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Why context is key to making AI successful in marketing

Published: November 24, 2025 by Matthew Griffiths, SVP of Technology, Audigent, a part of Experian

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.

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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:

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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).

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Environmental signals

The media or content environment; what type of program, article, or channel someone is engaging with when they see your ad.

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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:

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Input

Clean, accurate identity and audience data anchored in our privacy-first framework.

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Enrichment

Our models fuse household, device, and publisher context to reveal moment-based intent.

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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.

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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.

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A travel brand can shift creative from “dreaming” to “booking” mode when AI detects signals of active planning.

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A retailer can align promotions with trending content or regional weather shifts in real time.

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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

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

How does context make AI-driven marketing more effective?

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.

What is the context gap in AI-driven marketing?

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.

Does Experian interpret contextual signals in real-time?

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.

What does responsible intelligence look like in practice?

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.

What does Experian’s foundation in responsible automation look like?

– 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.


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Note: While third-party cookies are no longer being phased out, this webinar was recorded in 2023 when cookie deprecation was still a key industry focus. The strategies discussed reflect that time frame and remain relevant for addressing broader signal loss challenges. With major browsers discontinuing support for third-party cookies, marketers must rethink how to identify and engage their audiences. Contextual advertising offers a privacy-safe solution by combining contextual signals with machine learning to deliver highly targeted campaigns. In a Q&A with our experts with eMarketer, Jason Andersen, Senior Director of Strategic Initiatives and Partner Solutions at Experian, and Alex Johnston, Principal Product Manager at Yieldmo, we discuss how contextual advertising addresses signal loss, improves addressability, and delivers better outcomes for marketers. The macro trends impacting marketers How important is it for digital marketers to stay informed about the changes coming to third-party cookies, and what challenges do you see signal loss creating? Jason (Experian): Third-party cookies have already been eliminated from Firefox, Safari, and other browsers, while Chrome has held out. It’s just a matter of time before Chrome eliminates them too. Being proactive now by predicting potential impacts will be essential for maintaining growth when the third-party cookie finally disappears. Alex (Yieldmo): Third-party cookie loss is already a reality. As regulations like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) take effect, more than 50% of exchange traffic lacks associated identifiers. This means that marketers have to think differently about how they reach their audiences in an environment with fewer data points available for targeting purposes. It’s no longer something to consider at some point down the line – it’s here now! Also, as third-party cookies become more limited, reaching users online is becoming increasingly complex and competitive. Without access to as much data, the CPMs (cost per thousand impressions) that advertisers must pay are skyrocketing because everyone is trying to bid on those same valuable consumers. It’s essential for businesses desiring success in digital advertising now more than ever before. Solving signal loss with contextual advertising How does contextual advertising help marketers engage audiences with new strategies like machine learning and artificial intelligence (AI)? Jason (Experian): Contextual advertising helps marketers engage audiences by combining advanced machine learning with privacy-safe strategies. We focus on using AI and machine learning to better understand behavior, respect privacy, and deliver insights. As third-party cookies go away, alternative identifiers are coming to market, like Unified I.D. 2.0 (UID2). These are going to be particularly important for marketers to be able to utilize them. As cookie syncing becomes outdated, marketers will have to look for alternative methods to reach their target audiences. It’s essential to look beyond cookie-reliant solutions and use other options available regarding advertising. Alex (Yieldmo): There’s been a renaissance in contextual advertising over the last couple of years. Three key drivers are shaping this shift: The loss of identity signals is forcing marketers to rethink how they reach audiences. Advances in machine learning allow us to analyze more granular contextual signals, identifying patterns that are most valuable to advertisers. Tailored models now use these signals to deliver more effective campaigns. This transformation is occurring because of our ability to capture and operate on richer, more detailed data. 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