AdTech Collective by Seedtag

News, trends, and insights in Digital Advertising

Highighted

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 Advertising Services

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.

The Evolution to Neuro-Contextual Advertising

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.

Highighted

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.

TikTok: How AI in Digital Advertising Is Reshaping Social Commerce

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 AI in Digital Advertising - Agentic AI

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.

Highighted

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.

What Automated Media Buying Still Can't Replace

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 Automated Media Buying Still Can't Replace

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.

Highighted

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.

Our Blog

They say, a picture is worth a thousand words; holds mighty true in today’s world where the human attention span hovers around the 8-second mark. Users encounter numerous ads as they surf through the digital world, making it impossible for text-heavy formats to garner many eyeballs.

The human brain processes images 60,000 times faster than text, and 90% of the information transmitted to the brain is visual. From a human perspective, visualization works best as we respond and process it better than any other type of data. The human brain can recognize a familiar object within 100 milliseconds, and a study by MIT estimates that just 13 milliseconds are sufficient to recognize even unfamiliar images.

Marketers have access to myriad formats like full image, in-image, and videos, to garner one of the most valuable resources of the digital age, attention. Engaging visuals and succinct messaging capture consumer attention and leave a lasting impact.

Win big in the attention economy with the right blend of content and context

Nike, Apple, Budweiser, and Coca-Cola are a few brands that have nailed advertising campaigns that struck a chord and left the world talking for years. That’s the power of creativity.

Creativity plays a crucial role in capturing attention in a digital landscape where consumers are bombarded with information and messages. In a crowded marketplace, ads that are unique, imaginative, and distinctive help brands distinguish themselves and attract attention. Images or videos that are visually appealing are more likely to be shared and remembered. So, add to the mix striking visuals and innovative designs, and that’s an ad strategy that can capture attention quickly.

Contextual advertising enhances the effectiveness of capturing attention by tailoring ads to the specific context of a user's current line of interest. It leverages Artificial Intelligence (AI) to analyze the content and context of web pages, and places ads in the most optimal locations without using any third-party cookies. Since the ads align with the content users are currently engaging with, they are more relevant and personalized, thus increasing engagement.

Contextual advertising uses deep learning, computer vision, and natural language processing to aggregate insights that enable brands to target specific audiences by understanding the context in which the content will appear. Context relates to the content a user is currently consuming making ads more broadly applicable and effective than relying on individually identifiable signals.

Contextual AI can also provide contextual creatives that resonate with users and capture their attention. There are various formats that advertisers can choose from, such as in-article, in-image, and in-video. Using contextual signals, Dynamic Placement Optimization (DPO) ascertains the most suitable location to place the ads.

The power of creativity in today’s attention economy

The power of creativity: Metrics in the attention economy

Attention metrics provide more information for quality arbitrage, and help make smarter decisions. Vendors like Lumen and Adelaide are judging the quality of media based on the probability of attention given by any person to a creative placement. While it may not be considered a media currency yet, measuring creative and placement effectiveness based on the attention amassed is a fair assessment to get insights.

Attention time is a crucial metric that advertisers are closely monitoring in today’s attention economy. Attention time refers to the amount of time a user or consumer spends actively engaged with or paying attention to a particular ad. Relevance, creativity, format, placement, etc. all have a significant impact on this metric.

Research shows that in-image ads are 4x more effective while in-video ads are 6.7x more effective in maintaining attention. Common display ads have 1.5 seconds of viewer attention as against in-image ads at 6 seconds. Regular video ads have 0.6 seconds average viewer attention while in-video ads get 4 seconds.

According to Lumen’s research, as the view time for an advertisement increases, more impressions are converted into sales. For example, an ad that was viewed for 3 seconds was converted to a sale on 50% of occasions. For brands and marketers serving ads, every second counts. Contextual ads have greater engagement rates, boost impressions and brand recall, and help build a memorable and consistent brand identity.

Leveraging consumers’ natural inclination to look at imagery and acing ad placement with context has a direct impact on the bottom line and sales numbers. In-image contextual ads get noticed 3.5 seconds faster and drive attention 3.4 seconds longer. They also have a 4x stronger breakthrough and 3.9x higher purchase intent. These numbers further rise for in-video ads.

The future of Attention Economy

Going a step further, leveraging GenAI capabilities can further strengthen contextual targeting strategies. At Seedtag, we utilized the powers of GenAI and launched a capability that gives brands and agencies the capacity to build tailored creatives based on the context of the surrounding page-level content.

With GenAI, advertisers can create more sophisticated creatives that perfectly match the context of the content in an article or web page. Our contextual AI platform’s Deep Learning, Computer Vision, and Natural Language Processing capabilities enable it to understand the desired outcome of a campaign and creates prompts to modify the original creative to optimize for the best possible outcome.

The combination of GenAI and contextual advertising will empower brands to not just create stellar creatives, but ensure that they are relevant to the context in which they’re served. By create campaign creatives that seamlessly integrate with the context in which they are displayed, brands can win the attention battle and drive better results.

Get in touch to know more about our exclusive GenAI capabilities for contextual advertising.

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Streaming services are one of the most sought-after subscriptions of the decade. The pandemic was a catalyst that boosted demand, and the number of streaming service subscriptions passed 1 billion worldwide for the first time in 2020. As of March 2023, 78% of all American households subscribe to at least one or more streaming services. With 231 million subscribers, Netflix ranks as the most subscribed video streaming service globally.

The steady rise of popular streaming services like Netflix, Amazon Prime, Hulu, and Disney+ has contributed to the popularity of Connected TV or CTV. Connected TVs have become the choice among the masses because it gives them the flexibility to connect to the internet, and seamlessly switch between traditional television and online streaming. In 2023, a whopping 88% of U.S. households owned at least one internet-connected TV device, while the number of CTV users amounted to more than 110 million among Gen Z and Millennials.

Investing in Connected TV advertising

With a constantly rising viewership, advertisers quickly began exploring CTV advertising, recognized its potential, and have been making significant investments in the past few years. In 2023, CTV advertising spending in the United States was expected to grow by 21.2% to reach 25.09 billion USD. CTV ad spend is expected to grow to 40.9 billion USD by 2027.

A seamless and convenient option to deliver ads where the masses are, CTV ads are similar to YouTube ads. Marketers can serve personalized, skippable ads to target audiences while they are streaming content on their TVs. The appeal of CTVs has grown owing to more widespread and reliable internet connectivity.

Additionally, beyond the ability to pick between traditional TV and streaming, since connected TVs are connected to the internet, they are highly versatile and support additional features. They give users access to OTT streaming, social media browsing, and watching traditional television as scheduled, delivered through streaming TV apps over the internet rather than traditional broadcast networks.

As television devices become more affordable and a variety of content becomes more accessible, the audience is naturally inclined towards having the option to take their pick and have full control over what they watch.

Marketers: Get acquainted with FAST

FAST, or Free Ad-Supported Television, refers to streaming television services that are available to viewers at no cost. So, how do they generate revenue? Simple; advertising. These platforms do not charge users any subscription fee but, similar to subscription-based streaming services, they offer a variety of on-demand content. They rely solely on advertising for monetization to support their operations.

FAST platforms typically offer a range of content, including movies, TV shows, news, and sometimes live TV channels. Advertisers pay for ad slots, and the ads are displayed during and between content streaming. This revenue supports free access to content for viewers. Some examples of Free Ad-supported Streaming TV services include Roku Channel, Tubi, Pluto TV, Crackle, Peacock, and Samsung TV Plus.

Marketers have been investing in advertising on FAST platforms because it allows them to reach a diverse and sizable audience base and a broad demographic range. Another key aspect is that it allows marketers on a tight budget to reach a large audience without spending significant ad dollars. It is a more cost-effective option when compared to expensive traditional TV advertising.

As the “cord-cutting trends” rise and more viewers shift away from traditional cable in favor of streaming services, FAST opens up new opportunities. It allows marketers to stay relevant and reach audiences on platforms where they are increasingly spending their time. Marketers can explore innovative ad formats like interactive ad experiences and sponsored content to engage viewers. Tracking campaign effectiveness is also better on FAST platforms by accessing metrics such as impressions, click-through rates, and engagement that provide valuable insights.

Making the shift to CTV and FAST

Offering a unique opportunity to meet the audience where they choose to spend a significant amount of time watching content of their choice; CTV advertising and FAST platforms present marketers with a great alternative to traditional ad practices that are pricey and stereotyped. Traditional TV ads just display ads but with CTV and FAST, brands can choose what content they want to advertise beside. This gives marketers more flexibility to align messaging and design with user interests and brand values.

  • Improved understanding of viewer interests
  • Ads that are non-intrusive and relevant to the current content browsed by the audience
  • Messaging in line with the brand's ideas and values
  • Compliant with all privacy laws as it does not leverage third-party cookies

They also offer more control and transparency, allowing marketers to have a clearer understanding of where their ads are being displayed. Thus, the newer methods help marketers elevate brand safety, brand suitability, and the overall use experience.

Let’s take an example - You are a regular on a travel channel and passionately follow a particular show that covers unique experiences in lesser-known locations. If a brand curates exclusive, personalized travel itineraries and experiences, you fall under its “ideal target consumer” category. The chances of you wanting to know more about what they do, how they do it, and possibly wanting to plan an experience are much higher. So, if you see their ad during or right after your show, you are likely to explore more.

Still in its early days, CTV and FAST are growing rapidly but come with some challenges. While significant improvements have been made, measurement and tracking of campaigns on television still have certain difficulties. Ad blocking and ad fraud also continue to be significant obstacles in CTV targeting. However, partnering with the right experts and staying tuned to updates and enhancements in the space can hugely benefit marketers. The ability to leverage the latest tech and reach a wider audience that was not accessible before unfolds newer possibilities and opportunities that brands and marketers must explore to stay on top of their game.

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There are various reasons why the audience is tired of ads today. What tops the list is the age-old practice of violating user privacy and accessing their personal data to target users as they browse the web. Data privacy has been a hot topic for a while as consumers and advocates created a lot of noise around privacy, making for governance laws like GDPR and CCPA that advertisers must comply with.

Going beyond privacy, traditional targeting strategies carry another tag - stereotypes. Fundamentally, cookie-based advertising involves collecting user data like interests, browsing, and behavioral patterns. Users are grouped into categories mostly basing the entire categorization process on assumptions, stereotypes, and third-party cookies. The results are rather apparent today - Users are left irritable as irrelevant and intrusive ads disrupt their browsing experience.

Advertisers pay a hefty price as poor audience categorization results in incorrect targeting, wasted ad dollars, has a negative impact on user experience, and damages the brand image. The world is also actively championing diversity and inclusivity initiatives, and advertising needs to level up to meet audience preferences.

Old is new: Contextual targeting

The phasing out of third-party cookies has paved the way for various “new” advertising strategies that will help navigate the cookieless world. However, a solution that dates back to the very roots of advertising has garnered the trust and interest of both advertisers and the audience - Contextual advertising.

Built on the principle that targeting remains strictly contextual, this advertising strategy truly focuses on protecting consumer privacy and helps advertisers adopt a more inclusive targeting practice. With contextual targeting, advertisers can steer clear of third-party cookies’ discriminatory practices and not limit targeting based on outdated methodologies. Instead of drawing conclusions by relying on factors like age, race, gender, location, or other such characteristics, advertisers can adopt a privacy-first strategy that enables them to display relevant ads to the most suitable audience by aligning with their real-time interests.

Women like the color pink, prefer skinny jeans, invest extensively in makeup products; the assumptions are plenty. Instead of making conjectures, it is unquestionably better if brands could show ads relevant to people based on the content they are actually consuming. Relevancy helps maximize impact.

Powered by Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP) capabilities, contextual targeting presents an innovative alternative to stereotypical and non-privacy-compliant strategies. The ability to understand nuances and semantically interpret content makes contextual targeting all the more impressive as it allows advertisers to expand their horizons while elevating brand safety and suitability. Not only does contextual targeting eliminate the appearance of ads alongside negative or harmful content, but it also ensures ad placement aligns with the overall brand message and tonality.

Are you equipped to rise beyond stereotypes and dated advertising practices?

Contextual advertising empowers brands to make the most of AI-driven contextual targeting and elevate to inclusive advertising practices. With contextual targeting, half the battle is already won. You already know that the user is somewhat related to your product or service because ad placements are purely based on their current area of interest.

AI does a deep dive and analyzes the written and visual content of a web page, to understand the content and context. This analysis helps advertisers develop an understanding of what customers are browsing, their areas of interest, and how they engage and interact with content. Beyond just analyzing specific URLs that are limited to certain predefined categories, Network Level Analysis (NLA), looks at the entire universe of URLs. NLA develops an understanding of the network as a whole to understand content clusters and topics that audiences are engaging with at that moment. By appearing where a user is showing interest with an offering that aligns within that realm of interest, brands are more likely to not just convert better but win customers for life.

Like the Backstreet Boys sing, “But I want it that way…”; well, you can. Advertisers can cherry-pick who they want to target and users see only those ads that align with what they’re currently looking for. Truly inclusive and unbiased, contextual targeting is interest-based and does not profile a user based on who they are.

It’s a win-win for all parties involved, and an ideal alternative to cookie-based targeting practices.

Explore more about contextual advertising with us.

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The open web or walled gardens; an ongoing debate that has further intensified since Google’s announcement on the phasing out of third-party cookies. Before we get to what works better and what customers prefer, let’s cover the basics.

What is the open web?

Open web refers to the part of the internet ecosystem where information and resources are freely accessible to all users without any restrictions. Websites, apps, or any other online property that is not owned by a major technology company is typically categorized under the open web.

What are the walled gardens?

Walled gardens refer to closed internet ecosystems controlled by large corporations like Meta, Apple, Instagram, and Amazon without involvement from any outside organization. These big technology corporations ensure that all data, information, and technology stay within the organization, and the entity also controls user access to data, content, and services within the ecosystem.

So, what is the debate around?

For a long time, consumer trends showed a clear inclination towards walled gardens, as users spent significantly more time on platforms like Facebook and YouTube. Naturally, marketers began investing a significant part of their ad budgets in these walled gardens. However, there has been a radical shift in consumer behavior in the past few years.

According to a recent survey, 30% of people said they use Facebook less today than a year ago, while just 8% said they use the open web less than before.

What are the reasons behind this paradigm shift in consumer preference from walled gardens to the open web?

  • The survey revealed the number one reason cited by consumers as lack of relevance. Across Facebook, Instagram, YouTube, and Amazon, consumers felt the content displayed on walled gardens was not as relevant as it used to be before.
  • Another factor that marketers should pay heed to is the consumers’ state of mind. Consumers said they are more likely to be “zoning out and not paying attention” when browsing walled gardens.
  • Transparency is another factor that consumers stated when referring to content like news on walled gardens.

Thus, the open web is increasingly becoming the preferred choice among today’s consumers. According to the survey:

  • 48% of consumers spend more than 1 hour browsing the open web, while walled gardens stand at 30%.
  • Consumers are 4x more likely to say they will increase their open web usage over the next 12 months than decrease it, compared to both Facebook and Instagram where they said they will decrease usage.
  • People are not just spending more time on the open web. The majority are also “curious and in a mood to learn more” making it an ideal place for advertising.
  • 74% of people said they trust articles on news sites or apps more than walled gardens, and that they turn to the open web when looking for high-quality content.

The advertising landscape: Open web vs. Walled gardens

Ad budgets have been flowing into walled gardens for years now, but there seems to be a clear misalignment. With the audience revealing where their interests lie, marketers need to reevaluate their strategies. The change in audience preferences could be the reason certain campaigns don’t perform like they used to or content does not receive the same traction as it did in the past.

Marketers and brands must be more watchful of where their ad dollars are being spent, if campaigns are meeting their objectives, and what returns they are giving to brands. Today’s consumers are spending more time on the open web than walled gardens and this shift is only going to continue to widen in the coming days, putting an end to the walled gardens monopoly.

Why are marketers moving beyond walled gardens?

With the demise of third-party cookies expected to occur in 2024, marketers are exploring alternatives to walled gardens to diversify their advertising strategies and reduce reliance on closed, proprietary platforms. Also, as consumers shift their preferences, it is but obvious that marketers must relook strategies and advertise where their consumers are.

Some of the factors that are driving marketers away include:

  • Marketers don’t get full visibility into their campaign performance or customer insights because these platforms keep the granular data to themselves. This takes away the opportunity for brands to dive into the details and gather more meaningful insights that can help fine-tune campaigns and improve customer engagement. Restricted access to user data and lack of transparency hinders effective audience targeting and analytics.
  • The need to comply with data privacy laws has further tightened the ropes around data collection and usage, increasing the challenges within walled gardens.
  • The closed ecosystem limits marketers’ visibility into ad fraud and brand safety concerns.
  • Competition for ad inventory and the closed nature of walled gardens make advertising more expensive.
  • These closed ecosystems limit opportunities as they restrict access to marketing content within the ecosystem and only target consumers who are active users of the platform.

Consumers are more actively exploring the open web as it provides a wider range of choices, access to varied content, and diverse opinions and viewpoints. It also gives users greater control over their online data privacy.

Striking the right balance

Consumers’ shifting preferences and marketers’ hunt for alternatives have put the spotlight back on contextual targeting. Contextual advertising is becoming one of the most sought-after targeting strategies that empower marketers to create more effective campaigns. It allows marketers to display relevant ads to the desired audience by analyzing the content and context of web pages.

Contextual ads enable brands to provide a better user experience by creating a non-intrusive campaign that does not hamper the browsing experience of consumers. AI and ML models analyze millions of web pages to determine the content that best aligns with a campaign’s messaging and context, thus placing creatives in the most optimal locations without leveraging any third-party cookies. Since the ads are based on the content of the web page being viewed, contextual targeting ensures that the ads are relevant to what users are currently interested in.

Unlike the limitations of walled gardens, contextual advertising guarantees transparency. Marketers can deliver relevant ads without needing extensive user profiling or personal data, addressing privacy concerns and regulatory restrictions. With more control over where the ads appear, contextual advertising also promises the highest levels of brand safety and suitability.

Our joint research project with Havas and Kia revealed a 70% view rate for contextual ads vs. 64% for cookie-based ads, a 43% increase in brand awareness as against cookie-based ads’ 18%, and 29% higher digital ad recall.

Explore our contextual AI solution that is built to power new-age, privacy-first advertising strategies.

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Generative Artificial Intelligence or GenAI shines bright as the ‘it thing’ of this decade. GenAI goes beyond traditional Artificial Intelligence (AI) tasks like classification or prediction, and has the ability to create original content like images and text.

The growth of genAI tools has been explosive in the past year and the latest McKinsey Global Survey revealed that organizations are using genAI regularly in at least one business function.

The survey further revealed that nearly 25% of surveyed C-suite executives are personally using genAI tools for work. While more than 25% of respondents from companies using AI said genAI is already on their boards’ agendas. 40% of respondents said their organizations will increase investment in AI overall because of advances in genAI.

In the AI adoption race, organizations exploring genAI capabilities in conjunction with traditional AI are further ahead, have the first mover’s advantage, and are reaping more benefits. The ever-evolving adtech landscape is leaving no stone unturned in making the most out of genAI to level up.

How is the adtech landscape leveraging the latest in AI?

GenAI unlocks a whole new world of opportunities by providing creative assistance that enables marketers and advertisers with data-backed creative assistance to be more efficient and deliver more impactful campaigns.

From text and creatives to ads and marketing, the evolution of AI and the adoption of next-gen AI models like ChatGPT by Open AI, Bard by Google, and Microsoft Bing is creating huge waves of change and opening doors to never-seen-before possibilities.

This marks the beginning of a new era that is transforming the future of work by bringing together the power of human and artificial intelligence.

AI can assist through the entire process from research to content generation and distribution. It can expedite the creative process by suggesting design elements, layouts and color schemes, and help create more suitable ad copies, product descriptions, and marketing content.

What are the benefits of leveraging Generative AI in advertising?

Adopting genAI can help advertisers save time and resources by enabling them to produce content faster and with ease. By enhancing various aspects of advertising campaigns and strategies, genAI can have a significant impact on the adtech landscape.

The capabilities and use cases of genAI in advertising are vast:

  • Produce large volumes of high-quality content across formats like text, image, and video, with ease.
  • Analyze customer data and create personalized ad campaigns that have higher engagement and conversion rates.
  • Help advertisers in the creative process by suggesting ideas that inspire them to explore newer avenues, and curate fresh, innovative campaigns and messaging.
  • Easily create multiple ad variations, simplify A/B testing, and boost ad performance and ROI.
  • Explore vast datasets, evaluate, and derive takeaways on key aspects like customer behavior, preferences, and market trends.
  • The ability to hyper-personalize at scale using the learnings from AI.

The fusion of Contextual Targeting and GenAI: Fueling new-age advertising strategies

AI is no replacement but an assistant for humans to do more, better, and faster. The two big factors that are currently ruling the adtech landscape are Contextual and Generative AI.

What if you could bring the two together? Imagine the magic that can be created by capitalizing on these two revolutional tools?

Here’s how we leverage the two at Seedtag and enable brands to reap maximum benefits:

  • Our proprietary AI-powered contextual technology, Liz©, has the ability to analyze and comprehend expansive volumes of written and visual content to derive insights that help determine the best place to place an ad that will resonate with customers.
  • Our GenAI capabilities leverages the learnings from Liz© to provide more relevant creative inputs on colors, image elements, and text to further enhance the quality of the ads.

Advertisers and creative agencies are using the best of AI and contextual advertising to curate strategies and generate content that perform better than the conventional ones.

Contextual targeting primarily addresses the big concern of privacy and enables advertisers to make data-driven decisions, and reach their target audience without leveraging any third party cookies.

The intelligence from the analysis then enables generative AI in the creative process and empowering advertisers to work more efficiently and create more engaging and personalized campaigns.

While AI empowers customers with data to drive decision making, genAI uses these data points to understand patterns and create new content like text and images. The new content created by genAI is data-backed and hence more capable of identifying elements like the best keywords, colors, and images to use for a particular campaign. The two complement each other and power more effective ad campaigns by elevating brand messaging and creatives.

Benefits for advertisers

When used together, they allow advertisers to:

  • Produce high-quality, contextually relevant content by analyzing the context of a webpage or app and generating ad creatives that match the content and context of the page.
  • Generate personalized and contextual ad messaging based on a user’s current search or area of interest.  
  • Analyze the content and context of web pages or apps to identify relevant keywords and phrases that can be used to better target ads to specific content categories or topics.
  • Optimize ad copy to match the context and language style of the content it appears alongside.
  • Create narratives that align with the content and context ads appear alongside, and adapt ad content in real-time based on changing contextual factors.

Applying Contextual Targeting practices coupled with GenAI capabilities: The business impact

Developing a strategy that incorporates gen AI into contextual targeting strategies can help brands deliver more relevant and engaging ads to their desired audience. It allows them to align their advertising efforts by ensuring ads seamlessly integrate with the surrounding content and context, making it less intrusive and more engaging.

Using the duo together forges a much stronger strategy that offers myriad benefits:

  • Copies and creatives generated by integrating gen AI and contextual targeting are more optimized and relevant. Thus, they garner more attention, increase click-through rates, improve ad performance, and channel a better user experience overall.
  • The pair reinforces brand safety and suitability by ensuring that brand elements and messaging remain consistent across ad creatives and text. Content generated is contextually relevant and reflects the brand’s identity while avoiding ad placements on websites or apps with inappropriate or controversial content.
  • Contextual targeting with gen AI can boost ROI on advertising spends by optimizing ad creatives, messaging, targeting, and placement.
  • The combination can also protect brands from ad fraud by ensuring ads are displayed only on relevant and desired web pages and apps.

On the whole, using contextual targeting and gen AI in tandem enables brands to derive more value, gives them a competitive edge, and helps them future-proof their business. Advertisers can curate more personalized experiences that customers love and engage with, which in turn increases customer satisfaction and brand loyalty.

Early adoption of gen AI in integration with contextual targeting will enable brands to develop strategies that not only give a competitive advantage but help them adopt tech that is integral in the advertising space. It is an opportunity to level up and better position themselves in the ever-changing landscape for continued success.

Explore our contextual AI solution that is built to provide brands a premium advertising approach. To know more, get in touch.

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Connected TV (CTV) advertising is a rapidly growing segment within digital advertising, enabling brands to reach specific audiences through internet-connected devices. But what is CTV advertising? It refers to the delivery of video ads on smart TVs, gaming consoles, and other devices connected to the internet. Unlike traditional linear TV advertising, CTV offers precise audience targeting, allowing advertisers to measure the effectiveness of their campaigns with advanced analytics.

Internet-connected devices like Smart TVs have become one of the most sought-after products in the last decade. Access to OTT video streaming has become a must-have, especially among the younger generations.

Statista's 2023 research revealed that 92% of US households were reachable by CTV programmatic advertising, while Gen Z and Millennial CTV users amounted to more than 110 million.

With the rapid change in opting for CTV experiences over linear television and the solid foothold OTT platforms have gained globally, advertisers have quickly noticed the digital migration, putting advertise on CTV targeting in the spotlight. Despite the slowdown triggered by the pandemic, the research reported that CTV ad spending in the United States increased by 33% in 2022. The latest projections suggest that the expenditure will more than double and surpass USD 38 billion by 2026, accounting for more than 5% of US ad spending.

CTV targeting: For the new era of television

With a higher viewership, increased streaming time, and higher revenue numbers; the explosive rise of CTV and OTT services has powered an evident shift in advertising spending. Revenue in the OTT Video segment is projected to reach USD 315.50bn in 2023, with OTT Advertising being the most prominent segment having a market volume of USD 206.90bn in 2023. A report suggests that nearly 50% of marketers would spend more on CTV targeting if they had high-quality first-party data to back their targeting strategy.

Like most other new areas of advertising, CTV targeting has its challenges.

  • Since it's a relatively new ad space, there are a lot of knowledge gaps. This makes it harder to get organization buy-ins and budgets for exploration. Additionally, audience fragmentation across platforms and devices makes audience targeting tougher.
  • Measurement and tracking of campaigns on television have always been challenging. With CTV involving multiple devices, how can marketers track campaign performance or measure the effectiveness of your campaigns to understand if the ads reach the desired specific audience? The lack of standardized measurement makes it hard to evaluate the effectiveness of campaigns.
  • Ad blocking and ad fraud continue to be significant challenges in CTV targeting.
  • With access to limited audience information like demographics and geography, audience targeting poses a challenge. Marketers need access to audience data to create effective CTV campaigns that deliver ads to the right audience.
  • Limited ad inventory makes quality and scale difficult, as limited spots are available during peak viewing times.

What is CTV advertising All you need to know to advertise on ctv

Contextual advertising and CTV targeting

A strategy that is purely driven by the analysis of content and context, contextual advertising can enable marketers to overcome these challenges and enhance advertise on CTV strategies. Unlike behavioral targeting, which requires audience data to aid CTV campaigns, contextual AI focuses on targeting audience segments by placing ads alongside relevant streaming content that aligns with the audience's interests.

For example, contextual advertising can enable sports and fitness equipment or apparel brands to target viewers interested in live sports and sports-related shows. The video ads displayed are relatable and lie within the viewer's realm of interest, increasing visibility and reducing the possibility of showing the ads to viewers who are less likely to be interested in the product.

Additionally, advertisers can leverage gaming consoles as another prime avenue for advertising on CTV. Many modern gaming consoles support streaming services, allowing advertisers to reach a younger, highly engaged audience that frequently consumes video content on demand. This expands the reach of CTV advertising beyond traditional smart TV users and into the growing gaming community.

One of the key advantages of connected TV advertising is its ability to track video completion rate effectively. Since viewers are more likely to watch an entire video ad on CTV than on other digital platforms, advertisers can ensure that their messaging is fully delivered. This metric is crucial for measuring engagement and understanding how effectively an ad influences a viewer's decision to purchase after viewing an ad.

The future of CTV advertising

Advertise on CTV is promising, with advancements in AI and machine learning enabling even better ad placements and audience segmentation. As more brands invest in OTT advertising and fine-tune their CTV campaigns, the industry will see improved ROI and deeper insights into viewer behavior. Marketers who adapt early and integrate CTV advertising into their digital strategies will gain a competitive edge in reaching highly engaged audiences.

Contextual advertising-backed CTV targeting is more effective than demographic or geography-based targeting. It allows brands to render ads to viewers who are more likely to have a genuine interest in their products or services and not just show ads based on age or location.  

With this, marketers also elevate brand safety, brand suitability, and user experience -

  • Improved understanding of viewer interests
  • Ads that are non-intrusive and relevant to the content being viewed by the audience
  • Messaging in line with the brand's ideas and values
  • Compliant with all privacy laws as it does not leverage third-party cookies

CTV advertising is building future-ready strategies and brands are already leveraging it to steer ahead. Have you explored CTV targeting yet?

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Phasing out of third-party cookies, brand safety and brand suitability, privacy laws, and changing customer preferences are among the top factors that have brought the spotlight back on contextual advertising in the global ad tech landscape. Contextual ads are increasingly becoming the preferred choice among advertisers, publishers, and customers today.

A factor that plays a key role in helping brands reach their desired target audience is the audience selection process. An audience refers to a group of people with similar interests and shared characteristics. This crucial element helps brands reach the right individuals who are most likely to be interested in their product or service.

Traditionally, audience categorization is a process where people are grouped based on their interests and past behavior patterns. This method is limiting because it tends to group individuals based on stereotypes, and relies on third-party cookies. Poor categorization of personas can have a negative impact on marketing efforts and campaigns as the categories are not 100% accurate, resulting in incorrect targeting and wasted ad dollars.

We live in a world that is embracing diversity and inclusivity with open arms and actively steering away from stereotypes. Brands looking to level up their advertising game need to keep up with the changing times and better understand audience preferences.

What if they could go a step further with their targeting strategies?

What are Contextual Audiences?

Contextual advertising focuses on placing ads on web pages where the on-page content and context align with the ads. Contextual audiences refer to individuals who are identified and grouped based on their online behavior and the context of the content they are currently engaging with.

At first glance, contextual audiences may seem very similar to the traditional audience categorization process where people are grouped based on their interests. However, the key differentiator is that contextual audiences do not leverage any personal data, and create audience groups solely based on contextual cues.

Instead of using the most common and typical way of grouping individuals based on personal information, contextual audiences use the power of context to group people. Contextual audiences ensure scalability, privacy adherence, and greater precision, making it a method ideal for the post-cookie world.

What challenges do Contextual Audiences solve for customers?

Contextual audiences are a targeting capability that enables brands to ace audience segmentation and targeting by displaying ads that are most relevant to them.

  • With the deprecation of third-party cookies and the implementation of tighter data privacy laws, brands need a solution that empowers them to reach the desired target audience.
  • Consumers have raised concerns about data privacy and do not want to be tracked or are already untrackable. In a world that puts data privacy on the front seat, this targeting capability is a great way to deliver relevant ads without violating privacy.
  • It is also a great way to reach out to the most relevant customers with ads that better align with their real-time interests, using the right message, and displaying them at the right time.

Go a step further with Seedtag Contextual Audiences

The conventional way brands understand their audience does not work anymore as they are built on stereotypes, clichés, and non-privacy-compliant strategies. Contextual audiences can help brands find a diverse, inclusive, and relevant audience base using privacy-first technology.

Seedtag Contextual Audiences can help customers do all of that and more! Crafted using Custom AI, contextual categories, images, and cookieless sociodemographic models, our contextual audiences evolve from customer input and diverse market research.

Powered by Liz, our pioneering AI technology, Seedtag Contextual Audiences are built to deliver audiences that are unique and dynamic to suit specific business needs. Using AI models, our contextual audiences create a comprehensive network that generates audience categorizations that are relevant to a brand, whilst respecting consumer privacy.

Types of Contextual Audiences

To empower brands with our unique, AI-powered targeting capabilities, Seedtag offers three types of audiences:

  • Signature Audiences: These are audiences defined by Seedtag and backed by insights provided by Liz, panelists, and research data. Brands can seamlessly activate pre-defined and tested audiences with clear interests and attitudes toward their products. Signature Audiences provide very accurate results with room for a certain degree of customization to better suit brand needs.

Examples: ​​Luxury Car Enthusiasts, Adventure and Outdoor Enthusiasts, and Environmentally Conscious Consumers.

  • Off-the-shelf Seasonal Audiences: Similar to contextual audiences but more focused on a particular event in time, this type has a clear start and end date for activations, and takes advantage of interest spikes throughout the year.
    Examples: Black Friday sale, Earth Day awareness, and F1 Grand Prix season.
  • Custom Audiences: These are one-of-a-kind audiences engineered to help brands solve specific challenges. As the name suggests, this goes beyond the pre-set audiences, leverages the targeting capabilities of Liz, finds exactly where the users are, and creates a tailor-made audience targeting strategy.

What sets Seedtag´s Contextual Audiences apart from regular audiences?

Traditional audience targeting methods typically leverage cookies, and the audience categorization is based on stereotypes. This contributed to the increase in the popularity of contextual targeting methods which are interest-based. It targets the most relevant users at the right time with content that aligns with their current mindset.

However, even contextual targeting cannot solve every challenge and it has its limitations when it comes to scale. Seedtag contextual audiences go beyond these limitations and provide a targeting capability that is cookie-free, flexible, accurate, and precise.

Seedtag's contextual audiences are future-proof, thoroughly tested, built for scale, and backed by advanced AI models. The audiences are constantly updated using our network analysis capabilities to optimize targeting precision and meet KPIs. With Custom AI, our targeting capability offers unique audience definitions and real-time improvements.

We partnered with Metrix Lab to evaluate the effectiveness of our custom AI in delivering precision at scale to unique target audiences. The research revealed that using custom AI, which is the backbone of our contextual audiences, affinity went up by 92%.

  • Seedtag’s Custom AI model allows brands to craft unique contextual territories based on the audiences’ interests.
  • Our technology goes well beyond classic contextual technologies. We leverage external and internal innovation in the AI ecosystem to bring new capabilities like contextual audiences that go beyond standard taxonomies. For example, curating a campaign targeting automotive enthusiasts or city drivers and urban commuters.  
  • Brands can create unique, tailored audiences without any dependencies on cookies.
  • Our targeting capability is constantly evolving and improving as it is based on real-time data from our network.
  • It enables brands to engage with users at the most optimal time by effectively delivering personalized and optimized experiences.

Contextual audiences by Seedtag are advanced and garner users by capturing their attention at the ideal moment, without relying on cookies. It also addresses the reach and scalability issues that many brands currently face and is a flexible solution that goes beyond rigid taxonomies or stereotypes. The unique targeting capability fueled by AI offers greater precision and helps achieve higher accuracy when compared to traditional targeting practices.

Get in touch with us to know more about our latest targeting capabilities powered by AI models.

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Phasing out of third-party cookies, brand safety and brand suitability, privacy laws, and changing customer preferences are among the top factors that have brought the spotlight back on contextual advertising in the global ad tech landscape. Contextual ads are increasingly becoming the preferred choice among advertisers, publishers, and customers today.

A factor that plays a key role in helping brands reach their desired target audience is the audience selection process. An audience refers to a group of people with similar interests and shared characteristics. This crucial element helps brands reach the right individuals who are most likely to be interested in their product or service.

Traditionally, audience categorization is a process where people are grouped based on their interests and past behavior patterns. This method is limiting because it tends to group individuals based on stereotypes, and relies on third-party cookies. Poor categorization of personas can have a negative impact on marketing efforts and campaigns as the categories are not 100% accurate, resulting in incorrect targeting and wasted ad dollars.

We live in a world that is embracing diversity and inclusivity with open arms and actively steering away from stereotypes. Brands looking to level up their advertising game need to keep up with the changing times and better understand audience preferences.

What if they could go a step further with their targeting strategies?

What are Contextual Audiences?

Contextual advertising focuses on placing ads on web pages where the on-page content and context align with the ads. Contextual audiences refer to individuals who are identified and grouped based on their online behavior and the context of the content they are currently engaging with.

At first glance, contextual audiences may seem very similar to the traditional audience categorization process where people are grouped based on their interests. However, the key differentiator is that contextual audiences do not leverage any personal data, and create audience groups solely based on contextual cues.

Instead of using the most common and typical way of grouping individuals based on personal information, contextual audiences use the power of context to group people. Contextual audiences ensure scalability, privacy adherence, and greater precision, making it a method ideal for the post-cookie world.

What challenges do Contextual Audiences solve for customers?

Contextual audiences are a targeting capability that enables brands to ace audience segmentation and targeting by displaying ads that are most relevant to them.

  • With the deprecation of third-party cookies and the implementation of tighter data privacy laws, brands need a solution that empowers them to reach the desired target audience.
  • Consumers have raised concerns about data privacy and do not want to be tracked or are already untrackable. In a world that puts data privacy on the front seat, this targeting capability is a great way to deliver relevant ads without violating privacy.
  • It is also a great way to reach out to the most relevant customers with ads that better align with their real-time interests, using the right message, and displaying them at the right time.

Go a step further with Seedtag Contextual Audiences

The conventional way brands understand their audience does not work anymore as they are built on stereotypes, clichés, and non-privacy-compliant strategies. Contextual audiences can help brands find a diverse, inclusive, and relevant audience base using privacy-first technology.

Seedtag Contextual Audiences can help customers do all of that and more! Crafted using Custom AI, contextual categories, images, and cookieless sociodemographic models, our contextual audiences evolve from customer input and diverse market research.

Powered by Liz, our pioneering AI technology, Seedtag Contextual Audiences are built to deliver audiences that are unique and dynamic to suit specific business needs. Using AI models, our contextual audiences create a comprehensive network that generates audience categorizations that are relevant to a brand, whilst respecting consumer privacy.

Types of Contextual Audiences

To empower brands with our unique, AI-powered targeting capabilities, Seedtag offers three types of audiences:

  • Signature Audiences: These are audiences defined by Seedtag and backed by insights provided by Liz, panelists, and research data. Brands can seamlessly activate pre-defined and tested audiences with clear interests and attitudes toward their products. Signature Audiences provide very accurate results with room for a certain degree of customization to better suit brand needs.

Examples: ​​Luxury Car Enthusiasts, Adventure and Outdoor Enthusiasts, and Environmentally Conscious Consumers.

  • Off-the-shelf Seasonal Audiences: Similar to contextual audiences but more focused on a particular event in time, this type has a clear start and end date for activations, and takes advantage of interest spikes throughout the year.
    Examples: Black Friday sale, Earth Day awareness, and F1 Grand Prix season.
  • Custom Audiences: These are one-of-a-kind audiences engineered to help brands solve specific challenges. As the name suggests, this goes beyond the pre-set audiences, leverages the targeting capabilities of Liz, finds exactly where the users are, and creates a tailor-made audience targeting strategy.

What sets Seedtag´s Contextual Audiences apart from regular audiences?

Traditional audience targeting methods typically leverage cookies, and the audience categorization is based on stereotypes. This contributed to the increase in the popularity of contextual targeting methods which are interest-based. It targets the most relevant users at the right time with content that aligns with their current mindset.

However, even contextual targeting cannot solve every challenge and it has its limitations when it comes to scale. Seedtag contextual audiences go beyond these limitations and provide a targeting capability that is cookie-free, flexible, accurate, and precise.

Seedtag's contextual audiences are future-proof, thoroughly tested, built for scale, and backed by advanced AI models. The audiences are constantly updated using our network analysis capabilities to optimize targeting precision and meet KPIs. With Custom AI, our targeting capability offers unique audience definitions and real-time improvements.

We partnered with Metrix Lab to evaluate the effectiveness of our custom AI in delivering precision at scale to unique target audiences. The research revealed that using custom AI, which is the backbone of our contextual audiences, affinity went up by 92%.

  • Seedtag’s Custom AI model allows brands to craft unique contextual territories based on the audiences’ interests.
  • Our technology goes well beyond classic contextual technologies. We leverage external and internal innovation in the AI ecosystem to bring new capabilities like contextual audiences that go beyond standard taxonomies. For example, curating a campaign targeting automotive enthusiasts or city drivers and urban commuters.  
  • Brands can create unique, tailored audiences without any dependencies on cookies.
  • Our targeting capability is constantly evolving and improving as it is based on real-time data from our network.
  • It enables brands to engage with users at the most optimal time by effectively delivering personalized and optimized experiences.

Contextual audiences by Seedtag are advanced and garner users by capturing their attention at the ideal moment, without relying on cookies. It also addresses the reach and scalability issues that many brands currently face and is a flexible solution that goes beyond rigid taxonomies or stereotypes. The unique targeting capability fueled by AI offers greater precision and helps achieve higher accuracy when compared to traditional targeting practices.

Get in touch with us to know more about our latest targeting capabilities powered by AI models.

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Connected TV (CTV) gained popularity in the mid-2010s as internet-enabled smart TVs and streaming devices became commonplace. With the growth of platforms like Hulu, Roku, Disney and more, the spending on ads for CTV has also been rising quite steadily. According to e-marketer, CTV is one of the fastest-growing channels in digital advertising and is projected to reach $29.5 billion in 2024. Companies are seeing significant benefits from this channel, with Hulu making over $3 billion and YouTube making over $2.5 billion in ad revenues from CTV.

CTV has become an increasingly important part of the TV landscape, as viewers have increasingly turned to internet-connected devices to consume content. Like all things relatively new, this growth in the popularity of CTV as a medium for advertising has come with its own share of misconceptions and assumptions. Even the term CTV is ambiguous to many given the number of devices one can stream content on these days. Some of the common misconceptions about CTV advertising are as follows –

  1. CTV is only for younger audiences

While CTV has traditionally been associated with younger audiences, we saw a change in the demographics over the last couple of years. During the pandemic, there was a notable increase in not just the viewership of Gen-Z and millennial audiences, but also an increase in the number of baby boomers. CTV viewership is becoming increasingly mainstream, with a growing number of households disconnecting traditional cable TV in favor of streaming services. As a result, CTV offers a valuable opportunity for advertisers to reach a wide range of demographics, from youngsters to families to seniors, who are using CTV devices to consume content.  Advertisers find the extensive demographic coverage of CTV valuable because CTV viewers are deeply invested in the content they choose to watch and are less likely to skip ads.

  1. There’s no difference between CTV advertising and Linear TV advertising

Numerous traditional businesses still feel that there’s a large overlap between CTV and Linear TV advertising.  The reality is that the biggest difference between advertising on CTV and linear TV is the audience. Linear TV advertising tends to have a broad reach while CTV advertising can be more targeted, allowing advertisers to reach specific audiences based on demographics, interests, and behavior. Advertising on CTV allows better personalization and ensures TV viewers are more engaged and receptive to ads that are relevant to their interests. Today’s CTV advertising even allows audiences to interact with the ad, changing the very nature of advertising. Brands like Chevrolet, Pepsi, IKEA are already rolling out interactive ads.

  1. CTV and OTT are not the same, though they are related

Marketers continue to use the terms CTV and OTT (Over-The-Top) interchangeably.  While the two are related, they are not the same. OTT is a category that includes apps and services for streaming video content, independent of traditional cable or pay-TV subscriptions. Connected TV (CTV), on the other hand, refers to the device used by the viewer to access OTT content. In other words, CTV is a subset of OTT and is the platform on which viewers watch streaming video content without requiring traditional subscriptions.

  1. CTV ads cannot be skipped

If we look at a platform like YouTube, for those of us not looking to pay for ad-free subscription, YouTube offers a variety of options to skip or not skip ads. Some ads can be skipped after a certain amount of time has passed, while some ads need to be viewed entirely before you can access the content. Quite similarly, CTV ads can be skipped depending on the ad format and platform used. Some CTV platforms may offer non-skippable ads that require viewers to watch them in full before returning to their content. Meanwhile, other platforms may offer skippable ads that can be skipped after a set amount of time has passed. As discussed above, some CTV ad formats may also include interactive elements that allow viewers to engage with the ad and receive a more personalized experience. It is up to the advertiser to define how to engage with the consumer using the platform on CTV.

  1. CTV provides only high-quality inventory

Various types of CTV inventory are available, ranging from remnants to high-quality opportunities.Advertisers can access premium inventory opportunities to showcase their ads during popular TV shows and movies, and reach engaged audiences during prime hours. The quality of CTV inventory can vary significantly depending on multiple factors such as content providers, geographic locations, ad placements, and type of content.

  1. Measuring ROI from CTV advertising is difficult, hence not worth it

While it is true that measuring the effectiveness of CTV advertising can be more complex than traditional linear TV, advertising on CTV is measured with very similar digital advertising metrics like impressions delivered, click-through rate, cost per acquisition, performance by creative, geo and much more.  CTV advertising also covers all the relevant metrics around brand safety to ensure audiences stay engaged. Using AI technology in programmatic CTV ad campaigns is expected to enhance their efficiency and effectiveness. Marketing firms will be able to offer clients performance-based pricing models using AI, thereby increasing the attractiveness of CTV advertising.

CTV presents brands with a tremendous opportunity to address the growing number of users switching from traditional cable TV or liner TV to a more digital-friendly option. CTV advertising is quickly emerging as another powerful channel to successfully target and meaningfully engage with audiences. The ability to provide higher ROI, experiences to consumers and enhanced targeting makes CTV advertising a compelling investment for those seeking to diversify their advertising strategies and stay competitive in the dynamic advertising landscape. Write to us at Seedtag to understand how we’re helping leading brands across the globe foray into advertising on CTV and explore how we can help your business make the jump.

In 2017, technology giant Google came under extreme fire from large brands like Coca-Cola, Procter & Gamble, Microsoft and others for placing ads on YouTube videos promoting racist and anti-Semitic content . This resulted in other brands like Starbucks, PepsiCo and General Motors immediately pulling their ads from YouTube. Google also saw brands ramp down the spending on all Google advertising except targeted ads.

According to a 2020 study, 75% of global executives have experienced a recent reputational crisis that could have been prevented. Before online advertising became integral to brands, advertising campaigns were crafted based on viewability and subsequently ROI. The more places you saw the ad, the higher the recall with a direct impact on sales. As online avenues grew, brands too leveraged technology to maximize their reach.

When it came to digital advertising, it was no longer just about how many times the target audiences saw the ad, but also where the ad was presented, adjacent content, context where the consumer saw the ad and more. This shift gave rise to two frequently used terms – ‘Brand Safety’ and ‘Brand Suitability’.

‘Brand safety’ was the first major focus area for brands in the online world. ‘Brand safety’ is defined as the steps a brand takes to keep its reputation safe when advertising online. This ensures that

all the brand elements deliver a positive message, do not appear in unsafe environments or seem confrontational with other brands in the market. The lack of focus on this foundational element will result in financial losses and reputational backlash. In 2017, brand safety cost YouTube 5% of their top North American advertisers.

While ‘brand safety’ covered the basic premise of ensuring that an ad does not show up at inappropriate places or videos, it largely relies on primitive techniques like keyword-ban lists and URL block listing. The techniques used did miss out on one big component – ‘context’. This does not cover sites with fake news, extremist content, fraud sites and even relevant sites purely based on keywords. This is where ‘brand suitability’ comes in.

Brand suitability determines if the context in which an ad or piece of content appears is an appropriate fit for the brand that is advertising. Brand suitability is the logical next step in the evolution of brand safety that ensures displaying advertising in the right environment to the right audience based not on keywords, but on context. For example, an ad for a new car would not be suitable for a news article about a car crash. Very recently, CNN was criticized for an ill-timed ad placement of Applebee’s along with the announcement of the Russian invasion of Ukraine. This is where brand suitability leads the way.

As consumers become more aware of online privacy, and governments stepping in with acts like the GDPR and the California Consumer Privacy Act to protect consumer’s private data rights, we’re seeing a shift towards privacy-first advertising. Personal data-driven tools, like third-party cookies, while effective, are viewed as invasive and are being phased out of use. Brands are leveraging technologies like AI to discover new ways to place ads in a way that meet the expectations of consumers while ticking off the checklist for brand safety and brand suitability.

As we move ahead, ‘context’ along with high quality creatives will be the foundation of every ad strategy. Contextual advertising has proven to be the way forward for brands looking to maximize returns while ensuring the brand is perceived positively. The targeting mechanisms have proven to be more advanced allowing brands to focus on creating compelling marketing content. We at Seedtag have been helping brands craft effective advertising campaigns that maximize ROI while ensuring positive brand recall and association.

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As the amount of time consumers spent online exponentially grew over the last few years, brands began investing more and more in online advertising. Brands resorted to using all the means available to fight for the diminishing attention spans of their target audiences. However, consumers became increasingly aware of how they were being targeted and the perceptions of online advertising significantly worsened. It no longer became acceptable to collect personal data for advertising purposes without the explicit consent of the consumer. Tools like third-party cookies which were initially designed to enhance the consumer experience soon became the enemy. Tech giants like Apple and Google soon decided to do away with cookies altogether.

With challenges around data privacy and how brands were using personal information becoming one of the biggest concerns, governments stepped in with legislation such as the General Data Protection Regulation (GDPR) in Europe and the California Consumer Privacy Act (CCPA) to define how a business needed to be transparent about the way data was collected, stored and used. This resulted in all of us being subject to the cookie-consent pop up whenever we’ve visited a website. While most pop-ups try to define what data is being tracked and how it is being used, it’s done little to help consumer perception.

Most consumers continue to be bombarded with ads for a product or service they looked up online well after they’ve either lost interest or have already purchased. Despite the wealth of information in a cookie, consumers today continue to feel they aren’t getting value in return for the information they are giving up.

We at Seedtag collaborated with the international internet-based data analysis and market research firm YouGov to survey 3.000 adults across 6 European countries to understand how consumers perceive online advertising, their preferences for funding editorial content and the value they feel they get from the ads they encounter online. According to the survey, 84% of respondents feel the ads they are served online lack personal relevance. This is further backed up by nearly a third of all respondents stating that they deny all cookies on the sites they visit while 12% stating that they provide false information while filling out cookie forms. Clearly, there’s no love lost when it comes to consumers of today and online cookies. The survey generated three key insights:

  1. Data Privacy benefits both consumers and brands – Data privacy is a key concern for consumers. 82% of participants felt positive or very positive about brands ending their use of personal data for targeting. Brands that want to continue to be trusted need to have a robust data privacy policy in place and be transparent with their consumers. Companies that move away from leveraging third-party data or are more mindful about what consumer data they are collecting and why, will continue to be perceived positively in the online world.
  2. Consumers don’t mind being served advertising in exchange for free content – It’s not all bad news for advertisers. There is still a large section of users who are on-board with being served ads, provided they get value in terms of free editorial content tailored to their interests. 58% of participants chose hybrid or ad supported methods for funding the journalistic content they consume. Advertisers need to go back to the drawing board to evaluate how they can add more value to consumers seeing their ads.
  3. Relevant ads attract attention when placed in the right context – Context and creativity continue to lead the way in the online advertising world. 53% of users responded that ads embedded within high quality content were more likely to grab their attention. Consumers who spend a large part of their day on digital media place a high value on the context in which they see the ad. The survey indicates that “dedicated” readers, ie. those participants who spend time reading digital media multiple times a day, are 177% more likely to feel positive about a brand if the ad is shown to them alongside content that is relevant to them. This is where ‘context’ would play a large role in a post-cookie world for brands.

The market is at a very interesting inflection point when it comes to online advertising. Consumer expectations when it comes to data privacy swing between those who are completely against any use of personal data and those who are willing to share it as long as they get something of fair value in exchange. Advertisers and brands need to juggle with meeting these expectations and changes in the way they’ve been doing business. However, the challenges setby current data privacy acts are creating new opportunities for brands to innovate by leveraging new technologies. Early results do indicate that brands are able to target audiences better and see significantly higher returns on their investment, allowing them to focus on creativity rather than just inventory.

Brands that can successfully craft a privacy-first approach and are able to leverage new-age tools like Contextual AI, will be able to strike the perfect balance between personalization and privacy, and eventually thrive. To further understand the various perceptions consumers have towards online advertising, and subsequently build a strategy to effectively engage with them, download our research report today.

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Topics API is the new Privacy Sandbox entrant that is replacing Google’s previous Federated Learning of Cohorts (FLoC) proposal. There has been a huge buzz around Google’s decision to phase out third-party cookies and the Privacy Sandbox initiative was a step in that direction.

Globally, the focus today lies on data privacy. Consumers have made it abundantly clear that third-party cookies are violating their data privacy and thus began the motion to phase them out. FLoC was a part of the larger Privacy Sandbox initiative, a privacy-first web tracking technology. Google faced a lot of backlash ever since the announcement, and after collating feedback from the trials decided to drop the FLoC and replace it with a new initiative, Topics API.

The FLoC model revolved around the concept of grouping people into cohorts based on their browsing patterns. This idea did not fly well among privacy advocates as they believed the algorithm could be reverse-engineered, giving rise to new privacy concerns. Replacing FLoC is Topics API, the new initiative for privacy-first, interest-based advertising, created keeping in mind the learnings and community feedback on the earlier proposal.

What is the Topics API Privacy Sandbox proposal?

Topics API aims to provide a highly secure browsing experience for users:

  • The API labels every website within one of the high-level topics
  • It enables the browsers to determine your top interests for the week based on your browsing history.
  • Shared as one new topic per week, the topics are stored only for three weeks and all old topics are deleted.
  • There are no external servers (not even Google servers) involved as all the topics are selected on the user’s device.
  • Only 3 topics, one from each of the past three weeks are picked and shared with websites and its advertising partners.
  • The main list of Topics is a human-curated list that is visible to the public and capped at 350 topics to prevent any risk of fingerprinting.

That’s not all. Topics also excludes sensitive categories like gender or race, and extends more control to users as it is powered by their browser. Google aims to further facilitate transparency and data control by also giving users access to disable this feature entirely, or remove any topic they choose to.

Let’s take an example to better understand Topics API – Say you search for something related to automobiles, the API will label the website under the topic ‘Automobiles & Vehicles’. Similarly, based on your browsing history, your browser will collect your most recent topics of interest and share it with advertisers to show you ads that are relevant, without knowing any specifics about your browsing history. For more details about the API and how it works, click here.

With this, users have more visibility and control over their data unlike third-party cookies, while also enabling advertisers to serve relevant ads without involving any technique that invades user privacy.

How will Topics API impact the advertising industry?

This initiative will give advertisers access to topics users have been interested in recently, keeping the possibility of interest levels high as the topics are fresh and updated on a tri-weekly basis. However, this has been the latest worry factor for advertisers and marketers as it could dilute their targeting capabilities.

With cookies phasing out and Topics API still in its testing phase, without any clarity about its effectiveness or regulatory compliance, it is about time advertisers expand their horizons and explore other avenues they can leverage for successful interest-based advertising strategies.

A strategy that has been gaining popularity among global brands today is contextual advertising. An ideal solution for the cookieless era, contextual advertising analyzes both content and context of a website to determine if it will be the right fit. Contextual ads are compliant with all data protection standards and do not leverage any personal information of users. With contextual targeting, ads are non-intrusive and rendered only within the user’s area of interest.

Contextual advertising rates high on brand safety and suitability as the strategy incorporates the GARM framework. It traverses a vast ocean of content and picks only those websites and categories that are relevant to a brand’s products and services, while ensuring all sensitive and harmful content is avoided and also creating an apt balance between risk and opportunity.  Additionally, with Seedtag’s contextual AI technology, advertisers are also able to leverage the power of machine learning to get a human-like understanding of content to deliver ads that not only capture audience attention but also retain it longer.

For instance, the global technology giant, LG, leveraged contextual advertising to spread its campaign dynamically and creatively. They saw a +53% rise in CTR and +24% increase in viewability. Levis, one of America’s most loved clothing brands, opted for contextual ads to raise brand awareness and increase its association with sustainability. The results? 79.4%viewabilityand 66.5% VTR.

Get in touch with us and learn more about how our Contextual AI  is helping global brands lead the way in the cookieless world.

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Pursuit of excellence is what keeps great men moving and the pursuit of perfection is what keeps great brands exploring!

Seedtag’s contextual creativity has been focused on creating efficient and pro-privacy advertising solutions for brands in the cookieless era. In a strategic move towards strengthening its product portfolio, Seedtag, the leading contextual advertiser in EMEA and LATAM, recently acquired KMTX (previously Keymantics), a French company dedicated to building AI models to optimise and automate performance campaigns. This addition will further empower Seedtag to provide a full-funnel cookieless solution to advertisers that helps them achieve exceptional results in their ad campaigns.

KMTX, is a key French company centered on building the most transparent and data-driven approach to programmatic advertising that helps marketers improve their ad spend efficiency with a special attention on keyword and semantic audiences. With the focus on delivering mid and low funnel KPIs to advertisers, since 2019 they have consistently helped over 150 clients improve more than 500 campaigns and grown to become one of the most reliable digital media partners.

At Seedtag, as we help organizations prosper in the upcoming cookieless era, this acquisition is a logical expansion towards understanding audience insights more accurately and refining targeting strategies better to identify relevant contexts and place ads where they will matter the most.

Jorge Poyatos and Albert Nieto, Co-CEOs and Co-Founders of Seedtag, state: “Over the last few years, we have seen a strong correlation between contextual signals and performance results although we have not had the technology to predict post-click behaviours at scale. The acquisition of KMTX brings AI based predictive models into our stack that combined with our proprietary contextual data will constitute a leading solution for achieving performance results in a cookieless world”.

Arthur Querou, CEO and Co-Founder of KMTX, adds: “Over the past 5 years, we have built a successful business based on helping advertisers make better media buying decisions. With Seedtag we share a common vision of making advertising on the open web simpler through data-driven media investment. By combining KMTX’s technology with Seedtag’s, the industry will be able to avail of a full-funnel contextual AI solution that will help advertisers make accurate targeting decisions in a privacy-first world.”

Gone are the days when advertisers used to piggy-ride on cookies to track consumers anywhere and everywhere on the net. With concerns around data privacy growing by the day, governments and regulating agencies all over the world have strengthened the data privacy laws and brands are now obligated to tweak their strategies to incorporate pro-privacy measures and come up with ways to add to the user experience online and not interrupt it.

With data privacy on the rise and consumers’ attention span in the fall, it makes more sense for brands to invest in measures that are in sync with consumer’s evolving preferences. Such approaches not only garner better views and engagement but also amplify the trust in a brand.  The more conscious your consumers become, the more enriching digital experience would they demand. Do your ad campaigns incorporate this gradual shift towards relevance and interest or are they still going the cookies way?  Talk to us today and improve to thrive better than your competition.

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With the eventual phasing out of third-party cookies and the implementation of various regulatory compliances like CCPA and GDPR, audience targeting is getting tougher than ever in today’s privacy-first world. As the competition skyrockets in the advertising world, leading advertisers are leveraging what is believed to be the future of audience targeting – Contextual Intelligence.

From an estimated global market valuation of US$157.4 billion in the year 2020, today the contextual advertising market is growing at a CAGR of 13.3% and is projected to reach a whopping US$335.1 billion by 2026.

So, what is contextual intelligence? It has been a topic of interest for a long time in the advertising space and is closely associated with contextual advertising today, as this form of advertising has been developed on the same principles. Contextual intelligence involves a deep and thorough analysis of a webpage to determine if it will make a good fit based on various factors like its content, context, relevance, brand safety, and brand suitability. This analysis helps brands enhance their understanding of consumer interests, enables automation, and provides proof points that fuel confident, data-driven decision making.

Contextual advertising, as the name suggests, gives advertisers the power to leverage one of the biggest impact factors – context. With its Artificial Intelligence (AI) capabilities, contextual advertising delivers ads on relevant websites that target suitable audiences, without the use of cookies.

With context, advertisers and brands can better understand what customers are browsing, their areas of interest, and how they engage and interact with content. By analyzing both the written and visual content of a page, contextual AI offers advertisers the perfect environment where the values and ideas fit seamlessly with their own, thus ensuring the highest levels of brand safety.

Contextual intelligence does not analyze just the text but takes into account all visual elements as well to establish relevance between the text, visuals, and the webpage as a whole. With a complete understanding of customer interests, it is also highly capable of providing contextual creatives that resonate with consumers.

A superior understanding of user behavior coupled with purchase intent and consumer interests helps in serving ads to the right audience by rendering them in optimal places, besides relevant content. Contextual creatives have higher engagement rates and have proven to deliver better impressions, empowering brands to build a memorable and consistent brand identity.

Here’s what a study conducted on contextual targeting revealed:

  • 63% higher purchase intent
  • 83% higher recommendation of the product advertised
  • 40% higher brand favorability
  • 73% of consumers said contextual ads rendered alongside video content complemented their overall video experience

Better brand perception, improved sentiment analysis, a stronger connection between the ad and content, and a higher brand valuation on the whole – contextual targeting is paving the way for the future of advertising strategies that put customers and their data privacy first.

What are the top 5 factors that make contextual intelligence the best bet for audience targeting in the era of data privacy?

  • Greater ROI: Contextual intelligence-based targeting goes far beyond just keyword research and analyses the content and context of a page to draw customer insights that are leveraged for customer targeting. This has proven to be a more effective targeting strategy as the ads are non-intrusive, more relevant, and resonate better with the audiences, thereby increasing ROI on ad spending.  Businesses are constantly on the lookout for cost-effective solutions that fit the modern advertising landscape. Contextual AI makes a great fit as it is an effective, affordable, and scalable solution unlike alternatives such as behavioral advertising. Behavioral ad strategies are heavily reliant on data and need large volumes of data to deliver successful campaigns. Collation, analysis, and reporting of data, and then leveraging it is far more expensive and time-consuming.
  • Superior accuracy and personalization capabilities: Since the ad strategies are created based on data-driven insights, advertisers have access to all the information they need to narrow down their lists and target the right people who are looking for that particular product or service. Leveraging new-age tech like AI/ML, contextual intelligence ensures highly accurate targeting by performing a human-like analysis of the content. Contextual AI’s ability to build personalized segments at scale helps advertisers reach their desired target audience by building contextual segments beyond the standard IAB taxonomy.  With this, advertisers can deliver ads at a highly granular level, eliminating impression wastage. Brands can create ads that speak more directly and personally with their online consumers. Since the ads are contextual and relevant, consumers are more likely to pay attention and engage better.
  • Ensuring brand safety: The human-like analysis of content and context executed using AI/ML capabilities helps identify and avoid any harmful content. Contextual intelligence integrates the GARM framework, implementing universal brand safety standards. This helps avoid sensitive content that could potentially harm brands like sexual content, hate speech, spam, and terrorism.
  • Assuring brand suitability: Brand suitability is built atop the brand safety standards. While safety is universal, brand suitability needs are unique to each brand. Contextual intelligence helps focus on brand suitability along with the GARM framework. This intelligent targeting technique picks only those categories that are relevant to and resonate with the brand’s products, services, and unique positioning. The combination of safety and suitability helps brands strike the perfect balance between reach and security, by focusing on brand niches and nuances. This thoughtful mix helps reach the right audiences without missing out on potential high-value customers that could have otherwise been lost if the focus remained only on brand safety measures like block lists or exclusion lists.
  • Privacy-focused: An ideal fit for the cookieless future, contextual intelligence does not leverage any third-party data. The audience targeting is solely based on the analysis of webpage content and context to determine all factors from user intent and relevance to brand safety and suitability.

As businesses traverse through the post-cookie era, they need to find ways to adapt to the privacy-first world. Contextual AI is here to stay as it fits the bill. It does not depend on any third-party cookies and enables brands to reach specific customer segments while being respectful of their privacy, and mindful of brand safety, and suitability.

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Brand engagement just isn’t what it used to be. In “the good old days”, with TV, it was easy to identify which commercial break of which soap opera, cartoon or sporting event to place ads in, to drive brand recall. It is no wonder that brands are still willing to pay upwards of $6 million to reach 110 million viewers of the Super Bowl.

We’re not even factoring the cost of production of the ad at this point. Outside of the Super Bowl, the story is different.

Marketers world over will agree that with people consuming a mind boggling amount of content across a steadily growing number of devices, screens, platforms, channels, consumer attention has become extremely fragmented. With the average human having a relatively finite attention span, the battle to grab a slice of that pie has fiercely intensified.

Over the last few years, we’ve been seeing the word ‘Attention Economy’ popping up often. The attention economy treats attention as a scarce commodity, which everyone from brands, big businesses, politicians and numerous other entities are fighting for.  

In today’s digital age, the very real fight for this limited resource is shaking up the way marketers are measuring success. Human attention has quickly become the key measure of ad or content success.

It’s important to note that ‘attention’ is not the holy grail of content performance. It is, however, the next big step and builds on traditional metrics of success. At Seedtag, we see three key components that need to be in place to ensure attention is grabbed at every possible opportunity.

Context drives impact

As we move towards a privacy-first world, measuring whether the right audience saw their ad has become quite the task for marketers. The end of the cookie, industry regulations such as GDPR and CCPA are impacting the ability to target and measure success.

This is where context plays a key role for marketers. With the average consumer seeing anywhere between 6000-10000 ads a day, contextual marketing allows marketers to drive more than three times the engagement they would have got otherwise.

Studies show that placing ads in the right context not only drives engagement, but is directly correlated to higher sales. For example, a 12-year old watching the entire ad for a new car model is not going to result in an immediate sale. That’s where context makes the difference.

Creativity still matters

Creativity continues to be the central focus of any metric of success for placement of ads. What hasn’t changed since the day the first ad was ever printed is the human nature to engage more with something that is relevant and interesting.

Studies indicate that the variation between a good creative and bad creative can be as much as 17 percentage points when it comes to brand recall. This isn’t limited to just a great ad copy in today’s day and age but how can one creatively engage with the audience.

Millennials today are less trusting of traditional ads and rely on their network for recommendations on things to buy, places to eat, brands to engage with. Leveraging interactive technology to capture attention that’s mostly focused on social media and smartphones will yield better results than traditional ad posts.

Let’s take an example from a decade ago. Businesses leveraged the power of augmented reality delivered by the mobile game app Pokémon GO to drive footfalls without actually placing any advertisements. Businesses cemented a position on the virtual game board by investing in the sponsored location feature of the game.  A pizza business in Queens saw a 75 percent increase in business by ensuring app-users came to their restaurant in search of Pokémon.

Non-intrusive advertising equals better engagement

How many times have we been thoroughly annoyed by an ad popping up in the middle of a video online or while one is just getting in the groove of their favorite playlist? Studies show that ads viewed in non-disruptive environments, like below the article or in a newsfeed, drive 25 % higher attentiveness than ads placed in an interruptive environment like pre-roll… or worse, mid-roll.

It is paramount for brands to know where and when to place the ad so that consumers are in the best state of mind to engage with the ad. If one were watching a video of their favorite music artist performing, and were interrupted by an ad to buy a burger; no matter how good the burger looked in the ad, one would probably be irked and wait to get back to seeing the musical performance.

In the attention economy, it’s imperative to predict the mind-set of the consumer when placing the ad and the likelihood of them being in the right frame of mind to engage and eventually act.

In summary, it’s time marketers paid attention to attention. There’s no doubt that in the current scheme of things, it has become harder for brands to grab and hold people’s attention.

While we encourage a much required move towards an attention economy, and away from traditional measures of success, it’s important to set relevant benchmarks and demonstrate how attention is the next big impactful metric. It would serve marketers better to focus on optimizing attention, not just viewability or impressions, to improve the impact and effectiveness of their online advertising.

How to Drive Attention in a Privacy - First World?

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