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.
Contact us
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.
Latest posts

I’ve officially been at Experian Marketing Services for one month. That’s long enough to get past the onboarding checklists, meet an incredible number of people, and start connecting the dots between what I believed from the outside and what I now see clearly from the inside. What’s surprised me most is not the scale of Experian's assets. Everyone knows Experian operates at massive scale. It’s the uniqueness of how those assets come together. Identity. Activation. Curation. Optimization. Measurement. And a culture that understands the responsibility that comes with being the identity and data backbone for the AdTech ecosystem. There’s real energy here around not just what’s possible, but how to do it the right way. Very early on, this felt like the right move. The people confirmed it immediately. The leadership team reinforced it just as quickly. There’s alignment around how we go to market, how we think about identity, and how seriously we take client trust. That matters, especially in a moment when marketers are being asked to do more with less, prove everything, and still protect the consumer at every turn. The reality marketers are facing right now I’ve spent my career working with brands and agencies navigating change. What’s different right now is the level of fragmentation. Signals are everywhere. They’re coming from transactions, media exposure, location, content consumption, commerce, and increasingly from AI-driven interactions that don’t follow traditional linear paths. The challenge is no longer access to data. It’s coherence. If I’m a marketer today, my core question is simple: How do I tie a durable identity structure to constantly evolving consumer signals, and feed that intelligence into the right places at the right time? Especially as I start interacting with AI buying agents that will make decisions on my behalf. If the signals those systems receive are noisy, incomplete, or misaligned with my brand, I lose control fast. Identity has to be the foundation That’s where identity stops being a background capability and becomes foundational. Without a strong, continuously refreshed identity framework, everything downstream breaks. Planning becomes guesswork. Activation becomes inefficient. Measurement becomes misleading. I see too many brands treating identity as a one-time project. Build a graph. Do some householding. Declare victory. But people change. Households change. Signals multiply. Identity has to evolve just as fast. One of the biggest misconceptions I walked into was how narrowly Experian is often viewed. Many marketers still think of us as a place to buy attributes. Full stop. What I see now is a connected system that supports the full marketing lifecycle: Audience creation Activation Curation Optimization Measurement All grounded in identity and executed in a way that’s measurable and privacy-forward. Audigent + Experian’s data marketplace. This is where things click. This becomes even more powerful when you layer in Audigent. Audigent was foundational in defining curation, the idea that it’s not just about having data or inventory, but about intentionally pairing the right audience signals with the right supply to drive outcomes. When you combine Audigent’s curation expertise with Experian’s identity, data, and marketplace capabilities, something meaningful happens. That same philosophy extends directly into our data marketplace. It’s not just about accessing unique data sets. It’s about safely combining Experian data with partner data, or even multiple partner data sets together, to create audiences that simply don’t exist anywhere else. Then tying those audiences to real-world exposure and conversion across online and offline environments. This matters across industries, but especially in two places: Regulated verticals like healthcare and financial services, where accuracy and privacy are non-negotiable. Industries sitting on valuable first-party data like retail, travel, and automotive. No single company has all the signals they need. The opportunity is in collaboration. Partnering data in a trusted environment to create better outcomes and, in many cases, entirely new revenue streams. Looking ahead As AI continues to reshape how media is planned and bought, signals will become the currency. Not just any signals. The right ones. Curated, contextual, and connected to identity in a way that reflects real consumer behavior. Marketers who win will be the ones who control that signal flow, rather than reacting to it. After one month, what excites me most is that Experian is built for this moment. Years of investment in identity. A data marketplace designed for collaboration. And teams who understand that our job is not just to help marketers reach people, but to help them do it responsibly, efficiently, and in a way that actually drives outcomes. We’re just getting started. About the author Kevin Dunn Chief Revenue Officer, Experian Kevin Dunn joins Experian Marketing Services with more than 20 years of leadership experience across marketing and advertising technology, most recently serving as Senior Vice President of Brands and Agencies at LiveRamp. In that role, he led growth across retail, CPG, travel, hospitality, financial services, and healthcare, overseeing new business, account expansion, and channel partnerships. Kevin is known for building cohesive, accountable teams and leading with optimism, clarity, and a strong sense of shared purpose. His leadership philosophy centers on empowering people, driving positive outcomes for clients and fostering a culture where teams can grow, take smart risks, and succeed together. Latest posts

How should CMOs think about data as part of their audience strategy? The best digital marketers possess excellent storytelling capabilities—and they fuel the plot with data. When you think about it, your audience strategy is the whole story, and the type of data you use helps create each chapter. Just as any good book incorporates numerous literary devices, you must use more than one type of data to develop a dynamic, relevant, and timely narrative that captures your target users’ attention. In 2026, marketers should prioritize and invest in data and targeting strategies beyond just first-party to drive growth, improve efficiency, and strengthen customer relationships. Our 2026 Digital trends and predictions report is available now and reveals five trends that will define 2026. From curation becoming the standard in programmatic to AI moving from hype to implementation, each trend reflects a shift toward more connected, data-driven marketing. The interplay between them will define how marketers will lead in 2026. Download Why is first-party data not sufficient on its own? First-party data provides a strong foundation for targeting and measurement. It reflects information consumers have shared directly through brand interactions. That makes it reliable and central to audience strategy. That foundation alone does not tell the full story. First-party data defines known customers, but limits reach and frequency. Growth depends on expanding beyond existing relationships. Think of first-party data as a way to create an outline, not the whole story, about your target audiences—the main characters in your marketing. To flesh out the entire narrative about them, you must source, connect, and activate additional data. The ability to unify different data sources with accuracy, scale, and privacy at the forefront sits at the core of Experian’s business. We unify household, individual, device, demographic, behavioral, and first-party signals, along with contextual and geographic data points, to build a reliable view of consumers, even when specific signals are missing. This clarity helps you personalize, target, activate, and measure with confidence. By layering third-party data, contextual data, and geolocation data onto your first-party data foundation, your advertising strategies become stronger than if you used any of these sources as standalone solutions. How do different types of third-party data add depth to audience profiles? Third-party data expands understanding beyond known customers. If first-party data is the outline, third-party data helps with “character development”—a.k.a., adding detail to your audience profiles. Good third-party marketing data complements first-party insights with demographic, behavioral, and transactional context, providing the missing puzzle pieces to complete the full customer profile. Filling in gaps in customer understanding helps you identify, reach, and engage current and new customers more effectively. Third-party data allows brands to build loyalty with consumers by speaking to their interests and intent behind purchases. Third-party data opens up new targeting tactics for advertisers, such as: Behavioral How people engage with brands or how they use social media Demographic Age, gender, education, income, and religion Health A combination of demographics, behaviors, and health needs Interest Delivering ads based on interests, hobbies, or online activities Location Where people live, work, or spend large amounts of time Psychographics Shared characteristics like attitudes, lifestyles, and interests Purchases Using previous purchase behavior to identify the right audiences In addition to targeting, third-party data also remains critical to AI models, which must train on both structured and unstructured data. At Experian, our AI-powered technology interprets live bidstream data, device activity, content, and timing to optimize in the moment, ensuring campaigns deliver meaningful relevance, not just broader reach. How are contextual and geographic approaches reshaping audience targeting? Contextual and geographic approaches to targeting focus on environment and behavior rather than identifiers. Regulatory scrutiny, stricter and more fragmented compliance standards, and rising consumer expectations are transforming how marketers approach third-party data targeting. Evolving privacy laws and inconsistent identifiers across environments require new approaches that balance performance and privacy. Contextual and geographic targeting help marketers reach relevant audiences while maintaining privacy. What is data-informed contextual targeting? Contextual targeting connects audience attributes to the content environments people choose. It helps determine the setting of your story—where your characters spend their time. Solutions like Experian’s Contextually-Indexed Audiences harness advanced machine learning technology to combine contextual signals (a tried–and-true targeting tactic) with third-party targeting to ensure marketers reach their target audiences on the content they tend to consume, regardless of environment or location. What’s excellent about data-informed contextual targeting is that it moves beyond traditional keyword-based strategies to reach consumers on websites that over-index for visitors with the demographics, behaviors, or interests they are looking to target. What is data-informed geotargeting? Geotargeting uses shared location patterns to support relevance at scale. Geotargeting is another possibility for further developing the scene of your story. People with similar behaviors and interests tend to live in similar areas, which is why so much effort goes into location planning for brick-and-mortar stores. Data-informed geotargeting combines geos with third-party data to make more informed media buys based on common behaviors within a geographic location. We launched our Geo-Indexed audiences, which use advanced indexing technology to identify and reach consumers based on their geographic attributes. These audiences help marketers discover, segment, and craft messaging for consumers without relying on sensitive personal information, enabling them to reach target audiences while maintaining data privacy confidently. What role does AI play in third-party data targeting? AI acts like an automated editor of your book, refining and finding new ways to put valuable third-party audiences and data to work without relying on segments linked to known or disparate identifiers. We’ve used AI and machine learning at Experian for decades to bring identity, insight, and generative intelligence together so brands and agencies can reach the right people, with relevance, respect, and simplicity. Why does a balanced, integrated approach that combines first-party, third-party, contextual, and geo-targeting data matter? The combined effects of integrating third-party, contextual, and geotargeting data (and the marketing tactics it underpins) with first-party data will drive your success. Think of how any good author crafts a story. Regardless of whether it’s fiction or non-fiction, they draw on both first-person experience and external research and sources to develop their plot. No single data source tells the full story. Integration allows marketers to understand audiences more completely and act with confidence. Pooling these inputs together moves you closer to your goal of understanding the whole story about your target customers. In fact, an almost even number of marketers plan to use contextual targeting (41%) and first-party data (40%) as their main targeting strategies, amid privacy laws and the loss of persistent advertisers. Primary data strategyPercent of marketers that plan to use this data strategyContextual targeting41%First-party data40% A brand with strong first-party insights can extend reach by layering in additional signals. For example, a nutrition brand that knows who purchases protein supplements can expand prospecting by combining: First-party signals Customers who purchase protein supplements Contextual signals Engagement with fitness blogs, healthy recipe content, or workout apps Geographic signals Consumers located in the Greater Philadelphia area By connecting these inputs, the brand can identify new health-conscious audiences with similar interests and behaviors. This approach supports privacy-safe targeting while improving engagement and performance. How can marketers build an integrated data strategy in 2026? An integrated data strategy reduces friction and supports scale. The right data partner offers a unified solution that helps unify data, activate audiences, and adapt as the ecosystem evolves. Here’s how: Organize data Create a clean, usable data foundation by eliminating fragmented silos. Experian’s solutions unify disparate data, enabling identity resolution and a single customer view. Create a complete profile Experian links a persistent offline core of personally identifiable information (PII) data with fresh digital signals, giving you a high-fidelity view of consumers to decorate with marketing data. This allows for improved customer understanding and personalized marketing that competitors struggle to replicate. Build addressable audience segments Create audiences using a mixture of signals, including first-party data, third-party behavioral, interest, and demographic data, as well as contextual signals. If you partner with Experian, you can use audiences built on our identity graph to guarantee accuracy, scale, and maximum addressability. Drive innovation Look for partners and platforms that prioritize innovation in finding new ways to reach target audiences across the ecosystem. You don’t want a vendor or a system that can’t keep pace and adapt with our rapidly evolving industry. Marketers who want to create and activate campaigns more efficiently and effectively in 2026 need an integrated approach that combines first-party, third-party, contextual, and geotargeting data. Streamlining data integration and activation positions brands and agencies for sustainable growth and stronger consumer relationships in a privacy-conscious marketplace. Build your next chapter on a connected data foundation As audience strategies evolve, connection and interoperability matter more than ever. Connect with our team to learn how Experian helps marketers unify data, identity, and activation across channels. About the author Scott Kozub VP, Product Management, Experian Scott Kozub is the Vice President of the Product Management team at Experian Marketing Services working across the entire product portfolio. He has over 20 years of product experience in the marketing and advertising space. He’s been with a few startups and spent many years at FICO and Oracle Data Cloud heavily focused on loyalty marketing and advertising technology. FAQs How should CMOs think about data as part of their 2026 audience strategy? In 2026, CMOs should prioritize and invest in data and targeting strategies that combine first-party, third-party, contextual, and geographic data to drive growth, improve efficiency, and strengthen customer relationships. Why is first-party data not sufficient on its own? First-party data is not sufficient on its own because first-party data defines known customers but limits reach and frequency. Growth depends on expanding beyond existing relationships. The ability to unify different data sources with accuracy, scale, and privacy at the forefront sits at the core of Experian’s business. We unify household, individual, device, demographic, behavioral, and first-party signals, along with contextual and geographic data points, to build a reliable view of consumers, even when specific signals are missing. This clarity helps you personalize, target, activate, and measure with confidence. How do different types of third-party data add depth to audience profiles? Third-party data expands understanding beyond known customers. Third-party data opens up new targeting tactics for advertisers, such as: – Location: Where people live, work, or spend large amounts of time- Health: A combination of demographics, behaviors, and health needs- Purchases: Using previous purchase behavior to identify the right audiences – Behavioral: How people engage with brands or how they use social media – Interest: Delivering ads based on interests, hobbies, or online activities- Psychographics: Shared characteristics like attitudes, lifestyles, and interests- Demographic: Age, gender, education, income, and religion In addition to targeting, third-party data also remains critical to AI models, which must train on both structured and unstructured data. At Experian, our AI-powered technology interprets live bidstream data, device activity, content, and timing to optimize in the moment, ensuring campaigns deliver meaningful relevance, not just broader reach. What is data-informed contextual targeting? Data-informed contextual targeting connects audience attributes to the content environments people choose. It helps determine the setting of your story—where your characters spend their time. Experian’s Contextually-Indexed Audiences harness advanced machine learning technology to combine contextual signals (a tried–and-true targeting tactic) with third-party targeting to ensure marketers reach their target audiences on the content they tend to consume, regardless of environment or location. What is data-informed geotargeting? Data-informed geotargeting uses shared location patterns to support relevance at scale. Experian launched our Geo-Indexed audiences, which use advanced indexing technology to identify and reach consumers based on their geographic attributes. These audiences help marketers discover, segment, and craft messaging for consumers without relying on sensitive personal information, enabling them to reach target audiences while maintaining data privacy confidently. What role does AI play in third-party data targeting? In third-party data targeting, AI refines and finds new ways to put valuable third-party audiences and data to work without relying on segments linked to known or disparate identifiers. We’ve used AI and machine learning at Experian for decades to bring identity, insight, and generative intelligence together so brands and agencies can reach the right people, with relevance, respect, and simplicity. Latest posts

For years, marketers have worked around a familiar disconnect. Campaigns go live first. Measurement follows later. Insights arrive after audiences are reached, and budgets are committed. That gap has slowed decisions, blurred performance signals, and limited marketers’ ability to respond when it counts. In 2026, that model changes. Activation and measurement no longer operate as separate steps. They function as a single system, where insight informs action as campaigns unfold. Consistency across identity, data, and decision-making sits at the center of this shift, connecting the full campaign lifecycle from planning through outcomes. How is marketing measurement shifting from post-campaign reporting to in-flight intelligence in 2026? Marketing measurement in 2026 is moving from retrospective reporting to real-time input that shapes campaigns while they run. Instead of explaining performance after delivery, measurement now guides creative, audience, and channel decisions as verified outcomes appear. Historically, measurement worked like a post-mortem. Dashboards showed what happened after campaigns ended, or weeks after impressions were delivered. Those insights supported long-term planning but rarely influenced performance in the moment. That dynamic has changed. Today, marketers embed measurement directly into activation. Campaigns adapt while they run. Creative evolves based on engagement quality. Audience strategies adjust as verified outcomes come into view. Channel investments respond to performance signals, not assumptions. Connected ecosystems make this possible. Experian helps marketers plan, activate, and measure within a single framework by linking audiences, identity, and outcomes. When planning and performance live in the same environment, insight becomes actionable in the moment. Why is identity the connective layer between activation and measurement? Identity provides the consistent thread that links planning, activation, and outcomes into a unified system. Without it, marketers rely on proxy signals and disconnected views of performance. For years, fragmented identity frameworks made it difficult to connect media exposure to real-world outcomes. Without a consistent way to recognize audiences across planning, activation, and measurement, marketers relied on proxy metrics and modeled assumptions. That's changing as identity becomes interoperable across the ecosystem. Experian’s Digital and Offline Graphs help marketers onboard and resolve their data into a clean, connected foundation that supports everything that follows. From building audiences enriched with behavioral, demographic, and lifestyle insights, to activating those audiences across channels like connected TV (CTV), social, and programmatic through direct integrations with more than 200 platforms. When identity stays consistent from the first impression through final outcome, marketers gain a clearer view of what drives performance and where to act next. Our 2026 Digital trends and predictions report is available now and reveals five trends that will define 2026. From curation becoming the standard in programmatic to AI moving from hype to implementation, each trend reflects a shift toward more connected, data-driven marketing. The interplay between them will define how marketers will lead in 2026. Download How does closed-loop measurement become standard in 2026? Closed-loop measurement is becoming the default as activation and measurement come together. Marketers now tie exposure directly to verified business outcomes instead of relying on inferred signals. In partnership with MMGY Global, we helped Windstar Cruises connect digital impressions directly to bookings. The result was more than 6,500 verified bookings and $20 million in revenue tied back to campaign exposure. That translated to a 13:1 return on ad spend. Download the full case study here This level of accountability changes how marketers optimize. Instead of relying on clicks or inferred intent, teams can measure outcomes that reflect business impact. Store visits. Purchases. Site activity. These signals now guide decisions while campaigns are live. Through curated private marketplace deals and supply-path optimization, Experian also helps reduce cost, and improve reach and performance. With Experian and Audigent operating as one, marketers gain access to scalable, privacy-conscious data solutions that support both addressability and accountability across the supply chain. What should marketers plan for as activation and measurement connect in 2026? Marketing teams should prepare for an operating model built around continuous feedback, unified systems, and verified outcomes. This shift changes how success is defined and managed. Marketers should plan for: Always-on feedback loops Real-time signals guide creative, audience, and channel decisions while campaigns are in flight. Unified planning, activation, and outcome validation Integrated identity and audience frameworks allow marketers to trace value across every impression, not just the last click. Outcome-based performance signals Measurement will focus less on surface-level performance and more on true business impact, including sales, bookings, and long-term value. Greater use of first-party data Connected first-party data supports consistent activation and outcome validation across channels. Whether you're activating your own data or reaching new audiences, Experian connects every stage of the campaign. From early planners to last-minute buyers, we help you show up in the moments that matter and prove what is working. The takeaway Marketing's next chapter centers on connection. As data systems unify, activation and measurement operate as one. Insight flows directly into action. Decisions are guided by intelligence, not delayed reporting. With Experian, marketers plan, reach, and measure in a connected cycle. Every impression is measurable. Every audience is accurate. Every decision is powered by data ranked #1 in accuracy by Truthset. To explore this trend and the others shaping marketing in 2026, download our 2026 Digital trends and predictions report. Download Ready to connect with our team? About the author Ali Mack VP, AdTech Sales, Experian Ali Mack leads Experian’s AdTech business, overseeing global revenue across the company’s expansive tech and media portfolio. With over a decade of experience in digital and TV advertising, Ali drives strategic growth by aligning sales, customer success, and solutions teams to deliver impactful outcomes for clients and partners. She has successfully guided teams through two major acquisitions, integrating sales organizations and product portfolios into unified go-to-market strategies. Under her leadership, Experian has consistently exceeded revenue targets while fostering collaborative, results-driven teams and mentoring emerging leaders. Working closely with finance, product, and marketing, Ali develops strategies that support a diverse ecosystem of publishers, brands, and technology partners, positioning Experian at the forefront of data-driven advertising and identity resolution. FAQS How is marketing measurement shifting from post-campaign reporting to in-flight intelligence in 2026? Marketing measurement in 2026 is moving from retrospective reporting to real-time input that shapes campaigns while they run. Instead of explaining performance after delivery, measurement now guides creative, audience, and channel decisions as verified outcomes appear. Connected ecosystems make this possible. Experian helps marketers plan, activate, and measure within a single framework by linking audiences, identity, and outcomes. When planning and performance live in the same environment, insight becomes actionable in the moment. Why is identity the connective layer between activation and measurement? Identity provides the consistent thread that links planning, activation, and outcomes into a unified system. Without it, marketers rely on proxy signals and disconnected views of performance. Experian’s Digital and Offline Graphs help marketers onboard and resolve their data into a clean, connected foundation that supports everything that follows. From building audiences enriched with behavioral, demographic, and lifestyle insights, to activating those audiences across channels like connected TV (CTV), social, and programmatic through direct integrations with more than 200 platforms. How does closed-loop measurement become standard in 2026? Closed-loop measurement is becoming the default as activation and measurement come together. Marketers now tie exposure directly to verified business outcomes instead of relying on inferred signals. In partnership with MMGY Global, we helped Windstar Cruises connect digital impressions directly to bookings. The result was more than 6,500 verified bookings and $20 million in revenue tied back to campaign exposure. That translated to a 13:1 return on ad spend. What should marketers plan for as activation and measurement connect in 2026? Marketers should plan for: always-on feedback loops, unified planning, activation, and outcome validation, outcome-based performance signals, and greater use of first-party data. Whether you're activating your own data or reaching new audiences, Experian connects every stage of the campaign. From early planners to last-minute buyers, we help you show up in the moments that matter and prove what is working. Latest posts