6000-10000 ads a day, contextual marketing allows marketers to drive more than three times the engagement they would have got otherwise.
Studies show that placing ads in the right context not only drives engagement, but is directly correlated to higher sales. For example, a 12-year old watching the entire ad for a new car model is not going to result in an immediate sale. That’s where context makes the difference.
Creativity still matters
Creativity continues to be the central focus of any metric of success for placement of ads. What hasn’t changed since the day the first ad was ever printed is the human nature to engage more with something that is relevant and interesting.
Studies indicate that the variation between a good creative and bad creative can be as much as 17 percentage points when it comes to brand recall. This isn’t limited to just a great ad copy in today’s day and age but how can one creatively engage with the audience.
Millennials today are less trusting of traditional ads and rely on their network for recommendations on things to buy, places to eat, brands to engage with. Leveraging interactive technology to capture attention that’s mostly focused on social media and smartphones will yield better results than traditional ad posts.
Let’s take an example from a decade ago. Businesses leveraged the power of augmented reality delivered by the mobile game app Pokémon GO to drive footfalls without actually placing any advertisements. Businesses cemented a position on the virtual game board by investing in the sponsored location feature of the game. A pizza business in Queens saw a 75 percent increase in business by ensuring app-users came to their restaurant in search of Pokémon.
Non-intrusive advertising equals better engagement
How many times have we been thoroughly annoyed by an ad popping up in the middle of a video online or while one is just getting in the groove of their favorite playlist? Studies show that ads viewed in non-disruptive environments, like below the article or in a newsfeed, drive 25 % higher attentiveness than ads placed in an interruptive environment like pre-roll… or worse, mid-roll.
It is paramount for brands to know where and when to place the ad so that consumers are in the best state of mind to engage with the ad. If one were watching a video of their favorite music artist performing, and were interrupted by an ad to buy a burger; no matter how good the burger looked in the ad, one would probably be irked and wait to get back to seeing the musical performance.
In the attention economy, it’s imperative to predict the mind-set of the consumer when placing the ad and the likelihood of them being in the right frame of mind to engage and eventually act.
In summary, it’s time marketers paid attention to attention. There’s no doubt that in the current scheme of things, it has become harder for brands to grab and hold people’s attention.
While we encourage a much required move towards an attention economy, and away from traditional measures of success, it’s important to set relevant benchmarks and demonstrate how attention is the next big impactful metric. It would serve marketers better to focus on optimizing attention, not just viewability or impressions, to improve the impact and effectiveness of their online advertising.
How to Drive Attention in a Privacy - First World?
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Contextual advertising has evolved and how! In addition to being a better alternative to cookie-dependent behavioral advertising, it has had a unique journey of its own. In the early 1990s, contextual advertising was based on broad keywords. As we moved to the next decade, the focus shifted to analyzing individual web pages and categorizing them based on their content.
Today, we are at a juncture where contextual advertising helps undertake an almost human-like analysis of content encompassing text, image, video, and page quality, to categorize pages as safe and suitable. This offers a more robust method to advertisers and publishers to reach their network.
Why traditional targeting is not enough
A page has two main aspects– content + context. The content itself is made up of multiple elements like text, image, or video, while the context looks at broader aspects like page quality, page relevance, and categorization. All these come together in contextual advertising to determine where ads need to be placed and in what format. However, this may not always be a holistic strategy.
Two important, yet distinct, concepts come into play here – brand safety and brand suitability. Brand Safety enables a brand to avoid content that is generally considered to be inappropriate for any advertising. A brand-safe approach would mean that the ad from, for example, a travel company should not appear next to content on sites that have illegal, inappropriate, unsafe content.
Brand suitability is unique to each brand and situation. By being able to understand nuances in language and being able to semantically interpret editorial content, brand suitability bridges the divide between risk and opportunity and provides context-based protections for advertisers – and also for the publisher.
Both concepts are equally important for brands to be able to balance risk and opportunity. Incomplete considerations and analysis will otherwise lead to a smaller universe or a limited set of pages for the ads to appear on. A half-baked targeting approach also puts brands at an increased risk of associating themselves with content that might impact their brand negatively.
IAB Europe’s Brand Advertising Committee conducted an industry poll in 2019. It found that brand safety was a key priority for 77% of the respondents and that brands are asking more questions to know where their ads are appearing. So, it does make sense to focus on both.
Leveraging brand suitability and safety through contextual advertising
If we look at behavioral targeting, an ad is rendered on multiple sites across the internet. The sites are picked up from the publishers’ network and advertisers have little or no control over them. So, an ad promoting a toothpaste brand might appear on a page that is talking about airlines.
However, with contextual advertising that focuses on safety and suitability:
- The targeting is much more enhanced advertisers can select relevant categories which will be compatible with their products or services, while also not propagating any unsafe content.
- So, a toothpaste ad can appear on different websites that talk about good oral hygiene or overall health and wellness. A brand selling herbal toothpastes can drill down further to showcase their ads on sites talking about herbal, natural products.
- Both these brands can also avoid sites which are unsafe, a factor that is equally important.
With the deluge of harmful activities like domain spoofing, hidden ads, and ad stacking, maintaining a brand-safe environment can be challenging.
Since ads are rendered based on cookies, manual checks are not practical. Hence, the ads might be shown to a user if he/she goes to a specific, harmful site that is part of the publisher’s ad network. This is where AI-powered contextual targeting can help weed out harmful sites.
How brands can protect themselves while still ensuring a wider reach
The perfect combination of brand safety and suitability ensures optimum coverage for advertisers. A brand-safe approach will ensure that brands can avoid sites that are usually considered to be unsafe. It also ensures that content on a webpage is analyzed with a frame of reference, rather than picking out random words on the page.
Brand safety is not merely having a list of keywords to be blocked. Brands also need to understand the context in which content is presented so that their ads do not appear next to content that they do not want to associate themselves with.
A 2019 survey by Trustworthy Accountability Group (TAG) and Brand Safety Institute (BSI) discovered that more than 80% were looking to reduce investments or even stop buying from brands that were advertising in unsafe places. Brands appearing next to relevant, high-quality content are also perceived to be more likable. So, striking the right balance is important for brands to devise a campaign that reaches relevant folks, while also being considered safe and suitable.
Conclusion:
As contextual advertising evolves to enhance analysis of context and content, advertisers can simply focus on creating good marketing material.Brands have to find the sweet spot between ensuring brand safety, rendering ads on relevant websites, and targeting the right audience.A good contextual advertising platform can be trusted to take care of all these intricacies while optimizing the campaign reach. Some quick tips to get started:
- Understand your brand values and know which brands you would want to associate yourself with.
- Know which brands you would not want to get associated with.
- Draft a brand suitability guideline.
- Work with publishers to get their views around increasing the audience sets or sites while still being perceived to be completely safe.
- Have a plan in case of repercussions.
- Keep exclusion lists handy and keep revising the lists.
We have been helping brands be safe and relevant while working on great ad campaigns and content. Sensodyne, one of our premium clients, has been able to implement a robust contextual advertising strategy to get a 7.4 increase in view quality and 4.4 seconds faster notifications of their ads.
They were able to leverage placements enjoying higher attention spans while being within a carefully curated safety net. If you are wondering how you can ensure that your brand reaches the right audience while also being perceived well and safe, we have just the right strategy for you. Get in touch with us today!
Programmatic ads help brands automate and optimize their campaigns
Programmatic advertising, in simple terms, is the automated trading of online advertising space. It leverages Machine Learning (ML) and Artificial Intelligence (AI) to buy and optimize online campaigns. This reduces manual effort and negotiations with publishers, ensuring the focus stays on optimizing campaigns in real-time.
The process is smart and instant too. Here’s how it works:
- When a person visits a website, the ad impression is put up for auction (Supply side platform)
- The interested advertisers offer their bids for the ad impression (Demand side platform)
- The highest bidder is selected to showcase their ads.
- The ad is served to the user.
Programmatic ads can be useful for companies across industries. Back in 2014, Kellogg’s saw some impressive results. It ran programmatic ads in the digital space to drive offline sales. The brand enjoyed +70-80% impressions and 2X improved targeting. This was topped up with hyper-targeted ad campaigns.
Programmatic ads promise enhanced reach and improved marketing ROI
It is estimated that 88% of US digital ad spending will be programmatic by the end of 2021. It offers a more efficient and effective strategy for marketers looking to better their performance and returns. The major advantages are:
- Increased reach and scale: Multiple ad exchanges and networks work together to offer ad space and inventory to advertisers. Advertisers can thus run campaigns at scale, while enhancing the reach.
- Real-time optimization: Access to real-time insights helps advertisers focus on optimization techniques. This is better than spending energy on negotiating for better/more ad space.
- Less wastage: Since the process is automated, impressions are not wasted. Marketers are also in better control of their campaigns as adjustments and enhancements can be made proactively.
- Better marketing ROI: The focus is on getting relevant visitors. This ensures better CTRs and enhanced ROI.
- More transparency: Marketers have a better understanding of the sites on which their ads are appearing. Impressions, prospect activities, and other relevant stats also help make the process smoother.
Programmatic ads offer a range of targeting options
4 key types of targeting work in the world of programmatic advertising. Let’s take a look:
- Audience/Behavioural targeting: It targets users based on their behaviour, browsing history, and/or demographic data. Data like gender, income, age, location, etc. are looked at. The issue with this type of targeting, however, is that it depends on a users’ private data. This has become problematic in the recent past. With cookies phasing out soon, this strategy might not give long-lasting results.
- Website targeting: It targets specific websites for the ads to be rendered on. This strategy works best when marketers know which websites are relevant to them. But, it could limit the playing field as other relevant sites might get missed out.
- Retargeting: It re-engages users who might have previously interacted or seen a particular ad from a brand. This strategy focuses on getting users back to a brand’s website or to continue an action. It works well for persuading users to complete an action like purchasing an item or downloading a content piece. This again is a tricky territory as the dependency on user data is massive. Also, the websites where the ads get rendered might be irrelevant.
- Contextual targeting: It targets relevant content and context instead of users. This is a better strategy as there is no dependency on user data. It targets websites/pages based on the relevance of their content to a product/service being advertised. AI helps make the targeting a lot more precise. Sentiment analysis, brand safety, relevancy, and brand suitability make this a potent combination and strategy for marketers.
Contextual targeting – A marketer’s best bet
As we saw above, there are different types of programmatic ad targeting strategies but they all have some dependencies on user data. This, however, is not true for contextual targeting.
Let’s say you have clicked on an advertisement or simply visited a website. An ad of that particular brand might appear many times as you surf the web, leading to ad fatigue and poor user experience. Often, these ads appear on random websites too.
This is the problem with audience targeting and retargeting strategies. Even if you consider website targeting, the marketing universe could sometimes become a little limited. For example, assume that you are a brand selling luxury cars. There are only a limited number of sites that you can list down for website targeting.
With contextual targeting, you can expand your universe to list down relevant sites like fashion or lifestyle. These categories will help you reach your target audience in a smart, well-rounded manner, while still being relevant. It helps look at the complete context of a website and undertakes a human-like analysis of the page and all its elements. Text, video, imagery, URL – all of these are analyzed in totality to understand the context well. Hence, the ads can be placed in a way that matches the environment around them.
A good contextual advertising tool can help take your brand places. In fact, it can help you take your brand to all the RIGHT places, guaranteeing better marketing ROI. Your brand can leverage the power of AI and ML to optimize ads and keep innovating. Contact us today to know how!
Today’s consumers are increasingly concerned about data privacy but, there is also mounting pressure on advertisers to sell their products. Advertisers cannot get away with running campaigns that rely on collecting and using consumers’ data. A Cisco study from 2019 found that around 84% of consumers want more control over their data.
With cookies on their way out, better ways of advertising are just around the corner. But, the onus also lies on publishers to make smart decisions to deal with data privacy concerns, while keeping their businesses running. Contextual advertising, which focuses on running targeted ads around relevant content, is one of the best strategies for marketers in the current times.
Publishers stand to benefit the most as contextual advertising provides an excellent opportunity for them to engage with advertisers and help them reach out to consumers, by linking relevant content and context to ads. It can also be hugely profitable for them as they can expect 2.5X incremental revenue owing to ads that are relatable and act as a natural fit. Other key metrics like time spent on a page, impressions, returning users, ad recall, brand awareness, purchase intent, brand association etc. also see a surge on the back of contextual ads. The ads can enhance user perception by 72% and boost positive reaction by 40%.
Publishers’ views on data privacy concerns
The key element of relevancy is what attracts publishers to contextual advertising the most. Dario Holden, a publisher from Norway, says, “As a publisher, my focus is on ensuring that advertisers can reach a good set of consumers. But as they say, quality is more important than quantity. With contextual advertising, the focus might be specific, but the reach is far more relevant. That is what truly works for me.”
“When you think about the long-term strategy, companies would want to ensure greater ROI for their campaigns. So, having a wider reach may longer be the only thing that matters. When an ad appears next to relevant content, it is likely to have an enhanced impact. Be it impressions, clicks, conversions, or brand recall value, we will see better numbers across different metrics. Additionally, with cookies on the verge of being phased out, contextual advertising is a very strategic move in the right direction,” says Philline Cole, a leading publisher working with multiple advertisers across Europe.
Strategies adopted to overcome the above challenges
One way out is for publishers to collect first-party data of their audience around their interests, the content they consume, their demographics, etc. Advertisers can also collect data from their side and when there are synergies, advertisers and publishers can run ads on specific audiences. But, this requires complicated technical systems and is not a straightforward route.
A Digiday survey found that 74% publishers have been trying to work on solutions to fix the addressability issue for almost a year now. Publishers across the globe are also trying alternate tactics like using email address data, IP address data, device data etc. But, these might not work out in the long run.
- Ultimately, they all pertain to data which can become an issue in the future.
- Scale is also a challenge.
- There are technology, legal, and operational costs.
Though contextual advertising is a smarter way to deal with the cookie ban, it does require a well-thought-through approach. A McKinsey research says that publishers can lose 50-60% of their revenues if they turn-off third party data and do not transition to a better advertising strategy.
- The first step for publishers would be to craft an outreach strategy with advertisers where the focus lies on understanding consumers’ interests instead of collecting their data. If contextual advertising is undertaken, metrics can be defined before running campaigns. It is suggested to run multiple campaigns so that quantity and quality of leads are both covered.
- The next step would be to create different ads to suit different marketing goals.
- Third step should be to identify keywords for the different ads created above.
How contextual advertising can help keep the community at large happy and booming
The advertising ecosystem contains customers, advertisers, and publishers. While publishers strategize outreach campaigns to ensure better ROI for advertisers, customers shouldn’t be forgotten. Contextual advertising keeps the entire ecosystem happy.
Advertisers will get relevant audiences for their products, publishers will be able to use their inventory efficiently, and customers will see relevant ads around content that they are already consuming. This works better than behavioural advertising which predominantly focuses on ensuring that ads get promoted across all the sites which are a part of an inventory by reaching out to customers purely on the basis of their browsing details. Relevancy is not given much thought in behavioral advertising while contextual advertising is a lot more intelligent.
Publishers would also be able to focus on adding granularity and relevance to their ad inventory and thus be able to charge higher CPM for niche audiences. Since these ads would go beyond mere keywords to understand sentiments, user intent, and emotions, publishers can focus on selling quality which would have better results instead of quantity which may not be as valuable. Nearly half (44%) of the publishers who participated in the Digiday survey said they are already leveraging contextual ads in video formats.
Crafting a robust, contextually relevant outreach strategy
Contextual advertising is already on publishers’ radar as they look to increase their spends on strategies and ideas which can give better ROI. A robust advertising strategy starts with the right targeting strategy. With a good contextual advertising platform that leverages the latest technology stack, this task becomes a whole lot easier.
The scope or reach can be expanded based on the keywords that are initially selected. Also, since different users have varied reading styles (some like to focus on images while others might quickly scroll through articles to get a gist of the content), ad formats and placements should be adaptable to appeal to a variety of users. Video can be a powerful tool for interactive, yet crisp communication.
With the help of Machine Learning and Artificial Intelligence, content can be analyzed taking a human-like approach. From here, articles can be slotted into different categories so that the ads can be customized and placed in an optimum fashion. Brands should also look at platforms that can help them weed out websites that have inappropriate content, to ensure brands safety.
TMI – Does this acronym ring a bell? Well, for those of you who can relate to it, we give you a +1. For those who don’t, maybe this article will convince you to understand its significance. TMI, which stands for ‘Too Much Information’, conveys a fairly straightforward meaning – Information overload can be counterproductive for your communication.
In a fast-moving world with continuously shrinking attention spans (which is hovering around 8 seconds as per a Microsoft study), long paragraphs and essays are no longer the right ways of telling a story. A Visme 2021 survey saw 86% of businesses predicting that visuals will be a key part of their marketing strategy in 2020-21.
At Seedtag, we conducted a research with MetrixLab that covered around 1000 consumers and found that in-image ads are 4 to 6.7 times more effective in retaining consumer attention. Engaging formats and creative ad displays foster positive brand connections since they are more enticing, enjoyable, and interesting while conveying a lot more in a quicker fashion. Also, a whopping 90% of information transmitted to the brain is of a visual format, putting further stress on visual communication.
Marketers are offered multiple interesting options to leverage visuals through various formats – full-image display, in-image display, full image video, in-image video.
The key answer lies in drafting creative and engaging communications through content which should be a good mix of visuals and messaging, with visuals doing the heavy-lifting and being supported by fresh, crisp messaging. Visuals, encompassing multiple facets like images, videos, and animation, help elevate brand communication by breaking the monotony of text, bringing freshness, and simplifying complex concepts.
The power of visual marketing – A fresh perspective:
We are bombarded with ads, notifications, messages, and news every day. A brand needs much more than just a good budget to grab eyeballs. A great visual helps an ad stick around longer in a user’s mind. This is all the more favourable when contextual advertising is added to the mix.
The survey that we conducted with MetrixLab, also gives a thumbs-up to in-image video ads which deliver greater noticeability and 6.8X stronger view quality. Videos have the potential to help a user retain 95% of content, while text only helps retain 10% of the communication. Visuals are also more universal and appeal to a larger audience. When combined with a smart marketing strategy like contextual advertising, visuals can add some much-needed magic and propel a brand to take its message around the globe in an enticing and relevant manner.
How contextual advertising and visual marketing are a win-win combination:
Contextual advertising is already poised to win the marketing game by being relevant, on point, and smart owing to its focus on both context and content. While the ads themselves will leverage the environment of the pages on which they are placed, the ads can be further enhanced through great visuals. 69% of the respondents from the Seedtag+MetrixLab survey agreed that in-image contextual targeting leads to better ad placement and fitment, thereby adding to the natural, visually appealing flow of the ad. Image ads are also noticed 3.4 seconds faster than their regular counterparts, resulting in rapid impressions and actions.
Fernando Pascual, Global Head of Design at Seedtag, echoes the sentiment as he says: “By bringing the elements of contextual advertising and visualization together, we are helping our clients to be much more relevant for each audience because their ads are going to be seamlessly blended with the content the audience is interested in. Ads are blended into the content they are a part of”.
As contextual advertising supports all forms of communication (text, video, visuals etc.), it offers a great opportunity for marketers to focus on creating beautiful brand stories, so brands can focus on targeting relevant websites for promotions, understand the way words work with each other, embed their visual ads in the right place, and ensure their ads get placed in websites that offer safe, appropriate, relevant content. By leveraging the power of contextual advertising and visual marketing, everyone wins.
In a world where companies are trying to promote their products to an audience whose needs are changing rapidly, contextual advertising serves as a launchpad to convey brand stories. They help companies seamlessly integrate their ads with the website content and context, eliminate wastage of impressions, yield better results, and enable brands to meet their marketing objectives while respecting the data privacy needs of users.
Let us imagine a situation: It is a Saturday morning and you have a long day ahead of yourself. You want to try a delicious cookie recipe but have not found the time. So you start browsing for a recipe and an ad of a ready-to-make cookie brand catches your eye. What could be better than such a delightful quick fix for your sweet tooth?
Well, good luck with your cooking experiments but, what you saw there was not a mere coincidence. It was a well-thought-out contextual advertising strategy. This strategy placesan ad on a website where it blends well with its surrounding content, thereby optimizing messaging, audience selection, and the overall ad placement. The flow between the content and the ad helps grab a user’s attention without being intrusive.
Acing the marketing game: Contextual vs. Behavioural
Sans contextual advertising, non-intrusive ad experience would not have been the same. A mere click on one ad or a harmless search for cookie brands would have meant an ad following you around as you jumped from one website to another. So, if you searched for a recipe, you might end up seeing the ad everywhere, including irrelevant places like websites related to books, computers, or clothing etc. This is called behavioural targeting.
Behavioural targeting uses cookies that track a user’s browsing history details like pages visited, web searches, links accessed or past purchases. So, these ads are usually displayed without any thought on placement based on the assumption that the computer and user remain the same, which may not always be true.
“Contextual advertising helps identify trending keywords and reach customers through a human-like analysis of the content (including text, video, and imagery), their combination, and placement to be able to embed an ad that matches the content and environment of a page.”
It elevates the ad experience and relevancy by additionally looking at sentiments, sub-categories, brand suitability, and brand safety. This makes it a better fit as the likelihood of a person responding to an ad increases with improved relevance, context, and storytelling. It also increases ad recall and purchases intent through enhanced sentiment analysis. Another key factor it ensures is brand safety by keeping ads away from blacklisted sites and inappropriate content.
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