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
Originally appeared in AdExchanger Google’s decision not to deprecate cookies in the Chrome browser after all caused a stir across the industry. Companies invested heavily in developing solutions aligned with the Privacy Sandbox as a survival tactic for the post-cookie landscape. At first glance, Google’s about-face may appear to undercut those efforts. It’s easy, and perhaps even satisfying for some – but inaccurate – to say “all that effort was for nothing.” Given Chrome’s dominance among browsers, AdTech companies had no choice but to prepare for “what if” scenarios. The same goes for cookie deprecation. Google’s plan to end support for third-party cookies would have removed a mechanism that has been a cornerstone of addressability for the past 15 years. To be clear, those efforts have not been wasted. They spurred innovation across the AdTech landscape, driving progress in privacy-first targeting, alternative identifiers, supply-path data activation, and real-time data enrichment – all of which will pay dividends for years to come. Whether born directly from Privacy Sandbox participation or inspired by the broader trend toward privacy reform, industry-wide preparation for cookie loss and browser disruption has yielded tangible benefits. Pressure from Google, Apple, and evolving regulations served as a catalyst for modernization that could shape the next decade of advertising technology. An industry anchored in product innovation AdTech is a fundamentally product-driven industry defined by short innovation cycles and the imperative to build and test rapidly. This DNA enables companies to stay resilient, evolve and deliver innovation. Change is good. Disruption can be even better – but only for those who embrace it. Google’s evolving stance on cookies and Privacy Sandbox doesn’t negate what’s been learned. If anything, it underscores the need to keep innovating. The next wave of disruption is likely right around the corner. The payoff While some may argue that the time and effort spent preparing for cookie loss was wasted, those efforts have functioned as a forcing mechanism for several innovations in data activation. Supply-side data activation and optimization, aka “curation,” is an alternative to the traditional approach to data activation. Unlike the traditional data management platform (DMP) to demand-side platform (DSP) activation flow, curation allows buyers to utilize supply-path data more directly. The upshot? Improved performance and pricing for media agencies and brand advertisers. As curation continues to evolve, it’s poised to play a central role in how advertisers and publishers transact. Real-time data enrichment is another area that has benefited from this period of accelerated innovation. Many companies were compelled to improve their tech stacks to align with Sandbox protocols. These updates, particularly in real-time data enrichment capabilities, are now laying the groundwork for future data activation strategies across both the buy and sell-sides. Exiting out of tunnel vision Over the past five years, the AdTech industry has invested deeply in planning for a future without cookies. Still those investments have been well worth it. While cookies are not going away, the broader deprecation of signal continues. The work that was done to prepare will inevitably inform the next evolution of our industry. Contact us Latest posts
Marketers are under more pressure than ever to deliver personalized, high-performing campaigns—while navigating tighter budgets, shifting privacy expectations, and fragmented tech stacks. Despite an explosion of tools and data sources, the fundamentals of marketing haven’t changed. Every great campaign still starts with a simple question: Who are we trying to reach? The answer depends on how well you understand your customers. Increasingly, that understanding is hampered by data silos, inconsistent identity signals, and disconnected workflows between planning, activation, and measurement. When those pieces don’t align, it leads to inefficient spending, incomplete insights, and missed opportunities. To move forward, marketers need more than better tools—they need a more connected approach. Start with a complete view of the customer The foundation of effective marketing is understanding your audience—not just who they are, but what they care about and how to reach them across devices and platforms. That starts with building a complete customer profile. For many marketers, this means linking persistent offline data—such as name and address—with fresh digital signals like device IDs and online behaviors. When combined, these elements provide a high-fidelity view of the customer that can be enriched with attributes like demographics, purchase behavior, and lifestyle interests. This kind of profile doesn’t just help you understand people—it helps you build audience segments that actually perform. Whether you’re working with your own CRM data or third-party sources, the ability to create addressable segments that are both accurate and scalable is what separates good campaigns from great ones. 🛳️ That’s exactly what MMGY did for Windstar Cruises. By layering first-party data with behavioral and demographic insights, they built custom audiences that more than doubled campaign benchmarks. 🎮 Gaming platform Unity tapped into Experian audiences to understand player behaviors across web, mobile, and connected TV (CTV). These insights helped their advertisers reach gaming audiences more effectively—tailoring creative and delivery to real-world preferences, not assumptions. Activate with precision, not just volume Knowing your audience is only half the battle. The next challenge is reaching them—consistently and efficiently—across multiple channels. This is where fragmentation can creep back in. All too often, marketers build audiences in one system, but activate in another, causing data loss and targeting mismatches. A more connected strategy uses the same identity and audience spine across planning and activation, reducing signal loss and improving accuracy. 👉 Curated private marketplaces (PMPs), for example, allow marketers to match high-quality audiences with premium inventory in a targeted, transparent, and efficient way. These deals let marketers align their spending with their goals—whether that’s lowering cost-per-acquisition or boosting reach in a key vertical. Performance results are bearing this out: PMG By using Audigent’s curated PMP approach in combination with Experian audience data, they delivered campaigns that were 44% more cost-efficient across CTV. Boiron For Boiron, a homeopathic brand, using curated media buying reduced data costs by 30% and beat CPA goals for both video and display by more than 40%. Index Exchange Publishers benefit, too. When Index Exchange included Audigent-curated inventory in their PMPs, they saw an average 70% revenue lift for mobile and a 13% lift for CTV. When identity, audience, and inventory are aligned, everyone benefits—marketers, publishers, and consumers. Measure what matters Too often, measurement is treated as an afterthought. But in a connected campaign, it’s built in from the beginning. By using consistent identity across planning, activation, and measurement, marketers can connect ad exposure to real-world outcomes—whether that’s an online conversion, an in-store visit, or a new customer relationship. This kind of closed-loop measurement turns marketing into a learning engine. You don’t just see what happened—you understand why it happened and can use that information to improve the next campaign. 🛳️ In the case of Windstar Cruises, MMGY used Experian identity to precisely measure how digital ad exposures translated into bookings. That kind of visibility gives marketers more than a report card. It gives them the feedback they need to optimize smarter next time—and prove ROI every time. The future is connected To meet today’s demands, marketers need a new way of working—one that starts with a complete understanding of the customer, builds addressable audiences on a strong identity foundation, activates them precisely across channels, and measures impact in real time. The marketers embracing this approach are already seeing results: stronger performance, more efficient spending, and deeper insights that power what comes next. The future won’t be built on more tools—it will be built on more connection. Connect with us Latest posts
Curation — the intelligent packaging of data and inventory actionable in a private marketplace deal — can no longer be considered a trend or buzzword. With over 66% of all open exchange – representing $100 billion in annual spend – being transacted through private marketplace deals (PMPs), curation is a key part of how data and identity are addressed and actioned in programmatic media. Programmatic advertising is certainly known for big shifts, but as shared by Index Exchange CEO Andrew Casale, “Curation will be bigger than header bidding and as big as programmatic or real-time bidding (RTB) – that’s our bet.” And we agree. But why has curation become a critical component of brands and media agencies' digital advertising strategies? Put simply, the math. Case study after case study empirically shows curation performs well for both the buy and sell-sides. For media agencies and brands, curation consistently shows four main benefits: Significant cost efficiencies Buying curated PMPs shows significant cost efficiencies when compared to buying data from the buy-side alone. Strong performance Data-enriched, curated PMPs can be optimized through the supply path, unlike a data management platform (DMP) segment, which leads to strong performance. Futureproofs media buying When data is curated through the supply path, it does not need to rely on legacy identifiers (like cookies), and the door is open to robust, next-gen addressability which better futureproofs media buying opportunities. Value-added insights Curation comes with robust log-level data that can be used for value-added data science including analytics, insights, reporting, and attribution – all critical in a world where addressability and identity resolution are becoming even more challenging. Curation introduced efficiency into homeopathic brand Boiron’s media buys, reducing the brand’s data costs by 30%, which enabled the brand to reinvest the same budget in brand awareness goals. Curation not only met but also exceeded the CPA for display by 82% and for video by 41%. “Audigent has been a top 5 performer in terms of CPA during our testing, helping our teams deliver 44% more efficient spend for brands across CTV campaigns."Sam Bloom, Head of Partnerships at agency PMG A big boost for addressability Legacy identity signals are changing. Whether it’s by browser, device, or platform, both buy-side and sell-side platforms need strong identity signals to reach their intended audiences, and this has become harder than ever before. Curation, with its real-time data connection and enrichment capabilities, solves signal loss challenges by directly connecting to the supply path and using a broader spectrum of identity solutions to boost addressability. Curation allows platforms to target first-party, third-party, contextual, indexed and modeled audiences. This alleviates the dependence on any one identifier and boosts the relevant bidding opportunities for brands and media agencies to target audiences. Not all curation is created equally As with any hot innovation, AdTech is notorious for companies jumping on the bandwagon of the largest trends. Curation is no different, with seemingly everyone now claiming to be a “curator.” As the industry works to define what is and isn’t “curation," we are uniquely positioned to define this as Audigent has pioneered curation for seven years and is the industry leader. The definition of curation is the intelligent packaging and optimization of data curated against the inventory supply path. There are three definitional elements to any curation product: Unique audience data Curation must include first-party, third-party, contextual, indexed and/or modeled data. Robust SSP integration To apply data in real-time to the inventory supply path, a curator must have deep partnerships and integrations that enable the combination of data and inventory into a single package. Optimization The whole point of curating data against the supply path is that it opens the door for robust real-time optimization to drive performance. If the solution ticks all three boxes, then brands and agencies should test curation and gauge its results firsthand. Curation done right drives results for brands, agencies, and publishers When done well, curation improves media buying efficiency and performance for brands and agencies. Importantly, it also drives results for publishers and content creators. Advertisers realize average data segment savings of 36-81% when using PMPs over the open exchange (Internal data) Advertisers see 10-70% lower CPC, 1.5x-3.0x higher CTR, and 10-30% higher video completion rate when using data-enriched PMPs over the open exchange (Internal data) When including their inventory in curated PMPs, publishers see an average 70% revenue uplift for mobile and 13% for connected TV (CTV) Beyond voting with budgets, media agencies and brands are also weighing in on the curation conversation: “Our Conditions Marketplace strategies have driven a 48% improvement in eCPM and a 26% improvement in CPA across our pharma client portfolio as of May 2024. For one client, we saw ROAS improve by 58% compared to their overall omnichannel performance while maintaining quality. These results aren’t outliers—they’re proof that curation is no longer a nice-to-have; it’s a must-have for marketers who want performance, precision, and scale working in lockstep.”Amanda DeVito, Butler/Till Industry-leading curation with Experian Tapping into an end-to-end solution that enables marketers to understand and reach their desired customers across channels through curation is a win-win for all parties. In the past three years, Experian and curation company Audigent have delivered a range of industry-leading innovations together, including the integration of Experian data into Audigent’s PMPs. As one company now, Experian's unique identity and data capabilities amplify how curation activates on the buy-side at scale, setting a new standard for audience targeting with added benefits like audience customization and flexible activation through Audigent’s PMPs or demand-side platforms. Connect with us Latest posts