Contextual ad targeting paves the way for new opportunities
Advertisers and marketers are always looking for ways to remain competitive in the current digital landscape. The challenge of signal loss continues to prompt marketers to rethink their current and future strategies. With many major browsers phasing out support for third-party cookies due to privacy and data security concerns, marketers will need to find new ways to identify and reach their target audience. Contextual ad targeting offers an innovative solution; a way to combine contextual signals with machine learning to engage with your consumers more deeply through highly targeted accuracy. Contextual advertising can help you reach your desired audiences amidst signal loss – but what exactly is contextual advertising, and how can it help optimize digital ad success?
In a Q&A with our experts, Jason Andersen, Senior Director of Strategic Initiatives and Partner Solutions with Experian, and Alex Johnston, Principal Product Manager with Yieldmo, they explore:
- The challenges causing marketers to rethink their current strategies
- How contextual advertising addresses signal loss
- Why addressability is more important than ever
- Why good creative is still integral in digital marketing
- Tips for digital ad success
By understanding what contextual advertising can offer, you’ll be on the path toward creating powerful, effective campaigns that will engage your target audiences.
Check out Jason and Alex’s full conversation from our webinar, “Making the Most of Your Digital Ad Budget With Contextual Advertising and Audience Insights” by reading below. Or watch the full webinar recording now!
Macro impacts affecting marketers
How important is it for digital marketers to stay informed about the changes coming to third-party cookies, and what challenges do you see signal loss creating?
Jason: Marketers must stay informed to succeed as the digital marketing landscape continuously evolves. Third-party cookies have already been eliminated from Firefox, Safari, and other browsers, while Chrome has held out. It’s just a matter of time before Chrome eliminates them too. Being proactive now by predicting potential impacts will be essential for maintaining growth when the third-party cookie finally disappears.
Alex: Jason, I think you nailed it. Third-party cookie loss is already a reality. As regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) take effect, more than 50% of exchange traffic lacks associated identifiers. This means that marketers have to think differently about how they reach their audiences in an environment with fewer data points available for targeting purposes. It’s no longer something to consider at some point down the line – it’s here now!
Also, as third-party cookies become more limited, reaching users online is becoming increasingly complex and competitive. Without access to as much data, the CPMs (cost per thousand impressions) that advertisers must pay are skyrocketing because everyone is trying to bid on those same valuable consumers. It’s essential for businesses desiring success in digital advertising now more than ever before.
Contextual ad targeting: A solution for signal loss
How does contextual ad targeting help digital marketers find new ways to reach and engage with consumers? What can you share about some new strategies that have modernized marketing, such as machine learning and Artificial Intelligence (AI)?
Jason: We’re taking contextual marketing to the next level with advanced machine learning. We are unlocking new insights from data beyond what a single page can tell us about users. As third-party cookies go away, alternative identifiers are coming to market, like RampID and UID2. These are going to be particularly important for marketers to be able to utilize.
As cookie syncing becomes outdated, marketers will have to look for alternative methods to reach their target audiences. It’s essential to look beyond cookie-reliant solutions and use other options available regarding advertising.
Alex: I think, as Jason alluded to, there’s a renaissance in contextual advertising over the last couple of years. If I were to break this down, there are three core drivers:
- The loss of identity signals. It’s forcing us to change, and we must look elsewhere and figure out how to reach our audiences differently.
- There have been considerable advances in our ability to store and operate across a set of contextual signals far more extensive than anything we’ve ever worked with in the past and in far more granular ways. That’s a huge deal because when it comes to machine learning, the power and the impact of those machine learning models are entirely based on how extensive and granular the data set is that you can collect. Machine learning can pull together critical contextual signals and figure out which constellations, or which combinations of those signals, are most predictive and valuable to a given advertiser.
- We can tailor machine learning models to individual advertisers using all those signals and find patterns across those in ways that were previously impractical or unfeasible. The transformation is occurring because of our ability to capture much more granular data, operate across it, and then build models that work for advertisers.
Addressability: Connect your campaigns to consumers
How does advanced contextual targeting help marketers reach non-addressable audiences?
Jason: Advanced contextual targeting allows us to take a set of known data (identity) and draw inferences from it with all the other signals we see across the bitstream. It’s taking that small seed set of either, customers that transacted with you before that you have an identity for, or customers that match whom you’re looking for. We can use that as a seed set to train these new contextual models. We can now look at making the unknown known or the unaddressable addressable. So, it’s not addressable in an identity sense, it is addressable in a contextual or an advanced contextual sense that’s made available to us, and we can derive great insight from it.
One of the terms I like to use is contextual indexing. This is where we take a set of users we know something about. So, I may know the identity of a particular group of households, and I can look at how those households index against any of the rich data sets available to us in any data marketplace, for example, the data Yieldmo has. We can look at how that data indexes to those known users to find patterns in that data and then extrapolate from that. Now we can go out and find users surfing on any of the other sites that traditionally don’t have that identifier for that user or don’t at that moment in time and start to be able to advertise to them based on the contextually indexed data.
Historically, we’ve done some contextual ad targeting based on geo-contextual, and this is when people wanted to do one to one marketing, and geo-contextual outperformed the one to one. But marketers weren’t ready for alternatives to one to one yet. We want marketers to start testing these solutions. Advertisers must start trying them, learning how they work, and learn how to optimize them because they are based on a feedback loop, and they’re only going to get better with feedback.
Alex: Jason, you described that perfectly. I think the exciting opportunity for many people in the industry is figuring out how to reach your known audience in a non-addressable space, that is based on environmental and non-identity based signals, that helps your campaign perform. Your known audience are people that are already converting – those who like your products and services and are engaged with your ads. Machine learning advancements allow you to take your small sample audience and uncover those patterns in the non-addressable space.
It’s also worth noting that in this world in which we are using seed audiences, or you are using your performing audiences to build non-addressable counterpart targeting campaigns, having high-quality, privacy-resilient data sets becomes incredibly important. In many cases, companies like Experian, who have high quality, deep rich training data, are well positioned to support advertisers in building those extension audiences. As we see the industry evolve, we’re going to see some significant changes in terms of the types of, and ways in which, companies offer data, and make that available to advertisers for training their models or supporting validation and measurement of those models.
Jason: Addressable users, the new identity-based users, are critical to marketers’ performance initiatives. They’re essential to training the models we’re building with contextual advertising. Together, addressable users and contextual advertising are a powerful combination. It’s not just one in isolation. It’s not just using advanced contextual, and it’s not just using the new identifiers. It’s using a combination to meet your performance needs.
It’s imperative to start thinking about how you can begin building your seed audiences. What can you start learning from, and how do you put contextual into play today? You are looking to build off a known set and build a more advanced model. These can be specialized models based on your data. You can hone in and create a customized model for your customer type, their profile, and how they transact. It’s a greenfield opportunity, and we’re super excited about the future of advanced contextual targeting.
Turn great creative into measurable data points
Why does good creative still play an integral part in digital advertising success?
Jason: Good creative has always been meaningful. It’s vital in getting people to click on your ad and transact. But it’s becoming increasingly important in this new world that we’re talking about, this advanced contextual world. The more signal that we can get coming into these models, the better. Good creative in the proper ad format that you can test and learn from is paramount. It comes back to that feedback loop. We can use that as another signal in this equation to develop and refine the right set of audiences for your targeting needs.
Alex: If you imagine within the broader context of identity and signal loss, creative and ad format becomes incredibly powerful signals in understanding how different audiences interact with and engage with different creative. In the case of the formats that serve on the Yieldmo exchange, we’re collecting data every 200 milliseconds around how individual users are engaging with those ads. Interaction data like the user scrolling back or the number of pixel seconds they stay on the screen, fills this critical gap between video completes and clicks. Clicks are sparse and down the funnel, and views and completes are up the funnel. All those attention and creative engagement type metrics occupy the sweet spot where they’re super prevalent, and you can collect them and understand how different audiences engage with your ads. That data lets you build powerful models because they predict all kinds of other downstream actions.
Throughout my career, I learned that designing or tailoring your creative to different audience groups is one of the best ways to improve performance. We ran many lift studies with analysis to understand how you can tailor creative customized for individual audiences. That capability and the ability to do that on an identity basis is starting to deteriorate. The ability to do that using a sample of data or using a smaller set of users, either where you’re inferring characteristics or you’re looking at the identity that does exist in a smaller group, becomes powerful for being able to customize your creative to tell the right story to the right audience. When you layer together all the interaction data collected at the creative level on top of all the contextual and environmental signals, you can build powerful models. Whether those are driving proxy metrics, or downstream outcomes, puts us in a powerful position to respond to the broader loss of identity that we’ve relied on for so many years.
Our recommendations for marketers for 2023 and beyond
Do you have recommendations for marketers building out their yearly strategies or a campaign strategy?
Jason: Be proactive and start testing and learning these new solutions. I mentioned addressability and being in the right place at the right time. That’s easier in today’s third-party cookie world. But as traditional identity is further constricted, you will have these first-party solutions that will not be at scale, so you’re less likely to find your user at the scale you want. It would be best if you thought about how to reach that user at the right place at the right time. They may not be seen from an identity basis. They might not be at the right place at the right time when you were delivering or trying to deliver an ad. But you increase your chance of reaching them by building these advanced contextual targeting audiences using this privacy-safe seed ‘opted-in’ user set; this is a way to cast that wider net and achieve targeted scale.
Alex: Build your seed lists, test your formats with different audiences, and understand what’s resonating with whom. Take advantage of some of the pretty remarkable advances in machine learning that are allowing us, really, for the first time to fully uncork the potential and the opportunity with contextual in a way that we’ve never done before.
Jason: At the end of the day, it’s making the unaddressable addressable. So, it’s a complementary strategy; having that addressable piece will feed the models. But also, that addressable piece still needs to be identity-based, addressable still needs to be part of your overall marketing strategy, and you need to complement it with other strategies like advanced contextual targeting. The two of them together are super complimentary. They learn from each other, and it’s a cyclical loop. Now is the time to take advantage and start testing and understanding how these solutions work.
We can help you get started with contextual ad targeting
Contextual advertising can help you stay ahead of the curve, identify your target audience, and continue to drive conversions despite signal loss. We’ve partnered with Yieldmo to help make sure that your marketing campaigns are reaching the right target audiences on the platforms that are most relevant. To get started with contextual ad targeting to reach the right audience at the right time and drive conversions, contact our marketing professionals. Let’s get to work, together.
Find the right marketing mix in 2023
Check out our webinar, “Find the right marketing mix with rising consumer expectations.” Guest speaker, Nikhil Lai, Senior Analyst from Forrester Research, joins Experian experts Erin Haselkorn, and Eden Wilbur. We discuss:
- New data on the complexity and uncertainty facing marketers
- Consumer trends for 2023
- Recommendations on finding the right channel mix and the right consumers
Get in touch
About our experts
Jason Andersen, Senior Director, Strategic Initiatives and Partner Solutions, Experian
Jason Andersen heads Strategic Initiatives and Partner Enablement for Experian Marketing Services. He focuses on addressability and activation in digital marketing and working with partners to solve signal loss. Jason has worked in digital advertising for 15+ years, spanning roles from operations and product to strategy and partnerships.
Alex Johnston, Principal Product Manager, Yieldmo
Alex Johnston is the Principal Product Manager at Yieldmo, overseeing the Machine Learning and Optimization products. Before joining Yieldmo, Alex spent 13 years at Google, where he led the Reach & Audience Planning and Measurement products, overseeing a 10X increase in revenue. During his time, he launched numerous ad products, including YouTube’s Google Preferred offering. To learn more about Yieldmo, visit www.Yieldmo.com.
Latest posts
In our Ask the Expert Series, we interview leaders from our partner organizations who are helping lead their brands to new heights in AdTech. Today’s interview is with Allison Dewey (Director, Data & Curation) at 33Across. Navigating complexity in digital advertising Digital advertising is more fragmented and privacy-constrained than ever. How is 33Across helping marketers cut through that complexity to drive real outcomes, and what makes your approach distinct? Reaching audiences without compromising scale or performance is one of the toughest challenges for marketers. Users consume content across multiple devices and channels, making it difficult for marketers to identify and accurately target them with the right message. 33Across segments leverage AI-powered contextual and behavioral signals across privacy-safe environments to help marketers accurately identify audiences, whether they’re streaming content on their connected TV or researching products on their mobile device. What sets us apart is that we don’t just identify valuable audiences; we help marketers also target cookieless inventory and power it with real-time signals. Marketplace integration milestones What excites you most about bringing 33Across audiences into Experian’s data marketplace? We’re excited to bring 33Across audiences into Experian’s data marketplace because it connects our unique segments with a powerful data ecosystem that marketers already trust. Buyers looking to activate audiences that are both privacy-safe and performant continue to tap into the Experian data marketplace for high-quality, high-performing data. We offer a wide range of audience verticals, including B2B, demographic, retail purchase data, interest and intent, and political data. In addition, we offer the ability to create custom segments across verticals. Our intent-based audiences, built from contextual and engagement signals, help buyers reach consumers on CTV, desktop, or mobile devices with scale. Being part of Experian’s data marketplace accelerates access to these audiences, drives better ROI, and helps brands future-proof their strategies today. Retail demand signals Retail brands are racing toward privacy-safe, first-party data. Which 33Across retail datasets or segments are experiencing the highest demand, and what makes them a must-have? Retail marketers are leaning into contextual and behavioral intent signals to complement their first-party data strategies. At 33Across, we’re seeing high demand for segments tied to shopping intent, including in-market consumers browsing for categories like fashion, home goods, electronics, and health & wellness. What makes these segments essential is their real-time nature – they can capture consumer interest as it happens. For retail brands looking to expand their reach while respecting privacy, our segments offer scalable, actionable intent that drives results. B2B without cookies Reaching real B2B decision-makers at scale is tough with or without signals. How does 33Across deliver both precision and reach in this environment? B2B marketing often struggles with balancing scale and specificity. 33Across addresses this by combining contextual precision with AI-modeled behavioral signals; this segment approach reaches professionals actively engaging with relevant content and topics, even in environments where IDs are unavailable. Marketers gain access to more signals and, in turn, better reach from 33Across’ unique publisher integrations and audience curation built from machine learning and AI. We surface intent through content consumption patterns and contextual engagement, unlocking valuable, privacy-safe signals at scale. Allowing B2B marketers to reach real decision-makers in a signal-sparse world. Use cases With retail, B2B, and beyond, can you share an example of how brands in these verticals are utilizing your audiences? Top brands that have a user-focused approach use 33Across audiences to drive scale; performance. These brands enable our segments to precisely reach the right users across devices and increase conversion rates; brand awareness. By reaching the right users, brands have higher conversion rates and increase campaign efficiency. Supply path innovation As identifiers disappear, advertisers are looking for scalable, privacy-safe ways to reach real people. How is 33Across helping unlock more addressable inventory and drive performance? By combining contextual, semantic, and engagement-based signals, we deliver intent-based targeting that performs across CTV, display and video. Higher addressability helps marketers not only extend their reach but also deliver personalized messaging across digital channels in a privacy-compliant way. Contact us FAQs How can advertisers reach audiences without traditional identifiers? By using contextual and engagement-based signals, advertisers can target consumers across CTV, mobile, and desktop in a privacy compliant way, even as identifiers become less available. What audience segments are most in demand for retail marketers? Segments tied to shopping intent, such as consumers browsing fashion, electronics, or health products, are highly sought after because they capture real time interest and drive results. How can B2B marketers find decision-makers without cookies? Combining content engagement patterns with machine learning allows marketers to reach professionals actively engaging with relevant topics, even in environments where IDs are unavailable. What makes privacy safe audience targeting effective? Privacy safe targeting uses real time contextual and behavioral signals to deliver relevant messaging across devices and channels without compromising consumer trust. How can real-time intent signals drive demand? Real time intent signals allow advertisers to capture consumer interest as it happens, helping demand side platforms and brands deliver timely, relevant ads that increase engagement and drive conversions across devices like CTV, mobile, and desktop. About our expert Allison Dewey, Director of Data and Curation, 33Across Allison Dewey is the Director of Data & Curation at 33Across, where she oversees data partnerships, integrations, and supply-side curation. With a deep expertise in audience targeting and signal optimization, Allison plays a key role in connecting data into the programmatic world. Allison holds a Bachelor's degree in Psychology from Bates College. About 33Across Rooted in over 15 years of data expertise, 33Across harnesses signals to enrich and expand marketers’ audiences and reach them wherever they consume content. Built from over 300 billion proprietary data signals, we apply machine learning and AI to create over 1,500 B2C and B2B segments using privacy-first principles to reach audiences. Latest posts
Originally appeared in Adweek This holiday advertising season, identity is the real differentiator Marketers are betting big on AI to run their holiday advertising, using it to build predictive audiences, generate creative at scale, and optimize media buys in real time. The draw is clear: greater efficiency, delivered at scale. But here’s the problem: without a solid identity foundation, AI is just guessing. And in a year when consumers are cautious and competition is fierce, guesses won’t deliver the outcomes you need. Experian’s 2025 Holiday spending trends and insights report shows that success this season will depend on connecting the right data to the right audiences in real time. Download the report now Are shoppers really using AI to make holiday purchases? Not yet. Only 12% of consumers plan to use AI tools to shop this season, mostly for finding discounts. Instead, trusted influences (like retailer websites, product reviews, and recommendations) still guide buying decisions. For marketers, that’s a signal to focus on credibility and connection. AI can support your holiday advertising strategy, but trust still wins the sale. Consumer sentiment heading into the holidays is low, but that could mislead marketers Here's why How marketers are really using AI in holiday advertising Behind the scenes, AI is working overtime. Teams use it to segment audiences, test creative, and optimize media in real time. These capabilities are powerful, but only if they’re grounded in accurate, persistent data. Think about the typical holiday shopper. They may browse a product online, validate it in store, and finally purchase days later from a different device than they used while browsing. If AI isn’t anchored in identity, it struggles to connect those touchpoints. Instead of amplifying relevance, it amplifies noise. See our predictions for Black Friday 2025 Why identity is the GPS for AI-driven holiday advertising Identity is what turns AI from a blunt instrument into an accurate tool. By unifying fragmented signals across channels and devices, identity provides the consistent consumer view that AI needs to be effective. With that foundation, AI can do more than churn out models. Instead, it can: Identify the right audiences and filter out waste Personalize with context, not just scale Measure real outcomes, linking exposures to visits and purchases Identity doesn’t just improve efficiency; it creates accountability. And in a season where every holiday advertising campaign dollar is scrutinized, accountability is the difference between investment and waste. Why connected data will make or break Cyber Week How to turn complexity into clarity this holiday season This year's holiday advertising season is complicated. Marketers are confident, consumers are cautious, and AI is somewhere in the middle. The challenge isn’t just speed or volume, it’s accuracy. By pairing AI with identity, you can adapt to real behavior instead of assumptions. You can build campaigns that are consistent across connected TV, retail media, and social platforms. And you can prove results when it matters most. AI isn’t a holiday miracle. But when it’s powered by identity, it can give you clarity in a noisy season and proof of performance when budgets are under scrutiny. Explore Experian's holiday audiences to activate this season What’s the real takeaway for marketers this season? Don’t assume AI alone will save your holiday advertising strategy. It won’t. Consumers still trust human voices more than machines, and your AI models are only as strong as the data beneath them. Identity is the difference between guesswork and accuracy, between activity and impact. This holiday season, the winners won’t be the brands that simply spend more or automate faster. They’ll be the ones that put identity at the core of their AI strategy and meet consumers where they really are. Download Experian’s 2025 Holiday spending trends and insights report to see where consumers are spending and how identity can help your holiday advertising campaigns more effective. Download now FAQs Why isn’t AI enough on its own for holiday advertising? AI works best when it’s grounded in accurate data. Without identity, it can’t connect actions across devices or channels, which limits its effectiveness. How does identity improve AI-driven campaigns? Identity creates a single, persistent view of your audience. That means AI can personalize content, measure conversions, and cut waste with far greater accuracy. What does “identity” mean in marketing terms? It’s the data layer that connects people across their devices, browsers, and behaviors—so your campaigns reach real individuals. How can marketers prove ROI in holiday advertising? By tying exposure to verified outcomes—like store visits or purchases—using identity-linked data. That’s how Experian helps brands move from impressions to impact. Latest posts
What challenge did the pet brand face? A national e-commerce pet supplier wanted to expand into audio advertising to diversify beyond display campaigns. But with only one team member available to test this new channel, they faced three hurdles: Prove performance in a new channel Run lean with limited bandwidth Show purchase intent, engaged site visits, and completion rates fast They needed a partner to handle execution and supply optimization so their lean team could focus on strategy and selling audio internally. Hear how we're working with Audacy to help our clients connect beyond the screen Tune in here The solution: How did Experian Curated Deals help? Audigent, a part of Experian, ran point on setup, optimization, and real-time reporting. The brand turned to Experian Curated Deals. Together we: Streamlined access to curated inventory, cutting intermediaries and boosting efficiency Handled campaign setup and supply-side optimization Delivered real-time demand-side platform (DSP) reporting for agile targeting refinements Provided an extension of their in-house team, giving them bandwidth to focus on pitching audio internally “What stood out about Experian was their real-time control and the depth of their trading team. I knew I could hand them a campaign, and they’d run with it.”Programmatic Media Lead, National e-commerce pet supplier Want to see the full case study? Download it here What results did the campaign deliver? In just a few months, audio transformed from a small test into a top-performing channel: Exceeded KPIs by 63% Increased purchase intent and engagement vs. competing platforms Matched display performance without creative refreshes or incentive overlays Earned budget increases, positioning audio as a long-term investment Reduced internal setup time, freeing the team for strategic projects “Experian became more than just a media partner: they filled critical gaps that would typically require outsized investment in internal resourcing.”CMO, National e-commerce pet supplier Explore more examples of how brands are driving performance with Experian Windstar Cruises Leading athletic retailer Swiss Sense Why does this matter for marketers? For marketers, audio isn’t experimental anymore. It’s a proven channel that can drive both engagement and conversions. This case study shows how brands can: Use Experian Curated Deals to validate new channels with minimal risk. Lean on Experian to handle execution, freeing teams to focus on growth. Drive meaningful engagement and purchase intent, not just impressions. For marketers navigating limited resources and pressure to prove ROI fast, Experian Curated Deals provides both performance and confidence. Want to beat your campaign goals by double digits? Contact us today FAQs What is Experian Curated Deals? Experian Curated Deals streamline access to premium media inventory by eliminating unnecessary intermediaries, optimizing efficiency, and ensuring campaigns perform against KPIs. Why use curated deals for audio advertising? Curated deals help brands test and validate audio quickly, without the heavy lift of manual setup and supply path management. Can audio really drive conversions? Yes. In this case, audio campaigns not only exceeded awareness and engagement goals but also matched the conversion performance traditionally associated with display. How does Experian support lean teams? By managing setup, supply optimization, and reporting, Experian acts as an extension of your team, reducing internal workload while driving performance. Latest posts