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
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 $20 million in revenue tied back to campaign exposure. That translated to a 13:1 return on ad spend. What should marketers plan for as activation and measurement connect in 2026? Marketers should plan for: always-on feedback loops, unified planning, activation, and outcome validation, outcome-based performance signals, and greater use of first-party data. Whether you're activating your own data or reaching new audiences, Experian connects every stage of the campaign. From early planners to last-minute buyers, we help you show up in the moments that matter and prove what is working. Latest posts
Claritas, known for advanced consumer segmentation, is bringing its premium audiences into Experian Data Marketplace. PRIZM® Premier, P$YCLE® Premier, ConneXions® Premier and CultureCode® audiences are now available, giving marketers access to more than 1,700 syndicated segments in a frictionless, privacy-compliant way. Marketers can move from planning to activation faster, with lifestyle, and financial audiences built for modern media. The value of these insights is clear: richer, behavior-driven audience intelligence that supports more relevant targeting across connected TV (CTV), digital, and linear. How Claritas audiences are built Claritas audiences are built from more than 10,000 predictive behavioral indicators, robust survey linkages, and household-level demographic data. These inputs create deterministic, privacy-safe signals that go beyond broad demographic proxies and help reveal consumer intent. That detail matters in CTV and programmatic environments. Marketers can activate pre-modeled segments tied to automotive ownership, financial behaviors, telecom preferences, and brand affinities. Three ways Claritas audience support omnichannel activation High-fidelity signals for more effective targeting Claritas uses deterministic, behavior-based indicators to add context around lifestyle, purchase patterns, financial posture and technology behaviors. Each segment includes Living Unit ID (LUID) counts, CPM transparency, and match-rate details. Broad reach across channels Many segments include 30M–50M+ active LUIDs, supporting broad reach without sacrificing audience clarity. Activate these audiences in omnichannel campaigns across the destinations that matter most, including CTV, programmatic display/video, paid social, and email, enabled through integrations with major demand side platforms (DSPs) and activation platforms. Privacy-first design Claritas data is built from consented, privacy-safe inputs and does not rely on cookies or exposed personally identifiable information (PII). This approach supports cookieless media, including CTV. Where Experian adds lift to audience activation Experian's data marketplace and our identity and governance tools help operationalize Claritas segments for activation: Enhanced addressability: Deterministic identity resolution maps Claritas signals to reachable, active audiences. It utilizes Experian identity graphs, which are rooted in verified data, spanning 126 million U.S. households, 250 million individuals, and over four billion active digital identifiers. Activation: Integrations with major DSPs and media platforms support fast deployment. Governance: Our controls support responsible data handling through the activation workflow, and ensure available audiences comply to all federal, state, and local consumer privacy regulations. Together, Claritas segmentation depth and our identity resolution support audience planning, activation, and measurement at scale. How marketers use Claritas audiences Automotive: Connect with owners and intentenders A luxury automotive brand can target “Cadillac owners” or “Likely Luxury Intenders” using Claritas behavioral automotive indicators. With more than 42 million available LUIDs for Cadillac owners, original equipment manufacturers (OEM) can support CTV campaigns, conquest strategies, and multicultural initiatives with more confidence. Financial services: Reach high-value households Using P$YCLE® Premier, a card issuer can target consumers who actively use travel reward cards or who fall into specific wealth tiers. These insights help tailor offers, personalize messaging, and reach consumers more likely to convert, supported by Claritas’ AI-driven optimization that can increase conversions by up to 30%. The advantage: Claritas depth plus Experian scale Claritas audiences in Experian’s data marketplace give marketers a direct path from insight to activation. Claritas brings behavioral intelligence and segmentation depth and we bring identity, scale, and governance. Together, you can plan, activate, and measure campaigns with stronger audience clarity from day one. Contact us to get started FAQs What are Claritas audiences in Experian’s data marketplace? Claritas audiences are syndicated consumer segments built from behavioral, lifestyle, financial, and demographic data. Through Experian’s data marketplace, marketers can activate more than 1,700 Claritas segments using privacy-compliant, deterministic signals. Where can marketers activate Claritas audiences? Marketers can activate Claritas audiences directly through Experian’s data marketplace across CTV, programmatic display, social, email, and linear. Integrations with major DSPs and Experian identity resolution support privacy-compliant activation at scale. How are Claritas audiences built? Claritas audiences are built from more than 10,000 predictive behavioral indicators, survey-based insights, and household-level demographics. How does Experian support Claritas audience activation? Experian supports activation through identity resolution, governance controls, and direct platform integrations. Claritas signals are mapped to reachable audiences using the Experian identity graph. Latest posts
Why AI data governance determines trust in automated decisions AI is reshaping audience strategy, media investment, and measurement. Automated systems now make more decisions at scale and in real time. Trust in those decisions depends on the data that informs them. AI data governance provides the framework that allows organizations to answer foundational questions like: Which information or inputs guided this decision? Is the model respecting consumer rights? Could bias be influencing the outcome? If AI made the wrong call, how would we know? Without governed data, these questions remain unanswered. AI data governance creates accountability by establishing quality controls, consent validation and auditability before data enters automated systems. Most organizations are still building their readiness to govern data at scale. Many vendors highlight “fast insights” or “transparent reporting,” but few can support true data governance — the auditability, privacy-by-design, quality controls, and continuous compliance required for responsible AI. That foundation is where responsible automation begins. And it’s why trust in AI starts with data governance. Responsible automation begins with governed data Automation produces reliable outcomes only when data is accurate, current, consented and interoperable. AI data governance makes responsible automation possible by applying controls before data reaches models, workflows, or activation channels. AI systems may interpret context, predict signals, and act in real time. But no model, logic layer, or LLM can be responsible if the data feeding it isn’t governed responsibly from the start. This raises a core question: How do we ensure AI systems behave responsibly, at scale, across every channel and workflow? The answer begins with trust. And trust begins with AI data governance. Governing the data foundation for responsible AI Experian’s role in AI readiness begins at the data foundation. Our focus is on rigorously governing the data foundation so our clients have inputs they can trust. AI data governance at Experian includes: Model governance reviews before releasing new modeled attributes Feature-level checks ensuring no prohibited or sensitive signals are included Compliance-aware rebuilding and re-scoring, incorporating opt-outs and regulatory changes Validated delivery, ensuring attributes reflect the most current opt-outs, deletes, and compliance requirements By governing data at the source, we give our clients a transparent, accurate, and compliant starting point. Clients maintain responsibility for bias review within their own AI or LLM systems — but they can only perform those reviews effectively when the inputs are governed from the start. This is how AI data governance supports responsible automation downstream. 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 Privacy-by-design strengthens AI data governance Privacy gaps compound quickly when AI is involved. Once data enters automated workflows, errors or compliance issues become harder, and sometimes impossible, to correct. AI data governance addresses this risk through privacy-first design. Experian privacy-first AI data governance through: Consent-based, regulated identity resolution A signal-agnostic identity foundation that avoids exposing personal identifiers Ongoing validation and source verification before every refresh and delivery Compliance applied to each delivery, with opt-outs and deletes reflected immediately Governed attributes provided to clients, ensuring downstream applications remain compliant as data and regulations evolve Experian doesn’t govern our client’s AI. We govern the data their AI depends on, giving them confidence that what they load into any automated system meets the highest privacy and compliance standards. Good data isn’t just accurate or fresh. Good data is governed data. How AI data governance supports responsible automation at scale With AI data governance in place, organizations can build AI workflows that behave responsibly, predictably, and in alignment with compliance standards. Responsible automation emerges through four interconnected layers: 1. Input Privacy-first, governed data: accurate, consented, continuously updated, and compliant. 2. Enrichment Predictive and contextual insights built from governed data, ensuring downstream intelligence reflects current and compliant information. 3. Orchestration Reliable, AI-powered workflows where governed data inputs ensures consistency in audience selection, activation, and measurement at scale. 4. Guardrails Transparent, responsible innovation. Clients apply their own model governance, explainability, and oversight supported by the visibility they have into Experian’s governed inputs. Together, these layers show how data governance enables AI governance. AI integrity starts with AI data governance Automation is becoming widely accessible, but responsible AI still depends on governed data. Experian provides AI data governance to ensure the data that powers your AI workflows is accurate, compliant, consented, and refreshed with up-to-date opt-out and regulatory changes. That governance carries downstream, giving our clients confidence that their automated systems remain aligned with consumer expectations and regulatory requirements. We don’t build your AI. We enable it — by delivering the governed data it needs. Experian brings identity, insight, and privacy-first governance together to help marketers reach people with relevance, respect, and simplicity. Responsible AI starts with responsible data. AI data governance is the foundation that supports everything that follows. Get started About the author Jeremy Meade VP, Marketing Data Product & Operations, Experian Jeremy Meade is VP, Marketing Data Product & Operations at Experian Marketing Services. With over 15 years of experience in marketing data, Jeremy has consistently led data product, engineering, and analytics functions. He has also played a pivotal role in spearheading the implementation of policies and procedures to ensure compliance with state privacy regulations at two industry-leading companies. FAQs about AI data governance What is AI data governance? AI data governance is the framework that manages data quality, consent, compliance and auditability before data enters AI systems. Why does AI data governance matter? AI decisions reflect the data used as inputs. Governance provides transparency, accountability and trust in automated outcomes. Does AI data governance prevent bias? AI data governance does not eliminate bias in models. It provides governed inputs that allow organizations to identify and address bias more effectively. How does privacy-first design support AI data governance? Privacy-first governance applies consent validation and compliance controls before data is activated, reducing downstream risk. Who is responsible for AI governance? Organizations govern their AI systems. Data providers govern the data foundation that feeds those systems. Latest posts