At A Glance
Your audience strategy works like a story. First-party data sets the outline, but scale and relevance come from connecting additional signals such as contextual, geographic, and behavioral data. Experian helps CMOs unify these inputs through identity, enabling consistent activation, privacy-forward targeting, and measurable outcomes as marketing strategies evolve in 2026.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.
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., addingdetailto 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 youidentify, 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:
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 strategy | Percent of marketers that plan to use this data strategy |
| Contextual targeting | 41% |
| First-party data | 40% |
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:
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:
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
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.
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.
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.
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.
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.
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
How third-party data has changed and why it matters in 2025 For years, third-party data operated in an expansive, lightly regulated marketplace: fast-moving, high-growth, and filled with players eager to capitalize on digital marketing’s demand for audience insights. That era is over. Regulatory scrutiny, stricter compliance standards, and rising consumer expectations have already transformed the market. Today, third-party data belongs to partners with proven expertise and built-in compliance. This isn’t a space for opportunistic newcomers; it’s one that rewards long-term commitment and trust. Even the rapid rise of retail media networks (RMNs) reflects this shift. These platforms are built on long-standing, trusted relationships between brands, retailers, and data partners, utilizing that foundation in new ways to reach audiences responsibly and effectively. The best providers have already made this transition; those still “shifting” are catching up. From growth to governance: A market defined by accountability The third-party data ecosystem has matured. After years of rapid expansion and recalibration, the market has stabilized around a new standard: data quality and regulatory accountability. Third-party data enriches first-party insights with attributes such as income, gender, and interests that round out the customer view. But when the industry grew unchecked, unreliable providers diluted quality and trust. This resulted in a decline in the overall value and reliability of the third-party data marketplace. That breakdown led directly to today’s privacy laws, now active across more than 20 U.S. states and numerous countries worldwide. These regulations reflect a permanent consumer expectation: relevance delivered responsibly. Consumers aren’t rejecting personalization; they’re rejecting how it’s been done in the past. They still want relevant, tailored experiences, but they expect brands to deliver them through ethical, transparent data practices. Does third-party data still matter in a privacy-first era? Third-party data isn’t disappearing, if anything, it’s become more important. Brands will always need additional insight to deepen customer understanding; first-party data alone only reflects what’s already known. The industry has entered a mature phase where data quality and compliance are table stakes. The companies leading today built their data infrastructure on rigorous standards, regulatory foresight, and transparent governance. That same foundation powers the next wave of innovation, including the explosive growth of RMNs. RMNs rely on responsibly sourced third-party data to enrich shopper insights, validate audiences, and extend addressability beyond their own walls. Trusted data partners make that expansion possible, connecting retail environments with broader media ecosystems while maintaining privacy and accuracy. High-quality, compliant third-party data remains essential because it: Fills knowledge gaps 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. Improves accuracy Filling in gaps in customer understanding helps you identify, reach, and engage your customers more effectively. This helps improve the delivery of relevant messages and offers to your customers and prospects across channels. Builds connections Third-party data helps brands build loyalty with consumers by speaking to their interests, and intent behind purchases. Fuels prospecting Third-party data can help you find your best prospects. By enriching customer files, you can understand who your best customers are, and how to find more of them. By modeling this data, you can determine who your best customers are and source prospects similar to them. Advancements in AI and machine learning are reshaping how this data is used across the ecosystem. What was once primarily a buy-side tactic is now expanding into the sell-side, where publishers and platforms are using data to curate, package, and activate audiences more intelligently. As AI enhances modeling accuracy and automation, third-party data will play an even greater role in connecting brands and consumers in more meaningful, privacy-conscious ways. The bottom line: it’s not about having more data; it’s about having better, verified data you can trust. How can you spot a trustworthy data partner? The strongest third-party data partners demonstrate accountability through experience, infrastructure, and integrity. Swipe right on the perfect data partner Look for providers that: Operate with clear data principles Trustworthy partners publish and follow codified data principles that guide every step of data handling. Experian adheres to a set of global data principles designed to ensure ethical practices and consumer protection across all our operations. Treat new privacy regulations as routine For mature providers, evolving privacy laws are routine, not disruptive. At Experian, privacy and compliance have long been built in. Every partner and audience goes through Experian’s rigorous review process to meet federal, state, and local consumer privacy laws. Decades of experience have shaped processes that emphasize risk mitigation, transparency, and accountability. Stay deeply connected Leading data companies maintain deep relationships with technology partners and industry and regulatory groups to ensure that ethical data practices are put into practice and their customers are aware of platform-specific regulations. Experian's relationships with demand-side platforms (DSPs), supply-side platforms (SSPs), and even social platforms like Meta, ensures we are aware of any platform-specific initiatives that may impact audience targeting. We’re also active participants in many trade groups to ensure that the industry puts ethical data practices in place to ensure consumers still receive personalized experiences but their data usage and collection is opt-in, transparent and handled with their privacy at the center of the transaction. Have a proven track record in the industry Longevity matters in a regulated and compliance-driven industry. Providers that have thrived through economic cycles and regulatory shifts are the ones equipped for the future. The ability to source high-quality third-party data is core to their business, not an afterthought. Our data is ranked #1 in accuracy by Truthset, giving our clients confidence that every decision they make is backed by the industry’s most reliable insights. Why the future of third-party data depends on accountability The third-party data industry has already crossed the threshold from expansion to accountability. The companies leading this era have established their credibility through governance and proof. The future belongs to providers that: Build with regulatory foresight Maintain rigorous quality assurance Prioritize partnership over profit The Wild West days are long gone. The third-party data ecosystem is now defined by stability, transparency, and shared responsibility. Partner with Experian for data you can trust and results you can prove When accuracy and accountability define success, you need a partner built on both. Work with the company that’s setting the standard for responsible data-driven marketing and helping brands connect with people in meaningful, measurable ways. 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. Third-party data FAQs What is third-party data? Third-party data is information collected by organizations that don’t have a direct relationship with the consumer. It supplements first-party data by adding demographic, behavioral, and interest-based insights. Why are privacy regulations reshaping data practices? Privacy regulations are reshaping data practices because consumers expect control over how their information is used. That expectation led directly to today’s privacy laws, now active across more than 20 U.S. states and numerous countries worldwide. These regulations reflect a permanent consumer expectation: relevance delivered responsibly. Consumers aren’t rejecting personalization; they’re rejecting how it’s been done in the past. They still want relevant, tailored experiences, but they expect brands to deliver them through ethical, transparent data practices. Laws like the CCPA and state-level privacy acts enforce this expectation, holding brands and data providers accountable for the ethical use of data. Can brands still use third-party data safely? Yes, brands can still use third-party data safely when sourced responsibly. Partnering with established, compliant providers like Experian ensures both legal protection and data accuracy. How does Experian ensure compliance with evolving privacy regulations? Experian adheres to a set of global data principles designed to ensure ethical practices and consumer protection across all our operations. At Experian, privacy and compliance have long been built in. Every partner and audience goes through Experian’s rigorous review process to meet federal, state, and local consumer privacy laws. Decades of experience have shaped processes that emphasize risk mitigation, transparency, and accountability. Experian's relationships with demand-side platforms (DSPs), supply-side platforms (SSPs), and even social platforms like Meta, ensures we are aware of any platform-specific initiatives that may impact audience targeting. We’re also active participants in many trade groups to ensure that the industry puts ethical data practices in place to ensure consumers still receive personalized experiences but their data usage and collection is opt-in, transparent and handled with their privacy at the center of the transaction. What should marketers look for in a data partner? Marketers should look for transparency, longevity, and evidence of compliance when looking for a data partner. The best partners can clearly explain how their data is sourced, validated, and maintained. Read Experian's guide on how you can swipe right on the perfect data partner here. Latest posts
What makes data “good” in the age of AI? In AI-driven marketing, data quality now defines success. “Good data” in AI isn’t about volume; it’s about the balance of accuracy, freshness, consent, and interoperability. As algorithms guide decisions, they must learn from data that’s both accurate and ethical. At Experian, we believe good data must meet four conditions: 1. Accurate Verified and anchored in real human identity. 2. Fresh Continuously updated to reflect today’s consumers. 3. Consented Collected and governed transparently. 4. Interoperable Easily integrated across platforms through a secure, signal-agnostic identity spine, enabling seamless data activation. This is the data AI can trust and the data that keeps marketing relevant, predictive, and privacy-first. Listen to InfoSum's Identity Architect's podcast for more on AI, outcomes, and curation Why does data accuracy matter more than ever? AI models are only as intelligent as their inputs. Incomplete or inconsistent data leads to bad predictions and wasted spend. As the industry moves toward agentic advertising, where autonomous systems handle campaign buying and optimization, data accuracy becomes even more critical. If your ad server or audience data is flawed, these new AI agents will simply automate bad decisions faster. Experian applies rigorous quality filters and conflict resolution rules to ensure our data is both deterministic and accurate. Deterministic signals alone don’t guarantee accuracy; they must be verified, deduplicated, and contextualized. Our identity resolution process anchors every attribute to real people, giving brands and platforms the confidence that every insight stems from truth, not noise. Our data is ranked #1 in accuracy by Truthset, giving our clients confidence that every decision they make is backed by the industry’s most reliable insights. See how Experian's Digital Graph improved attribution accuracy for a demand-side platform (DSP) with 84% of IDs resolved Just because it is deterministic, doesn’t mean it’s highly accurate. You still need to refine and validate your data to make sure it tells a consistent story. You need to anchor your data around real people. Calculate the real impact of data accuracy Why does AI need fresh data? Outdated data can’t predict tomorrow’s behavior. AI thrives on recency. At Experian, our audiences are refreshed continuously to mirror real-world signals, from purchase intent to media habits, so every campaign reflects what’s happening now, not six months ago. And we don’t just advocate for fresh data, we rely on it ourselves. Our own AI-powered models, used across our audience and identity platforms, are continuously retrained on the most current, consented signals. This allows us to see firsthand how freshness drives better accuracy, faster optimization cycles, and more relevant outcomes. But freshness alone isn’t enough. With predictive insights, our models go beyond describing the past. They forecast behaviors, fill gaps with inferred attributes, and recommend next-best audiences, helping you anticipate opportunity before it happens. Fresh and predictive data means you’re reaching people in the moment that matters and shaping what comes next. With AI, that’s what defines performance. Explore Experian's most popular audiences, ready to activate now How do consent and governance build trust in AI? Responsible AI starts with responsible data. With 20 U.S. states now enforcing privacy laws, data compliance isn’t optional, it’s operational. 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. Governance isn’t just about regulation, it’s also about innovation done right. We drive transparent and responsible innovation through safe, modular experimentation, from generative applications to agentic workflows. By balancing bold ideas with ethical guardrails and staying ahead of evolving legislation, we ensure our innovations protect consumers, brands, and the broader ecosystem while moving the industry forward responsibly. Compliance and governance aren’t just boxes to check; they’re the foundation that gives AI its license to operate. How does interoperability enable AI’s full potential? AI delivers its best insights when data connects seamlessly across fragmented environments. Our signal-agnostic identity spine allows data to move securely between platforms (connected TV, retail media networks, and demand-side platforms) without losing context or compliance. Interoperability isn’t just about moving data between systems; it’s about connecting insights across them. When signals connect across environments, AI gains a more complete view of the customer journey revealing true behavior patterns, intent signals, and cross-channel impact that would otherwise remain hidden. This unified perspective allows AI to connect insights in real time, improving predictions, performance, and personalization while protecting privacy. Where do AI and human oversight meet? AI can make marketing more predictive, but people make it meaningful. At Experian, our technology brings identity, insight, and generative intelligence together so brands, agencies, and platforms can reach the right people with relevance, respect, and simplicity. Our AI-powered models surface connections, recommend audiences, and uncover insights that would take humans months to find. But our experts shape the process, crafting the right inputs, ensuring data quality, reviewing model outputs, and refining recommendations based on industry knowledge and client goals. It’s this partnership between advanced AI and experienced people that turns predictions into actionable, trustworthy solutions. What “good data” looks like in action “Good data” becomes most powerful when it’s put to work. At Experian, our marketing data and identity solutions help brands and their partners connect accurate, consented, and interoperable data across the ecosystem, turning insight into measurable outcomes. Learn more about Experian's data solutions Learn more about Experian's identity solutions When Windstar Cruises and their agency partner MMGY set out to connect digital media spend to real-world bookings, they turned to Experian’s marketing data and identity solutions to close the attribution loop. By deploying pixels across digital placements and using Experian’s identity graph to connect ad exposure data with reservation records, we created a closed-loop attribution system that revealed the full traveler journey, from impression to confirmed booking. The results were clear: 6,500+ bookings directly tied to digital campaigns, representing more than $20 million in revenue, with a 13:1 ROAS and $236 average cost per booking. Attributed audiences booked $500 higher on average, and MMGY’s Terminal audience segments powered by Experian data achieved a 28:1 ROAS. This collaboration shows that responsible, high-quality data and AI-driven insights don’t just tell a better story; they deliver measurable business performance. Download the full case study How to choose the partner built for responsible AI Why the future of AI depends on “good” data The next phase of AI-driven marketing won’t be defined by who has the most data, but by who has the best. Leaders will: Operate with clear data principles grounded in transparency and truth Build consent and compliance into every workflow Keep data accurate, current, and interoperable Pair automation with human oversight AI success starts with good data. And good data starts with Experian, where accuracy, privacy, and purpose come together to make marketing more human, not less. Partner with Experian for AI you can trust About the author Budi Tanzi VP, Product, Experian Budi Tanzi is the Vice President of Product at Experian Marketing Services, overseeing all identity products. Prior to joining Experian, Budi worked at various stakeholders of the ad-tech ecosystem, such as Tapad, Sizmek, and StrikeAd. During his career, he held leadership roles in both Product Management and Solution Engineering. Budi has been living in New York for almost 11 years and enjoys being outdoors as well as sailing around NYC whenever possible. "Good" data in AI FAQs What defines “good data” according to Experian? At Experian, we define "good data" as the balance of accuracy, consent, freshness, and interoperability. We apply rigorous governance, validation, and cleansing across every signal to ensure that AI systems learn from real-time behaviors, not assumptions. This approach turns data into a foundation for reliable, ethical, and high-performing intelligence. How does Experian ensure AI-ready data accuracy? Experian ensures AI-ready data accuracy through advanced cleansing, conflict resolution, and human anchoring. Experian ensures AI models rely on verified, high-quality inputs. Experian's data is ranked #1 in accuracy by Truthset. Can Experian help brands stay compliant with privacy laws? Yes, Experian can help brands stay compliant with privacy laws. Experian’s privacy-first governance framework integrates ongoing audits, legal oversight, and consent management to ensure compliance with all federal, state, and global privacy laws. Compliance isn’t an afterthought; it’s embedded in every step of our data lifecycle. How does Experian make AI more human? Experian makes AI more human by pairing innovation with human oversight to ensure AI helps marketers understand people, not just profiles. At Experian, we believe the future of marketing is intelligent, respectful, and human-centered. AI has long been part of how we help brands connect identity, behavior, and context to deliver personalization that balances privacy with performance. Our AI-powered solutions combine predictive insight, real-time intelligence, and responsible automation to make every interaction more relevant and ethical. Where can marketers access Experian’s high-quality data? Marketers can activate Experian's high-quality data directly in Experian’s Audience Engine, or on-the-shelf of our platform partners where Experian Audiences are ready to activate. Built on trusted identity data and enhanced with partner insights, it’s where accuracy meets accessibility, helping brands power campaigns with confidence across every channel. Latest posts
Artificial intelligence (AI) is becoming a bigger part of modern advertising, changing how brands connect with people. At Experian, we believe this technology should make marketing more human, not less. We use AI to help marketers understand consumer behavior, respect privacy, and deliver messages that matter. As part of our latest Cannes Content Studio series, we spoke with leaders from AdRoll, MiQ, OpenX, Optable, PMG, PubMatic, and Yieldmo. Their insights show a clear path forward; one where technology supports human strategy to create more meaningful connections. 1. How does AI help you see audiences more clearly? AI decodes complex behavioral signals to reveal the values and mindsets behind decisions, and increasingly, it predicts what audiences will care about next. This allows marketers to deliver timely, relevant messages that resonate with audiences. At Experian, we help brands use these insights to connect more meaningfully and ethically. Takeaway: Experian’s tools help brands uncover audience insights, enabling more meaningful and ethical connections. 2. Where does AI actually save time, and improve results? Running campaigns is time-consuming. Solutions like Agentic AI now orchestrate end-to-end campaign workflows, audience building, trafficking, QA, pacing, and routine optimizations, so teams focus on strategy and creativity. Many leaders (94%) are investing broadly in AI to drive efficiency and impact, and 49% of marketers use it daily for image and video generation, shifting repetitive tasks from people to tools. By quickly combining past and current performance data, AI can pre-optimize before launch and refine mid-flight, while marketers steer the message and experience. "AI uses past campaign data to optimize performance before launch, continues learning during the campaign, and refines strategies based on the insights it generates, driving better results over time.”Howard Luks Takeaway: Experian’s solutions streamline campaign workflows, allowing marketers to focus on creativity and strategy while improving results. 3. How do AI and human strategy work together in real time? AI handles real-time data analysis and optimization, freeing marketers to focus on strategy, messaging, and creativity. By defining audiences once and activating them across platforms, teams can adapt quickly and confidently. At Experian, we combine machine intelligence with human insight to deliver smarter, more agile campaigns. “AI analyzes data, pulls insights, and automates optimizations, allowing marketers to focus on strategy, messaging, and creativity instead of spending time digging through numbers and data."Lizzie Chapman Takeaway: Experian solutions empower marketers to adapt quickly and confidently, combining human strategy with insights. 4. What does privacy-first look like now? Relying on simple, static data points is no longer enough. A modern approach to identity blends deterministic data (like known identifiers) with modeled components, ensuring data remains de-identified where possible. Clear, transparent guardrails, permitted-use policies, retention limits, sensitive-category blocks, and audit trails, help brands balance personalization with privacy, build trust, and respect user choice. "A new blend of identity systems combines deterministic data, known identifiers, and model driven components, creating fresh ways to address identity and activate campaigns with precision.” Vlad Stesin Takeaway: Experian’s privacy-first identity solutions help brands balance personalization with safety, ensuring trust and compliance. 5. Which new data signals matter, and why? AI is unlocking a new generation of data signals, like content context, sentiment, emotional tone, suitability, attention, and commerce intent, that go beyond legacy identifiers like cookies and demographics. These signals can help brand messages appear in the most relevant environments and by high-value audiences. Used well, they improve relevance, avoid placements near unsuitable or off-brand content, and drive stronger campaign outcomes. "Unlocking new data sets (like emotion, sentiment, and context), AI is creating innovative ways to connect client content with advertising opportunities and rethink how we approach the market.” Sam Bloom Takeaway: Experian’s solutions use advanced data signals to help marketers create more effective and innovative campaigns. Why Experian for human-centered AI? We deliver on the promise of AI-powered marketing through five pillars: See audiences clearly across households, individuals, and devices. Recommend next‑best audiences and automate setup for faster execution. Adapt in real‑time to keep relevance high. Innovate responsibly with strong governance and transparency. Plan, activate, and measure campaigns on one unified platform. The future of intelligent marketing AI will keep accelerating, but the goal stands: make marketing more human. Teams that blend privacy‑first identity, predictive insight, AI‑powered simplicity, and real‑time intelligence will earn trust and drive outcomes. Experian helps you bring those pieces together so every campaign moves from assumptions to clarity, and from activity to measurable results. Talk to Experian about building human-centered AI into your marketing strategy AI marketing trends FAQs How does AI help marketers understand audiences better? AI analyzes complex signals, behaviors, values, and mindsets to provide a clearer picture of what matters to audiences. That clarity makes messaging feel personal and relevant. Learn more about Experian’s Digital Graph and how it can help marketers understand audiences better. Where is AI improving campaign efficiency today? Automation reduces manual setup and reporting, so teams focus on strategy and creative. Nearly half of marketers (49%) use AI daily for image and video generation, reflecting this shift. What does “smarter activation across platforms” mean? Smarter activation across platforms means defining audiences once, then carrying them across channels with live feedback, so relevance and suitability stay high. See how Experian enables smarter activation with our data and identity solutions. How is AI changing identity? Privacy‑first identity blends deterministic and modeled components, keeping data de‑identified where possible. Experian’s solutions balance personalization with safety. Learn about Experian’s identity solutions is changing identity. Why is structured data important for AI‑driven marketing? AI systems rely heavily on brand‑managed sources. 86% of citations come from websites, listings, and reviews, so clean, accurate, structured data makes your answers and your brand more discoverable. Discover how Experian supports structured data for AI-driven marketing. Latest posts