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
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.
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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 Ben Smith, VP of Product, Data Products at Infillion. Adapting to signal loss What does the Experian–Infillion integration mean for advertisers looking to reach audiences as signals fade? As cookies and mobile identifiers disappear, brands need a new way to find and reach their audiences. The Experian integration strengthens Infillion’s XGraph, a cookieless, interoperable identity graph that supports all major ID frameworks, unifying people and households across devices with privacy compliance, by providing a stronger identity foundation with household- and person-level data. This allows us to connect the dots deterministically and compliantly across devices and channels, including connected TV (CTV). The result is better match rates on your first-party data, more scalable reach in cookieless environments, and more effective frequency management across every screen. Connecting audiences across channels How does Experian’s Digital Graph strengthen Infillion’s ability to deliver addressable media across channels like CTV and mobile? Experian strengthens the household spine of XGraph, which means we can accurately connect CTV impressions to the people and devices in that home – then extend those connections to mobile and web. This lets us plan, activate, and measure campaigns at the right level: household for CTV, and person or device for mobile and web. The outcome is smarter reach, less waste from over-frequency, and campaigns that truly work together across channels. The value of earned attention Infillion has long championed “guaranteed attention” in advertising. How does that philosophy translate into measurable outcomes for brands? Our engagement formats, such as TrueX, are based on a simple principle: attention should be earned, not forced. Viewers choose to engage with the ad and complete an action, which means every impression represents real, voluntary attention rather than passive exposure. Because of that, we consistently see stronger completion rates, deeper engagement, and clearer downstream results – like lower acquisition costs, improved on-site behavior, and measurable brand lift. To take that a step further, we measure attention through UpLift, our real-time brand lift tool. UpLift helps quantify how exposure to a campaign influences awareness, consideration, or purchase intent, providing a more complete picture of how earned attention translates into business impact. Creative innovation and location insights Beyond identity resolution, what are some of Infillion’s capabilities, like advanced creative formats or location-based insights, that set you apart in the market? One key area is location intelligence, which combines privacy-safe geospatial insights with location-based targeting through our proprietary geofencing technology. This allows us to build custom, data-driven campaigns that connect media exposure to real-world outcomes – like store visits and dwell time – measured through Arrival, our in-house footfall attribution product. We also build custom audiences using a mix of zero-party survey data, first-party location-based segments, and bespoke audience builds aligned to each advertiser’s specific strategy. Then there’s creative innovation, which is a major differentiator for us. Our high-impact formats go beyond static display, such as interactive video units that let viewers explore products through hotspots or carousels, rich-media ads that feature polls, quizzes, dynamic distance, or gamified elements, and immersive experiences that encourage active participation rather than passive viewing. These creative formats not only capture attention but also generate deeper engagement and stronger performance for a variety of KPIs. Future ready media strategies How does Infillion’s ID-agnostic approach help brands future-proof their media strategies amid ongoing privacy and tech changes? We don’t put all our eggs in one basket. XGraph securely unifies multiple durable identifiers alongside our proprietary TrueX supply to strengthen CTV household reach. This agnostic design allows us to adapt as platforms, regulations, and browsers evolve – so you can preserve reach and measurement capabilities without getting locked into a single ID or losing coverage when the next signal deprecates. Raising the bar for media accountability Looking ahead, how is Infillion evolving its platform to meet the next wave of challenges in audience engagement and media accountability? From an engagement standpoint, we’re expanding our ability to support the full customer journey, offering ad experiences that move seamlessly from awareness to consideration to conversion. That includes smarter creative that adapts to context, intelligent targeting and retargeting informed by real data, and formats designed to drive measurable outcomes rather than just impressions. When it comes to accountability, we’re ensuring that measurement is both flexible and credible. In addition to our proprietary tools, we partner with leading third-party measurement providers to validate results and give advertisers confidence that their investment is truly performing. Within our DSP, we emphasize full transparency and log-level data access, ensuring advertisers can see exactly what’s happening on every impression. All of this builds toward the next era of agentic media buying – one enabled by our MCP suite and modular, component-based tools. This evolution brings greater accountability and next-generation audience engagement to an increasingly automated, intelligent media landscape. Our goal is to help brands connect more meaningfully with audiences while holding every impression – and every outcome – to a higher standard of transparency and effectiveness. Driving impact across the funnel What is a success story or use cases that demonstrate the impact of the Experian–Infillion integration? We recently partnered with a national veterans’ organization to raise awareness of its programs for injured or ill veterans and their families. Using the Experian integration, we combined persistent household- and person-level identifiers with cross-device activation to reach veteran and donor audiences more precisely across CTV, display, and rich media. The campaign achieved standout results – industry-leading engagement rates, a 99% video completion rate, and measurable lifts in both brand awareness (3.6 % increase) and donation consideration (13.7% lift). It’s a clear example of how stronger identity and smarter activation can drive meaningful outcomes across the full funnel. Contact us Identity resolution FAQs Why is identity resolution critical for CTV and cross-channel campaigns? Identity resolution ensures accurate connections between devices, households, and individuals. Experian's Offline Identity Resolution and Digital Graph strengthen these connections for improved targeting and consistent measurement across CTV, mobile, and web. What strategies help address the loss of cookies and mobile IDs? Solutions like Experian's Digital Graph enable brands to connect first-party data to household and person-level identifiers, ensuring scalable reach and compliant audience targeting legacy signals fade. How can engagement translate into measurable results? Focusing on earned attention (where audiences actively choose to engage) leads to stronger completion rates, improves on-site behavior, and drives measurable increases in brand awareness and consideration. What makes cross-channel targeting more effective? By linking CTV impressions to households and extending those connections to mobile and web, Experian's identity solutions ensure campaigns work together seamlessly, reducing over-frequency and improving overall reach. About our expert Ben Smith VP Product, Data Products, Infillion Ben Smith leads Infillion’s Data Products organization, delivering identity, audience, and measurement solutions across the platform. Previously, he was CEO and co-founder of Fysical, a location intelligence startup acquired by Infillion in 2019. About Infillion Infillion is the first fully composable advertising platform, built to solve the challenges of complexity, fragmentation, and opacity in the digital media ecosystem. With MediaMath at its core, Infillion’s modular approach enables advertisers to seamlessly integrate or independently deploy key components—including demand, data, creative, and supply. This flexibility allows brands, agencies, commerce and retail media networks, and resellers to create tailored, high-performance solutions without the constraints of traditional, all-or-nothing legacy systems. Latest posts
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