AdTech Collective by Seedtag
News, trends, and insights in Digital Advertising
For a long time, contextual advertising worked like a matching game. A recipe page showed a cookware ad. A marathon training guide showed running shoes. It was relevant, privacy-safe, and it worked at scale.
But people don’t experience a web page as a list of keywords.
They read a recipe differently on a rushed Tuesday night than on a slow Saturday morning. They feel something when they watch a tense final quarter or a quiet documentary. And what they feel shapes what they notice, remember, and decide.
That’s where relevance reaches its ceiling. An ad can sit next to the right topic and still miss the moment. And as the signals the industry once used to track users fade, that gap matters more than ever.
Most contextual advertising services still stop at classifying content. The next step is understanding the moment: what people are interested in, how they feel, and what they’re ready to do next. At Seedtag, we call it Neuro-Contextual Advertising. Here’s how contextual got here, and what comes next for brands and agencies.
Key Takeaways
- Contextual advertising services place ads based on the content people engage with, not on who they are.
- Unlike behavioral advertising, contextual targeting doesn’t need to track users or rely on third-party data.
- Relevance has a ceiling: an ad can match the topic and still miss the moment.
- Contextual advertising has evolved from keyword matching to natural language processing, and Neuro-Contextual Advertising is the next step: understanding the moment.
- Liz, our Neuro-Contextual AI, reads interest, emotion, and intent to align ads with how a moment feels, without personal data.
What Are Contextual Advertising Services?
Contextual advertising services help brands serve ads based on the content of a web page, video, or stream, rather than on a person's browsing history. The ad follows the context. If someone is reading about a weekend camping trip, an outdoor gear brand can appear in that same environment.
It's a simple principle, and one of the oldest in advertising.
Long before digital, brands chose magazines, TV shows, and radio programs because the content matched their products or services. Contextual ads bring that same logic to the open web, video, and CTV, at scale and in real time.
So how does contextual advertising work in practice? Each time content loads, the technology analyzes it and decides whether it's a good fit for a campaign. If it is, the ad is served. If it isn't, the impression is skipped. The quality of that decision depends on how deeply the technology understands what it's reading.
That's where contextual advertising services start to differ.
Contextual vs. Behavioral Advertising: Context Over Identity
Behavioral advertising was built on a different question. Instead of asking what someone is looking at, it asked who they are. It tracked users across sites, built profiles from past clicks, visits, and purchases, and used those profiles to target ads, often relying heavily on third-party data.
For years, audience targeting meant exactly that. But profiles have limits.
A profile describes someone’s past. It says little about what they need right now. The same person who researched a new car last month may be planning a family dinner today. Nothing about them has changed. Only their context has.
Contextual targeting starts from the present instead. It reads the environment someone is in and the content they’ve chosen to engage with, which is often the clearest signal of current interest available. And because it doesn’t need to know who someone is, it respects privacy by design.
This shift isn’t about giving up on audiences. It’s about reaching them through what they’re experiencing, rather than through who a dataset says they were.
Context tells you where someone is. It doesn’t yet tell you how they feel there. That’s the gap the next stage of contextual is built to close.
Traditional Contextual Advertising Services: Keywords and Categories
Traditional contextual advertising typically works in one of two ways: matching keywords, or classifying a page by topic and category. Both have moved the industry forward. Both still stop at the page.
Here’s a closer look at how each one works
Keyword-Based Contextual Advertising
The first generation scanned a page for specific words and matched them to campaigns. Early tools like Google AdSense helped popularize this approach, displaying ads that matched the terms on a page.
It was a breakthrough at the time. But keywords miss nuance. “Apple” could be a fruit or a brand. A word like “shot” means something very different in a basketball recap than in a news report.
Keywords also miss tone, which makes brand safety harder. Picture an airline ad next to a news story about a plane crash. A keyword match might see “flight” and approve the placement, even though the context calls for the opposite.
Topic and Category Classification
A more advanced approach classifies content by topic and category, often using natural language processing. Instead of matching single words, it analyzes full sentences to understand what a page is actually about. Some systems can also assess sentiment across text, images, and video.
The result is more accurate targeting and stronger brand safety controls. Still, it understands the page, not the person reading it.
It can tell that an article is about family cars. It can’t tell whether the reader is daydreaming, comparing prices, or ready to book a test drive.
What Is Neuro-Contextual Advertising?
Here at Seedtag, we see Neuro-Contextual Advertising as the next evolution of contextual. Combining neuroscience and AI, it starts from a simple premise: the content people engage with reveals not just what they’re reading or watching, but how they feel.
Who someone is rarely changes from one hour to the next. How they feel, and what they’re focused on, can change in an instant. That’s why Neuro-Contextual Advertising looks at three signals that shape how people respond to advertising. Interest determines whether someone is engaged at all. Emotion affects how easily a new message connects with what they already know. Intent determines whether they’re in the right situation to act.
It’s also why viewability alone isn’t enough. An ad can be seen without ever being processed.
Liz, our Neuro-Contextual AI, reads these signals across the content people consume on the open web, video, and CTV. Where traditional approaches stop at what a page is about, it interprets the moment around it, all without personal data or identifiers. Brands and agencies can then align with that moment across the full funnel, from building awareness to driving action.
The difference is backed by science. In our neuroscience research, developed with Prof. Moran Cerf of Columbia University, Neuro-Contextual ads drove 3.5x higher neural engagement than non-contextual ads, and a 26% stronger emotional response than standard contextual ads.
What This Shift Means for Brands, Agencies, and Publishers
- For brands, the question changes. It’s no longer just where an ad should appear, but what someone is experiencing when they see it.
- For agencies, measurement changes too. Clicks and viewability show that an ad could be seen. They say little about whether it was noticed, felt, or remembered. Planning needs signals that reflect how people actually respond, and audiences they can look inside, rather than segments they have to take on trust.
- For publishers, quality content gains new value. When advertising responds to how content makes people feel, the stories that hold attention and spark emotion become the most valuable environments, not just the ones with the most traffic.
And across the open web, video, and CTV, that understanding can move from screen to screen, without following the people themselves.
From Context to the Moment
Contextual advertising began as a way to decide where an ad should appear. Neuro-Contextual Advertising takes it further, helping brands understand the people on the other side of the screen without needing to know who they are.
Keywords told us what a page said. Classification told us what it meant. Neuro-Contextual Advertising helps us understand how it feels.
That’s the next shift for every marketing strategy. Brands that win won’t just reach audiences. They’ll resonate with people, one moment at a time.
For most of digital advertising’s history, discovery and purchase lived in different places. People found a product in one channel, researched it in another, and bought it somewhere else, often after a long chain of clicks, forms, and checkout pages. Every step in between was a chance to lose them.
Social platforms are closing that gap. On TikTok, a single moment can hold the whole journey: people discover a product, watch a creator explain it, and buy it without leaving the app. A platform once seen mainly as a place to build awareness has become a place where brands drive real business results.
Two forces are making that possible. Creators give products a voice audiences already trust. And AI in digital advertising is removing friction from nearly every step in between, from producing creative to finding the right audience to measuring what worked.
In this episode of AdTech Heroes, our host Jon Wallett sat down with David Kaufman, VP of Product Management and Head of Monetization Product Solutions & Operations at TikTok, to explore how those forces come together.
They talked about integrated commerce, how brands of every size are using TikTok Shop, and how automation and agentic AI are reshaping creative production, media buying, and measurement. At the center of it all is the goal that shapes Kaufman’s work: removing every bit of friction between a client’s investment and the business result it’s meant to drive.
Key Takeaways
- When discovery and purchase happen in the same place, the hard part of selling online shifts from building a storefront to finding the right audience.
- Brands use TikTok Shop in different ways: as a primary channel for small businesses, a category accelerator for retailers, and a product testing ground for large CPG companies.
- On creator-led platforms, creative increasingly does the work of targeting by letting the message find its audience.
- Agentic AI for media buying gives marketers a choice between full automation and precise, hands-on control.
- Measurement credibility depends on third-party validation and on letting the client define what value means.
How TikTok Shop Turns Discovery Into Commerce
TikTok’s roots are in short-form video, and early on, brands saw it mainly as a way to build brand equity. Today, the platform supports a much wider range of business objectives, and more of them are about performance.
TikTok Shop has made social commerce part of everyday shopping.
Kaufman walked through the traditional online journey: see an ad, click it, visit a website, create an account, enter payment details, add to cart, check out. Every one of those steps is friction. Every step also loses people along the way, which weighs on engagement and conversion rates. On TikTok Shop, most of those steps disappear. People see a product, like it, tap it, and buy it.
The power of commerce at the point of discovery, he said, can’t be overstated.
It also changes what’s hard about selling online. Earlier in his career, as an entrepreneur, Kaufman worked in distributed e-commerce, sharing product data across the social web. Many of his clients believed building the website was the hardest part. It wasn’t. On TikTok Shop, the platform, its users, and its creator ecosystem do much of that work, helping brands find their audience faster and see results sooner.
“Finding your audience is the hard part.”
How CPG Brands and Retailers Use TikTok Shop to Test and Grow
Not every brand comes to TikTok Shop for the same reason. Kaufman described three distinct patterns, each shaped by the size and mechanics of the business.
Small and medium-sized businesses often treat it as another sales channel, and sometimes the main one. Around seven and a half million SMBs in the US use TikTok solutions. Some run their own websites, and some don’t. Either way, integrated commerce is easy to set up, and sales happen naturally as people discover products in their feed.
Established retailers tend to enter one category at a time. Health and beauty has been especially strong, which fits how much of the platform’s content already lives there. “Get ready with me” videos and hair and makeup tutorials create a natural home for products people want to see in action.
The third pattern may be the most surprising.
Large CPG (consumer packaged goods) companies without a direct-to-consumer presence are using TikTok Shop as a product testing ground. How do people respond to a new snack flavor? What kind of engagement does a new beverage concept earn? Instead of waiting on traditional research, these brands get real-time insights from real buyers. Fulfillment is the main challenge on the back end, and brands can either manage it themselves or work with TikTok.
The result is a hybrid of sales and market research, and it isn’t limited to large companies. For emerging brands, a low barrier to entry makes it easier to test an idea before committing to a bigger launch.
Why Creators Power Integrated Commerce on TikTok
If TikTok Shop is where the sale happens, creators are often what make it happen.
Kaufman pointed to TikTok’s creator ecosystem as one of its biggest strengths. Through the TikTok One platform, brands can work directly with creators who have already built trusted voices and the audiences brands want to reach.
That authenticity is changing performance advertising too. With Smart+, TikTok’s automated performance solution, a brand can bring a large product catalog and let the system match the right product to the right person in the right format.
The creative is evolving as well. Five or ten years ago, a product ad might have been a static image against a white background. Now, brands can bring in creators to explain and enrich the product, and TikTok Shop sellers can work with affiliate creators who make content specifically around what they sell.
On a platform like TikTok, creative has become the targeting. Rather than defining every audience in advance, brands can let their message find the people who respond to it. Personalizing content becomes less about who someone is and more about what they choose to engage with.
What Is AI in Digital Advertising and How Has It Evolved?
Behind the creators and the commerce sits a lot of AI. Kaufman’s view of it is a calm one: AI in advertising is not scary at all.
The industry has relied on ranking for years. What we used to call machine learning, we now call AI, and AI models have long decided which ad appears in front of which person. Kaufman called it maybe the most established and valuable use case for AI anywhere.
He remembers when that work was manual. As an entrepreneur, he found those kinds of insights through hands-on data analysis. Today, they live inside AI algorithms, built into how ads are delivered.
What’s new is where AI shows up next. Some use cases are small but practical: fixing aspect ratios, correcting color, or adding promotional overlays across a catalog of hundreds of thousands of assets. These are repetitive tasks that would be nearly impossible to do by hand at scale. Others are more ambitious. Through TikTok’s Symphony platform, AI enables brands to generate scripts and video from a prompt, or to create a digital avatar that explains a product.
What Is the Difference Between Traditional AI and Agentic AI in Digital Advertising?
Traditional AI works in the background. It ranks, predicts, and optimizes within rules a team has already set. Agentic AI goes a step further. It can understand a goal, plan the work, and act on it.
Kaufman sees TikTok’s role as offering both paths.
A marketer can upload a CRM file of their highest-value customers for a retargeting campaign, or turn on automation and let the system find those customers on its own. Teams that want a deterministic setup can program their business logic against the campaign management API (application programming interface). Others are testing the MCP (Model Context Protocol) offering TikTok announced at TikTok World in May. It lets an agent trained on a brand’s business logic connect directly to the ads platform and manage campaigns.
According to Kaufman, the most sophisticated advertisers are doing a little of everything to learn what works. That’s the real promise of agentic AI for media buying: giving teams the freedom to decide where automation helps and where precision matters more.
How Can Marketers Use Agentic AI in Digital Advertising to Streamline Creator Briefs and Targeting?
Creator marketing has long been one of the most manual parts of social media advertising. Finding the right partner meant researching profiles, scrolling through social media posts, and reaching out directly or tracking down a business manager.
This is where agentic AI in marketing starts to change the work. With natural language processing, a marketer can describe a goal in plain words and get back a shortlist of relevant creators, suggested outreach, and draft briefs. On TikTok, that happens through the Symphony agent, part of what Kaufman calls an agentic buying flow.
What doesn’t change is the need for judgment. An agent can surface options, but teams still decide which creators genuinely fit the brand and which messages will feel authentic to their audience.
AI avatars have a role too, but a different one. If a brand has already defined its audience and wants to test many versions of a message quickly, generative AI makes that possible without a camera crew or a long production timeline. When it comes to authenticity, though, most of the excitement Kaufman hears from advertisers is still about creators.
Why AI-Powered Digital Advertising Campaigns Need Independent Measurement
As commerce and automation grow, so does the need for proof. Sophisticated brands build marketing strategies across every channel, so measurement can’t stop at one platform’s walls.
Measurement was one of the defining topics at Cannes Lions this year, and the message from brands was consistent: they want partners that aren’t checking their own homework. That’s why third-party validation and multi-touch attribution matter as much as the numbers a platform reports on its own.
Kaufman added a principle worth remembering: the client owns the definition of value. For some brands, that means brand lift surveys. For others, it’s media mix models or in-house business intelligence teams. Either way, the platform’s job is to understand how each advertiser defines success and deliver against it.
Premium Formats and the Power of the Moment
Not every outcome is a sale. Some brands need to own a moment.
TopView, the ad people see when they first open the app, is built for advertisers who want a high share of voice around a moment that matters to their business. Pulse Premier lets brands appear alongside content tied to major events such as the World Cup, often to extend sponsorships they run on other channels.
Timing matters too. During the Super Bowl, TikTok found clear spikes in engagement during game breaks, a strong signal for sponsors to run complementary content on the platform. The exception was Bad Bunny’s halftime show, when engagement dipped. Some moments simply command full attention.
It’s an idea we come back to often. Attention clusters around moments, and the brands that understand those moments as they happen are the ones that earn real engagement.
Future Trends: Where Commerce, Creators, and AI Meet
The future trends Kaufman described point in one direction: less friction between discovery and purchase. Creators give products a trusted voice. Integrated commerce turns interest into action in a few taps. And AI adoption is speeding up everything around it, from creative production to buying and measurement.
The brands that grow fastest will treat discovery, creative, and commerce as one connected experience, built around the people they want to reach.
Automated media buying has changed almost every part of how campaigns get planned, priced, and delivered. Programmatic advertising and real-time bidding now move faster than any human could, and machine learning models decide which ad space and ad inventory fit a brand in milliseconds.
Will AI replace media buyers and turn paid advertising automation into the whole job? Not at all, because the parts of this job that actually move a client's business rarely show up in a dashboard.
In this episode of AdTech Heroes, I sat down with Sascha Lock, Executive Director, SVP of Integrated Investment at Hearts & Science, to talk about what automation has genuinely changed in media buying, what it hasn't touched, and why the agencies that win are the ones who treat data-driven tools as a starting point rather than the whole answer.
Key Takeaways
- Automated media buying has made the buying process faster, but it hasn't replaced the relationship-driven work that determines whether a campaign succeeds.
- AI in advertising is following the same path mobile did: it will keep growing until it stops being a separate conversation and simply becomes how digital advertising works.
- Programmatic advertising and first-party data give agencies more signal, but clients still need a human point of view to translate that signal into a decision.
- Real-time bidding has automated pricing, shifting negotiation from "what's the best price" to "what's the best strategic partnership."
- The most valuable habit in media buying right now is filtering. There's more data and more platforms than any one person can track.
Why Automated Media Buying Still Needs a Human at the Center
Ask most people what an "investment" role in media buying actually involves, and they'll picture spreadsheets and numbers moving between columns. Lock pushed back on that idea early in our conversation. His role, he explained, is much more about relationship capital than transaction management.
That distinction matters more as automation takes over the mechanical parts of the buying process. When machine learning and buying platforms handle pricing and placement, the value an agency brings shifts toward judgment: knowing which of the thousands of available options actually fits a client's goals, and being willing to say so.
Lock compared it to any real relationship, built on direct but kind communication and consistency. Automated media buying can optimize an auction. It can't build that trust on its own.
"The actual product isn't everything. You're buying service, and you're buying commitment, and you're buying this mutual strive to do better and to grow together."
Will AI Replace Media Buyers? Not Anytime Soon, Because Context Still Matters
Lock drew a comparison that's hard to argue with. Mobile advertising, he pointed out, used to get its own line item on every media plan. Eventually it stopped being a special category and simply became how advertising works.
He believes artificial intelligence is on the same track. Right now, AI in advertising gets a dedicated conversation on nearly every panel and podcast. Eventually, it will stop being a separate topic and just become the infrastructure underneath everything, the same way connectivity and speed are for the internet today.
That's a useful way to think about whether AI replaces media buyers and paid advertising automation makes the role obsolete. History in this industry tends to be cyclical. Each wave feels revolutionary in the moment, but what people actually need from a partner changes far more slowly than the tools do.
How Programmatic Advertising and First-Party Data Are Reshaping Client Conversations
With hundreds of CTV platforms and thousands of potential partners now available in the US alone, no single person can be an expert on everything. Lock described his role as a connector: someone who listens to every new product release, filters out what's genuinely relevant, and brings a clear point of view to the client.
That filtering depends on data, but the decision itself still depends on people. Clients see the same headlines about programmatic advertising and first-party data that agencies do. What they need isn't more information. It's a trusted read on what that information means for their business, and someone willing to make a recommendation rather than just present options.
From Transactional to Strategic: How Real-Time Bidding Changed Negotiation
Real-time bidding automated a huge part of what negotiation used to mean. Ask a newcomer to define negotiation, Lock said, and they'll usually describe getting the best price. That's still true, and it still matters.
But once pricing and inventory decisions run through an algorithm, the conversation left for humans is a different one. It's less about the number on a line item and more about building something together: better flexibility, stronger strategic terms, and closer collaboration between everyone at the table.
Some of the most productive moments, Lock noted, still come from putting the right minds from a media partner, a client, and an agency in the same room to work through a problem together.
What a Strong, Data-Driven Buying Process Actually Looks Like
When I asked Lock what a strong modern media partnership requires, he didn't point to a platform. He pointed to three habits: transparency, accountability, and speed.
Transparency means being upfront when something goes wrong, not just when it goes right. Accountability means showing up when you say you will, and explaining clearly when you can't. Speed means pivoting quickly once the data shows something isn't working, rather than over-analyzing a decision that's already clear.
The Two Questions Every Agency Should Be Asking Clients Right Now
Lock narrowed the most important client conversations down to two questions. The first is simple to ask and hard to answer well: what does success actually look like, and what sources of truth will we agree to measure it by?
The second is about risk tolerance. Our guest described a rough 70/20/10 framework many teams use: most investment into what's already proven, a portion into promising opportunities, and a smaller share for bolder tests. That last bucket should expand or shrink with how much risk a client can absorb, and it's worth revisiting often.
Getting clear on goals and risk tolerance matters more than any new platform. It's the foundation everything else in the buying process gets built on.
Toward the end of our conversation, I asked Lock what superpower he'd want in ad tech. His answer was "Mr. Transparency": the ability to see exactly what an algorithm is doing and why, not to fight the technology, but to bring that insight back into planning. It's a fitting note to end on. The tools keep getting faster. What agencies bring to the table is still deciding what that speed should be used for.
You can watch the full conversation with Sascha Lock above.
Publishers, agencies, and brands don't always sit on the same side of the table. But at the end of the day, they're facing the same challenge.
For publishers, the question is how to create content relevant enough that brands and agencies want to advertise within it. For agencies, it's where to place their clients and which environments are truly brand safe. For brands, it's where to invest to build a closer connection with their customers. The perspectives are different, and so are the priorities. But the challenge is shared: as the way people discover information keeps evolving, quality content needs to keep being found, valued, and sustained.
That challenge was one of many conversations we brought to Barcelona. From September 15 to 17, the Seedtag Innovation Summit gathered clients and partners from the United States, Latin America, and Europe, opening at the Joan Miró Foundation.
During the Summit, Brian Gleason, our CEO, added another layer: "We're more connected than we've ever been, but we're more distracted than we've ever been." For Brian, finding out how to connect in that moment is the most important thing, whether you're a brand, an agency, or a publisher.
The agenda combined dedicated sessions for the supply side and the demand side with joint sessions that put both in the same room. Topics ranged from the agentic shift and AI search to attention measurement, brand safety, CTV, creative, and life after the traffic. At lunches and dinners, the conversations kept going.
Across all of them, one thing became clear. The challenges facing the adtech ecosystem aren't local. They're global. And they become easier to solve when both sides look at them together.
Key Takeaways
- Consumers are more connected and more distracted than ever, and connecting with them in the moment matters for brands, agencies, and publishers alike.
- The same person makes different decisions in different situations, shaped by signals like time of day, screen, weather, and place.
- Fewer impressions carry identifiers, but audiences haven't gone anywhere, and reaching them requires a new structure.
- Interest, emotion, and intent shape how people process advertising, while viewability alone says nothing about that processing.
- Publishers, agencies, and brands face the same challenges from different perspectives, and the conversation is global, spanning the United States, Latin America, and Europe.
What Are the Biggest Challenges Facing the Digital Advertising Landscape?
Throughout the Summit, Brian Gleason put the consumer at the center of the conversation. For him, it's the one thing the industry doesn't focus on enough. We talk about acronyms, LLMs, and chats, but rarely about what consumers are doing every day or what their world is like.
And that world is full of noise. Attention is fleeting, and capturing it is hard. At the same time, clients are under pressure to grow and differentiate, and Brian raised an open question about what happens to them as products become commoditized in AI chat environments.
Grego Martínez, our Chief Product Officer, pointed to another challenge: media buying itself.
In CTV, most buying happens at the platform level, yet streaming services rarely have exclusive content. To illustrate the point, Grego shared a simple example: in Spain, Harry Potter is available on eight different platforms. So when a brand buys one of them, it's buying the service, not the moment. It learns nothing about the show being watched, the emotion it creates, or the hour and day it's being seen.
Buying through demand side platforms (DSPs) has a similar limitation. Brands and agencies can target IAB categories, keywords, domains, geography, or day part, but combining all of those signals to build moments manually is very complicated. The signals exist, but programmatic fragmentation keeps them apart.
Why the Adtech Ecosystem Is Moving From Understanding the Who to the Moment
For Grego, solving that fragmentation starts with a simple idea: the same person can make very different decisions depending on the situation they're in.
Picture someone commuting to work on a rainy Monday morning, phone in one hand, about to lose connection in five or six minutes. Any message has to be fast. Now picture the same person on a sunny Sunday morning, planning the week ahead with Monday off. They might spend 90 seconds on a powerful long video, one that takes them to the next step.
Nothing about them has changed. Only the moment has.
The same happens with a recipe. On a Tuesday evening after work, someone looking one up wants something fast. On a Saturday morning, with family and friends coming over, they're far more open to a message tied to that interest. The article is exactly the same. The moment is not.
That's why content is only one piece of context. The hour, the day of the week, and the season all matter. So do the type of screen someone is using, the weather, and the place they're in. On their own, these signals won't massively improve advertising. Combined, they create a scenario where advertising works much better.
Moments also change across environments. On mobile, things happen faster. On desktop, people are usually sitting down and paying more attention. CTV is often watched in a group rather than alone.
"We've spent more than 20 years understanding the who. Now, I think the future will be won by those who understand the moment much better," Grego said as he closed his session.
Audiences Were Never Identifiers
Hannes Sieling, our VP of Data & AI, started from programmatic advertising's long reliance on identifiers. They gave data teams structure, plus the reach to find people again. Today, fewer impressions carry them, but the reality hasn't changed. The same people are consuming the same content. And audiences were never identifiers in the first place.
What the industry needs is a new structure, built around the content people consume. That's the idea behind vector-based targeting: grouping similar content together so brands and agencies can find the environments closest to their goals, while balancing reach and precision.
Hannes also pointed to the technology that makes this possible: "Embedders are a little bit the hidden champions, the unsung heroes of the whole rise of large-language models."
The real question is what counts as similar. For him, the answer needs to go beyond clicks or categories and help find the right environment at the right moment. Understanding how people actually process what they see is a key part of that answer.
The Science Behind Attention, Emotion, and Intent
Professor Tino Meitz from the University of Münster explained how people process advertising. Who we are stays fairly stable, but how we feel and what we're focused on can change in milliseconds. When people consume media or advertising, that state of mind matters most.
That's also why viewability isn't enough. It shows that an ad could be seen, but says nothing about whether it was actually processed.
Three contextual signals shape that processing:
- Interest: If people aren't motivated to watch a show, they're unlikely to engage with the advertising within it.
- Emotion and affect: The brain relates new situations to past experiences, so a context that connects to familiar feelings makes new information easier to process.
- Intent: People need to be in the right situation for a message. If you want to buy a mid-sized SUV, you probably won't walk into a Ferrari dealership.
Tino was careful to separate affect from emotion: "Affect is something you can't govern. It's something that's happening, it's also, to a certain extent unconscious. Emotion is an evaluation of your affect afterwards."
How Can Supply and Demand Collaborate Across the Adtech Ecosystem?
Rob Beeler, who led the Two Sides, One Signal working session, explained why collaboration and supply and demand alignment matter. “Both sides are trying to solve the same things. This is a relationship-driven industry, and relationships are built by talking to each other in person. When both sides start working together, he said, they can be more effective for advertisers”, he said.
Kevin Donker, Head of Programmatic & Media Automation at Omnicom Media, brought that same spirit to the agentic conversation. For Kevin, agentic buying is still in its infancy, and the industry will have to come together to adopt protocols that make it reliable. When that happens, the productivity gains from AI should be reinvested in people.
In his view, the winners will be organizations that use AI to boost creativity, leadership, and judgment. The ones left behind will simply put an AI layer on top of an already fragmented workflow.
Brian Gleason echoed that idea in his closing remarks. He pointed to the feedback shared over the three days on different ways of working, ad inventory sources, and ways to measure. He also stressed the importance of trust: when you know you can trust someone, you know they'll do what they say they're going to do.
"There are a lot of pressures and challenges we think about in the world, and the things we shared over the last few days were brilliant. That's what we love to do: share information. It's an ecosystem that works together, and that's what we're trying to create", Brian Gleason.
How Does Neuro-Contextual Advertising Bridge the Gap Between Supply and Demand?
If both sides face the same challenge, they also need a shared way to understand the moment. That's what Neuro-Contextual Advertising offers.
Liz, our Neuro-Contextual AI, reads signals of interest, emotion, and intent to understand the moment behind each impression, without personal data or identifiers. For brands and agencies, that means reaching people when it matters most. For publishers, it means their content is valued for the moments it creates.
And it goes beyond advertising. Bringing value back to the open web helps keep quality content alive, and that's a responsibility the whole industry shares.
From Barcelona to the Next Conversation
Over three days, publishers, agencies, and brands from the United States, Latin America, and Europe approached the same questions from different perspectives. How do we capture attention? How do we reach audiences without identifiers? How do we make sure quality content keeps being found and valued as the way people discover information changes?
For us, at Seedtag, those conversations reinforce the vision behind Neuro-Contextual Advertising: understanding people's interest, emotion, and intent in the moment they're in.
It's not about knowing who. It's about understanding the moment.
Thank you to everyone who joined us in Barcelona. If you'd like to keep the conversation going, our team is here.
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For many years, brands were able to leverage the benefits of third-party cookies to help them identify consumer behavior and target them online with ads. Consumers were not particularly pleased with this approach and considered it an intrusion of privacy. This focus on data privacy became especially relevant in 2020 as online activity sky-rocketed, with most people staying home.
Companies like Apple have already moved to phase out third-party cookies, with Google looking to complete the same by 2024. With acts like GDPR and CCPA put in place by governments, the death of third-party cookies and other means to identify online behavior was welcomed by consumers; advertisers did not share the same enthusiasm.
The marketing and advertising industry has again looked to technology to solve the same challenges technology has created.
Contextual advertising emerged as one of the relatively easy options for companies to adopt and ensure they could still target consumers with some degree of certainty. It showed more significant benefits in targeting, increased sales, improved adherence to brand safety and suitability, and much more.
Reports estimate that the global market for contextual advertising will reach a size of US$335.1 Billion by 2026, growing at a CAGR of 13.3% over the analysis period.
Contextual advertising is all about analyzing the web page's content and context to determine whether an advertisement is relevant and suitable to that page. The tools in the market today allow brands to study a variety of parameters including keywords, page type,media channel, positive or negative connotations and more, without the use of third-party cookies.
Brands are able to optimize ad positions and deliver relevant and engaging communications with the target audience. The goal of contextual advertising is to make the ads as relevant as possible to the user to increase their chances of clicking on the ad. For example, someone reading a webpage on golf is more likely to buy golfing equipment and related apparel than possibly place an order for fast food.
Contextual advertising is continuously being refined by technologies like AI, machine learning, natural language processing and more. For the longest time, AI was confined to the realms of science fiction, books and movies. However, the science fiction of yesterday has become the reality of today. The advertising world got its first taste of the power of AI when Lexus released an advertisement entirely scripted by AI. By studying over a decade of award-winning car advertisements, Watson from IBM identified the winning elements and put them together in a single ad.
With AI, brands are able to gain actionable insights with regard to context behind digital content beyond just keywords and user behavior. AI is helping brands determine suitability of an ad in correlation to a webpage with greater accuracy, determine optimal spots for ad placement to yield higher returns on ad spend, enhance targeting through real-time analytics, deliver more relevant and personalized experiences to readers and much more.
Marketers and advertisers prefer to leverage AI to palace contextual ads than third-party cookies for various reasons. Some of the top reasons include the following –
- Adherence to data privacy - Third-party cookies have been under scrutiny for their potential impact on consumer privacy. Cookieless advertising methods, such as AI-powered contextual advertising, do not rely on personal data from users to target ads. AI can analyze data from first-party sources to create a complete picture of the user. This includes demographics, first-party customer data, interests, and behavior, which can be used to target ads more accurately.
- Improved targeting – AI algorithms can analyze and understand the context of a webpage or app beyond just text and keywords. These algorithms can optimize ad campaigns by adjusting targeting by studying performance metrics such as click-through and conversion rates to know what ads work in the page's context. AI-based NLP is even able to understand the intent behind a search query, allowing for more accurate ad targeting. AI is also helping brands locate the optimal spots for ad placements so as to ensure maximum return on advertising investments
- Enhanced personalization - Consumers today find most digital ads to be disruptive to their online experience. AI is helping address this challenge by not only finding the best spot to place the ad, but deliver the ability to blend ads into images or video more seamlessly into the larger webpage content, that is more attractive and interesting to readers and enabling a higher quality experience and subsequently returns
- Increased brand safety and suitability – AI algorithms can also identify negative articles, fake news, fraudulent articles, etc., and avoid placing content there to enhance favorability with audiences and avoid financial losses. When going beyond browsing data, AI allows brands to ensure that users see ads in the proper context. AI can also detect and prevent fraud, such as bots clicking on ads, making the advertising ecosystem more secure.
The market spending for AI in marketing is expected to grow significantly in the coming years. According to a report by Markets and Markets, the global market size of AI in marketing is expected to reach USD 40.09 billion by 2025. AI constantly improves, learns, and adapts as needed to make better decisions. This will allow brands to future-proof their targeting efforts and advertising spending as the market evolves. Cookie-less advertising is the future of digital advertising, and AI is set to usher in a new era of contextual advertising. If you are yet to adopt contextual advertising and technologies like AI to improve the return on your marketing investments, contact us at Seedtag today.
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The privacy era will reshape the ad tech landscape, and contextual advertising is set to emerge as a lynchpin for brands looking to adopt effective, privacy-first ad strategies.
According to research, the global digital advertising market is projected to reach 562 billion USD by 2030, growing at a CAGR of 13.8%.
With the progressive loss of effectiveness of third-party cookies and the introduction of data privacy laws, brands must explore privacy-first, future-proof alternatives. Contextual advertising is emerging as a frontrunner as it bridges the gap between privacy and targeting. The traditional practice of relying on personal information will not make the cut going forward.
How Contextual Advertising is Shaping the Future of Advertising
The shift in focus: Quality over Quantity
For the longest time, both advertisers and publishers have relied on data collected through profiling to attract audiences and make ad-buying decisions. The focus has always been on bringing in a large number of general audiences and never on what truly interests them. These traditional methods solely rely on the intrusive collection of personal data not backed by any other privacy-first approach.
This method of automated or programmatic ad buying has had a significant impact on the quality of content online. Programmatic advertising focuses on reaching a broad audience, thus incentivizing publishers to prioritize the volume game and diluting the emphasis on catering to specific audience interests.
But with the spotlight on data privacy laws and the progressive loss of reach of third-party cookies, the emphasis is back on content quality over engaging with generic audience pools. Contextual advertising offers a privacy-compliant alternative to display ads on relevant websites that target relevant audiences beyond just using cookies.
The rise of contextual advertising
Artificial Intelligence (AI) and Machine Learning (ML) have already made their way into various walks of life, and the advertising industry is no exception. AI-powered contextual advertising has the ability to analyze the written and visual content on a web page and display relevant ads that reach the desired targeted audience.
With rising privacy concerns and the progressive loss of reach of third-party cookies, contextual advertising is poised for significant growth in the coming years. It offers a more privacy-compliant and relevant way to target consumers compared to traditional methods by providing a solution that balances user privacy with effective targeting.
The Role of AI in Contextual Advertising
AI and machine learning are transforming the way digital ads are placed in the advertising industry. By analyzing consumer behavior and the content of web pages in real time, AI-driven ad campaigns ensure that ads are displayed in the most relevant ad space. Evolving at a rapid pace, and brands must adapt to the new reality where third-party data is no longer the gold standard. This method not only increases engagement but also prevents ads from being placed near inappropriate content, ensuring brand safety.
By leveraging first-party data and AI-powered contextual advertising, advertisers can make data-driven decisions without compromising consumer privacy. This privacy-first approach aligns with data protection regulations like GDPR and CCPA, ensuring brands remain compliant while still delivering highly relevant online ads.
A Privacy-First Future of Advertising
Privacy-first marketing strategies will shape the future of advertising as consumers demand more control over their data. As regulations tighten and consumers become more aware of their personal data, businesses that adopt contextual advertising will stay ahead in the digital advertising landscape. Those who fail to embrace it, risks falling behind as the industry shifts towards a more secure, transparent, and ethical future.
Additionally, linear TV is losing its dominance to Connected TV (CTV) and digital platforms, making programmatic advertising and contextual targeting the best strategies for brands looking to maximize ad spending while adhering to data privacy laws. Building niche audience segments, leveraging first-party data, and exploring new-age strategies like CTV advertising are a few among the myriad opportunities contextual advertising offers.
Contextual advertising is not just an alternative to cookie-based tracking; it is the foundation of the future of advertising. By focusing on real-time analysis, AI-powered targeting, and privacy-first approaches, brands can build trust and loyalty with their audiences. Interested to learn more about how you can benefit from contextual advertising?
As the number of consumers moving online grows at a meteoric pace, brands today are doubling down on the effort spent to understand and control what kind of online content their ads run along with. Growing consumer focus on brand reputation and data privacy have every brand treating ad placement with kid gloves.
Until 2019, brands defined their own rules and strategies of what was considered appropriate in the online space. It was in 2019 that the focus on brand safety and brand suitability saw a concrete direction with GARM.
For the uninitiated, GARM stands for the Global Alliance for Responsible Media. It is an industry-led initiative founded in 2019 that aims to improve the safety and sustainability of digital advertising, reduce harmful content online, and promote integrity and accountability in the digital media ecosystem.
Since the standard procedures and guidelines have been defined by representatives of agencies, advertisers, media platforms, and industry bodies, GARM is widely regarded as having set the brand safety and suitability standard for all to follow.
Despite the standards being defined, a report featured in The Guardian in 2020 found that over 100 big brands like Samsung, Decathlon, Audi, L'oreal were unknowingly running their advertisements on YouTube videos on the site that were actively promoting climate misinformation. These incidents highlighted the need for greater transparency and responsibility in digital advertising practices and underscored the importance of initiatives like GARM.
Brands can demonstrate their commitment to responsible advertising practices by aligning with the practice set forth by GARM in the following manner –
- Understand the GARM Framework - A comprehensive grasp of the brand safety floor and suitability framework enables organizations to identify hazardous content and convey an incorrect message about brand values, which can significantly affect consumer perception. Without knowing the tools that one is working with, building a successful concrete campaign would be improbable.
- Audit existing brand campaigns and partners – Once you know what the playing field looks like, you must audit your brand's advertising practices and make changes as necessary to ensure compliance with GARM standards. This is not limited to just the company that owns the brand itself but needs to extend into the larger ecosystem to ensure partners, including media platforms and agencies, and everyone responsible for developing and implementing brand campaigns understands and implements the standards thoroughly. For example, in 2020, Unilever announced that it would stop advertising on Facebook, Instagram, and Twitter in the United States until at least the end of the year, citing concerns over hate speech and divisive content on the platforms.
- Leverage relevant tools and technologies to monitor the brand: Leverage available technologies and tools, such as brand safety verification services, to monitor where your ads are being placed and ensure that they do not appear next to harmful content. With the growing focus on contextual advertising, brands can leverage advanced tools like AI to determine brand suitability and contextual fit. Brands like P&G and Nestle are already experimenting with AI in market analysis and product development, analyzing ad placements in real-time and ensuring that ads are not appearing next to inappropriate content.
- Given the pace of change in the digital advertising landscape, the renewed interest in contextual advertising, and the bright spotlight focused on brand suitability, it is essential for brands to continuously engage with the GARM community and work with partners who understand how brands can thrive in the digital space.
We at Seedtag understand the digital advertising landscape and possess the relevant technical knowledge to ensure that brands can grow in today's world. Do write to us to know how we can audit and help your brand stay safe by adopting the latest GARM standards.
The cord-cutting era is here! We’re officially in the age where streaming services have changed the course of television and how content is delivered worldwide. As a result, the shift from traditional TV (Linear TV) to Connected TV (CTV) is also impacting the landscape of online ads, making them more dynamic, interactive, and personalized for viewers.
According to a survey, 2023 was the first year non-pay TV households stood at 68.7 million vs. traditional cable at 62.8 million, outnumbering cable connections for the first time in the United States. Broadcast and cable fell below 50% of all TV usage, and Statista revealed that in 2023, 88% of U.S. households owned at least one internet-connected TV device. The number of CTV users totalled more than 110 million among Gen Z and Millennials.
What is CTV? Laying the Foundations for CTV advertising
Connected TV refers to the device that delivers streaming content, a rapidly growing market with increasing popularity. The past years have seen a growing cord-cutting trend, as people are canceling traditional cable and switching to streaming services. Connected TVs have become the most sought-after and popular choice among the masses as they offer a vast library of content beyond traditional channels, the freedom to browse in one's own time, and choose content that aligns with one’s interests.
Connected TVs give users on-demand access to streaming services like Netflix, Hulu, Disney+, and HBO Max which stream movies, TV shows, documentaries, and even live programs. Flexibility, content diversity, convenience, and overall experience are among the top reasons why people increasingly turn to Connected TV.
The change in trend and massive viewership have naturally garnered the attention of advertisers too. Brands want to display their ads where their audiences are, and today, CTV advertising has gained a top spot. CTV advertising allows brands to reach this growing audience base by offering far superior audience targeting capabilities, higher engagement rates, deeper insights, and measurable results.
CTV advertising is transforming the digital ad landscape, allowing brands to reach highly engaged audiences with more precise targeting. Unlike traditional display ads, CTV ads offer immersive, full-screen experiences that drive higher engagement and brand recall.
Advertising tips: How to choose the right CTV partner for your brand
A strong CTV partner should offer advanced ad tech solutions, including programmatic ad buying, to optimize placements and maximize reach. This ensures advertisers can automate their media buying processes efficiently while targeting the right audiences at the right time.
Inventory quality
Advertisers need to be mindful of the quality of the inventory and its relevance to their brand and audience. Brands need to target their audience effectively and avoid irrelevant placements. Rather than choosing any CTV partner based on demographics or audience types, the focus should be contextual relevance. Placing ads that align with the content audiences are engaging which ensures better engagement.
Brands must also know what type of content will accompany the CTV ads. While CTV ads can be placed across various platforms, the inventory must comprise premium and professionally produced content to attract the right audience and capture their attention. The right CTV partner helps advertisers place ads alongside content the audience trusts, thus going beyond just engagement, elevating brand credibility, and increasing brand loyalty.
Brand safety and brand suitability
As advertisers unlock CTV inventory, it is important to ensure ad messaging and placement are optimal. Ads appearing alongside content that is offensive or harmful can have a negative impact on a brand's reputation. Advertisers must pick CTV partners who provide tried and tested brand safety expertise and contextual relevance to suit the brand’s values, messaging, and positioning.
Many CTV partners leverage AI in advertising, using AI-powered tools and AI and machine learning algorithms to analyze metadata and ensure brand safety. They analyze metadata like the descriptions of CTV videos and titles to determine safety and relevance. It’s crucial to go beyond just metadata and analyze the full content of a video to assess safety and suitability. Brands must gain a complete understanding of a video’s suitability before finalizing a campaign or any ad placement.
This approach goes beyond simple keyword scanning, allowing advertisers to understand the full context of video content and make informed decisions on ad placements."
Reporting capabilities
Like any advertising campaign, understanding performance in-depth for attribution measurement is critical for advertisers. Beyond real-time metrics, brands can analyze search results to evaluate audience interest after exposure to CTV ads. The effectiveness of CTV campaigns relies on analyzing party data and other data collected from audience interactions to better understand consumer behavior.
By tracking how often users search for a brand or product after seeing an ad, advertisers can gain deeper insights into brand recall and effectiveness. When picking a CTV partner, brands must analyze what metrics will be accessible to measure the impact of CTV ads. Transparency of campaign performance and reporting is critical to evaluate ROI.
How did the target audience engage with the brand after viewing an ad, what was the viewer intent and how did the ad impact this journey, what action did they take after viewing the ad, etc. are key metrics that advertisers must have access to. Brands must ensure real-time reporting and insights into metrics like impressions, reach, completion rates, and frequency for transparency.
Enhancing CTV Campaigns with Effective Advertising Tips
To maximize the effectiveness of CTV advertising, brands should adopt advertising tips that enhance their overall campaign strategy. Incorporating eye-catching creatives ensures that ads capture audience attention and leave a lasting impression. Additionally, brands should integrate email marketing strategies such as email newsletters to complement CTV ad campaigns and maintain ongoing engagement with their audience.
Using programmatic ad buying can also improve efficiency by automating ad placements, ensuring that brands reach the right audience at the right time. By leveraging AI-driven insights, advertisers can fine-tune their CTV advertising efforts and optimize results.
Introducing Contextual TV by Seedtag
Seedtag’s latest offering for the Connected TV ecosystem, Contextual TV aims to extend our contextual expertise to enable brands to activate strong CTV campaigns with precise targeting capabilities that go beyond the standard targeting practices.
CTV has now become one of the most effective ways to target audiences, especially the new generations like the Millenials and Gen Z, who have cut the cord. For over a decade, we at Seedtag have been empowering brands to effectively connect with their audiences using our unmatched technology that provides superior targeting capabilities and user understanding.
With Contextual TV, we’re not just adapting to trends, but actively helping to shape the future of advertising in the CTV space. Brands can now leverage open web benefits for the big screen, eliminating today’s limitations of targeting precision and reporting in the CTV advertising landscape.
- Combining the Open Web with Connected TV empowers brands to explore, uncover untapped opportunities, and engage with the right audience at the right time with the right message.
- Comprehensive reporting options to ensure you truly understand the effectiveness of your campaigns.
- Engaging creatives that garner audience attention.
Trust, reputation, review, and recommendations play a critical role among consumers today, during any decision-making process. Customers want to purchase from a reputed brand. Thus, brands invest significant budget and workforce to ensure their image and reputation are built and safeguarded at all times.
The public's overall perception of a brand is forged over a period based on the brand’s values, messaging, reviews, and the customer’s interactions and experiences with the brand. The brand image focuses on the messages a business intends to convey through marketing, design, and communication efforts. Brand reputation reflects trustworthiness, ethics, reliability, the quality of their products or services, and the high-quality advertising content they create and place.
Advertising plays a key role in making or breaking a brand’s image and reputation: The messaging and creatives floated by brands through their ads are a direct reflection of their ideas and values. So, the ads a brand creates and where it chooses to place them have a crucial impact on consumer perception. Effective ad campaigns should take into consideration brand safety, ensuring that the messaging aligns with the company’s values and avoids harmful contexts.
For example, a children's toy company running ads on a website or article that features explicit language or violent content can negatively impact how they are perceived. Similarly, a brand that sells vitamins or fitness products placing ads on a platform that promotes unhealthy lifestyle choices and dangerous behaviors such as extreme dieting or risky physical activities, it goes against its fundamental values.
Brand safety: The need of the hour
Today, there is an ever-increasing need to be mindful of the advertising content created and where they are showcased, making way for the implementation of brand safety and suitability measures. These advertising practices aim to shield a brand's image and reputation from being negatively impacted by online advertising placements.
Whether it is social media or the web universe, ad placement plays a critical role in ensuring brands avoid content that may harm their image, maintain trust with consumers, and build their reputation. To protect your brand’s image, it is essential to ensure that your ads do not appear in inappropriate contexts or next to harmful content. So, the focus lies in making sure brand ads do not show up next to content that could be considered harmful or inappropriate.
Factors pose a threat to brand safety in today’s digital landscape
- Placing ads in inappropriate or controversial contexts using exclusion lists, etc.
- Ad placement alongside unrelated or conflicting content.
- Brand presence besides fake news or misinformation, preventing ads from showing alongside unrelated or harmful content.
- Losing precious advertising dollars to ad fraud on dubious websites set up to generate false clicks.
- Data breaches or data privacy violations of precious consumer information.
The deprecation of third-party cookies has already put contextual advertising as a front runner in the digital landscape. However, contextual AI’s ability to ensure the highest levels of brand safety and suitability is another reason that makes contextual ads an ideal alternative to cookie-based advertising practices. Contextual advertising and AI advertising enable a brand to target relevant audiences while ensuring the ads align with its values, thus protecting its reputation.
The spotlight on brand safety and brand suitability
Contextual advertising relies on Artificial Intelligence (AI) to deliver ads on relevant websites that target relevant audiences without the use of cookies. Contextual advertising’s Machine Learning (ML) and Natural Language Processing (NLP) capabilities go a step further and have the ability to understand nuances in language and semantically interpret editorial content.
By analyzing the written and visual content of a page, contextual advertising offers brands an environment where the values and ideas seamlessly fit with their image and values, thus ensuring the highest levels of brand safety. Additionally, brand suitability helps bridge the divide between risk and opportunity and provides context-based protections.
The merge of brand safety and suitability
It helps brands elevate their targeting strategy:
- Shields your brand image and reputation from any negative impact
- Prevents your ads from appearing alongside harmful or inappropriate content
- Aligns ad placement with content that reflects brand identity and values .
- Places ads where they resonate with the right audience.
What can we expect of the future of brand safety and suitability
With brand safety and suitability, brands can navigate tricky spaces where there is a risk of exposure to controversial and harmful content. For instance, a website that focuses on financial news might cover some topics that brands might deem unsafe. However, websites that cover topics like finance or the stock market might be a great bet for a luxury watch brand. Therefore, strategic ad placement plays an important role in maximizing opportunity and impact.
As we venture into the future of digital marketing, the combination of brand safety and suitability emerges as a guiding light for brands seeking to safeguard their reputation while maximizing their reach. By embracing contextual advertising and its contextual AI capabilities, brands can confidently navigate the complexities of online advertising, secure in the knowledge that their message is not just heard, but heard in the right place, at the right time, by the right audience.
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Connected TV or CTV advertising is swiftly becoming a core advertising strategy as internet-connected televisions take over households and the interest shifts towards content streaming platforms. Leichtman Research Group reported that 88% of US households own at least one Internet-connected TV device. The number of adults in the United States households who watch videos on a TV via a connected device daily rose from 6% in 2013 to a staggering 49% in 2023.
Audience inclination toward CTV from traditional television has shifted the spotlight to CTV advertising, making it the next big thing in the ad tech space for brands seeking to reach their target audiences. Brands need to be where their audiences are and make their presence felt. With the audience behavior shifting toward streaming platforms, understanding consumer behavior is essential for brands to adapt their advertising strategies accordingly. Likewise, dedicating a significant amount of time in their day-to-day to spend on streaming platforms like Netflix, Amazon Prime Video, Disney+, and Hulu; it is only obvious that brands are changing gears in their ad strategies and allocating more more advertising budgets to CTV ads.
Beyond just the viewership
While the rising viewership numbers are an important factor that is shining the light on CTV advertising, another critical aspect is brand safety. Maintaining brand reputation is imperative in today’s chaotic digital landscape where there are myriad stories, news pieces, opinions, and debates. As a more regulated and transparent medium, Connected TV offers a safer space for brands to engage with the audience in the digital age.
Brand safety refers to the practice of protecting a brand's online reputation and image by taking steps to prevent its ads from appearing alongside inappropriate or harmful content. For example, no brand would want its ads to appear next to content about hate speech or terrorism. Similarly, a fast food chain will not want ads to appear in an article about heart attacks or a travel company’s ad next to news around layoffs or economic downturns.
Tackling Ad Fraud and Viewability in the CTV Advertising Landscape
As CTV advertising continues to shape the modern advertising landscape, brands must also consider the impact of ad fraud and viewability challenges. Unlike traditional TV, where ad placements are predetermined, CTV operates in a dynamic digital environment where fraudsters exploit loopholes through practices like device spoofing and invalid traffic.
To ensure both brand safety and budget efficiency, advertisers must leverage advanced verification tools and collaborate with trusted ad tech partners. Implementing AI-driven fraud detection and adopting programmatic transparency measures will help brands safeguard their campaigns from wasted ad spend and reputational damage.
Brand safety and Connected TV (CTV)
A survey revealed that 70% of advertisers felt brand safety incidents impacted their campaigns. It also showed that 67% of brands said they believe they are taking a serious financial risk by not addressing brand safety online. 37% of brands have experienced a brand safety issue and the worldwide advertising dollars wasted due to a lack of brand safety in 2019 was estimated to be $14.8 billion.
While there is transparency in the inventory and regulations in the space, CTV advertising is still a struggle for brands and advertisers when it comes to a buying environment. They need a more in-depth understanding of the inventory and where their ads will appear. With no industry-wide protocols in place yet and a lack of transparency on what marketers are buying, the need of the hour is visibility. Brands and marketers need real-time visibility of ad placement to prevent their ads from appearing in inappropriate or harmful environments and requiere to be watchful of ad placement to prevent their ads from appearing in inappropriate or harmful environments.
A mix of reputable inventory sources and contextual relevance is a tactic many brands are opting for to overcome the brand safety issues that the sought-after CTV advertising currently poses. Analyzing and reviewing media buying at a content level can help alleviate brand safety concerns by ensuring the content is not just safe but relevant too.
With contextual advertising-backed CTV targeting, brands can address both brand safety and brand suitability. By analyzing the content and context of shows, contextual targeting empowers brands to place their ads alongside the most brand-safe and relevant content. Users are more likely to engage with an ad that aligns with the content they are currently viewing, thus driving engagement and ad recall by garnering more impactful consumer attention.
Relevant and engaging content creates a great connection with the user, increases the time users spend on an ad, and goes beyond just visibility to deliver meaningful engagement. CTV ads bolstered by contextual targeting help brands better navigate the relatively new ad space, improve ad targeting, deliver more impactful outcomes, and enhance the overall brand impression.
The Future of Brand Safety in CTV Advertising
n today’s evolving advertising landscape, winning brand safety in CTV advertising requires a multi-faceted approach that combines transparency, technology, and strategic media buying. As brands continue to shift budgets toward CTV, adopting proactive safety measures, such as contextual targeting, premium inventory selection, and third-party verification, will be key to maintaining brand integrity. By staying ahead of industry developments and investing in secure advertising practices, brands can maximize the potential of CTV advertising while ensuring their message reaches the right audience in a safe and suitable environment.
In today’s privacy-first world, , cookie-based targeting has been a central pillar that both advertisers and publishers have relied on heavily for decades. According to a Deloitte survey, the average projected revenue risk ranged from around $91 million to $203 million per year, with some companies risking upward of $300 million in revenue. A Google study showed that for the top 500 global publishers, the average publisher revenue decreased by 52% with a median per-publisher decline of 64%.
Publishers who have exclusively relied on third-party cookies have begun to feel the heat. Much like advertisers, publishers have been evaluating other strategies to help them grow their revenue while remaining privacy-compliant. Beyond business-as-usual, the progressive loss of signal and reach of cookies presents publishers an opportunity to future-proof their business and generate new revenue streams. This approach is not just a short-term fix, but a sustainable, long-term strategy to future-proof the business against privacy changes.
How are publishers riding the Data Privacy-First World wave?
Publishers are looking to continue to expand their readership and audience trust and audience trust in a privacy-first world, where privacy compliance and transparent data usage are becoming paramount. While large tech companies have traditionally dominated the advertising space, publishers are now taking more control over their ad inventories through privacy-compliant solutions.
Topics API is the Privacy Sandbox entrant that was initially introduced as an alternative to third-party cookies, to enable privacy-first, interest-based advertising. To make the most out of Topics, publishers and advertisers must use them with other tools to develop more innovative marketing strategies that cater to the new-age audiences.
Leveraging First-Party Data for Better Targeting
While third-party data has been a staple for targeting, publishers are increasingly focusing on first-party data, which is more reliable and privacy-compliant. Information that audiences willingly share can be used alongside Topics for a more tailored and relevant targeting approach. First-party data is a gold mine that publishers can leverage to monetize audiences and boost revenue numbers. Secure collation of first-party data is essential to collate privacy-safe media that can be monetized by publishers, but they must be cautious with personal data, ensuring that they only use it with user consent and in accordance with privacy regulations with the General Data Protection Regulation (GDPR) to avoid potential legal risks.
"The amount of data publishers can collect from first-party sources is growing, allowing for more personalized and relevant ad targeting".
Evaluating and Upgrading Tech Stacks to Enable Privacy-Safe Data Collaboration
Publishers are working towards evaluating their current tech stacks and upgrading them to create more data clean rooms that enable privacy-safe media collaboration. Publishers can collaborate with advertisers and monetize the data by giving them access to the valuable repository. Effective consent management is crucial for publishers to ensure that the data they collect is used appropriately and in compliance with privacy regulations.
AI-Powered Contextual Advertising: Boosting Monetization and User Experience
AI-powered contextual advertising offers publishers a cookie-free solution that aces targeting and better utilizes first-party data. Contextual ads are proving to be a game-changer for publishers by enabling them to navigate privacy regulations and create a sustainable monetization strategy.
- Contextual AI analyzes the written content of a page and empowers publishers to provide advertisers with an environment that offers the highest levels of brand safety and suitability. Machine Learning (ML) and Natural Language Processing (NLP) capabilities of contextual advertising enable understanding of nuances in language and the ability to semantically interpret editorial content. Brand suitability bridges the divide between risk and opportunity and provides context-based protections for advertisers and publishers. Brand safety ensures they steer clear of any negative or harmful content that can impact user perception and damage the reputation of publishers or advertisers.
- With contextual ads, publishers can have a higher impact on users as they are relevant ads displayed alongside high-quality content. The ads are more relevant and impactful as they speak more directly and personally with the readers, increasing the likelihood of users paying attention and engaging with contextual ads. Publishers who host contextual ads unlock a new, steady revenue stream as the relevance to the content users are currently consuming increases brand recall. Better brand recall and ROI on dollars spent increase the chances of advertisers continuing to buy inventory. By using AI-powered contextual advertising, publishers can expect higher conversion rates as ads are more relevant to the audience’s interests.
- Contextual advertising also enables publishers to enhance the overall user experience. Contextual ads are more relevant to the real-time interests of users, are less intrusive, and do not hamper their browsing experience. A more pleasant overall experience will help publishers grow their readership as users are more likely to come back and recommend them to other readers. It allows publishers to focus on reaching and engaging the right audience, ensuring that the ads displayed are highly relevant and impactful.
Collaborating with a contextual partner will help publishers unearth new monetization opportunities and provide a superior user experience. Engaging creatives, content alignment, and intelligent ad placement ensure contextual ads are seamlessly integrated with the on-page content, thus maximizing visibility, impact, and revenue potential.
Embracing a Privacy-First World for Sustainable Growth
We have partnered with over 11,900+ digital publishers across the globe, and our combination of relevant data and new-age technology helps them make the most out of every ad placement in a privacy-first world. 80% higher viewability, 15% longer in-view time, and 1.3% more click-throughs; our unique, data-backed targeting strategies and innovative methods like custom AI, backed by our in-house contextual AI solution, Liz, have delivered exceptional results when compared to exclusively relying on cookie-based targeting practices.
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The ad tech world is steadily shifting to more inclusive and privacy-centric advertising practices that align with the requisites of consumers and data privacy regulations. Fundamentally, audience categorization has largely been based on the demographics and past behavior patterns of users. This practice is based on assumptions and stereotypes that are limiting, not always accurate, and relies on third-party cookies.
The audience selection and classification process plays a crucial role in determining the success of an ad campaign. By collecting data from various sources, advertisers leverage data to display ads to users based on their assumed interests, hobbies, and browsing activities. The main data points include -
- The websites and apps a user chooses to visit, browsing patterns and interactions, and what kind of content they engage with
- Demographics like age, gender, and location
- Interests listed by the user on platforms like social media
- Third-party data
Using this data, marketers profile potential customers who are most likely to buy their product or service and target their ads to those individuals.
What is interest-based targeting?
Consumers have become increasingly apprised of digital advertising practices and are well-informed about their data and personal information being collected whenever they are online. The increase in awareness and rising frustration of consumers around data privacy resulted in the decision to phase out third-party cookies and governments implementing more stringent data privacy regulations. Marketers are facing several restrictions today and the conventional audience categorization and targeting practices will result ineffective as they are built on stereotypes and assumptions, and are not privacy compliant.
While traditional advertising practices reach a broader audience, they are not necessarily effective as everyone who views the ad might not be interested in the product/service, leading to wasted ad spend. Consumers have access to a plethora of information and are bombarded with hundreds of ads daily. A blanket targeting approach sans any personalization or relevance is not just ineffective but could have a negative impact as it disrupts the user journey. Additionally, consumers are also using ad blockers to avoid traditional ads while streaming services give them the option to skip ads.
New-age targeting goes well beyond the conventional, identity-based targeting approach and focuses on a user’s current areas of interest and the context of the content they consume. Breaking away from stereotypes, interest-based targeting is held as a more effective, non-intrusive, and privacy-centric alternative.
The rise of interest-based targeting in the cookieless world
Contextual targeting is a strategy that focuses on categorizing consumers based on what they are interested in at present, by displaying ads that align with the content they are consuming on a web page or app. When the on-page content and context align with the ads, it ensures a seamless, privacy-centric, and non-intrusive customer experience. Interest-based targeting enables personalization and allows marketers to tailor ads to individual preferences, thus enhancing relevance and engagement. Users are more likely to engage and resonate with the ad because it aligns with what they are looking for in the moment and since the ads blend with the content they are reading, the ads don’t hamper their browsing experience.
Seedtag Contextual Audiences help brands go beyond conventional targeting practices and engage with users based on what they are looking for or interested in at the moment. Powered by Liz©, our pioneering AI technology, custom AI, contextual categories, images, and cookieless sociodemographic models, allows brands to target an audience base that’s diverse, inclusive, and relevant. Our Contextual Audiences evolve from customer input and diverse market research enabling brands to build unique and dynamic audience categories to suit specific business needs.
Interest-based targeting practices like contextual targeting empower marketers to appeal to a more relevant customer base with ads that align with their real-time interests. Contextual ads appear at the most optimal time and place with tailored messaging without violating privacy, thus helping brands reach the desired audiences with a targeting capability that is more flexible and accurate. With interest-based targeting, brands can capture user attention at the ideal moment without relying on cookies, and overcome the limitations of rigid taxonomies and stereotypes.
With Seedtag Contextual Audiences, brands can build a hyper-personalized target group. Backed by AI, this unique targeting capability provides flexibility, scale, and higher accuracy. To know more about the exclusive offering and types of contextual audiences, contact us.
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With the demise of the third-party tracking cookie just months away for Chrome users, digital advertisers who have yet to begin preparations need to catch up swiftly to navigate the transition successfully.
One of the primary alternatives to the deterministic data enabled by cookies is Google’s Privacy Sandbox, which the company describes as “a series of proposals to satisfy cross-site use cases without third-party cookies or other tracking mechanisms.” Initially composed to include audience models like Google’s Federated Learning of Cohorts (FLOC), which was sunsetted in 2022, the Privacy Sandbox includes Protected Audiences (formally known as FLEDGE or “First Locally-Executed Decision over Groups Experiment”) and other APIs that will undoubtedly dictate the contours of the market to come. Businesses across the ecosystem should consider the following details when preparing.
Reevaluating The Focus: Beyond IP Addresses
In the past, digital advertising heavily relied on tracking users through cookies and IP addresses. Protected Audiences and Google Topics moves away from this practice, emphasizing a more privacy-focused approach. It presents a challenge and an opportunity for marketers to improve performance on a device level without resorting to invasive tracking methods.
A crucial aspect of working with Google Topics is to integrate contextual information with situational and device-specific data provided by Google Topics signals. The zip code, for instance, can be a valuable contextual signal. By combining these data sources, advertisers can gain a better understanding of users' preferences and needs, all while respecting their privacy. This approach opens the door to a new world where the cohort can contribute to a more nuanced contextual understanding.
The Evolution Of Performance Marketing
As Protected Audiences and Topics contextual models become increasingly relevant, performance marketers need to adapt to the changing landscape. This transformation involves elongating the marketing funnel and focusing on strategies beyond traditional last-click attribution.
- First-Click Strategies. Performance marketers can adopt first-click strategies to recapture email addresses for retargeting or directly upload data from CRM systems. This shift might result in a longer turnaround time, possibly extending from a six-day window to 10-15 days. However, the potential benefits in terms of privacy and engagement could make it worthwhile.
- Dynamic Creative Optimization (DCO). With privacy concerns taking center stage, it's essential to shift from audience-centric advertising to context-centric advertising. DCO allows advertisers to tailor content to the context of the page rather than focusing solely on the audience. This approach ensures that ads remain relevant while respecting user privacy.
- Redefining Retargeting. Retargeting is evolving. Instead of relying solely on traditional methods, marketers can explore new avenues like email retargeting and mobile site optimizations. These practices add value for the user, offering content, discount codes, tips and trends. It's a broader approach to content marketing, where the emphasis is on reengaging with users in a more meaningful way. Loyalty programs can also play a significant role in this transformation, allowing users to choose their preferred engagement strategies.
- Contextual Lookalikes. One exciting development in this landscape is the emergence of contextual lookalikes. This approach leverages first-party data, whether it's cookie-based or segmentation data, to identify commonalities among users. Instead of relying on tracking and personal data, contextual lookalikes provide a privacy-friendly way to find users with similar interests and behaviors.
In the coming transition, choosing the right partners is crucial. Marketers should seek out tech-forward partners who are committed to responsible and privacy-conscious advertising practices. It's important to avoid partners engaged in arbitrage or those who use "AI" as a copout without a genuine commitment to user privacy.
The Importance Of Retooling Analytics
As performance marketing evolves, it's crucial to retool analytics. Media mix modeling remains essential, even if it's probabilistic. Marketers should look closely at unit economics that can lead to conversion metrics. For instance, understanding the return on ad spend (ROAS) as a "three to one" ratio requires a deep understanding of the step functions involved. This level of analysis is more critical now than ever as privacy and user consent become paramount.
The era of the Privacy Sandbox and its two main APIs, Protected Audience and Topics, signals a significant shift in the world of digital advertising. Performance marketers must adapt to these changes by embracing contextual models, moving away from invasive tracking methods and respecting user privacy. Strategies that elongate the marketing funnel, focus on context over audience and leverage first-party data offer a path forward. By selecting tech-forward partners and retooling analytics, marketers can navigate this evolving landscape successfully, ensuring both effective advertising and user privacy.
By Mike Villalobos, VP of Strategy and Partnerships at Seedtag.
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From browsers like Firefox, Safari, and Opera completely banning third-party cookies to their complete demise in 2024 with Google’s phase-out of cookies; all eyes are on privacy and global regulations. The end of third-party cookies marks the beginning of a new era in advertising as the go-to targeting practice worldwide will become obsolete.
In a survey conducted by Statista, 75% of marketers revealed that they heavily relied on third-party cookies. 45% of respondents stated spending at least half of their marketing budgets on cookie-based advertising. With the fundamentals of audience tracking, targeting, and personalization becoming obsolete, there is a lot of debate around what will be the next best approach for audience targeting that will give marketers a competitive edge.
How are marketers preparing for the cookieless world?
Among the options marketers are evaluating, contextual advertising has been one effective stand-out targeting alternative that has gotten the nod from leading global brands. Contextual advertising is backed by new-age tech like AI, ML, and NLP, paving the way for personalized and impactful advertising in the privacy-first world.
Another alternative that has been around for a while but has garnered more importance ever since the deprecation of third-party cookies is first-party data. First-party data is collected with the knowledge and consent of users when they interact with a brand’s website or advertisement, or purchase a product. However, first-party data is not a magic formula. When utilized individually, first-party data lacks the ability to scale, enhance the precision of audience segmentation, or improve ad placement.
Contextual advertising is scalable and allows marketers to create custom audiences. This opens doors to never-seen-before opportunities and delivers advertising strategies that go beyond traditional metrics like impressions and CTRs. Contextual ads rank high across impactful attention metrics that provide insights into more quantifiable data like the quality of user engagement and campaign efficacy. Contextual advertising aces granularity, accuracy, and relevance by placing ads based on the content and context of web pages, thus helping marketers go beyond stereotypical audience segmentation practices that rely on audience demographics, past browsing patterns, and assumptions.
It also ensures enhanced levels of brand safety and brand suitability. Its ability to understand nuances in language and interpret the meaning of content used within a given context empowers brands to avoid harmful or negative content and maximize opportunities. With AI-powered contextual targeting, marketers can display ads in environments where the messaging aligns with a brand’s values and positioning.
Maximizing impact with the duo
What if marketers could take contextual advertising up a couple more notches? By utilizing precious first-party data repositories along with contextual advertising, marketers can further fine-tune their strategy and maximize the impact of a campaign. Based on the audience information derived from first-party data, audiences can be further segmented based on factors like age group, gender, or location. Since this data is collated with user consent, it is compliant with all privacy regulations. With first-party data-backed audience categorization, marketers can tailor messaging to suit very specific audience segments.
For example, with the combination of intel from first-party data with contextual advertising, a brand can target its repeat customer base with a new product launch or launch an exclusive privé members-only sale. Campaigns and messaging are more tailored and relevant to the target audience, driving more impact and ROI. It can also be used to create geo-specific campaigns during a particular time of the year or during festivals that are more prominent in a particular location. For celebrations like Valentine’s Week, curated gifting ideas or product collections can be showcased to specific genders and age groups to drive more engagement.
Fueling contextual advertising with first-party data will empower marketers to strengthen their strategies and create high-impact campaigns that connect with the desired audiences. The duo ensures seamless, privacy-centric, and non-intrusive experiences that customers love.
Interested to learn more about contextual advertising and its capabilities?
Cue Lover by Taylor Swift…It’s Cupid’s time of the year and the hearts are all afloat. From roses to teddy bears, cards, and jewelry, romance is brewing strong. Couples are on the lookout for the perfect date nights and the ideal gifts to present their loved ones. World over, Valentine’s Day is one of the highlights of February.
In today’s rapidly changing environment, seasonal events like Valentine’s unfold every other day. It is important for brands to not just track, but truly understand these special occasions to capitalize on them. We analyzed the evolution of content creation and its consumption to show how this day impacts the open web. In 2023, Valentine's Day was an engaging and relevant topic, with a particular interest in high-profile couples and commercial promotions. The data showed a steady increase in the number of views as Valentine's Day approached, peaking on February 20th, with the top articles indicating a mix of celebrity news, product promotions, and romantic rumors.
So what’s trending this Valentine’s?
According to our 2024 analysis, the interest in content is mirroring a pattern very similar to that of the previous year. However, we are experiencing a higher viewership when compared to the same time period last year. As a result, we anticipate a substantial increase in views, with the peak expected to reach a staggering 500,000 views on the most prominent days!
The top category with over 15% article distribution is events and attractions, followed by pop culture and family and relationships hovering over 10%. Travel, music and audio, food and drink, and movies are the next set of categories with a 5 - 10% distribution. The last 3 in the top 10 are television, home and garden, and sports.
What are the areas of interest of the Valentine's Day-focused audience?
- Garnering over 2.82M impressions, Love Life is a key interest area where the content centers on the romantic journeys of individuals. The content interest ranges from finding a partner to tying the knot and building a family. The top keywords include power couple, baby son, beautiful family, heartfelt message, closeness, life together, and happy marriage.
- Love life is followed by Celebrities Relationships with 2.4M impressions. The content shines the spotlight on well-known celebrities and public figures, delving into the intricacies of their breakups, romantic escapes, and the elaborate ways in which they celebrate Valentine's Day. Some prominent keywords are relationship timeline, Georgina, Kardashians, Gigi, Love Island, couple, Taylor Swift, celebrity news, and daily celebrity.
- Up next is the much-talked-about Valentine’s Day Plans with 2.32M impressions. This genre places the importance on enhancing the celebration of love and connection through activities and arrangements that couples can enjoy together. This includes keywords like a romantic date, hotel, romantic stroll, romantic dinner, laser tag, authentic Italian, night sky, and outdoor adventure.
- With 2.05M impressions, Rom-Coms are next in line, emphasizing the charm of romantic comedy films and the relaxed, comforting atmosphere they provide. Some trending keywords are Ryan Gosling, Love Actually, Dicaprio, Cameron Diaz, Jennifer Aniston, comedy film, streaming platform, and pride.
- Valentine’s Day Presents come in fifth, gathering 1.53M + impressions by throwing light on the importance of thoughtful presents as a tangible expression of love and appreciation, thus enhancing the romantic connection. The top keywords are gift box, wishlist, Etsy, gift card, pet shop, spa treatment, happy valentine, chocolate, and jewelry.
These areas of interest and keywords are unique to this Valentine’s season. Seasonal audiences have a high affinity for particular environments within the content universe. Brands must engage with this audience pool by sharing the right messaging within their realm of interest at the most optimal time. This requires a shift from the ordinary.
Move beyond traditional audience segmentation based on stereotypes and go contextual to deliver a scalable strategy for the open web. With Seasonal Audiences powered by Liz, brands can engage audiences with a privacy-centric strategy during the peak of specific global seasonal events like Valentine’s Day.
As the phase-out of third-party cookies begins, marketers worldwide are pondering over ideal alternatives and weighing in on what could be the ideal replacement solutions. The DoubleVerify report, Post-Cookie Questions: The Evolution of Advertising Strategies and Sentiments revealed that publishers and advertisers are divided on which solutions they believe hold the greatest promise in replacing cookie-dependent solutions. 47.3% of publishers said publisher first-party data activation was their top choice while 49% of advertisers picked advertiser first-party data activation. Social media targeting, Google Topics, Attention-based metrics, and contextual advertising were among the other solutions.
Interestingly, the report also found that 96% of publishers surveyed said that contextual advertising capabilities will be important for their businesses in 2023. 94% of advertisers stated they were planning to rely on contextual advertising for some or most of their buys in 2023. However, contextual targeting has significantly evolved over the past few years, transforming from a mere cookie-replacement alternative to a must-have strategy for future-proof, privacy-first advertising.
The magic of AI-powered contextual targeting
Today, contextual targeting is backed by AI, ML, and NLP capabilities that enable the possibility to go beyond just keywords, understand nuances in language, and semantically interpret content. Contextual targeting’s ability to understand the meaning and sentiment of full pages of content with their complete context is opening doors to several new targeting possibilities.
For example, let’s take an article titled Makeup for Everyone: Organic products for all skin tones and types. Earlier, contextual targeting’s capability was limited to identifying that it is an article on makeup products in a lifestyle publication. The new and enhanced contextual targeting understands and interprets that it is an article on organic beauty products for people of different skin types and colors.
Contextual targeting’s ability to derive that level of granular detail about an article ergo means a heightened understanding of the readership, their mindset, and interests; fundamentally changing the way audiences are segmented and targeted. Advertisers can leverage pre-defined contextual audiences, modify them, or even build their own personalized audience segments based on who they want to reach with a particular message.
Displaying a vegan beauty product ad to women who are interested in premium beauty products that are cruelty-free, vegan, and suitable for acne-prone skin; that’s the level of granularity, accuracy, and relevance contextual targeting brings to the table. It presents an opportunity for advertisers to look beyond conventional, stereotypical audience segmentation and targeting practices that are not very detailed or precise.
Contextual targeting: More than just a cookie deprecation alternative
Contextual targeting fueled by AI is not just an option or alternative but a door to a whole new world of possibilities in digital advertising. Advertisers and publishers can finally look beyond standard taxonomies, demographics, traditional cohorts, or off-the-shelf audience segments. It’s a chance to finally break free from the ordinary and meet users within their realm of current interests, at the right time. Contextual targeting empowers advertisers to unearth new opportunities and capitalize on those that were overlooked or never even considered before. While zero and first-party data gain more importance, contextual targeting can help brands maximize the impact they can create using this data repository.
Contextual targeting’s ability to understand the meaning of content within a set context significantly boosts brand safety and brand suitability as it avoids any negative or harmful content and provides brands an environment where the values and ideas fit seamlessly with their own. In the ever-evolving digital landscape, contextual targeting presents an opportunity for advertisers to level up their strategy and win big. The difference lies in the approach; marketers who look at contextual targeting as just an option to overcome the privacy limitations won’t reap much when compared to those who go all in to make the most out of it.
Ready to shift gears and embrace new-age contextual targeting?
The Consumer Electronic Show, CES, by the Consumer Technology Association (CTA) was once again one of the world's most powerful and sort-after tech events this year, setting the tone for all things innovation in 2024. Packed with conferences, exhibits, and more, the world's most influential business leaders, industry advocates, and pioneering thinkers were all at the CES trade show to meet and hear from global innovators on the year’s breakthrough technologies and latest releases. From 3D printing to AI, marketing & advertising, and robotics, CES showcased the latest from myriad industries like manufacturers, developers, and suppliers of consumer technology hardware.
CES brings the industry together to discuss the most salient trends in the advertising and tech industry. The networking possibilities and quick interactions are valuable as it is a knowledge-sharing opportunity for business leaders. These conversations help leaders identify trends and analyze market positioning for the year ahead.
We at Seedtag were thrilled to be at CES 2024! At our exclusive Rejuvenation Suite in the ARIA hotel, we discussed cookie deprecation, CTV advancements, and the reimagination of audiences through Seedtag’s Contextual Audiences. One of the biggest events for the advertising industry, this year was the biggest and most well-attended CES yet!
What’s hot: Standout technological innovations from CES 2024
This year's themes largely revolved around Artificial Intelligence (AI) and its future, next-gen television sets, and Augmented/Mixed reality (AR/VR). The specific use cases of AI have been discussed and leveraged over the past few years. But this year, AI was a central theme as presenters showcased deeper integration into various technologies and gadgets, changing the way humans interact with devices.
The automotive sector also showcased advancements in tech and how they are being integrated into vehicles. Television sets have always been a highlight at CES and this year was no exception. From 8K displays to bigger and smarter TVs, there is a lot of innovation happening in the television space that was on showcase.
What’s top of mind for consumers?
Privacy has taken center stage as the world continues the conversation around consumer privacy. People have voiced their strong opinion about the need for data privacy and transparency on how their data is captured and utilized.
New data privacy protection laws and rising consumer demands are making way for a paradigm shift in marketing strategies as advertisers are mindful of the need for change in the way they collate and utilize user data. The new era of advertising demands marketers to strike the right balance between personalization and privacy while delivering a seamless user experience.
Another big shift has been the sheer volume of streaming platforms over the past few years. The global change in content consumption patterns has made way for the addition of a whole new ad-based tier to subscription platforms like Netflix and Amazon Prime. This shift has opened doors to a new channel of advertising for marketers as they rethink their strategies for the domain and make streaming a key aspect of their ad budgets.
The future landscape of digital advertising
The innovations and topics of discussion at CES 2024 have brought key aspects of digital advertising to life by shining light on the need for transformation to keep up with new-age tech and evolving trends. Marketers need to re-evaluate their strategies to ensure they comply with data privacy laws and cater to the evolving demands of customers. Advertising strategies need to go beyond mere clicks or views and focus on curating a personalized, relevant, and seamless brand experience that amass genuine attention.
As AI makes its way into various walks of life, right from audience categorization to ad creatives, content, and placement, it is revolutionizing the advertising space. Contextual AI is gaining significant popularity as marketers want to leverage AI to help them enhance their understanding of consumer interests and deliver ads on relevant websites that target relevant audiences without the use of cookies.
Key takeaways from CES 2024
Here’s our SVP of East Coast Sales, Lora Feinman’s take on what you need to know from this year’s trade show:
- It is the year of AI
AI has the potential to help businesses save time and money by enhancing workflows. It impacts multiple areas of marketing and will continue to be a huge focal point for marketers. They will leverage AI to understand more about a brand’s competitive edge and how to improve the overall customer experience.
- The evolution of Digital and Streaming Media
CES 2024 highlighted the industry's transition from traditional to streaming platforms, with a specific focus on streaming services and digital media. Notably, free, ad-supported streaming services and ad-based tiers in subscription platforms like Prime Video, Netflix, and Disney+ signify a significant shift in content consumption trends. This shift indicates increased investment and opportunities in streaming, prompting a reconsideration of advertising strategies. he introduction of ad-supported tier options intensified the rivalry, with Netflix reporting an increase to 23 million monthly active global users. Disney made a strong impact with its in-person Tech & Data Showcase, emphasizing shoppable TV, data clean rooms, programmatic advertising, and advanced measurement techniques. Amazon strategically prioritized Prime Video over Freevee, announcing default ads for subscribers in the upcoming month.
- All eyes on Data Privacy
Ever since Google announced its plans to phase out all third-party cookies, brands have been extremely keen on exploring cookie-free strategies. Brands are concerned about user privacy and want to ensure they do not breach the trust of their consumers while marketers are preparing for a new way to conduct business-as-usual. They are very interested in exploring “alternative IDs” and leveraging first-party data to serve ads to consumers.
The depreciation of cookies has augmented the need for interest-based targeting now more than ever. Marketers want to go beyond the obvious and find new targeting opportunities. The advertising world is excited about the possibilities AI unfolds like locating audiences in new environments or unearthing new audience segments that they never knew existed.
- Navigating the Horizon of Television Innovation
As an enduring highlight at CES, televisions continue to captivate audiences with their evolving features and capabilities. The trend of larger, more powerful, and smarter TVs persists, promising an enriched viewing and auditory adventure. This constant evolution not only elevates the home entertainment experience but also solidifies the pivotal role of television technology in the realms of consumer electronics and advertising. Unveiling cutting-edge screen technologies remains a focal point at CES, evident in the remarkable display advancements showcased across various devices, from expansive TVs to experimental bendable phones. Renowned manufacturers showcased their latest television sets, with a notable emphasis on the integration of advanced AI chips.
These are the trending topics and points of discussion from CES 2024. However, these aren’t just fleeting topics of discussion or a mere trade show round-up. These topics are key indicators showing the world the direction in which industries are moving and how they are leveling up to meet consumer expectations.
Interested to learn more about what we do at Seedtag? Explore our success stories here or drop us a line and we’ll get in touch with you.
It’s 2024, the year of privacy is finally here. Google announced the deprecation of third-party cookies back in 2019 and the world has been abuzz ever since. The countdown has finally begun. January 4th marked the pivotal change as Google Chrome began the third-party cookie phase-out by initiating its restriction for 1% of users. Google also revealed that it plans to ramp up third-party cookie restrictions to 100% of users from Q3 2024. However, it was finally announced that the cookie deprecation would not take place as such.
With this, the digital advertising world marks a fundamental change in ad strategies and the go-to source of user targeting will soon cease to exist. Now publishers and advertisers must look for alternative approaches to reach users with tailored content that matches their preferences. As traditional, cookie-dependent practices become obsolete, the need to transition is inevitably clear. In a survey conducted in late 2022, 59% of respondents stated that they were either accelerating their readiness for a cookieless future or keeping it a high priority.
In anticipation of the cookieless future, Google introduces Privacy Sandbox. The Privacy Sandbox is Google’s initiative that aims to provide phase-out support for third-party cookies when new solutions are in place. It plays a crucial role in enabling advertisers and publishers to continue offering content online by ensuring a balance between user privacy and the sustainability of online services, reducing cross-site and cross-app tracking.
Digital marketing in the privacy-first world
Beyond Google’s Privacy Sandbox, advertisers are also exploring other alternatives to third-party cookies to make a seamless transition and create effective privacy-first ad strategies. One of the more obvious emphasis has fallen on first-party data. Data collected with the knowledge and consent of users, first-party data refers to the information that a brand collates from users when they interact with the brand’s website and marketing/advertising literature or make a purchase. This data gives advertisers insights into user preferences that help them segment audiences and deliver ads that align with their interests.
Zero-party data is always a great option as the data is directly and intentionally shared by the user to receive personalized communications from the brand. Both zero and first-party data are collected with the user’s consent and are authentic sources of information that brands can rely on as they are accurate and compliant with data privacy regulations.
Other options of programmatic advertising include demographic, geographic, or device-based targeting but these don’t offer the ability to create and share relevant content to users. Zero and First-party targeting practices are also limiting as advertisers are restricted to their existing audience base. Advertisers and publishers need a privacy-safe solution that combines relevance with scale.
Contextual targeting has emerged as a front-runner in the transition to the cookieless world as it bridges the gap between relevance and scale and offers a new-age, non-intrusive solution. Looking at data beyond a user’s browsing history or leveraging third-party cookie data, contextual targeting focuses on a user’s current interests based on the content they are consuming. Without tracking a user’s browsing patterns or using alternative IDs, contextual advertising powered by AI goes beyond stereotypes and enables precise targeting. Network Level Analysis (NLA) provides real-time insights and recognizes trends that power more effective strategies by reaching the right audiences where they are.
Contextual advertising is pushing the boundaries by transcending conventional, stereotypical, and invasive practices of categorizing users based on interests and past browsing patterns that are not always accurate. Instead, the focus lies on placing ads on web pages where the on-page content and context align with the ads. This ensures the ads match the content a user is currently consuming, maximizing relevance without violating their privacy.
Built for scale, contextual targeting empowers advertisers to create custom audience categories that align with their brand based on contextual cues. It presents an opportunity to elevate to a future-proof strategy that embraces diversity and inclusivity through a more in-depth understanding of audience preferences. Contextual targeting’s ability to understand nuances and semantically interpret content also enhances brand safety and brand suitability by eliminating the display of ads beside negative or harmful content and ensuring ad placement falls in line with the overall message and tonality of the brand.
Custom AI has become an indispensable tool for agencies seeking a competitive edge in the rapidly evolving digital marketing landscape.
Beyond its initial application in audience targeting, custom AI is revolutionizing various aspects of digital advertising, from lookalike audiences and bidding strategies to measurement and optimization. Its most profound impact, however, lies in introducing campaign objectives into automated decision-making across marketing organizations, indicating a new era in contextual advertising strategy.
While audience targeting has been a foundational application of custom AI in digital advertising, its potential extends far beyond. Forward-thinking advertisers have leveraged custom AI to guide their contextual strategies for years. As the industry moves toward a privacy-first future, this application of custom AI promises the most significant breakthroughs.
Moving beyond lookalike modeling, custom AI is unlocking cookieless audience targeting
Digital advertising has shifted from predefined audience targeting to adopting more sophisticated, custom AI-driven methods. Initially, brands relied on predefined audiences for user targeting, a necessary compromise given the technological limitations of the time. However, this approach often sacrificed accuracy for simplicity.
Lookalike modeling represented a significant leap forward, enabling brands to expand their target audiences by identifying users with characteristics similar to their specific brand audience. This technique became a staple in the toolkits of major platforms like Facebook and Google.
The latest advancement in this evolution is fully customized targeting designed for the privacy-first web.
This approach employs custom AI to build campaign-specific machine-learning models using first-party data and contextual signals. These models analyze URLs, scoring them based on their semantic relevance to a brand’s campaign brief. The result is a refined selection of content that aligns closely with the campaign’s objectives, surpassing the accuracy of standard segments.
Custom contextual AI is driving improved ad recall
A critical aspect of audience targeting with custom AI is the quality of the underlying audience data and the integrity of the matching process. A study by Truthset highlighted the reliability issues in data used for ad targeting and audience measurement. The study found that matches between hashed email addresses and postal addresses across various data providers were accurate only about 51% of the time, casting doubt on the accuracy of such audience data matches.
Several innovations underpin custom AI’s data integrity and advanced targeting capability. For example, network-level analysis (NLA) is crucial, examining the entire universe of URLs to discern content clusters, trends and semantic relationships. Content retrieval techniques scan this network, identifying URLs that align with the advertiser’s brief. A custom AI model, built and trained with this filtered content set, classifies new articles and ensures that only the most relevant ones are selected for the campaign.
The efficacy of custom contextual AI is evident in its results. For instance, Seedtag’s Affinity Index, which measures context relevancy for the intended audience and message, is typically 92% higher than scores derived from predefined taxonomies. Moreover, ads placed using this technology enhance ad/content fit by 9%, leading to significant uplifts in ad recall (22%) and message association (19%) compared to standard IAB categories.
Custom contextual advertising allows advertisers to adapt in a privacy-first environment
With the progressive loss of reach of third-party cookies, first-party data will play a more important role. However, translating this limited data into scalable marketing campaigns poses a significant challenge.
Contextual targeting, focusing on the environment of the ad placement rather than gathering information from potentially unreliable audience data, ensures relevance to the content being consumed at the moment. This approach bypasses the uncertainties of personal data matching, offering a powerful and sustainable alternative to traditional methods.
Custom contextual advertising, therefore, emerges as a key solution in a privacy-first world. It adapts to the evolving digital landscape and outperforms standardized segments, offering a more accurate and reliable method for placing ads in relevant contexts.
As the digital advertising industry grapples with signal loss and heightened privacy standards, custom contextual AI stands as a beacon of innovation, guiding the way to more effective, responsible and sustainable advertising practices.
By Chad Schulte, Senior Vice President of Agency Partnerships and Strategy at Seedtag.
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