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.
Latest posts

Advertising today is more complex than ever. Consumers demand personalized, relevant experiences from brands, making it increasingly challenging to meet expectations without external support. Businesses must work with publishers, retailers, and platforms to thrive, using these partnerships for data insights that refine their strategies and fuel growth. We spoke with industry leaders from Ampersand, AppsFlyer, Audigent, Comcast Advertising, Fox, ID5, and Snowflake to gather insights on how strategic collaboration can expand audience reach, improve targeting precision, and drive measurable advertising success. 1. Expand your reach with strategic collaborations Gone are the days when brands relied solely on third-party data. By linking their first-party insights with equally valuable data from partners, brands develop a far more comprehensive understanding of their audiences. This collaborative approach creates richer audience profiles, improves targeting, and enhances campaign performance. Partnerships also create opportunities for operational efficiencies. For instance, brands that share data and expertise with collaborators can expand their audience reach without overhauling existing systems. These collaborations allow marketers to work smarter, turning shared knowledge into strategic wins. \”Partnerships are everything. We can\’t fulfill our goals on the sale side, marketers can\’t fulfill their goals of finding their audience where they need to reach them and with the right level of outcomes without partnering together. Why? Because each of them has their own line of sight to the data that they have access to and the data that they know best.\”Justin Rosen, Ampersand 2. Identify the right partnership model Choosing the right partnership model is key to achieving your business objectives. For some, pairing first-party data with publishers\’ insights creates better targeting. For others, aligning with complementary brands allows them to engage shared audiences. For large-scale efforts, agencies can unify collaboration frameworks, making onboarding and activation seamless. Meanwhile, emerging categories like FinTech, hospitality, and commerce media provide brands new avenues for impactful partnerships. Evaluating these options thoroughly will ensure your collaboration aligns with long-term marketing goals. \”With first-party data being really the central point of signal today, we see more and more of our advertisers identifying partnerships with maybe potentially historical competitors or partners they would\’ve never considered.\”Tami Harrigan, AppsFlyer 3. Utilize the power of pooled insights Combining various data sources, like CRM records, browsing behavior, and shopping receipts, creates an in-depth view of your customers. By understanding what motivates consumers at every stage of their journey, brands can better tailor messaging and funnel marketing spend to where it matters most. This approach also enables data-driven agility. Real-time insights help brands make informed adjustments, whether it’s shifting strategies mid-campaign or identifying new growth opportunities. When brands share data responsibly, the results are campaigns that resonate and deliver measurable improvements. \”A lot of advertisers have gotten smarter about their data than they were just two, three years ago. They’re now doing that segmentation on their side with their data and bringing that to Fox and saying, ‘Look, match this segment against your entire user base.’ In order to do that, we can work with providers like Experian, or with data clean rooms to really bring that data and do a direct match without going through a third party.\”Darren Sherriff, Fox 4. Adopt the right tools and technology The right tools empower a collaborative data ecosystem. Solutions like data clean rooms ensure privacy-first data matching and measurement. Identity frameworks, such as Unified ID 2.0 (UID2) or ID5, enable secure data alignment across platforms, simplifying audience targeting while safeguarding sensitive information. Shared dashboards are another crucial tool, providing all collaborators with clear, co-owned performance metrics. Yet, while technology is an enabler, success ultimately depends on how well tools align with each partner’s goals and build trust within the collaboration. “You have to make it accessible to non-technical personas and you have to have the ability to have it stood up and pay dividends in a short amount of time. The other thing is interoperability. We very much think as an industry we need to have interoperability with clean rooms, ones that operate on different frameworks.” David Wells, Snowflake 5. 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The way to solve that is with more interoperability and connect the data in very privacy-safe ways, offering more opportunity to reach high fidelity audiences and incorporate better measurement methodologies.”Carmela Fournier, Comcast Advertising The path to growth through partnership Those who prioritize collaboration will outrun the competition and drive sustainable growth through smarter, more connected advertising. By choosing the right models, using powerful technology, and addressing potential obstacles, brands can co-create campaigns that resonate deeply with their audiences. Connect with our experts Latest posts

RampUp 2025 brought together some of the smartest minds in AdTech to talk about the future of our industry. I had the opportunity to ask attendees key questions about AI, data collaboration, and the challenges they wish they could solve instantly. Here’s what they had to say. Watch my interviews here AI is everywhere in ads—How is it changing things? AI’s influence on advertising is undeniable, and industry leaders at RampUp 2025 emphasized how it is transforming the way data is used across marketing workflows. The increasing presence of Generative AI like ChatGPT is making it easier to stitch together data from various sources and act on insights, helping marketers execute campaigns with more efficiency. AI is no longer just about automation; it is now deeply embedded in audience building, personalization, and measurement, enabling marketers to optimize every step of the customer journey. What’s the one AdTech headache you’d fix forever? 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Experian remains committed to helping advertisers and marketers navigate these changes by enabling smarter, more connected, and privacy-conscious advertising solutions. We’re excited to see how these themes evolve throughout the year and look forward to collaborating with our partners to shape the future of digital advertising. Follow us on LinkedIn or sign up for our email newsletter for more insights on the latest industry trends and data-driven marketing strategies. Latest posts

Originally appeared in AdExchanger Navigating the world of data and identity partners feels like scrolling through a dating app: a sea of options, but only a select few worth swiping right. To find your perfect match, look for a partner who ticks all the right boxes. Here’s your guide to finding your perfect match. 1. Identity resolution: It all starts with a strong foundation Great identity resolution depends on a rock-solid foundation. The best partners rely on offline data—like names, addresses, and emails—that rarely change, ensuring a consistent view of households, individuals, and their devices over time. You want someone who gives you the same understanding of your audience across every stage of a campaign. 2. In search of: A well-rounded, reliable identity partner When evaluating identity graphs, it’s essential to distinguish between digital-only graphs, offline graphs, and those rare gems who combine both. 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Download our full matchmaking guide So, swipe right on a partner who can handle the complexities of modern marketing and deliver consistent, scalable successful marketing outcomes. Could we be your perfect match? Find out if it\’s a match today Latest posts