At A Glance
Experian and Yieldmo collaborate to help marketers navigate signal loss with privacy-safe contextual advertising. By combining Experian’s identity solutions with Yieldmo’s advanced targeting, this collaboration enables effective audience engagement in a world with fewer traditional signals.Note: While third-party cookies are no longer being phased out, this webinar was recorded in 2023 when cookie deprecation was still a key industry focus. The strategies discussed reflect that time frame and remain relevant for addressing broader signal loss challenges.
With major browsers discontinuing support for third-party cookies, marketers must rethink how to identify and engage their audiences. Contextual advertising offers a privacy-safe solution by combining contextual signals with machine learning to deliver highly targeted campaigns. In a Q&A with our experts with eMarketer, Jason Andersen, Senior Director of Strategic Initiatives and Partner Solutions at Experian, and Alex Johnston, Principal Product Manager at Yieldmo, we discuss how contextual advertising addresses signal loss, improves addressability, and delivers better outcomes for marketers.
The macro trends impacting 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 (Experian): 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 (Yieldmo): Third-party cookie loss is already a reality. As regulations like theGeneral 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.
Solving signal loss with contextual advertising
How does contextual advertising help marketers engage audiences with new strategies like machine learning and artificial intelligence (AI)?
Jason (Experian): Contextual advertising helps marketers engage audiences by combining advanced machine learning with privacy-safe strategies. We focus on using AI and machine learning to better understand behavior, respect privacy, and deliver insights. As third-party cookies go away, alternative identifiers are coming to market, like Unified I.D. 2.0 (UID2). These are going to be particularly important for marketers to be able to utilize them. 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 (Yieldmo): There’s been a renaissance in contextual advertising over the last couple of years. Three key drivers are shaping this shift:
- The loss of identity signals is forcing marketers to rethink how they reach audiences.
- Advances in machine learning allow us to analyze more granular contextual signals, identifying patterns that are most valuable to advertisers.
- Tailored models now use these signals to deliver more effective campaigns. This transformation is occurring because of our ability to capture and operate on richer, more detailed data.
Reach consumers with advanced addressability
How does advanced contextual advertising help marketers reach non-addressable audiences?
Jason (Experian): Advanced contextual advertising helps marketers reach non-addressable audiences by taking a set of known data (identity) and drawing inferences from it with all the other signals we see across the bidstream. It’s about using a small seed set of customers, those who have transacted with you before or match your target audience, and training contextual models to make the unknown known. 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.
Alex (Yieldmo): 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. Machine learning advancements allow you to take your small sample audience and uncover those patterns in the non-addressable space. High-quality, privacy-resilient data sets are critical for building these campaigns. Companies like Experian, with deep, rich training data, are well positioned to support advertisers in building extension audiences.
Creative strategies that improve ad performance
Why does creative strategy remain essential for digital advertising success?
Jason (Experian): Creative strategy remains essential because it provides valuable signals for targeting and engages audiences effectively. In this advanced contextual world, 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 (Yieldmo): Creative and ad formats are powerful signals for understanding audience engagement. At Yieldmo, we collect interaction data every 200 milliseconds, such as scrolling behavior or time spent on an ad. This data fills the gap between clicks and video completions, helping us build models that predict downstream actions. Tailoring creative to specific audience groups has always been one of the best ways to improve performance, and it remains essential in this new era of contextual advertising. 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.
Our recommendations for actionable marketing strategies
Do you have recommendations for marketers building out their yearly strategies or a campaign strategy?
Jason (Experian): My recommendation for marketers building out their yearly strategies is to be proactive and start testing and learning these new solutions now. 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 (Yieldmo): 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.
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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.
About Yieldmo
Yieldmo is an advertising platform that fuses media and creative to meet audiences in the moments that matter. Using proprietary data and AI, Yieldmo uses advanced targeting to deliver context-aware creative when and where it’s most effective, all while respecting user privacy. The result: ads that belong on inventory brands trust. For more information, please visit www.yieldmo.com.
Contextual advertising FAQs
Contextual advertising works by targeting audiences based on the content they’re engaging with, rather than relying on personal identifiers or traditional tracking methods. Yieldmo’s platform uses advanced contextual signals and machine learning to deliver relevant ads in privacy-safe ways.
Contextual advertising addresses signal loss by focusing on environmental and content-based signals instead of relying on thir-dparty cookies or other traditional identifiers. Experian’s identity solutions complement this approach by enabling marketers to connect with audiences in a compliant and scalable way.
Creative is important in contextual advertising because it engages audiences and provides valuable signals for targeting. Yieldmo’s platform collects interaction data, such as scrolling and time spent on ads, to refine campaigns and improve performance.
Marketers can reach non-addressable audience through advanced contextual targeting, which uses known data, like seed audiences, to identify patterns and extend reach. Experian’s identity solutions and contextual data from, Audigent, a part of Experian, help marketers connect with these audiences in privacy-safe and effective ways.
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Conventional TV advertising campaigns have historically relied on general audience metrics like impressions and ratings to measure outcomes. These metrics can help marketers understand how many people have seen an ad, but they don’t reveal its real-world impact, which leaves a gap between ad exposure and results. Outcome-based TV measurement bridges this gap and helps marketers tie ad spending directly to their business goals. Instead of counting eyeballs alone, TV measurement zeroes in on what viewers do after seeing an ad — whether signing up for a service, visiting your website, or purchasing a product. TV ad measurement helps marketers adjust campaigns based on clear, trackable outcomes rather than guesswork. Let’s talk about how marketers can get started with outcome-based TV measurement and start experiencing tangible results. Why outcome-based TV measurement matters Outcome-based measurement indicates a massive shift in how marketers evaluate TV advertising success. As a principal analyst at Forrester explained, the industry is about to “move into a whole different world" where multiple metrics are tailored to advertisers’ unique goals, such as sales, store traffic, or web engagement. This shift is driven by improved tools for tracking TV outcomes, which help justify spending and clarify ROI. With TV measurement, you can see how your campaigns impact aspects of your marketing like sales and engagement. Aligning TV ad spend with business goals Every business has distinct objectives. Outcome-based measurement ties your marketing efforts to business goals and enables smarter decisions, campaign optimization, and ROI improvements. Whether you're a B2C brand wanting immediate sales or a B2B organization looking to drive website traffic, this method provides the insights needed for strategic decision-making. Marketers can deliver the most value by adjusting TV ad spending to maximize desired results: Sales goals: Identify which ads and platforms directly influence purchases to ensure TV ad spend contributes to revenue growth. Customer engagement: Link actions like website visits or app downloads to TV campaigns and refine messaging to deepen audience connections. Desired outcomes: Align ad spend with goals like consumer awareness or repeat purchases to allocate resources effectively for measurable success. Reducing wasted spend on ineffective channels Outcome-based TV measurement allows you to pinpoint which networks, times, or programs drive the most engagement and conversion. When you know your underperforming channels, you can reallocate budgets to those with a higher ROI and avoid waste. Core metrics in outcome-based TV measurement The effective implementation of outcome-based measurement requires advanced TV advertising analytics and tracking metrics that shed light on TV ad performance. Incremental lift This metric measures the increase in desired actions and business results — like purchases or site visits — that can be attributed directly to a TV campaign. Incremental lift quantifies your campaign’s impact and separates organic activity from the results your ads have driven. Let’s say a meal kit service experiences a 20% lift in subscriptions within a single week of running TV ads compared to a week without ads. They’d want to be able to isolate the impact of their ad from their organic growth so they can determine if the growth is actually a result of the TV ads or another effort. Attribution and conversions Attribution links TV ad exposure to specific customer actions, such as newsletter sign-ups and product purchases. Conversion data helps marketers understand the whole customer journey to optimize messaging, targeting, and channel mix to improve conversion rates. A retailer that knows 50% of TV ad viewers visit its e-commerce site within 36 hours of exposure could use that information to adjust the timing of its retargeting and align with site visit spikes. Audience segmentation for targeted measurement Outcome-based measurement breaks down performance across target demographics and allows for granular audience segmentation so TV ads resonate with the right audiences. For example, if a luxury brand saw better TV ad performance with high-earning Millennials, they’d want to refine their campaign messaging based on this group’s habits and preferences. Customer journey tracking Knowing how viewers move from awareness to conversion is critical. Outcome-based TV measurement helps you track the customer journey by pinpointing touchpoints where engagement happens and tying these to your TV campaigns. If a fitness brand found that TV campaigns drive app downloads, it could combine app analytics and TV exposure data to find out when most of their conversions happen after ad exposure and create follow-up messaging for that window of time. Integrating these insights with other marketing channels allows you to fine-tune your messaging, channel mix, and audience targeting to drive better outcomes and deliver more personalized customer experiences. Lifetime value (LTV) Beyond immediate conversions, outcome-based TV ad measurement helps brands identify which TV campaigns attract high-value customers with long-term revenue potential. If a financial institution ran a TV ad campaign centered on its new credit card, for instance, it could use LTV to track new cardholders and determine whether ads occurring during financial news airtime produced customers with higher average annual spend compared to other segments. How outcome-based TV measurement works Outcome-based measurement is a data-driven process that involves collecting, analyzing, and applying insights to improve TV ad performance. 1. Collect data When someone sees your TV ad, they might take action, like downloading your app or buying something. Outcome-based TV measurement begins by tracking these actions and gathering data from various sources, such as: TV viewership CRM Digital engagement Purchase behavior Cross-platform interactions And more Data integration with digital platforms Combining TV data with insights from platforms like social media or website analytics creates a more unified view of campaign performance. This integration powers easier retargeting and better alignment between digital and TV advertising strategies. Some marketers enhance this integration further using artificial intelligence (AI) to streamline data coordination and ensure campaigns are optimized for effectiveness and ROI. 2. Connect the dots Next, marketers need to find out which actions were influenced by TV ads. It’s important to ask questions like these as you work to connect the dots: Did website traffic spike right after the ad aired? Did the ad viewers match the people who signed up for the service or made a purchase? You can link TV exposure to real-world behaviors with tools and identifiers like hashed emails, device IDs, surveys, and privacy-safe data-matching techniques. 3. Analyze the data Then, the data needs to be analyzed for patterns like these: Which TV ads or time slots drove the most engagement? Did certain customer groups respond better than others? Was there a noticeable lift in sales or signups after the ad campaign? This step can help you uncover what’s working and what’s not. Role of advanced analytics and machine learning The data analysis required in this process can be overwhelming, time-consuming, and risky without the right tools. Fortunately, advanced analytics and fast, effective artificial intelligence tools can process large amounts of data from digital platforms, TV viewership, and customer interactions in less time to reveal accurate, actionable insights and patterns. They can also predict which audiences, messages, and channels will be most profitable so campaigns can adapt in real time, whether by reallocating spend to higher-performing channels or refining audience targeting. 4. Turn insights into action Once you have your data-derived insights, you can tweak your campaign in a number of ways, whether you decide to: Adjust your ads: If one message works better than another, lean into it. Refine your targeting: Focus on the audience segments most likely to act. Optimize your spend: Invest in channels or times that deliver the best return. For example, if you see that ads during prime time lead to more purchases than morning slots, you can shift your budget accordingly. This type of knowledge can be used to continuously improve your campaigns. Each time you run a new ad, you measure again, building on past insights to make your outcome-based TV advertising even smarter. Applications of outcome-based TV measurement Outcome-based TV measurement has wide-ranging applications across industries. Here’s how it’s helping businesses link TV ad exposure to real-world actions and optimize campaigns for better results. E-commerce and retail: Retailers can track how TV ads influence purchases and use those insights to refine their assets and target specific customer groups. A clothing retailer may track how well a TV ad boosts online traffic and in-store purchases. For instance, if a seasonal sale commercial correlates with a spike in website visits or mobile app downloads, the brand can refine its ad placement to focus on the most responsive demographics. Automotive: Automakers use outcome-based TV measurement insights to determine how ads drive dealership visits, test drives, or inquiries. A car manufacturer could analyze whether TV spots featuring a new vehicle increase traffic to its dealership locator or car configuration tool online. Healthcare: Pharmaceutical companies could assess whether TV spots lead to increased prescription fills, or a health provider could test how ads promoting flu shots result in appointment bookings through its website or app. If any messages resonate more with families, the provider can create similar campaigns for the future. How Experian enhances outcome-based TV measurement Experian has recently partnered with EDO, an outcomes-based measurement provider, to offer more granular TV measurement across platforms. Our identity resolution and matching capabilities enhance EDO’s IdentitySpine™ solution with rich consumer data, including age, gender, and household income, all in a privacy-centric way. Integrating these demographic attributes is helping advertisers achieve more precise audience insights and connect their first-party data to actionable outcomes. As a result of this collaboration, brands, agencies, and networks can optimize their TV campaigns by identifying which ads drive the most decisive engagement among specific audience segments. We’re improving accuracy, targeting, and more so advertisers can maximize the performance of their CTV strategies. Get in touch with Experian’s TV experts If you’re ready to take your data-driven TV advertising strategies to the next level, connect with our team. We combine advanced data and identity solutions as well as strong industry collaborations to help brands optimize their TV campaigns. Whether you're navigating traditional or advanced TV formats, our expertise ensures your efforts deliver maximum impact. Connect with us today to drive engagement, connect with audiences, and achieve better ROI. Let’s transform the way you measure success on TV. Reach out to our TV experts Contact us 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. Overcome barriers to collaboration Collaboration often faces obstacles, like differing goals, fragmented data, or resource gaps. Brands can tackle these issues by aligning stakeholders on clear KPIs, standardizing data-sharing practices, and selecting tools that integrate smoothly with existing systems. Breaking down barriers early fosters fluid cooperation and improves outcomes for everyone involved. When goals, tools, and resources are in sync, these partnerships deliver lasting value and stronger results. “The key is to bring together data assets and work collaboratively to address fragmentation. 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? AdTech leaders agreed that some industry challenges have lingered for too long. Many expressed frustrations with the ongoing conversation about unifying cross-screen targeting and measurement. While the technology exists, aligning business priorities remains a roadblock. Others highlighted issues like the complexity of billing and reporting, which still needs to be faster and more reliable. There was also a strong push to educate brand marketers on the continued impact of offline media, such as billboards, and how data-driven strategies can enhance the effectiveness of out-of-home advertising. Beyond these operational challenges, another recurring theme was the increasing importance of identity as the backbone of effective advertising. While brands are focused on collecting first-party data, the true challenge lies in activating that data at scale. Without a strong identity resolution strategy, first-party data alone is not enough to create meaningful audience connections across multiple platforms and devices. What's one AdTech tool or strategy you can’t live without? When it comes to must-have tools and strategies, data collaboration and clean rooms emerged as essential. These solutions help companies, agencies, and publishers work together seamlessly while maintaining security and efficiency. Another key strategy discussed was traffic shaping, which allows advertisers to push activation closer to publishers, reducing data leakage and improving overall performance. Both of these approaches are critical for advertisers aiming to scale. However, as brands continue to seek more flexibility and efficiency, the conversation at RampUp expanded beyond individual tools toward a broader industry transformation. Interoperability has become a top priority, with brands, platforms, and data providers focused on ensuring seamless connectivity across clean rooms, customer data platforms (CDPs), and activation partners. The days of being locked into a single walled garden are over—the future is about data portability. "RampUp made it clear that the industry is shifting toward curated, interoperable, and always-on identity solutions—and Experian is perfectly positioned to lead this next phase of growth."Suzanna Stevens, Sr. Enterprise Partnerships Manager This shift is also driving changes in how brands manage identity. Rather than relying on one-off data onboarding, companies are increasingly adopting subscription-based identity solutions that provide an always-on, continuously refreshed identity graph. This model ensures that brands have up-to-date customer profiles while reducing inefficiencies associated with batch processing. What privacy regulations should marketers be watching? Privacy remains one of the most pressing concerns in AdTech, and industry experts highlighted the need for a better approach to regulation. Consent management was identified as a major priority since it is fluid and directly impacts how marketers engage with consumers. There was also a strong sentiment that the current state-by-state approach to privacy regulation in the U.S. is unsustainable. Instead, the industry would benefit from a national framework that simplifies compliance and ensures more consistent data governance across all states. Final thoughts from RampUp 2025 RampUp 2025 showcased the rapid shifts happening in AdTech, from AI-driven efficiencies to the growing importance of data collaboration and privacy-first strategies. As the industry works to solve long-standing challenges, such as unification and regulatory fragmentation, innovation continues to drive new opportunities. 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. Contact us Latest posts