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:
Temporal signals
Time-based patterns such as daypart (morning vs. evening), recency (how fresh a signal is), seasonality (holidays, life events), and micro-moments (split-second intent-driven actions).
Environmental signals
The media or content environment; what type of program, article, or channel someone is engaging with when they see your ad.
Situational intent
Signals like browsing behavior or purchase patterns that hint at a person’s stage in the buying journey, from early research to final decision.
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:
Input
Clean, accurate identity and audience data anchored in our privacy-first framework.
Enrichment
Our models fuse household, device, and publisher context to reveal moment-based intent.
Activation
We’re investing in agentic workflows that help marketers plan and execute performance campaigns at scale, activated via our real-time technology that dynamically adjusts deals and surfaces contextually aligned opportunities.
Governance
Every signal and recommendation follows Experian’s principles of transparency, consent, and ethical oversight.
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.
A travel brand can shift creative from “dreaming” to “booking” mode when AI detects signals of active planning.
A retailer can align promotions with trending content or regional weather shifts in real time.
A CPG brand can trigger different product messages based on the context of recipes or household occasions.
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.
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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
2022 was a year of adjustment. Consumers adjusted to a post-pandemic world and returned to pre-pandemic shopping behaviors. Consumers adjusted their budgets as the price of goods skyrocketed, as a result of high inflation. To combat inflation, the U.S. Federal Reserve adjusted interest rates. This further restricted consumer buying power. The AdTech ecosystem also experienced adjustments. Google adjusted the date of cookie deprecation. Federal legislation forced technology companies to adjust their consumer privacy practices. Marketers and advertisers adjusted how they address interoperability issues by investing in clean room solutions. This year of adjustment makes it harder to predict where consumers will spend and how marketers should plan their digital audience strategies. What will 2023 bring to AdTech? Download our 2023 AdTech trends and predictions report to access our forecast to help you plan for 2023. Our report will answer: How has digital activation changed over the last four years? What are the top advertising platforms? Which digital audiences are advertisers buying? Do digital audience strategies vary by vertical? Our AdTech trends forecast In 2023, digital activation will increase. Digital audience activation continues to grow at a significant rate despite market shocks like the pandemic, inflation, and higher interest rates. Given the current economic uncertainty, we predict that marketers will look toward tried and true channels where they are confident they will have quality audiences, inventory, and be able to drive ROI. What will digital activation look like in 2023? Between 2018-2021, digital audience activation increased annually by 46%. Using projected 2022 results, between 2018-2022, it will increase annually by 34%. We anticipate continued growth in 2023. Top advertising platforms in 2023 2023 will see increased digital activation, but which platforms will advertisers use to serve their ads? Advertisers will shift their focus to demand-side, video, and supply-side platforms. Social media platforms will continue to experience volatility. Advertisers will place bigger bets on the combination of addressable and CTV. Our report will also reveal which platforms are creating a path toward a post-cookie future and where data-sharing relationships will become the strongest. The most popular advertiser audiences trending now in AdTech Which digital audiences are advertisers buying? Demographics Modeled Lifestyles Behavioral Custom Audiences Traditional targeting methods like Demographics and Modeled Lifestyles are the baseline of many marketing strategies. We predict that we will continue to see marketers activate against these data sets. Digital audience strategies by vertical Digital audience strategies vary by vertical. Download our report to uncover the digital audiences purchased by advertisers in the following industries: Financial Services Health Retail & CPG Technology & Communication Download our new 2025 Digital trends and predictions report Marketers, agencies, and platforms are facing new challenges as privacy regulations evolve, AI technology advances, and consumer behaviors shift. Our latest report highlights actionable strategies for navigating these changes and improving how you connect with audiences, measure impact, and deliver results. What you’ll learn Navigating signal loss: Explore the rise of alternative IDs and contextual targeting as privacy regulations and signal loss reshape data-driven advertising. Connected TV (CTV): Understand the growth of connected TV (CTV), the importance of frequency capping, and strategies for effective audience activation. Omnichannel campaigns: Learn how marketers are moving from channel-specific strategies to audience-led omnichannel campaigns that tell a more cohesive story. Retail media networks: Learn how retail media networks (RMNs) are capitalizing on enriched first-party data to learn more about their customers and reach them across on-site and off-site inventory. Curation: Examine how curation is transforming programmatic campaigns by combining audience, contextual, and supply chain signals to deliver premium inventory packages that maximize addressability, efficiency, and performance. Download now Get in touch
Advertisers continue to increase their spending across addressable TV, connected TV (CTV), and digital. According to IAB's "2021 Video Ad Spend and 2022 Outlook" report, digital video ad spending is expected to increase by 26% to $49.2 billion in 2022. Understanding who consumers are and how to best reach them in their preferred channel is becoming more complex. Damian Amitin and Colleen Dawe discuss how a seamless identity strategy can address the complexity of the emerging TV space. The evolution of identity resolution Around ten years ago, the idea of digital “identity resolution” or “Device Graphs” was born. This idea connected cookies and MAIDs to understand when many IDs were the same person or household. In more recent years, our industry began to connect that initial understanding to the CTV ecosystem. But, a large part of the TV ecosystem existed in silos, like first and third-party audience data, and the growing advanced TV market. The goal of identity resolution has always been to understand the consumer better. To achieve more accurate targeting and measurement in the CTV ecosystem, we must incorporate the following: What we know about the household and consumer from an ID perspective Who the consumer is as it relates to audience data, as well as the wealth of first-party data in the advanced TV space We know the cookie is a flawed way to collect data. While Google delayed the deprecation of third-party cookies, there are other challenges that we face right now. Such as the glaring gap in Safari traffic and the Identifier for Advertisers (IDFA) turning to “opt-in." Understanding consumer behavior across devices and platforms continues to challenge marketers and publishers. These challenges are creating the need to find more stable identifiers. Though the cookie remains valuable, it has an uncertain future. This has led advertisers to place bigger bets on the combination of addressable and CTV. The overlap in addressable and CTV data leads to fragmentation Personally identifiable information (PII) makes up the majority of addressable TV households' data. Part of the attraction to CTV is that their IDs remain universal, persistent, and stable. Analysts project that CTV ad spending will hit $23B in 2023. Consumers now have an average of 4.7 streaming subscriptions per household. It’s no surprise then, that Disney+, HBO, and Netflix released or announced ad-supported tiers. Addressable TV and CTV are often thought of as distinct markets across the industry. But, in the context of identity, we should look at them through the same lens. Millions of households still consume TV and video content via a set-top box or through apps on CTVs. This is in addition to what they consume on their laptops, tablets, and phones. Of the top 11 cable and satellite providers, 65 million U.S. households still have a box in their homes. On the other hand, approximately 96 million U.S. households have at least one or more Smart TVs and streaming services. With about 126 million total U.S. TV households, that’s a lot of overlap. There are still significant numbers of both addressable and CTV homes. How can we address fragmented TV consumption? Through a holistic and comprehensive approach to identity. An approach that captures addressable TV, CTV, and digital identifiers. An approach that captures all audience attributes inside of a single identity graph. This is the ideal approach for publishers, AdTech vendors, and brands. Discover how to unlock holistic identity How can we achieve a holistic identity? Through a three-pillared approach: First-party data onboarding Digital identifiers Consumer data First-party data onboarding Bringing offline data from a brand’s consumers is very valuable due to the quality of the data. Because the data is being collected right from the source, you know it’s accurate. It provides the foundation you can build your identity strategy from. Digital identifiers Once you create a foundation with first-party data, you need to connect it. Either with an internal or licensed digital ID graph. Then you can understand the connections between all devices within the household. Consumer data After you know which devices tie to a single consumer, you'll want to act on that knowledge. The next step is to partner with a data provider that can help you understand your consumers. Establishing this partnership will help improve targeting, measurement, and the customer experience. To achieve a well-rounded customer view tomorrow, we need to start today The three-pillared approach bridges the gap between the offline and online worlds. This provides a well-rounded view of customers and audiences. However, the ability to tie these aspects of identity together still presents several challenges. To achieve the three-pillared approach today, you need to use many vendors and fragmented data sources. Often with conflicting data. As we look forward, the tools to do this are becoming more advanced and unified. The players in our ecosystem should adopt a seamless identity strategy. One that provides a privacy-safe yet full-picture solution. That means capturing and unifying all devices within a household. While also understanding the consumer behaviors and profiles behind those devices. As TV becomes more sophisticated, our data and services will enable you to unlock a holistic identity. Chris Feo, SVP of Advanced TV and Platforms, spoke with Broadcasting & Cable about how our data powers measurement, audience insights, and results for businesses within the TV space. "As more and more companies enter the general TV space, whether you're a publisher, an advertiser or anyone in between that's doing measurement, insights, analytics, our data or our services will play a role in some part of that value exchange." – Chris Feo, SVP of Advanced TV and Platforms, Experian Marketing Services Keep up with your customers and their data Once we create an informed identity strategy, we can begin to understand the makeup of each household and the individuals within. In this new world, personalizing the experience for an audience is key. Where do they prefer to spend their time? What type of content are they most engaged in? Only then can we as an industry provide an optimal experience for each consumer. All while driving greater ROI for advertisers and publishers. Are you ready to know more about your customers than ever before? Let's get to work together to achieve your marketing goals. Contact us to learn how we can connect the complex dots of identity resolution. About our experts Damian Amitin, VP of Enterprise Partnerships, Experian Marketing Services Damian Amitin is the VP of Enterprise Partnerships and joined Experian during the Tapad acquisition in November 2020. Damian is a senior sales and partnerships executive, specializing in the identity resolution and marketing data ecosystem. Damian helps brands, publishers, and technology vendors enable enhanced ID resolution through The Experian/Tapad platform to attain a 360 view of the customer across targeting analytics, attribution, and personalization. Colleen Dawe, Senior Account Executive, Experian Marketing Services Colleen Dawe is a Senior Account Executive on the Advanced TV Team within Experian Marketing Services. With 15 years of experience working within the television ecosystem, Colleen works with clients to bring the value and expertise of Experian to support their objectives in the areas of data, identity, activation, and measurement. Get in touch
Over the past two decades, we’ve seen healthcare become increasingly interconnected. Healthcare systems can share a patient's clinical information in a variety of ways. A Pharmacy Benefits Manager can share it through an Electronic Health Record. An MRI scanner can also capture and store patient images on a picture archiving and communication system (PACS). Despite this wealth of information, according to the CDC, 20 million U.S. citizens don’t have access to medical care when they need it. A patient’s well-being should represent more than their clinical data. How can we increase access to care for those individuals? We can look towards non-clinical factors, like the social determinants of health, for answers. Coordinate care for at-risk patients What if you could identify patients who are likely to readmit due to factors outside of their medical conditions? We can use demographic, geographic, and socioeconomic data to discover patients that need greater access to care. The social determinants of health (SDOH) can uncover factors that may increase the burden of disease for some populations. What are the social determinants of health? They are the conditions in the environments where people are born, live, learn, work, play, worship, and age. Think of factors like safe housing, transportation, job opportunities, and education. These conditions can affect a wide range of health, functioning, and quality-of-life outcomes and risks. What insights can the social determinants of health reveal? Experian Health’s Social Determinants of Health solution offers holistic insight into the financial, transportation, and technological barriers individuals may experience. These barriers could hinder their access to care, medication, food, and housing. It's important to find a solution like ours that offers prioritized, proactive suggestions for interventions that help remove or reduce such barriers for improved health outcomes. Our rich household data sets can provide key insights into the SDOH. This data can answer key questions such as: Are there existing populations with housing instability issues? How much price sensitivity do consumers have for medication? Are there markets or locations that have food instability issues? Is transportation an issue that makes it hard for patients to access care facilities? Are there geographic influences that drive or prevent diagnosis and care? In the chart below, we break down the SDOH into five categories. We outline key considerations that offer insights to provide patient-specific context for your caregivers. Finally, we present patient engagement strategies that are SDOH factor-specific and based on best practice interventions and program types. Social determinants of health data in action While much of healthcare focuses on clinical outcomes, our Consumer View data can provide a wealth of insight into a variety of non-clinical factors that can influence quality of care. A profile of core demographics such as age, ethnicity, and gender can uncover new opportunities or highlight areas where engagement does not align with medical research. We can discover patients at-risk for not being able to access essential services utilizing key, social determinants of health and geographic profiling. When combined with core demographics like age, gender, and ethnicity, we can compare any patient population against expected SDOH norms to uncover significant gaps in access to care. Our data shows that: 1 in 12 households have no access to a vehicle 1 in 4 households are sensitive to the cost of medication 1 in 5 households have very low technology sophistication 1 in 7 households live below the federal poverty level Once you have this data, what can you do with it? You can develop an inclusive education and communication campaign with our data-driven content and contact engagement solution. This solution empowers you to pair the perfect messaging styles with the right channels to deliver a personalized experience to broaden your reach. For those individuals who have little access to technology, an email campaign may not reach them. We can identify additional engagement channels like the traditional newspaper, radio, direct mail, or even broadcast TV to determine the best medium to expand your market while increasing access to care. By using decision making styles and engagement channels, together we can reduce the burden of care on the medically underserved. Let’s drive inclusive healthcare together Develop a more holistic view of your patient population while increasing healthcare equity. We can help you use the social determinants of health for actionable care management. Contact us to learn how you can fold this data into your healthcare ecosystem. Get in touch