All posts by Aimee Irwin, VP of Strategy

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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

Published: January 28, 2026 by Scott Kozub, VP, Product Management

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

Published: January 27, 2026 by Ali Mack, VP, AdTech Sales

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

Published: January 22, 2026 by Experian Marketing Services

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

Published: January 14, 2026 by Jeremy Meade, VP, Marketing Data Product & Operations

A decade ago, you could buy media by broad categories and call it a day. But today, your audience lives in a curated world. They watch what they want, skip what they don’t, and expect what they see to match their interests. Research shows that when ads are tailored to households, people pay more attention, stay engaged longer, and are more likely to remember your ads. That shift in expectations is why addressable advertising continues to grow. It’s a practical response to how media works today, with audiences moving fluidly across platforms, streaming spread across services, and measurement spanning screens and environments. Under these conditions, reaching the right people depends on clarity, not approximation. Artificial intelligence (AI) strengthens that clarity. When applied responsibly, AI helps connect signals, deepen audience understanding, and deliver relevant messages while protecting consumer data. The result is advertising that feels more human, not less. What is addressable advertising? Addressable advertising is the ability to deliver personalized ads to specific individuals or households and measure results using privacy-safe data and identity.  It works across digital, connected TV (CTV), linear TV, and over-the-top (OTT) streaming and relies on strong identity resolution and accurate data inputs to ensure your audience definitions remain consistent across channels and over time. Benefits of addressable advertising Addressable advertising changes how advertising performs by delivering messages to defined audiences, reducing wasted impressions, and making results simpler to measure. BenefitWhat it means for youClarityReach the right audience with the personalized messages they want, instead of hoping the right people are watchingEfficiencyAvoid wasted impressions by focusing spend where interest already existsHigher ROIImprove conversion by delivering messages that feel relevantOmnichannel consistencyCarry the same message across digital and TV without starting overMeasurable impactConnect exposure to actions so performance is clearPrivacy and complianceActivate audiences responsibly using privacy-safe data, clear governance, and compliant practices These are some of the reasons that addressable advertising has moved from a niche tactic to a core strategy. When audiences are clear, identity is connected, and measurement is built in, advertising becomes relevant, accountable, and easy to improve over time. Addressable advertising vs. traditional advertising Unlike traditional advertising, addressable advertising doesn’t depend on broad exposure or assumptions. It’s personalized by design and measurable by default, making it possible to connect ad exposure to outcomes. Another distinction is in how addressable delivers advertising to audiences and how performance is measured. Traditional media buysAddressable advertising buysYou pay for broad reachYou pay for relevant reach to defined audiencesAds run by placement or programAds are delivered to known households or individualsPersonalization is limitedPersonalization is built into deliveryMeasurement indicates trends, not who actually actedMeasurement connects exposure to actions by linking ads to defined audiences across channels But before you can activate addressable advertising, you need to understand who you’re actually trying to reach. What is an addressable audience? An addressable audience is a group of people you can identify and reach using data-based targeting. In other words, they’re not anonymous “maybe” viewers. They’re a defined audience you can activate across channels. Here’s what typically builds addressable audiences: FactorWhat it isWhy it mattersFirst-party dataData from your own relationships (site activity, app activity, CRM, emails, purchases)It’s your most direct view of existing customers and prospectsThird-party household and individual dataDemographic, behavioral, lifestyle, interest, and intent attributes from trusted providersIt fills gaps so your audience definitions don’t collapse when your own data is limitedIdentity resolutionA privacy-first way to match people across devices, households, and channelsIt improves accuracy so you don’t over-message the same people or miss them entirelyContextual signalsPage-level, content, or viewing context where ads appearIt reinforces relevance in the moment and complements addressable targeting when identity signals are limited How Experian helps with addressable audiences Experian helps you build and activate addressable audiences at scale without losing accuracy or trust. With more than 3,500 syndicated audiences available, you can activate consistently across 200+ destinations — including social platforms like Meta and Pinterest, TV and programmatic environments, and private marketplaces (PMPs) through Audigent. That means reaching people based on who they are, where they live, and their household makeup, using data governed with care. Our approach is built on accuracy first, which is why Experian data is ranked #1 in accuracy by Truthset for key demographic attributes. And when standard customer segments aren’t enough, Experian Partner Audiences expand what’s possible. These unique audiences are available through Experian’s data marketplace, within Audigent for PMP activation, and directly on platforms like DIRECTV, Dish, Magnite, OpenAP, and The Trade Desk. The evolution of addressability and why it matters more than ever As the media ecosystem shifts, reaching people across browsers, apps, CTV, and streaming platforms has become more complex. Signals are fragmenting everywhere as expectations for relevant, personalized experiences continue to rise, while reliable identifiers become increasingly challenging to access. In response, addressability is shifting from a channel-specific tactic to an identity-driven approach to reach and measure defined audiences across screens. That evolution puts new pressure on performance. Marketing budgets require accuracy and accountability, which means targeting must deliver measurable reach and outcomes you can trust. At the same time, the growth of CTV and streaming is expanding addressable TV opportunities. As CTV inventory grows, so does the need for cross-channel, identity-based activation that works consistently and supports reach, frequency, and measurement in one connected view. That’s why identity has become the foundation for making addressable advertising work today. When to apply addressable advertising You don’t need addressable for everything, but it shines when you need your spend to go farther with accurate targeting and resonant messaging. ScenarioWhy addressable helpsProduct launches and seasonal pushesReach people who are more likely to care without flooding everyone elseHigh-consideration purchases (auto, travel, financial services)Focus on likely intent and suppress audiences that don’t fitCross-channel campaigns (digital, TV, mobile)Keep messaging consistent across screensWhen using first-party data with AIUse AI customer segmentation to scale responsibly and improve performance without sacrificing accuracyRegulated categoriesRely on compliant data practices and clearer controls for regulated industries Addressable advertising is one way to put relevance and respect into practice — but it shouldn’t be the only time these principles apply. Marketers are expected to be thoughtful about who they reach, how often they show up, and how data is used across every channel. Addressable simply makes it easier to live up to that standard when accuracy, accountability, and scale matter most. Addressable advertising and third-party data There’s a common misconception that third-party data is no longer useful, but what’s really changed is the environment around it. In the early days of digital advertising, third-party data often felt like the Wild West. Today, modern third-party data is more transparent, better governed, and held to far higher standards with: Clear data sourcing Documented consent practices Regular quality audits Strict limits on how data can be used Used responsibly, third-party data plays a critical role in addressable advertising by complementing your first-party data and keeping audience strategies flexible as signals change. Benefits of third-party data When paired with identity resolution, high-quality third-party data helps you: Fill first-party gaps: Add demographic, behavioral, and interest-based insight when your own data is limited. Expand prospecting: Reach new audiences through modeling and lookalike expansion. Enrich segmentation: Combine household, behavioral, and interest signals to tailor creative, offers, and messaging to interests for more accurate and personalized activation. Support cross-channel addressability: Maintain consistent audience reach across devices and channels even as individual signals change. Why work with Experian for your data needs? At Experian, we approach third-party data with the belief that trust comes first. Our data is privacy-compliant, ethically sourced, and governed by strict standards so you can use it confidently. Accuracy matters just as much. Our identity and data-quality framework verifies that the data behind your audiences holds up in the real world — a key reason Experian is ranked #1 by Truthset for key demographic attributes. And because addressable advertising only delivers value when audiences move seamlessly from planning to activation, our audiences are interoperable by design. You can activate them across digital, social, and CTV platforms without rebuilding or reformatting your strategy for each channel. How AI is redefining customer segmentation Addressable advertising depends on audiences that stay accurate as people move across devices, platforms, and moments. Traditional segmentation built on static rules and snapshots in time can’t keep up with that reality. AI customer segmentation analyzes massive sets of household and individual data (such as intent, household demographics, purchase behavior, and content consumption) to identify patterns, predict intent, and group people into addressable audiences. As the AI advertising ecosystem continues to mature, reflected in industry frameworks like the LUMA AI Lumascape, segmentation and identity have become foundational layers rather than standalone tools. Those audiences update as conditions change, so they stay relevant instead of aging out. Here’s how AI-driven segmentation supports addressable advertising. What AI enablesWhy it mattersPredictive, intent-based audiencesAnalyze behavioral and transactional data to group people based on likely next actionsBroader audience availabilityAs more data signals are incorporated responsibly, AI makes it possible to support a wider range of addressable audience options without sacrificing accuracyDeeper insights from dataDiscover what people care about, how intent is forming, and which signals are most important with larger, more diverse data setsReal-time audience updatesKeep segments aligned as behaviors change, not weeks laterHigher accuracy, less guessworkRely on data-driven patterns for decision-making instead of assumptionsOngoing optimizationRefine audiences throughout the campaign lifecycle as performance signals come in We’ve used machine learning and analytics for decades to support responsible segmentation — balancing performance with privacy and transparency. That foundation now supports addressable advertising that adapts in real time while staying grounded in trust. Addressable TV: Targeting in the streaming era TV has become an addressable channel powered by data and identity resolution. CTV and OTT streaming are booming, while linear TV continues to decline, reshaping how people watch and how advertising works alongside it. For the first time, CTV spending is expected to outpace traditional TV ad spending in 2028, reaching $46.89 billion and signaling that addressable TV is now central to the media mix. With CTV and OTT platforms, advertising can now be delivered at the household level. That means two homes watching the same show can see different ads based on who lives there and what they like. This is what makes addressable TV possible. Benefits of addressable TV As streaming inventory continues to grow, addressable TV creates new ways to bring relevance and accountability to a channel once defined by broad exposure. Experian links identity data across streaming, linear, and digital platforms to help you manage frequency, attribution, and household-level insights in one connected view. Addressable TV also raises the bar. To manage reach, frequency, and measurement across streaming and linear environments, addressable TV depends on identity resolution that connects households across screens. Here’s how addressable TV helps you when identity is in place. What addressable TV enablesWhy it mattersHousehold-level targetingDeliver messages that reflect who’s watching, not just what’s onFrequency control across screensReduce overexposure and improve viewer experienceCross-channel measurement and attributionConnect TV exposure to digital actions, site visits, and conversionsMore efficient use of TV spendBring accuracy, accountability, and outcome-based insight to premium inventory and improve reach of streaming-first, harder-to-reach viewer segments Ultimately, addressable TV isn’t a replacement for linear TV, but it is an evolution. As streaming becomes the default viewing experience, the ability to engage TV audiences with the same care and clarity as digital is essential. Use cases for addressable advertising Addressable advertising works across industries because it adapts to how people make decisions. The examples below are illustrative scenarios that show how addressable audiences, identity resolution, and AI-driven segmentation can come together in practice using Experian solutions. Retail: Seasonal promotions A home décor retailer could use identity resolution and AI-driven segmentation to build addressable audiences, such as holiday decorators and recent movers, who are more likely to engage during peak seasonal periods. Campaigns could then be activated across CTV, display, and social, helping the retailer stay visible across screens while tailoring creative to seasonal intent. Automotive: In-market car buyers An auto brand might identify consumers nearing lease expiration using automotive-specific data tied to household and individual attributes. By suppressing current owners, the brand could avoid wasted impressions and activate addressable audiences across OTT and mobile to reach likely buyers during active consideration. Financial services: Credit card launch For a new credit card launch, a national bank could use modeled financial segments to reach credit-qualified prospects. Addressable digital advertising campaigns could apply frequency controls and personalized messaging, balancing reach with relevance while seamlessly measuring response. Streaming media: New subscriber growth A streaming platform looking to grow subscriptions could use an identity graph to exclude current subscribers. Likely viewers could then be targeted across CTV based on content preferences and viewing behavior, keeping spend focused on net-new growth. Media and entertainment: Audience expansion for a new release Ahead of a new release, a film studio could use behavioral and lifestyle data to identify likely moviegoers and fans of similar franchises. Addressable campaigns across CTV and digital video could help drive awareness and opening weekend attendance. Travel: High-value traveler acquisition A travel brand could use travel propensity data and household-level demographics to identify frequent flyers and family vacation planners. Personalized offers could then be activated across display, social, and programmatic channels to increase bookings while keeping spend focused on higher-value travelers. How Experian enables more effective addressable campaigns Addressable advertising is most effective when identity, data, and activation are connected from the start. Experian brings trusted household and individual data, privacy-first identity resolution, and broad activation partnerships together so you can move from audience insights to activation with minimal friction. Here’s how that comes to life across our core offerings. Identity resolution with Consumer Sync Consumer Sync connects devices, emails, digital identifiers, and offline data into a single, privacy-safe identity foundation. This connection helps your audiences stay consistent across streaming, linear TV, mobile, and digital despite changing signals. Audience insight and segmentation with Consumer View Consumer View supports clear segmentation, prospecting, and enrichment across industries. It combines demographic, behavioral, and interest-based data to help you build accurate, intent-driven audiences that reflect real people, not assumptions. Data is continuously updated and governed for accuracy. Omnichannel activation with Audience Engine Audience Engine enables direct activation of Experian audiences across CTV, digital, social, and programmatic platforms. It supports suppression, frequency management, and cross-channel consistency to keep messaging aligned and exposure controlled. More efficient media through curation and Curated Deals Curation combines data, identity, and inventory through Experian Curated Deals. These deal IDs, available off-the-shelf or privately, make it easier to activate high-quality audiences and premium inventory in the platforms you already use without custom setup. AI-enhanced segmentation and optimization Our AI-enhanced models analyze large data sets to create and refresh addressable audiences in real time, supporting intent-based targeting and ongoing optimization throughout the campaign lifecycle. These models work seamlessly with demand-side platforms (DSPs), ad platforms, and data clean rooms, so audience insights flow directly into activation and measurement without added complexity. Seamless integration with your ecosystem As an advertiser, you want addressable advertising to fit naturally into how you already plan and buy media. That’s why integration matters as much as insight. Experian integrates with leading DSPs, ad platforms, and data clean rooms, so you can activate addressable audiences in the environments you already use without reworking your strategy or adding complexity. This approach helps you: Build and activate addressable audiences: Reach the people you want with accuracy and respect. Activate across channels: Keep messaging consistent across digital, TV, and streaming. Optimize with data ranked #1 in accuracy by Truthset: Improve performance using the industry’s most reliable data. When identity, data, AI, and activation come together, addressable advertising does what it’s supposed to do: deliver relevance naturally, measure impact clearly, and give you confidence in every decision along the way. That’s the foundation for campaigns people want to engage with. Start creating campaigns audiences want to see Experian can help you apply addressable advertising in ways that respect consumers, perform across channels, and stand up to real-world measurement. Connect with our experts today to explore how addressable audiences, AI-driven segmentation, and identity-powered activation can work together in support of your goals. FAQs about addressable advertising What is addressable advertising? Addressable data-driven advertising involves delivering personalized ads to specific individuals or households using privacy-safe data and identity. What is an addressable audience? An addressable audience is a defined group of consumers you can identify and reach based on known household or individual attributes. What makes advertising addressable? Advertising becomes addressable when it’s possible to identify the audience by linking devices and households to people through identity graphs. This allows you to measure ad performance at the audience level and provide more personalized advertising. Is addressable advertising just for TV? Addressable advertising isn’t just for TV; it also works across digital, mobile, streaming, and social channels. How does AI help addressable advertising? AI improves addressable advertising by analyzing large data sets to predict intent, build more accurate audiences, boost performance over time, and improve your ability to find and build your audiences. Can addressable advertising work without cookies? Yes — identity resolution and first-party data are key to cookieless addressability. How does Experian support addressable advertising? Experian supports addressable advertising by providing trusted consumer data, privacy-centric identity resolution, and curated audience segments that activate across CTV, digital, mobile, and streaming platforms. Latest posts

Published: January 13, 2026 by Experian Marketing Services

Year after year, CES signals where marketing is headed next. In 2026, the message was clear. Progress comes from connecting data, intelligence, and outcomes with discipline, not spectacle. Across AI, programmatic media, and measurement, the same priorities surfaced again and again. Under the bright lights of Las Vegas, three themes cut through, and each one pointed to a future where data, intelligence, and outcomes move in lockstep. Here are the three themes that defined CES 2026. 1. Agentic AI proved that it’s only as good as its data inputs AI was once again the star of the show. At CES 2026, marketers focused less on demos and more on proof that AI improves decisions, reduces friction, and drives outcomes. Every credible use case traced back to accurate, privacy-first data. What changed at CES was how that intelligence is being applied. Agentic AI systems designed to act autonomously are moving beyond insights and into execution. From media buying to optimization, these agents are increasingly expected to make decisions at speed and scale. That shift raises the stakes for data quality. When AI is operating campaigns, not just informing them, accuracy and privacy are non-negotiable. “This year's CES made agency priorities crystal clear. Efficiency, differentiation, and outcomes. As agentic AI takes on more responsibility across planning, activation, and measurement, Experian gives agencies a robust data and identity foundation they can trust to own the outcome for every client.”Greg Williams, Chief Operating Officer Without accurate, privacy-compliant data, AI agents struggle to reflect real behavior or support responsible personalization. A reliable, privacy-first data foundation is what turns AI from an interesting experiment into an operational advantage. That advantage gets even stronger when it’s anchored in an identity graph that understands people and households across channels. When identity and intelligence move together, AI becomes more accurate, accountable, and effective at driving outcomes. In an AI first world, the strongest signal isn't scale. It's data quality. 2. Curation goes mainstream Curation is no longer experimental. At CES, it showed up as a mandated capability for buyers and sellers navigating fragmented signals and complex supply paths. Marketers want intentional media buys they can explain, defend, and repeat. AI is accelerating this shift. As AI systems take on more responsibility for planning, packaging, and optimization, curation provides the guardrails. It defines what “good” looks like (premium supply, trusted data, and clear performance goals), and allows AI to operate within those constraints driving the optimal outcomes for marketers. “Our sell-side clients walked into CES asking how to stand out in a crowded landscape. The answer kept coming back to data-driven curation. With Experian Audiences and Curated Deals, SSPs and publishers can improve targeting within PMPs, package inventory more intelligently, and prove value with confidence. As we head into 2026, data is no longer a supporting input. It needs to be at the center of every conversation.”Chris Meredith, Head of Sell-Side Rather than maximizing inventory access, curation prioritizes control, transparency, and performance. Buyers want premium supply aligned to specific goals. Sellers want clearer paths to demand. They can play the odds or own the outcome. When data leads, they own it. When curation is powered by high-fidelity audiences and a connected identity framework, it becomes even stronger. That’s what allows curated deals to deliver clarity, confidence, and repeatable performance. This shift reflects a broader move away from probability-based buying toward outcome ownership, where AI-driven systems are measured not on activity, but on results. 3. Activation and measurement finally shared the same stage Activation and measurement are now coming together around shared data and identity. CES 2026 marked a turning point where closing the loop felt achievable, not aspirational. Both the buy-side and sell-side face pressure to show that media investment drives outcomes. Agentic AI was a quiet driver of this optimism. As AI agents increasingly manage activation decisions in real time, marketers need measurement systems that can keep up. That requires a shared data and identity foundation. One that allows AI-driven actions to be evaluated against outcomes consistently, across channels and partners. In healthcare, accuracy is everything. Our clients need to reach patients and healthcare professionals in ways that respect privacy while driving meaningful outcomes. CES underscored that privacy, identity, and measurement must work in harmony. That’s how health marketers reduce risk and increase the likelihood that every message leads to better care.Sheila Wirick, Sales Director, Health Achieving that requires a consistent identity spine that connects planning, activation, and outcomes across channels. And that spine is strongest when it’s built on accurate, privacy-first data and audiences that understand people and households. That connection allows marketers to move beyond proxy metrics and evaluate performance based on tangible results. When campaigns and measurement rely on the same data foundation, AI-driven platforms can optimize toward outcomes such as new customers, account growth, or in-store activity, not just delivery metrics. That’s the connective layer that turns disconnected touch points into a measurable, outcomes-based system. 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 now Three takeaways from CES 2026 AI is maturing, but only for teams with accurate, connected, privacy-first data that AI agents can act on responsibly. Curation is scaling, giving both humans and AI systems clearer paths to quality, control, and differentiation. Activation and measurement are aligning, allowing AI-driven decisions to be judged on outcomes, not assumptions. We’re building for that world today. One where agentic AI operates on a trusted data and identity foundation, curation defines the rules, and outcomes determine success. With the right foundation and the deep data inputs, you can move faster, reduce risk, and let intelligence (human and artificial) work together to deliver results that last long after the neon lights fade. Connect with us FAQs What was the biggest shift discussed at CES 2026 for marketers? The biggest shift was the move from hype to accountability. Marketers focused on data quality, intentional media buying, and outcome-based measurement rather than experimental technology. Why did AI discussions emphasize privacy-first data? Privacy-first data supports accuracy, compliance, and trust. AI models built on unreliable or opaque data struggle to reflect real consumer behavior and create risk for brands. At Experian, privacy and compliance are built in. Every data signal, attribute, audience, and partner goes through our rigorous review process to meet federal, state, and local consumer privacy laws. With decades of experience in highly regulated industries, we’ve built processes that emphasize risk mitigation, transparency, and accountability. How does curation help reduce programmatic complexity? Curation simplifies buying by pairing premium inventory with specific audience and performance goals. This approach reduces waste and creates clearer, more repeatable buying paths. With the acquisition of Audigent, Experian is now more than just a premier data provider. We’re also a full-service curation partner. Together, we deliver end-to-end programmatic curation across data, inventory, and optimization, helping brands and publishers unlock smarter, more scalable media strategies. What does it mean to align activation and measurement? It means using the same identity and data foundation to plan campaigns and evaluate results. This alignment allows marketers to measure success based on business outcomes, not just delivery metrics. With Experian, marketers can 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. Why is identity central to all three CES themes? Identity connects data across channels and stages of the customer journey. It enables accurate AI, effective curation, and consistent measurement within one system. Experian delivers identity resolution at the scale, accuracy, and compliance required by the world’s largest enterprises. Our solutions are:- Built on trust: Backed by 40+ years as a regulated data steward and rated #1 in data accuracy by Truthset, so you can act with confidence.- Powered by our proprietary AI-enhanced identity graph: Combining breadth, accuracy, and recency across four billion identifiers, continuously refined by machine learning for maximum accuracy.- Seamlessly connected: Pre-built data integration with leading CDPs, DSPs, and MarTech platforms for faster time to value.- Always up to date: Frequent enrichment and near-real-time identity resolution through Activity Feed for timely personalization and more responsive customer engagement.- Privacy-first by design: Compliance with GLBA, FCRA, and emerging state regulations baked in at every step, supported by rigorous partner vetting. Latest posts

Published: January 12, 2026 by Experian Marketing Services

Why an identity framework matters more than any single identifier The challenge facing marketers today isn't a single identifier on a deprecation timeline; it’s the increasing fragmentation of signals and identifiers across browsers, devices, apps, and platforms. This shift introduces complexity into how audiences are reached and measured, as signals behave differently in every environment, and it becomes more complex to piece together a complete view of the consumer. Each environment contributes to its own set of visibility gaps, making identity less predictable and more uneven. The result is a patchwork of inconsistent identity signals rather than a single, predictable decline. While you can’t control how platforms evolve, you can control how you respond to fragmentation. The future won’t be defined by the loss of any single identifier, but by your ability to unify, interpret, and activate the many signals that remain. Marketers who adopt a flexible, identity framework will be best positioned to create consistency in an otherwise fragmented landscape. At Experian, we believe flexibility starts with intelligence. For decades, we’ve used AI and machine learning to help marketers understand people’s behavior more clearly, respect their privacy, and deliver messages that drive business outcomes. Our technology brings identity, insight, and intelligence together, so even as the number of signals grows and becomes more varied across environments, marketers can reach the right people with relevance, respect, and simplicity. This intelligence acts as the connective tissue across fragmented ecosystems, ensuring marketers can recognize and reach audiences consistently wherever they appear. What forces are driving fragmentation in identity and signals? Changes to traditional IDs Since Apple introduced App Tracking Transparency (ATT), access to the Identifier for Advertisers (IDFA) has become inconsistent across apps and devices. Google’s evolving Android privacy roadmap adds another layer of variability, fragmenting mobile addressability. Safari and Firefox have long restricted third-party cookies, while Chrome continues to support them for now. This creates different signal availability across browsers, contributing to an uneven and increasingly fragmented identity landscape on the open web. Shifts in signals IPv4 to IPv6 migration introduces mismatched identity structures that complicate continuity across environments. Platform-driven fragmentation Closed ecosystems and uneven adoption of evolving RTB standards (like OpenRTB 2.6 updates designed to support new identifiers and consent signals) create differences in which identifiers and consent signals are shared in the bidstream. At the same time, the rise of alternative or “universal” IDs—often developed by individual platforms, publishers, or technology companies—means that multiple ID types can appear within the same auction, each with its own structure, rules, and level of support. These differences reduce interoperability across platforms and contribute to a more fragmented activation landscape. Each change creates an identity silo. Together, they form an ecosystem defined by fragmentation rather than absence. Without an identity framework, these environments operate as disconnected identity islands. A multi-ID world requires a unified identity framework Alternative IDs play an important role, but they also expand the number of signals marketers must reconcile. Without a consistent identity layer, more IDs often mean more complexity—not more clarity. Common alternative IDs in use today: UID2: The Trade Desk’s Unified I.D. 2.0, an iteration of their original Unified ID 1.0, which was still reliant on third-party cookies, creates persistent IDs with user-provided email addresses and phone numbers. ID5: This independent identity provider builds an identity infrastructure that powers addressable advertising across channels. It can create an ID based on both deterministic and probabilistic data. Hadron ID: Hadron ID is a unique, interoperable identity system (including first-party, audience-based, contextual, deterministic, and probabilistic) developed by Audigent, now part of Experian, to drive revenue for publishers by making their audience data and inventory actionable for media buyers. Industry reports suggest roughly one-third to two-fifths of open-auction traffic carries alternative IDs, sometimes multiple per request. Among Experian clients, adoption of alternative IDs rose 50% year over year, with a 30% increase in IDs resolved to individuals via our Digital Graph. Identity isn’t disappearing; it’s multiplying. A modern identity framework resolves these identifiers into a single, privacy-safe consumer view. Why CTV makes an identity framework essential Beyond alternative IDs, device-level identifiers also play a major role in today’s ecosystem and add to the fragmentation marketers must navigate. Connected TV (CTV) environments introduce additional fragmentation. CTV IDs A CTV ID is an identifier used to deliver, target, and measure ads on CTV devices, including smart TVs, streaming devices, gaming consoles, and more. Unlike MAIDs, which act as universal device identifiers across apps, CTV environments often generate multiple, platform-specific IDs for the same physical device. Different operating systems, publishers, or streaming platforms may each assign their own identifier—such as Roku ID for Advertisers, Amazon Fire Advertising ID, Samsung TIFA, or Apple IDFA for CTV. As a result, a single household or TV can appear under several distinct IDs, making cross-app or cross-platform recognition more complex and further reinforcing the need for a unified identity framework. Experian’s identity framework is powered by predictive and generative intelligence that makes resolution faster and more human-centered. Our AI models fill gaps where data signals are missing, infer behaviors responsibly, and continuously optimize for accuracy, so marketers can personalize ads responsibly, even in a fragmented ecosystem. More importantly, our framework normalizes signals across disconnected environments, creating a consistent identity spine that follows the consumer through their fragmented digital journey. An identity framework connects online and offline signals Fragmentation extends beyond digital environments. Marketers manage offline data from in-store transactions, loyalty programs, household identifiers, and phone numbers that rarely align cleanly with digital signals. As consumers move between online and offline touch points, an identity framework connects these signals into a coherent view of the individual. This foundation allows marketers to recognize the same consumer across environments that expose different identifiers. Four keys to future-proofing your media with an identity framework 1. Know your customer: Unify and enrich your first-party data First-party data is a marketer’s most durable asset, but it’s often scattered and incomplete. Unify it: Bring CRM records, site interactions, and loyalty data into a single platform to build a holistic customer view. Use Offline Identity Resolution to resolve your first-party offline personally identifiable information (PII) back to a consolidated consumer profile, removing duplication of users in your data set. Enrich it: Append Experian Marketing Attributes to uncover demographics, lifestyle markers, and purchase behaviors you can’t see on your own, and use Offline Identity Append to fill in missing offline data points (such as name, address, phone, etc.) to create a more complete and actionable customer profile. This gives you richer profiles that drive more personalized targeting and messaging. Fragmented ecosystems make unified first-party data even more essential. A connected view allows marketers to anchor identity against a stable, proprietary foundation. As identifiers vary across environments, marketers need flexible, privacy-first ways to understand where their audiences are and how to reach them. 2. Find your customer: Expand how you discover and reach audiences in a fragmented landscape As identifiers vary across environments, marketers need flexible, privacy-first ways to understand where their audiences are and how to reach them. Contextual signals: Experian’s Contextually-Indexed Audiences map content to consumer insights, so you can target intent-rich environments. Geographic insights: Our Geo-Indexed Audiences help you find regions that over-index for specific traits and activate them across your preferred platforms. Syndicated and Partner Audiences: Choose from 3,500+ prebuilt segments or 30+ partner data sources spanning health, retail, travel, and more. Curation: As a full-service curation partner, we enable private marketplace (PMP) deals that are privacy-safe, identity-agnostic, and performance-optimized. Together, these approaches help you confidently reach your audiences - using multiple types of signals that complement your identity strategy and create a clearer picture across fragmented environments. 3. Reach your customer: Maximize scale through interoperability As signals and identifiers proliferate across environments, interoperability is essential to maintain consistent reach. Experian’s Offline and Digital Graphs unify disparate signals (MAIDs, CTV IDs, alternative IDs, IP, and more) so marketers can recognize and engage audiences reliably across channels, devices, and platforms. Interoperability matters because it turns a collection of disconnected identifiers into a coherent identity framework that can actually be activated. The following capabilities demonstrate how that comes to life. Unified identity: Create a consistent view of your audience, even when different environments expose different identifiers. Experian’s identity framework connects these signals into a single, actionable identity spine. Expanded reach: OpenX enriched its supply-side identity graph with Experian’s audiences, making our data available directly across OpenX supply and formats. By matching more of the starting audience and identifying more users in the bidstream, marketers see higher match and activation rates, extending reach in hard-to-address environments like Safari and mobile web. Measure success: Optimize based on outcomes If you can't measure your marketing, you can't improve it. Experian Outcomes, powered by our holistic understanding of the user across online and offline touch points, closes the loop by connecting media exposures to real-world actions (store visits, purchases, or site conversions). With these insights, you can: Prove ROI across digital and TV Attribute success to the right channels and tactics Continuously refine targeting, creative, and spend allocation Outcome-based measurement makes your strategy adaptive, so dollars flow to what drives results. As signals multiply across environments, connecting exposures to outcomes requires a unified identity foundation. Experian closes the loop by unifying exposures across disconnected touch points, enabling holistic attribution and optimization. Our AI-powered simplicity drives continuous improvement. From predictive modeling to agentic workflows that automate optimization, we’re investing in generative AI to help marketers spend less time on manual setup and more time on strategy and outcomes. The Experian identity framework advantage Experian connects fragmented signals into a single, actionable identity framework built for long-term resilience. What our identity framework delivers Interoperability: We support all major identifiers, including alternative IDs, IP address (v4 and v6), contextual signals, and both first- and third-party data. Flexibility: Whether you’re activating syndicated audiences, tapping into partner audiences from 30+ data providers, or curating custom segments through Audigent, our solutions meet you where you are. Scale: With four billion IDs resolved in our Digital Graph and 280 million telephones in our Offline Graph, we deliver unmatched reach across digital and offline environments. AI that makes marketing more human: We bring together identity, insight, and automation through responsible AI, helping marketers see audiences clearly, act with intelligence, and optimize with respect for privacy. Our approach is delivering results across a range of programmatic players. These outcomes demonstrate how a unified identity framework delivers performance in environments where signals, identifiers, and devices operate in silos. Proven results powered by Experian’s identity framework Sonobi increased programmatic addressability across the mobile web by 25% and delivered a 20% lift in impression value through our identity graph, driving stronger campaign connections and greater publisher returns. One DSP used our Digital Graph to match more MAIDs, CTV IDs, and IP addresses to online conversions, enabling increased accuracy of their attribution and measurement. They achieved an 84% synced ID rate and a 9% increase in match rate. For Cuebiq, we significantly increased match rates and resolved data from cookieless environments, such as Safari. By combining separate data streams and resolving 85% of total events to a household, Cuebiq expanded on the household IDs to identify MAIDs that are observed in-store, enabling accurate cross-channel measurement. Our Digital Graph allowed MiQ and their clients to expand the reach of their seed audiences across devices by 51% and cookieless IDs by 64%. As a result, MiQ can provide marketers with future-proofed connected planning, advanced targeting, and precise measurement. We’re your partner in building identity framework that lasts: resilient to change, adaptive to new signals, and focused on outcomes. What comes next for signals and identity? The future isn’t defined by any single identifier. It’s defined by the ability to unify and activate across a fragmented identity ecosystem. The winners will be those who adopt interoperable, outcome-driven identity frameworks today. Those strategies will increasingly be powered by responsible AI, systems that simplify workflows, predict opportunity, and optimize in real time while keeping people at the center. At Experian, we see AI not as automation for its own sake, but as a way to make marketing more human, relevant, and respectful. Your playbook for navigating fragmentation Experian connects the fragmented identity ecosystem, unifying alternative IDs, IP signals, contextual data, and first- and third-party assets into a consistent, actionable identity foundation. With proven lift across partners like Sonobi and new offerings like Contextually-Indexed Audiences, we help you build campaigns that perform in a fragmented landscape. Download our 2026 Digital trends and predictions report to explore how identity, interoperability, and measurement will define the future of advertising. Download About the author Henry Schenker Group Product Manager, Experian Henry has nearly 15 years of experience in Digital Advertising, Social Media Marketing, Data Licensing & Analytics, Front-End Engineering, Technical Architecture & Integrations, Profit & Loss Management, and Enterprise-Level Contract Negotiation across the U.S., EMEA, and Asia Pacific regions. Prior to re-joining Experian, Henry held critical go-to-market and product roles at noted industry-disruptors Media.Monks and Attain. From 2018 - 2020, he served as the Vice President, APAC of Innovid (now publicly traded, NYSE:CTV), leading the company's expansion into Japan, Singapore, and Australia. The preceding 4 years with Tapad (acquired by Experian), allowed Henry to become a seasoned Sales Engineer, grow and lead a global Technical Integrations team, and relocate to Singapore, leading sales and operations in the APAC region. Before beginning his career and learning front-end engineering on-the-job at Wyng (formerly Offerpop), Henry received a dual-major (BA/BS) in Sociology and Economics & Finance from Bard College in New York. FAQs Why is signal and identity fragmentation increasing across digital and offline channels? Signal and identity fragmentation is increasing across digital and offline channels because consumers now engage across more devices, platforms, and environments. Each environment introduces its own identifiers and privacy rules. This growth creates more signals overall, which increases the need for unification rather than reliance on a single ID. How should marketers think about alternative IDs in a multi-signal ecosystem? Alternative IDs add reach and coverage when they connect through a common identity framework. They work best alongside first-party data, device identifiers, and contextual signals. Resolution turns multiple IDs into one consistent view of the consumer. What role does unified identity play in CTV and cross-device media? CTV environments often assign multiple platform-specific identifiers to the same household or device. A unified identity layer links those identifiers together. This approach supports consistent audience recognition across streaming apps, devices, and digital channels. How does unified identity support accurate measurement and attribution? Unified identity connects media exposure to outcomes across digital, TV, and offline touch points. It enables marketers to see how different channels contribute to real actions like visits or purchases. Measurement improves when identity remains consistent across the full journey. Why does an identity strategy matter beyond digital advertising? Identity extends into offline signals such as transactions, loyalty activity, and household data. A unified foundation aligns online and offline interactions into one coherent profile. This connection supports planning, activation, and measurement across the entire customer experience. Latest posts

Published: January 9, 2026 by Henry Schenker, Group Product Manager

Experian Audiences help financial marketers serve consumers with very different financial habits, digital behaviors, and spending patterns. Backed by our deep insight into income, debt, and credit, digital behavior, and household dynamics, our approximately 400 financial audiences and 3,500+ syndicated segments give financial marketers the ability to engage consumers with relevance across every life stage, channel, and financial mindset. To help financial marketers build effective, more adaptable programs, in this article, we’ll explore two approaches: Generational: How financial behaviors differ across life stages Seasonal: How consumer financial motivation spikes at key times of year Together, these approaches help financial marketers reach the right consumers with the right message at the right moment. Generational approach Financial marketers face a new kind of challenge: some consumers still visit branches, while others manage nearly every financial task from their phones. That gap reflects more than a channel preference; it signals distinct financial needs, confidence levels, and expectations for how money should work across generations. How do financial behaviors differ across generations? Generational digital behaviors The data below highlights key differences in how younger consumers engage with digital financial tools compared with Boomers. Behavior/metricGen Z and MillennialsBoomersUse peer-to-peer transfer apps (Venmo, PayPal)~50%~20%Use a mobile wallet daily79% (Gen Z), 67% (Millennial)Nearly 70% have never used one Younger generations are driving a mobile-first approach to money management, while Boomers are far less likely to manage their finances this way. They prioritize tools that help them build credit, reduce debt, manage rising costs, and automate everyday tasks. This behavior is reshaping how financial institutions think about acquisition, product relevance, and loyalty. Generational workforce and retirement dynamics As Boomers retire, their focus shifts to protecting accumulated wealth, steady income, and simplified service experiences. These changes are reshaping household finances and long-term planning behaviors across the country. The table below outlines how shifting workforce composition and retirement milestones differ across generations. Behavior/metricGen Z and MillennialsBoomersShare of the U.S. workforceGrowing toward 74% of the global workforce by 2030 (younger generations collectively)~15% of the U.S. workforce and shrinkingRetirement outlookExpected age to retire 67-69~75 million people will have retired by 2030 Marketers need to do more than track trends; they need to act on them with confidence. That’s where Experian Audiences come in. Turn generational insights into action with Experian Audiences Experian Audiences turn complex generational data into actionable marketing segments, helping financial brands reach the right people with the right message across every life stage. We offer approximately 400 financial audiences, each reflecting distinct financial priorities, from debt management to wealth preservation. These audiences are built using privacy-safe data and grounded in our deep understanding of income, debt, and digital behavior. Experian’s financial audiences blend credit, behavioral, and demographic signals to help you connect with consumers based on: Debt profile, including type and overall burden Income tier and earning stage Financial confidence and digital engagement habits How can marketers activate generational insights with Experian Audiences? Each generation has unique financial journeys, needs, and motivations that marketers can address with Experian Audiences designed to reach: Generation Z (Gen Z) Millennials Generation X (Gen X) Baby boomers (Boomers) In addition to these four generational segments, Experian Audiences also includes segments that apply broadly across life stages. These audiences reflect core financial attributes, such as income, capacity, and lifestyle, that are consistently relevant and can be layered onto any generational strategy. Ability to pay Generational income bands  Income Mosaic® USA While Fair Lending regulations prohibit age-based targeting, these groups are not built on age itself. Instead, they’re derived from observable financial behaviors and signals that often align with different life stages; allowing marketers to engage consumers in a compliant, behavior-driven way. We also offer FLA-friendly¹ audience segments when required, alongside expanded options for non-lending campaigns, supporting initiatives such as brand and product awareness, deposit growth, credit union membership, and other programs that don’t rely on credit-based targeting. You can find the full taxonomy paths in the appendix. This generation is young, digitally savvy, and highly engaged. Gen Z is beginning their financial journey with a focus on independence and debt management. Their preference for mobile-first tools and peer-to-peer payments reflects an expectation for simple, accessible financial experiences. Campaigns centered on credit-building tools, savings apps, and financial literacy resources are especially relevant for this group. Behavior/metricGen ZUse peer-to-peer transfer apps80%+Use mobile wallets daily79% Here are seven recommended audiences to target Gen Z:  Credit Card Financial Personality Discretionary Spend: Dining Out Discretionary Spend: Education Discretionary Spend: Entertainment In Market Buy Now Pay Later In Market for Auto Loan or Lease Renter How to use these audiences Financial marketers can activate audiences like Credit Card Financial Personality, In-Market Buy Now Pay Later, and Renter to introduce credit-building tools and mobile-first financial products. Millennials are entering their peak earning years while balancing family, homeownership, and digital convenience. Their preference for digital and contactless payments reflects a broader expectation for seamless, mobile-first financial experiences. Campaigns highlighting mortgage products, family insurance, and digital banking resonate across connected TV, mobile, and display. Behavior/metricMillennialPrefer digital or contactless payments~85% Here are ten audiences to target Millennials:  Deposits Financial Personality Discretionary Spend Education Discretionary Spend Home Furnishings In Market Buy Now Pay Later In Market Real Estate Investable Assets Likely to Move Mortgage Financial Personality New Parents Student Loan Age How to use these audiences Financial marketers can use audiences such as Mortgage Financial Personality, New Parents, and Discretionary Spend: Home Furnishings to reach Millennials navigating homeownership, family growth, and major financial decisions. Gen X leads in household income and prioritizes investments, education, and long-term financial stability. They respond well to data-driven offers for refinancing, college planning, and wealth management, especially across digital video, streaming, and email channels. Behavior/metricGen ZMillennialsGen XBoomersMedian income$71,200~$104,000~$126,000~$54,000 Here are ten audiences to target Gen X:  Discretionary Spend Discretionary Spend Donations Discretionary Spend Entertainment Discretionary Spend Travel Equity Loan Age Insurance Financial Personality Investment Financial Personality Investable Assets Mortgage Loan Age Net Asset Score (Net Worth) How to use these audiences Financial marketers can utilize audiences like Investment Financial Personality, Equity Loan Age, and Net Asset Score to promote refinancing, college planning, and wealth-building solutions. Boomers tend to have lower debt loads and more stable income, but place a high value on security and simplicity. Their channel preferences skew traditional, focusing on direct mail, television, and formats that reinforce trust and familiarity. Behavior/metricBoomerMedian net worth$410,000TV consumption98% watch TV; 77% watch more than 2 hours per dayNewspaper readership50%+ still read print or a mix of print and digital Here are eight audiences to target Boomers:  Charitable Causes Discretionary Spend Discretionary Spend Donations Discretionary Spend Travel Equity Loan Age Home Equity Financial Personality Mortgage Loan Paid Off or “Has Existing” Net Asset Score (Net Worth) How to use these audiences Financial marketers can target audiences such as Home Equity Financial Personality, Mortgage Loan Paid Off, and Net Asset Score to support messaging around wealth preservation, estate planning, and retirement security. Seasonal approach Alongside generation insights, financial advertisers should also capitalize on key seasonal events where financial motivation naturally spikes. Each season brings unique consumer behaviors, and Experian Audiences can be activated to align with these key seasonal moments. Tax season Refunds and debt payoff are top of mind as consumers prepare and file their returns. Experian Audiences you can activate: Household Tax Shelter User Tax Preparation Services and Software Tax Return: Professional Service Prepare User Tax Return: Self Prepare User How to use these audiences Use Tax Preparation Services and Software or Tax Return: Self Prepare User to reach consumers actively preparing returns, paying down debt, or planning how to use their refunds.  Home buying season Mortgage, refinancing, and home equity activity increases as consumers enter the peak home buying window. Experian Audiences you can activate: In Market First Mortgage In Market Home Equity In Market New Mortgage In Market Second Mortgage Refinancing Homeowners How to use these audiences Use In Market First Mortgage or Refinancing Homeowners to connect with consumers exploring first-time home purchases, refinance options, or equity-based borrowing. Back-to-school Household spending increases as families manage education costs, holiday purchases, and year-end budgeting. This period also drives heightened activity around payments, credit usage, and financial planning. Experian Audiences you can activate: Back to School High Spend Back to School Moderate Spend Back to School Spend: PreK through High School College Tuition Geo Index High Spenders Credit Card Age <2 Years Credit Seeking Card Switcher In Market Credit Card In Market Personal Loan Mobile Location > College Students Student Loan Age <5 Years Student Loan Existing How to use these audiences Activate Back to School High Spend, Back to School Moderate Spend, or Back to School Spend: PreK through High School audiences to reach households actively preparing for the school year. Year-end planning (October-December) As Boomers and Gen X plan for retirement or tax optimization, focus on wealth preservation and investment management.  Experian Audiences you can activate: Baby Boomer Household Income $150K–$249K Baby Boomer Household Income $250K–$499K Estimated Household Income Range $500K Gen X Household Income $1M Plus Geo-Indexed Household Income $1M Plus How to use these audiences Use Estimated Household Income Range $500K or Geo-Indexed Household Income $1M Plus to engage consumers focused on financial wrap-up activities. What sets Experian Audiences apart? Our syndicated audiences give you an advantage across channels, offering both scale and accuracy: Experian’s 3,500+ syndicated audiences can be sent to 200+ leading social platforms, such as Meta and Pinterest, TV, and programmatic advertising platforms, and activated directly within Audigent, a part of Experian,  with private marketplaces (PMPs). Reach consumers based on who they are, where they live, and their household makeup. Experian ranked #1 in accuracy by Truthset for key demographic attributes. Access to unique audiences through Experian’s Partner Audiences available on Experian’s data marketplace, within Audigent, a part of Experian, for activation in PMPs, and directly on platforms like DirectTV, Dish, Magnite, OpenAP, and The Trade Desk. You can activate our syndicated audiences on-the-shelf of most major platforms. For a full list, download our syndicated audiences guide. Explore Experian and FMCG Direct’s financial audiences in non-financial campaigns Where can you activate Experian Audiences? Experian Audiences can be activated on 200+ leading destinations or found directly on over 30 platforms, including: Basis  FreeWheel  Magnite  Nexxen  The Trade Desk  Viant  Microsoft Advertising and more Need a custom audience? Reach out to our audience team and we can help you build and activate an Experian audience on the platform of your choice. Want to activate an Experian Audience on Meta, Pinterest, Snap, TikTok or on a platform not listed above? Contact us today. Explore our other audiences that you can activate today Activate Experian Audiences today with Audigent Audigent will build customized deals that combine premium Experian Audiences or Partner Audiences and inventory into a single, streamlined deal ID – tailored to your campaign needs. Plus, our powerful supply-side optimization ensures your campaigns deliver top marks in performance. Connect with the Audigent team today at AudigentAgency_Brands@experian.com to get started. Make every consumer part of your financial strategy From first paychecks to retirement portfolios, every generation has its own financial story, and seasonal moments create predictable spikes in financial behavior. With Experian Audiences, you can plan across life stages and timing to meet consumers when intent is highest, building relationships grounded in trust, relevance, and meas Reach out to us today FAQs What are Experian Audiences? Experian Audiences are pre-built, privacy-compliant consumer segments that help marketers target based on verified demographic, financial, and behavioral data.They’re designed for flexibility across channels and can be activated on 200+ platforms, including major social, CTV, and programmatic partners.Experian ranks #1 in demographic accuracy according to Truthset, and marketers can choose from 3,500+ syndicated audiences that capture signals such as income, spending behavior, household structure, financial attitudes, and ability to pay. These same audiences are also available through partnerships on platforms like DirecTV, Dish, Magnite, OpenAP, and The Trade Desk.For a deeper look at our audience catalog, explore our syndicated audience guide.  How can financial marketers use Experian Audiences effectively? Financial marketers can use Experian Audiences by aligning audience selection with generational priorities, such as digital banking for Gen Z or retirement planning for Boomers, to improve engagement and ROI. Are Experian Audiences compliant with financial marketing regulations? Experian Audiences are designed to meet a variety of needs while respecting different levels of privacy standards. For example, we offer FLA-compliant segments where required, as well as broader audiences for objectives such as brand awareness, promotion, credit union membership growth, and more.Experian’s approach to data is guided by our Global Data Principles, which reflect how we protect and manage information:Data security: safeguarding data against unauthorized access, use, or lossAccuracy: ensuring data is as accurate, complete, and relevant as possibleFairness: collecting and using data responsibly and for legitimate purposesTransparency: being open about the data we collect, how it’s used, and where it’s sharedInclusion: using data to expand financial access and support consumer financial health Where can you activate Experian Audiences? You can activate Experian Audiences are available across 200+ digital and connected TV platforms, including Meta, Pinterest, The Trade Desk, and Audigent PMPs. Can I combine Experian data with my own? Yes, you can combine Experian data with your own. You can combine your own first-party data with Experian’s 3,500+ syndicated audiences and additional segments from multiple Partner data providers, as a custom audience within a Curated Deal or self-service via Audience Engine. Footnote “Fair Lending Friendly” indicates data fields that Experian has made available without use of certain demographic attributes that may increase the likelihood of discriminatory practices prohibited by the Fair Housing Act (“FHA”) and Equal Credit Opportunity Act (“ECOA”). These excluded attributes include, but may not be limited to, race, color, religion, national origin, sex, marital status, age, disability, handicap, family status, ancestry, sexual orientation, unfavorable military discharge, and gender. Experian’s provision of Fair Lending Friendly indicators does not constitute legal advice or otherwise assures your compliance with the FHA, ECOA, or any other applicable laws. Clients should seek legal advice with respect to your use of data in connection with lending decisions or application and compliance with applicable laws. Appendix Generation Z Financial Personalities > Credit Card Financial Personality > Uninterested, Average Credit Card Balance Financial Personalities > Credit Card Financial Personality > Reluctant User, High Credit Card Balance Financial Personalities > Credit Card Financial Personality > Loyal Rewards Enthusiast, Low Credit Card Balance Financial Personalities > Credit Card Financial Personality > Credit Seeking Card Switcher, High Credit Card Balance Financial Personalities > Credit Card Financial Personality > Complacent Card User, Low Credit Card Balance Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $4302-$99999 Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $2084-$4301 Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $0-$2083 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $512-$1227 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $1228-$99999 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $0-$511 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $4607-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $2230-$4606 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $0-$2229 Financial FLA Friendly > In Market > Buy Now Pay Later Financial > In Market > Buy Now Pay Later Financial FLA Friendly > In Market Auto Loan Financial FLA Friendly > In Market Auto Lease Demographics > Homeowners/Renters > Renter Millennials Financial Personalities > Deposits Financial Personality > Uninterested, Average Deposit Balance Financial Personalities > Deposits Financial Personality > Self-Directed Diversifier, Very High Deposit Balance Financial Personalities > Deposits Financial Personality > Hesitant Borrower, Low Deposit Balance Financial Personalities > Deposits Financial Personality > Demanding Advice Seeker, Low Deposit Balance Financial Personalities > Deposits Financial Personality > Conservative Branch Banker, Very High Deposit Balance Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $512-$1227 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $1228-$99999 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $0-$511 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $2602-$99999 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $1272-$2601 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $0-$1271 Financial FLA Friendly > In Market > Buy Now Pay Later Financial > In Market > Buy Now Pay Later Publisher Derived > In-Market: Real Estate > In-Market Real Estate Consumer Financial Insights > Investable Assets > Investable Annual Assets Score Less Than $10000 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $10000-$49999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $50000-$99999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $100000-$249999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $250000-$499999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $500000-$999999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $1000000 Plus Lifestyle and Interests (Affinity) > Movers > Likely to Move Financial Personalities > Mortgage Financial Personality > Uninterested, Slightly Below Average Mortgage Balance Financial Personalities > Mortgage Financial Personality > Secure, Active Refinancer, Above Average Mortgage Balance Financial Personalities > Mortgage Financial Personality > Disciplined, Passive Borrower, Below Average Mortgage Balance Financial Personalities > Mortgage Financial Personality > Conservative, Bank Loyalist, Slightly Below Average Mortgage Balance Financial Personalities > Mortgage Financial Personality > Advice Seeking Refinancer, Slightly Above Average Mortgage Balance Life Events > New Parents > Child Age 0-36 Months Financial FLA Friendly > Student Loan Age > 9 Years Financial FLA Friendly > Student Loan Age > 8 Years Financial FLA Friendly > Student Loan Age > 7 Years Financial FLA Friendly > Student Loan Age > 6 Years Financial FLA Friendly > Student Loan Age > 12 Years Financial FLA Friendly > Student Loan Age > 11 Years Financial FLA Friendly > Student Loan Age > 10 Years Financial FLA Friendly > Student Loan Age > <5 Years Generation X Financial - Analytics IQ > Discretionary Spend > Travel Annual Spend $682-$1364 Financial - Analytics IQ > Discretionary Spend > Travel Annual Spend $1365-$99999 Financial - Analytics IQ > Discretionary Spend > Travel Annual Spend $0-$681 Financial - Analytics IQ > Discretionary Spend > Reading Annual Spend $193-$99999 Financial - Analytics IQ > Discretionary Spend > Reading Annual Spend $102-$192 Financial - Analytics IQ > Discretionary Spend > Reading Annual Spend $0-$101 Financial - Analytics IQ > Discretionary Spend > Personal Annual Spend $993-$99999 Financial - Analytics IQ > Discretionary Spend > Personal Annual Spend $525-$992 Financial - Analytics IQ > Discretionary Spend > Personal Annual Spend $0-$524 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $2602-$99999 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $1272-$2601 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $0-$1271 Financial - Analytics IQ > Discretionary Spend > Entertainment Other Annual Spend $911-$1973 Financial - Analytics IQ > Discretionary Spend > Entertainment Other Annual Spend $1974-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment Other Annual Spend $0-$910 Financial - Analytics IQ > Discretionary Spend > Entertainment AV Annual Spend $952-$1763 Financial - Analytics IQ > Discretionary Spend > Entertainment AV Annual Spend $1764-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment AV Annual Spend $0-$951 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $4607-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $2230-$4606 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $0-$2229 Financial - Analytics IQ > Discretionary Spend > Entertainment Admissions Annual Spend $833-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment Admissions Annual Spend $326-$832 Financial - Analytics IQ > Discretionary Spend > Entertainment Admissions Annual Spend $0-$325 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $512-$1227 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $1228-$99999 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $0-$511 Financial - Analytics IQ > Discretionary Spend > Donation Annual Spend $2568-$99999 Financial - Analytics IQ > Discretionary Spend > Donation Annual Spend $1265-$2567 Financial - Analytics IQ > Discretionary Spend > Donation Annual Spend $0-$1264 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $31619-$99999 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $0-$7900 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $7901-$10930 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $21952-$31618 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $15180-$21951 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $10931-$15179 Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $4302-$99999 Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $2084-$4301 Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $0-$2083 Financial - Analytics IQ > Discretionary Spend > Apparel Annual Spend $2818-$99999 Financial - Analytics IQ > Discretionary Spend > Apparel Annual Spend $1459-$2817 Financial - Analytics IQ > Discretionary Spend > Apparel Annual Spend $0-$1458 Financial - Analytics IQ > Discretionary Spend > Alcohol and Wine Annual Spend $727-$99999 Financial - Analytics IQ > Discretionary Spend > Alcohol and Wine Annual Spend $331-$726 Financial - Analytics IQ > Discretionary Spend > Alcohol and Wine Annual Spend $0-$330 Financial FLA Friendly > Equity Loan Age > 9 Years Financial FLA Friendly > Equity Loan Age > 7-8 Years Financial FLA Friendly > Equity Loan Age > 12+ Years Financial FLA Friendly > Equity Loan Age > 11 Years Financial FLA Friendly > Equity Loan Age > 10 Years Financial FLA Friendly > Equity Loan Age > <6 Years Financial Personalities > Insurance Financial Personality > Uninterested, Below Average Insurance Policy Face Value Financial Personalities > Insurance Financial Personality > Secure Agent-Oriented Loyalist, High Insurance Policy Face Value Financial Personalities > Insurance Financial Personality > Reluctant Insurance Skeptic, Below Average Insurance Policy Face Value Financial Personalities > Insurance Financial Personality > Insurance Averse, Below Average Insurance Policy Face Value Financial Personalities > Insurance Financial Personality > Engaged Advice Seeker, Average Insurance Policy Face Value Financial Personalities > Insurance Financial Personality > Confident, Self-Directed Planner, High Insurance Policy Face Value Financial Personalities > Investments Financial Personality > Skeptical, Fund-Oriented Investor, Low to Medium Investable Assets Financial Personalities > Investments Financial Personality > Savvy Sounding-Board Seeking Investor, Average Investable Assets Financial Personalities > Investments Financial Personality > Price Sensitive, Self-Directed Investor, Very High Investable Assets Financial Personalities > Investments Financial Personality > Cautious Investing Novice, Low Investable Assets Financial Personalities > Investments Financial Personality > Broker-Reliant Delegator, Very High Investable Assets Consumer Financial Insights > Investable Assets > Investable Annual Assets Score Less Than $10000 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $10000-$49999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $50000-$99999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $100000-$249999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $250000-$499999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $500000-$999999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $1000000 Plus Financial FLA Friendly > Mortgage Loan Age > 9 Years Financial FLA Friendly > Mortgage Loan Age > 8 Years Financial FLA Friendly > Mortgage Loan Age > 7 Years Financial FLA Friendly > Mortgage Loan Age > 6 Years Financial FLA Friendly > Mortgage Loan Age > 5 Years Financial FLA Friendly > Mortgage Loan Age > 13 Years Financial FLA Friendly > Mortgage Loan Age > 11-12 Years Financial FLA Friendly > Mortgage Loan Age > 10 Years Financial FLA Friendly > Mortgage Loan Age > <4 Years Consumer Financial Insights > Net Assets Score (Net Worth) > Net Asset Score Net Worth $1000000 Plus Consumer Financial Insights > Net Assets Score (Net Worth) > Net Asset Score $2500000 Plus Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score Less Than $25000 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $750000-$999999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $75000-$99999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $500000-$749999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $50000-$74999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Asset Score $5000000 Plus Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $250000-$499999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $25000-$49999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $2500000-$4999999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $100000-$249999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $1000000-$2499999 Baby boomers Lifestyle and Interests (Affinity) > Charitable Causes > Contributes to Private Foundations Lifestyle and Interests (Affinity) > Charitable Causes > Contributes to Political Charities Lifestyle and Interests (Affinity) > Charitable Causes > Contributes to Health Charities Lifestyle and Interests (Affinity) > Charitable Causes > Contributes to Education Charities Lifestyle and Interests (Affinity) > Charitable Causes > Contributes to Charities Lifestyle and Interests (Affinity) > Charitable Causes > Contributes to Arts/Culture Charities Lifestyle and Interests (Affinity) > Charitable Causes > Contributes by Volunteering Financial - Analytics IQ > Discretionary Spend > Travel Annual Spend $682-$1364 Financial - Analytics IQ > Discretionary Spend > Travel Annual Spend $1365-$99999 Financial - Analytics IQ > Discretionary Spend > Travel Annual Spend $0-$681 Financial - Analytics IQ > Discretionary Spend > Reading Annual Spend $193-$99999 Financial - Analytics IQ > Discretionary Spend > Reading Annual Spend $102-$192 Financial - Analytics IQ > Discretionary Spend > Reading Annual Spend $0-$101 Financial - Analytics IQ > Discretionary Spend > Personal Annual Spend $993-$99999 Financial - Analytics IQ > Discretionary Spend > Personal Annual Spend $525-$992 Financial - Analytics IQ > Discretionary Spend > Personal Annual Spend $0-$524 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $2602-$99999 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $1272-$2601 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $0-$1271 Financial - Analytics IQ > Discretionary Spend > Entertainment Other Annual Spend $911-$1973 Financial - Analytics IQ > Discretionary Spend > Entertainment Other Annual Spend $1974-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment Other Annual Spend $0-$910 Financial - Analytics IQ > Discretionary Spend > Entertainment AV Annual Spend $952-$1763 Financial - Analytics IQ > Discretionary Spend > Entertainment AV Annual Spend $1764-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment AV Annual Spend $0-$951 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $4607-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $2230-$4606 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $0-$2229 Financial - Analytics IQ > Discretionary Spend > Entertainment Admissions Annual Spend $833-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment Admissions Annual Spend $326-$832 Financial - Analytics IQ > Discretionary Spend > Entertainment Admissions Annual Spend $0-$325 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $512-$1227 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $1228-$99999 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $0-$511 Financial - Analytics IQ > Discretionary Spend > Donation Annual Spend $2568-$99999 Financial - Analytics IQ > Discretionary Spend > Donation Annual Spend $1265-$2567 Financial - Analytics IQ > Discretionary Spend > Donation Annual Spend $0-$1264 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $31619-$99999 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $0-$7900 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $7901-$10930 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $21952-$31618 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $15180-$21951 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $10931-$15179 Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $4302-$99999 Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $2084-$4301 Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $0-$2083 Financial - Analytics IQ > Discretionary Spend > Apparel Annual Spend $2818-$99999 Financial - Analytics IQ > Discretionary Spend > Apparel Annual Spend $1459-$2817 Financial - Analytics IQ > Discretionary Spend > Apparel Annual Spend $0-$1458 Financial - Analytics IQ > Discretionary Spend > Alcohol and Wine Annual Spend $727-$99999 Financial - Analytics IQ > Discretionary Spend > Alcohol and Wine Annual Spend $331-$726 Financial - Analytics IQ > Discretionary Spend > Alcohol and Wine Annual Spend $0-$330 Financial FLA Friendly > Equity Loan Age > 9 Years Financial FLA Friendly > Equity Loan Age > 7-8 Years Financial FLA Friendly > Equity Loan Age > 12+ Years Financial FLA Friendly > Equity Loan Age > 11 Years Financial FLA Friendly > Equity Loan Age > 10 Years Financial FLA Friendly > Equity Loan Age > <6 Years Financial Personalities > Home Equity Financial Personality > Uninterested, Low Home Equity Balance Financial Personalities > Home Equity Financial Personality > Secure, Savvy Credit User, High Home Equity Balance Financial Personalities > Home Equity Financial Personality > Home Equity Enthusiast, Very High Home Equity Balance Financial Personalities > Home Equity Financial Personality > Home Equity Averse Skeptic, Very Low Home Equity Balance Financial Personalities > Home Equity Financial Personality > Hesitant Borrower, Low Home Equity Balance Financial FLA Friendly > Mortgage Loan Paid Off Financial FLA Friendly > Mortgage Loan Has Existing Consumer Financial Insights > Net Assets Score (Net Worth) > Net Asset Score Net Worth $1000000 Plus Consumer Financial Insights > Net Assets Score (Net Worth) > Net Asset Score $2500000 Plus Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score Less Than $25000 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $750000-$999999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $75000-$99999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $500000-$749999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $50000-$74999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Asset Score $5000000 Plus Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $250000-$499999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $25000-$49999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $2500000-$4999999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $100000-$249999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $1000000-$2499999 Tax season Lifestyle and Interests (Affinity) > Financial Behavior > Household Tax Shelter User Publisher Derived > In-Market: Financial Services > Tax Preparation Services and Software Lifestyle and Interests (Affinity) > Financial Behavior > Tax Return --Professional Service Prepare user Lifestyle and Interests (Affinity) > Financial Behavior > Tax Return - Self prepare user Home buying season Financial FLA Friendly > In Market First Mortgage Financial FLA Friendly > In Market Home Equity Financial FLA Friendly > In Market New Mortgage Financial FLA Friendly > In Market Second Mortgage Financial FLA Friendly > Refinancing Homeowners Back to school Retail Shoppers: Purchase Based > Seasonal > Back to School Apparel - High School Retail Shoppers: Purchase Based > Seasonal > Back to School Moderate Spend Retail Shoppers: Purchase Based > Seasonal > Back to School High Spend - PreK (Early Ed - PreK) Geo-Indexed > Discretionary Spend > College Tuition GeoIndex High Spenders Financial Personalities > Credit Card Financial Personality > Credit Seeking Card Switcher, High Credit Card Balance Financial FLA Friendly > In Market Credit Card Financial FLA Friendly > In Market Personal Loan Consolidated Mobile Location Models > Visits > College Students Financial FLA Friendly > Student Loan Age > <5 Years Financial FLA Friendly > Student Loan Has Existing Year-end planning Demographics > Household Income (HHI) > Baby Boomer Household Income $150K-$249K Demographics > Household Income (HHI) > Baby Boomer Household Income $250K-$499K Demographics > Household Income (HHI) > Estimated Household Income Range $500K Plus Demographics > Household Income (HHI) > Gen X Household Income $1M Plus Geo-Indexed > Demographics > Geo-Indexed Household Income $1M Plus Latest posts

Published: January 7, 2026 by Experian Marketing Services

Remember when “6-7” was all over your feed and no one really knew why, but somehow everyone got it? In 2025, the internet proved that connection doesn’t always make sense — at least not at first. The “6-7” meme was random, ridiculous, and everywhere. It spread because it felt connected; an inside joke everyone could share. Marketing in 2026 will have its own 6-7 moment. Experian's 2026 Digital trends and predictions report explores how 2026 will be defined by connection: between activation and measurement, data and AI, platforms and outcomes. After years of fragmentation, the industry is finally unifying around shared foundations: data accuracy, identity resilience, and measurable performance. Here are three connections to watch for in 2026. 1. AI is only as good as its data foundation AI’s performance depends on the quality, recency, and integrity of its inputs. In 2026, marketers will recognize that the differentiator is not the algorithm itself but the data that informs it. As AI becomes embedded into workflows (from audience discovery to media optimization) accurate identity and privacy-safe data become essential. Why it matters Good data fuels responsible automation, predictive insight, and personalization that feels human. Without it, even the most advanced models will simply automate bad decisions faster. What actions should marketers take to strengthen their data foundation? To make AI adaptive, ethical, and aligned with real-world context, marketers need to strengthen the data foundation beneath it. In 2026, that means taking four core actions: 1. Prioritize accuracy Verify data and anchor it in real human identity, rather than inferred or fragmented signals. 2. Keep data fresh Ensure inputs stay current through continuous updates that reflect real-time consumer behavior and conditions. 3. Maintain consent standards Source data responsibly and stay compliant with privacy regulations emerging across 20+ U.S. states. 4. Enable interoperability Connect data securely across platforms through a signal-agnostic identity framework that supports consistency and scale.    When these elements come together, AI becomes more than just automation: it becomes adaptive, ethical, and responsive to real-world context. 2. Commerce media expands beyond retail Commerce media is no longer just a retail play. What began as retailers monetizing their data and media has evolved into a multi-sector movement uniting data, media, and transaction insights. Auto, travel, CPG, and even financial brands are launching their own media networks or partnering with existing ones to close the loop between exposure and conversion. More than half (58%) of advertisers are interested in advertising on non-retail media networks. eMarketer Why it matters In 2026, commerce media becomes a strategy for any brand with first-party data, measurable outcomes, and the need for closed-loop insight. What should marketers do with this expansion? Activate beyond owned channels Extend audiences beyond owned inventory into addressable connected TV (CTV) and open-web environments where identity links every impression to real outcomes. Make identity the growth engine Privacy-first identity resolution increases data addressability and keeps media measurable across every channel. Collaborate for scale and consistency Partner with providers that deliver transparency, interoperability, and shared measurement - not just data volume. 3. Curation becomes the programmatic standard Curation is reshaping programmatic advertising into something more focused, efficient, and accountable. In an era shaped by privacy regulation and signal loss, curation brings identity, quality, and control together, allowing marketers to target confidently across CTV, audio, and the open web. More than 66% of open-exchange ad spend (over $100 billion annually) now runs through curated private marketplaces (PMPs). eMarketer Why it matters Curation aligns with the industry’s need for accurate identity, transparent supply, and stable outcomes, especially as traditional signals fluctuate. How can marketers use curation more effectively? Utilize supply-side innovation Use supply-side platform (SSP) curation tools from partners like Index Exchange and Magnite to optimize in real time and keep your supply paths transparent. Adopt curated marketplaces Work with agency-built marketplaces from groups like GroupM and Butler/Till to control data costs, maintain transparency, and improve performance. Activate with Experian Curated Deals Tap high-performing audience segments, including PurpleLab’s HIPAA-compliant health audiences, through curated PMPs in leading demand-side platforms (DSPs) such as Amazon DSP. Optimize and prove performance Combine Experian data with Audigent supply-path intelligence to adjust campaigns mid-flight using metrics like CPM, CTR, and video completion rate. 2026 will be the 6-7 era for marketing The “6-7” meme didn’t need to make sense to go viral. But your marketing does. 2026 will be the year marketers move from fragmentation to connection. Download Experian’s 2026 Digital trends and predictions report to explore all five digital marketing trends shaping 2026. Download now Ready to get started? Connect with a member of our team About the author Fred Cheung  Director, Partnership Sales, Audigent, a part of Experian  Fred Cheung has spent over a decade in the programmatic advertising space, with roles at Mindshare, Jounce Media, Twitter, and The Trade Desk. His deep experience in trading and product management helps in his current function on the Experian Marketing Services’ Sales team where he focuses on data growth and adoption across the industries’ leading buy-side platforms.  FAQs Why does Experian describe 2026 as marketing’s “6–7 moment”? Experian uses this phrase to describe the inflection point where AI, identity, commerce media, and programmatic curation finally connect in practical, scalable ways. It reflects the shift from fragmentation toward unified activation and measurement. Experian covers five digital marketing trends to watch for in 2026 in our 2026 Digital marketing trends and predictions report. How does Experian support AI strategies for marketers? Experian provides verified consumer data, identity resolution, and privacy-first frameworks that strengthen AI accuracy. AI tools require reliable inputs, and Experian’s data foundation helps marketers apply AI in predictive modeling, audience insight, and media optimization. Why is identity central to commerce media growth? Identity allows brands and media networks to connect exposure to conversion across sites, screens, and environments. Experian supports this through resilient identity frameworks that maintain recognition even as signals shift. How does Experian help marketers activate curated programmatic buys? Experian provides high-performing audience segments and outcome-based signals that improve curated PMP performance. These capabilities give buyers more control, more stability, and clearer pathways to measurable results. Where can marketers learn more about Experian’s 2026 predictions? Experian’s 2026 Digital trends and predictions report outlines the five forces shaping the year ahead, including AI’s dependence on data quality, commerce media expansion, and the rise of curation. 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Published: December 15, 2025 by Fred Cheung, Director, Partnership Sales

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