At A Glance
AI can make marketing more human when it understands people in context. Experian’s technology interprets real-time contextual signals—from temporal to situational intent—to align every message with the moment. By connecting identity and context, marketers can create timely, relevant, and responsible engagement that builds trust and drives meaningful outcomes.Personalization without context misses the moment
Marketers have spent years perfecting personalization — but personalization alone often misses the mark. We’ve all seen it. You shop for a weekend getaway, then get served travel ads weeks later when you’re already home. The data was right. The timing wasn’t.
Personalization based only on identity and behavior knows who you are but not when or why you’re ready to act.
At Experian, we believe AI should make marketing feel more human. That means understanding people in context, recognizing their environment, mindset, and the moment, to create relevance that feels timely, not intrusive.
The context gap: Why identity and behavior aren’t enough
Identity and behavioral data can reveal the kind of consumer someone is and the kind of products they may want to buy. But they don’t explain what’s happening right now.
The missing layer is context: the dynamic, real-time signal that shows why this moment matters. Context bridges the gap between knowing something about a consumer and understanding their intent.
In an era of fragmented signals and stricter privacy rules, context is one of the most reliable ways to stay relevant without over-reliance on personal identifiers. It helps marketers adapt to shifting needs while keeping privacy intact.
How Experian interprets context in real-time
By context, we mean all the subtle, in-the-moment signals, like time of day, location, or what someone’s watching, that shape what people care about in real-time. At Experian, our technology interprets these in real-time:
By layering these signals over verified identity and behavioral data, Experian’s AI-powered technology helps marketers predict not just who will act, but when they’re ready to act.
Experian’s approach: Turning context into relevance
Consumer behavior changes by the minute, and marketers need to adapt just as quickly. Our technology interprets live bidstream data, device activity, content, and timing to optimize in the moment, ensuring your campaigns deliver meaningful relevance, not just broader reach.
Our process combines:
We call this AI-powered simplicity tools that help marketers work more efficiently, with intelligence that feels intuitive and human-centered.
How context changes the game for marketers
AI without real-time context can only react based on what it already knows. AI-powered by in-the-moment contextual data points enables marketers to anticipate, not just react.
Adjustments based on contextual signals compound into meaningful gains — higher engagement, better efficiency, and a consumer experience that feels natural rather than intrusive.
Context makes AI more human
Context introduces empathy into automation. It’s what keeps AI from overstepping, ensuring the message fits the moment. When marketers respect timing, environment, and intent, ads feel like service, not surveillance. Context transforms relevance into respect.
At Experian, our vision is to make every signal serve people, not profiles. Because the more our technology (including our AI tools and capabilities) understands context, the more human marketing becomes.
At Experian, responsible intelligence is built in
Every contextual model we deploy adheres to our standards for transparent and responsible innovation. We validate inputs, monitor model drift, and ensure no context-based variable introduces bias or privacy risk. This is what responsible automation looks like in practice: intelligent, explainable, and ethical.
From who to when: Context is the future of AI-driven marketing
Identity tells us who someone is. Context tells us when it matters.
The next wave of AI-driven marketing will unite privacy-first identity with contextual intelligence to deliver real-time relevance, responsibly. At Experian, we’re building that future now. Our AI-driven capabilities bring identity, insight, and generative intelligence together so brands, agencies, and platforms can reach the right people, at the right moment, with relevance and respect.
Get started now
About the author
Matthew Griffiths
SVP of Technology, Audigent, a part of Experian
Matthew Griffiths is a seasoned technology entrepreneur and a driving force in advertising technology, data technology, and AI. As the Co-Founder and former CTO (now SVP of Technology) at Audigent, a part of Experian, he plays a pivotal role in shaping the company’s cutting-edge solutions for data activation, curation, and identity management.
With years of executive experience across the U.S., Africa, and the U.K., Matthew has a proven track record of leadership in steering the adoption and use of cutting-edge technologies to drive business outcomes. His expertise spans from collaborating with top global corporations and governments to spearheading award-winning technology projects that deliver life-changing impacts in some of the world’s most underserved communities.
Matthew’s dynamic approach to solving complex business and technology challenges makes him a visionary leader in the AdTech space, consistently driving innovation and performance through technology.
FAQs
Context makes AI-driven marketing more effective because it helps marketers understand people in context, recognizing their environment, mindset, and the moment, to create relevance that feels timely, not intrusive. Context helps marketers understand not just who a person is, but when and why they’re ready to act. Experian’s AI-powered technology layers contextual signals over verified identity data to deliver relevance that feels intuitive, not invasive. This approach connects recognition with understanding, making every campaign more effective and more human.
Identity and behavioral data can reveal the kind of consumer someone is and the kind of products they may want to buy. But they don’t explain what’s happening right now. That’s the context gap—the missing link between knowing something about a consumer and understanding their intent. Context closes this gap by analyzing environmental, temporal, and situational signals that reveal intent—without using invasive identifiers.
Yes, at Experian, our technology interprets contextual signals, including temporal, environmental, and situational, in real-time. By layering these signals over Experian’s verified identity and behavioral data graph, marketers can predict when consumers are most receptive, turning data into real-time opportunity.
At Experian, every contextual model we deploy adheres to our standards for transparent and responsible innovation. We validate inputs, monitor model drift, and ensure no context-based variable introduces bias or privacy risk.
– Privacy-first clarity: We unify household, individual, device, demographic, behavioral, publisher first-party signals, and contextual data points to build a reliable view of consumers, even when certain signals are missing. This clarity helps marketers personalize, target, activate, and measure with confidence.
– Predictive insight: Our models go beyond describing the past. They forecast behaviors, fill gaps with inferred attributes, create lookalikes, and recommend next-best audiences so clients can anticipate opportunity.
– AI-powered simplicity: We’re investing in generative AI and exploring emerging agentic workflows to reimagine how marketers work. Our vision is to move beyond basic audience recommendations toward intelligent audience discovery and automated setup, helping teams uncover opportunities they may not have considered, while spending less time on manual work and more time on strategy and outcomes.
– Real-time intelligence: Consumer journeys never stand still. 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.
– Transparent and responsible innovation: We drive safe, modular experimentation, from generative applications to agentic workflows, always balancing bold ideas with ethical guardrails. We stay at the forefront of evolving legislation and regulation, ensuring our innovations protect consumers, brands, and the broader ecosystem while moving the industry forward responsibly.
Latest posts
In our Ask the Expert series, we interview leaders from our partner organizations who are helping lead their brands to new heights in AdTech. Today’s interview is with Samantha Zhang, Senior Data Scientist, and Jim Meyer, General Manager of the DASH TV Universe Study at the Advertising Research Foundation (ARF). DASH is an annual tracking study conducted by the ARF to define and better understand TV audience behavior and household dynamics. What does DASH measure, and how does it help the industry understand TV consumption today? By capturing hundreds of individual- and household-level data points from each respondent in a rigorous and nationally projectable sample, DASH creates a comprehensive picture of U.S. consumer TV “infrastructure” – how America watches. Core elements in DASHElements that create context in DASHTV setsLocation | brand | smartness | service modes | sources DemographicsConnected devices Game consoles |video players | streaming devicesYesterday viewing Daypart | TV/device genre | Out-of-home viewingMobile devicesOwners | sharing usersShoppingOnline and in-store | Exposure to major RMNsInternet serviceModes | ISPs | connectivity by device Streaming audio Streaming TVSVOD/AVOD tiers and sharing | FAST Email accounts and apps Live TV Modes of access | including casting from devices Social media For example, DASH gathers: Data on every TV set, including brand, room location, age, “smartness,” and connection devices and modes Household connectivity and video service data, even in homes with no TV set Internet Service Providers (ISP) and TV service usage, including Multichannel Video Programming Distributors (MVPDs), virtual vMVPDs, streamers (ad-supported and premium), and Free Ad-Supported Television (FAST) channels Person-level ownership and usage of video-capable mobile devices, including smartphones, tablets, and laptops Measures of viewing and co-viewing across dayparts, devices, and services Additional modules covering shopping and retail media networks, streaming audio, social media, email, and apps Broad coverage and granularity make DASH a uniquely robust source of truth for practitioners across the industry, including measurement experts and ad programming strategists. DASH also reports regularly (and publicly) on key industry dynamics. DASH identified a growing segment of device-only viewers – now nearly 9 million households that watch TV, but do not own a TV set – and highlighted the implications of that trend for traditional ratings systems based only on households with TV sets. Households (HHs – million)2025 HHs (M) U.S. penetrationChange vs. 2024 (M)Total US134.8100%+2.7Connected TV (CTV)114.685%+2.1TV (Set)124.292.2%+1.1Device-only8.86.6%+1.6TV-Accessible133.198.7%+2.7 DASH called out the rise in app-based pay TV and proposed a new connection framework that better represents the modern TV world, in which linear and streaming overlap. DASH also defines the universes of households reachable with advertising. This graphic, for example, shows how all ad-supported linear and streaming properties in aggregate define the true scale of TV advertising. While 35 million households (and growing) are reachable only with streaming ads and 13 million (and falling) only with linear ads, most households are reachable with both, underscoring the importance of understanding the “overlap.” Who uses DASH data, and what decisions does it help inform? There are three primary users of DASH, each with its own use cases: Measurement providers, including Nielsen, use DASH to calibrate viewership data, turn household data into persons data (and vice versa) and estimate potential reached audiences–what the providers call media-related universe estimate (MRUEs)–for the calculation of ratings. Not surprisingly, measurement companies were the first to see the value that an independent TV universe study could provide. Media companies, including major broadcasters and streamers, use DASH to add context and color to their ad sales presentations – and to track the measurement providers, whose ratings play a major role in valuing ad inventory. AdTech companies, including Experian, use DASH to create high-value audience segments for activation. The recent accreditation of DASH by the Media Rating Council (MRC) and adoption by Nielsen as an input to its TV ratings have generated interest from a broad range of companies. We are actively pursuing new licensees and partners to make DASH more useful within, and even outside, the TV ecosystem. What does MRC accreditation signify, and why is it meaningful for DASH? MRC accreditation means DASH passed a rigorous audit conducted by Ernst & Young over many months, which validated our methodology, controls, and data quality. MRC accreditation establishes that DASH is an industry-standard dataset. While the service provider normally announces its own accreditation, the MRC took the unusual step of issuing its own release on DASH, announcing the accreditation of DASH for TV universe estimation and endorsing the study for broader, cross-media use. How does Experian use DASH data to build audiences? The segments combine specific TV usage habits and behaviors from DASH with Experian data on demographics, spending, and other contextual inputs to create a fuller view of consumer viewing behavior. They are designed to be valuable to advertisers in many categories and planning contexts – and to be customizable to fit advertisers’ media targets. The segments can be used to: Apply or suppress audiences to improve target coverage across a campaign Better align media and creative Reach elusive but high-value viewers, such as Ad Avoiders Drive valuable consumer behavior Achieve specific advertising objectives What are some practical use cases for DASH-based audiences? Here are some practical use cases for four different kinds of DASH segments in five different advertiser categories. Travel Co-WatchersA couples-only resort uses TV Co-Watching Households without Children to strengthen target reach and ad memory recallA big theme park destination uses TV Co-Watching Households with Children to reach families in moments of togetherness Home Entertainment TV Owners and Brand LoyalistsA premium TV manufacturer uses the overlap of Multi Brand TV Owners and Single Brand TV Loyalist Households to market its newest TV model to its most loyal consumers. Fast Food Screen Size ViewersA fast food chain with a high-impact new brand campaign uses Large Screen TV Viewers to better align the media and creativeThat same fast food chain uses Small-Screen TV Viewers to drive store traffic by increasing exposure of its retail campaign among on-the-go viewers Financial Services Cord Cutters A personal cost management app and a cash-back credit card target Streaming-First Cord Cutter Households to reach young, tech-savvy, cost-conscious consumers Thanks for the interview. Where can readers learn more about DASH? We started work on DASH seven years ago, and it’s been fun to watch it “grow up.” Our partnership with Experian is a big step toward putting DASH to work for advertisers and agencies. To learn more, visit our site at https://theARF.org/DASH or contact us at DASH@theARF.org. Contact us About our experts Samantha Zhang, Senior Data Scientist at ARF Samantha Zhang is a Senior Data Scientist at the Advertising Research Foundation working on the DASH TV Universe Study, with additional research spanning areas including attention measurement, digital privacy, and artificial intelligence. Jim Meyer, General Manager, DASH, at ARF Jim Meyer is general manager and co-founder of the ARF DASH TV Universe Study and managing partner of Golden Square, LLC, which advises media and research technology companies on growth strategy and development. Latest posts
Reach buyers based on how they shop in a changing market. Experian Audiences help target switchers, align to budgets, and match messaging to inventory.
Explore how Experian utilizes AI to power data-driven programmatic advertising with greater accuracy, efficiency, and consumer trust.