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Marketing without segmentation is a lot like shouting into a crowded room and hoping the right person hears you. Without a clear way to communicate in a noisy marketing environment, your message gets lost in the mix.
With segmentation, you can identify your target audience, speak to their needs, and deliver the right message at the right moment. Companies that use segmentation are 130% more likely to understand customer motivations, resulting in more effective campaigns and deeper audience relationships.
In this article, we’ll break down four of the most effective customer segmentation methods, when to use each, and how Experian’s audience solutions can help.
What is segmentation in marketing?
Segmentation is the process of splitting a large audience into smaller groups that share similar traits, like demographics, location, behavior, or firmographic characteristics. As a marketer, these segments enable you to choose channels, messaging, and offers that resonate with each group.
Whether you’re targeting new homeowners in Texas, loyalty shoppers in retail, or small business decision-makers in finance, segmentation helps you stand out to them and get results.
Why should marketers segment their audiences?
Effective audience segmentation fuels accuracy, performance, and personalization at scale. Here’s why you should invest your time and marketing budget in honing your audience segments.
Maximize your marketing ROI
Nobody wants to waste money talking to the wrong crowd. Using various methods of segmentation, you can focus on those who want to hear from you — and the payoff can be huge. For marketing channels like email, segmentation can drive up to 760% more revenue than non-segmented campaigns. The more targeted your message, the better the return.
Create a unified omnichannel strategy
Segmentation helps ensure that every channel, from email and social media to display, SMS, and direct mail, operates from the same playbook.
Once you define your target audience segments, you also need a trusted identity partner to sync them across platforms and environments. This ensures you can deliver consistent, personalized experiences at every touchpoint and your audience receives the same message in the proper context, regardless of where they engage.
Strengthen customer loyalty
Roughly 75% of consumers are loyal to brands that “get” them. When you strive to understand your customers, they’re more likely to stay. Segmentation enables you to personalize communications based on your target segment’s values, behaviors, or preferences, encouraging repeat business.
Expand into new markets
With segmentation, you can analyze existing customers to identify common traits and use that data to pinpoint similar groups in new regions or markets. For example, if your top customers are middle-class parents in suburban areas, you can target lookalike segments in other cities with tailored messaging.
This makes it easier to expand with confidence, knowing you’re reaching people who are more likely to convert.
Lower customer acquisition costs
Rather than forcing you to cast a wide net, segmentation enables you to focus your budget on high-potential audiences across channels, reduce acquisition costs, and minimize wasted spend on low-intent audiences.
Four segmentation methods and examples
Let’s look at four different methods of market segmentation. We’ll define each, share when to use them, and give real-world examples to help you apply them.
1. Demographic segmentation
Demographic segmentation breaks your audience into groups based on gender, income, age, education, marital status, occupation, and household size. It’s one of the most foundational segmentation methods because it’s easy to implement and often tied directly to buying behavior.
Demographic data makes it easier to get the tone, offer, and channel right from the start. And when you combine demographic segmentation with other segmentation methods, such as behavior or location, the impact multiplies.
When to use it
Use demographic segmentation when your product or service is clearly more relevant to people in a specific life stage, income bracket, or household type.
Among all methods of market segmentation, demographic data is often the easiest starting point. It’s especially effective for industries such as financial services, healthcare, education, retail, and others, where consumer needs change based on demographics.
Examples
As a real-world example, a health supplement company used Experian data to segment its ambassador program audience into four demographic groups based on lifestyle and household makeup. These included younger singles, value-seeking families, high-income spenders, and older empty nesters.
Applying these insights at registration allowed the brand to deliver personalized, channel-specific communications that boosted acquisition and retention. The approach led to stronger engagement and more meaningful customer connections.
2. Geographic segmentation
This method of market segmentation categorizes people by location, including country, region, state, city, zip code, or even climate. It’s a simple yet effective way to tailor your marketing, as location often influences everything from lifestyle and language to shopping habits and product needs. It’s most often used among brands with physical locations or region-specific campaigns.
Whether you’re promoting snow boots in Colorado or sunscreen in California, geographic segmentation helps you stay relevant to the local context.
When to use it
Geographic segmentation is ideal when your offer or message changes depending on climate, culture, availability, or local regulations. It’s also helpful for planning market expansion or testing the performance of different methods of market segmentation across regions.
Examples
One home furnishings retailer partnered with Experian to understand how customer needs varied across store locations. Using a mix of client data and Experian demographics, we segmented stores based on their surrounding customer base, like urban, white-collar shoppers in metro centers versus lower-income households in more remote cities.
These insights enabled the retailer to tailor inventory, marketing strategies, and ad copy for each store type, resulting in more relevant customer experiences.
3. Behavioral segmentation
Behavioral segmentation centers on how people live their lives — their interests, habits, and decision-making patterns. It includes factors like past purchases, engagement frequency, brand loyalty, product usage, browsing patterns, and responsiveness to offers or promotions.
Among all of the segmentation methods, this one provides insight into intent, helping you go beyond who your audience is to understand what they do. You can use behavioral insights to re-engage former customers with relevant offers, reward loyal buyers with personalized perks, or guide high-intent shoppers toward conversion with timely nudges.
When to use it
Behavioral segmentation is best when you want to personalize based on intent, habits, or engagement stage. It’s particularly useful for retention, reactivation, or cross-selling strategies.
Examples
In practice, a national big-box retailer partnered with Experian to better understand customer behavior during grocery store visits. The goal was to identify distinct “trip missions” that could drive category trial and increase basket size. We analyzed everything from basket contents to customer composition and segmented visits into 11 unique missions.
For example, the “All Aisles Online” segment represented large households (often homeowners with families) stocking up on household staples through online orders. In contrast, the “Marketable Mission” segment captured smaller, likely renter households making quick trips for non-essentials.
These behavioral insights empowered the retailer to adjust promotions based on the intent behind each visit, strengthen customer relationships, and drive growth.
4. Firmographic segmentation (B2B)
Firmographic segmentation is like demographic segmentation for businesses. It groups B2B audiences based on attributes such as annual revenue, location, company size, industry, and organizational structure. You can also segment by job title or decision-maker role to better target key stakeholders.
This method is great for aligning your messaging, sales strategy, or product offerings with the unique needs of various business types. A startup in the tech sector will likely respond to a very different pitch than an enterprise manufacturer, and firmographic data helps you speak to both with precision.
When to use it
Use firmographic segmentation when marketing to other businesses, especially when your product or service has different benefits depending on business size or sector.
Examples
Recently, a B2B client partnered with Experian to gain a deeper understanding of the revenue potential of their existing business customers. Using firmographic data, we segmented the client’s customers into distinct groups based on the characteristics most strongly tied to spending behavior.
For each segment, we calculated potential spend, defined as the 80th percentile of annual spend within that segment. This allowed the client to identify high-value accounts with untapped growth potential.
For example, one customer, ABC Construction, had spent $4,750. But based on their segment’s profile, their annual potential was $9,000. That insight revealed a $4,250 opportunity to deepen the relationship through more targeted marketing and sales efforts.
Best practices for market segmentation
Regardless of the segmentation method you use, the following best practices will help you maximize the benefits of your efforts.
Start with clean, reliable data
Segments are only as good as the data behind them. If your data is outdated, inaccurate, or incomplete, your segments will result in ineffective targeting and a wasted budget. Utilize accurate, compliant, up-to-date sources like Experian Marketing Data, ranked #1 in accuracy by Truthset, to ensure your targeting is on point.
Test and refine segments continuously
Business goals, market conditions, and behaviors are constantly changing. What worked last month or even last week might not work today. By adjusting your segments over time, you make sure your marketing stays relevant, focused, and effective. Use A/B testing, performance metrics, and audience analytics to iterate on your segments and improve results over time.
Align segments with personalized messaging and offers
Each segment has distinct needs, preferences, and motivations, which means generic messaging won’t resonate effectively. Once you’ve built your segments, personalize your creative, copy, and offers to appeal to each group and increase the likelihood of engagement and conversions.
Integrate segmentation across all platforms
If someone sees one message in an email and a completely different one in an ad or on your website, it creates confusion and weakens trust. From CRMs and email platforms to ad tech and analytics tools, make sure your segmentation method is applied consistently across every channel to improve performance and build a cohesive brand experience.
Segment your audiences with Experian
Effective audience segmentation is at the heart of every successful marketing strategy, but in this fragmented, privacy-conscious landscape, grouping your audience into meaningful, actionable subgroups is more challenging than ever. That’s where we come in.
With coverage of the entire U.S. population, Experian helps marketers define and categorize broad audiences into precise segments using rich data on demographics, behaviors, financial profiles, and lifestyle traits. These insights make it easier to personalize messaging, optimize media spend, and drive better outcomes.
From ready-to-use syndicated audiences to custom segments and even Contextually-Indexed Audiences that align targeting with content, Experian offers flexible segmentation solutions that perform across digital, TV, programmatic, and social channels.
In our most recent release, we introduced over 750 new and updated audience segments across key categories, including a brand-new category for Experian, giving marketers more accurate, behavior-based targeting options than ever before.
- 135+ new CPG audiences, a brand-new category for Experian, built from opt-in loyalty card and receipt scan data
- 240+ new automotive audiences covering ownership and in-market shoppers
- 100+ new high-spending behavior audiences focused on specific merchant categories
- 24 new wealth and income segments with refined household net worth tiers
- 13 new lifestyle-based housing audiences for family- and household-focused targeting
- 250+ refreshed financial segments with improved naming conventions for better discoverability and clarity
Together, these segments give marketers more accuracy to reach high-intent consumers based on real-world behaviors, spending patterns, and financial capacity.
Audience solutions powered by consumer insights
Experian Marketing Data, one of the most comprehensive and accurate consumer databases in the U.S., is the core of our segmentation capabilities. Backed by over 5,000 demographic and behavioral attributes, it helps you understand not just who your customers are but how they live, shop, spend, and engage, too.
Each audience segment is built with privacy and precision in mind, using a blend of demographic data, financial behaviors, lifestyle signals, and media habits. With these consumer insights, we’ll help you uncover meaningful patterns that lead to smarter strategy.
Experian’s pre-built audiences
Our syndicated audiences are pre-built, ready-to-activate segments based on shared characteristics from age and income to purchase behavior and lifestyle indicators. When speed and scale are a priority, these segments offer a fast, effective way to reach your target audience.
Experian’s 2,400+ syndicated audiences are available directly on over 30 leading television, social, and programmatic advertising platforms, as well as within Audigent for activation within private marketplaces (PMPs).
Here’s what’s new from our August 2025 release:
- CPG shoppers by category (e.g., Frozen Food Shoppers, Multi-Vitamin Shoppers)
- Luxury EV owners and auto brand shoppers (e.g., Rivian, Polestar, Cadillac)
- High spenders in specific categories (e.g., men’s grooming and women’s accessories)
- Ultra high-net-worth households (e.g., Net Worth $50M+) and likely home sellers
- Young Family Homeowners and Growing Family Apartment Renters
Custom audiences for specialized targeting
Need a custom audience? Reach out to our audience team, and we can help you build and activate an Experian audience on your preferred platform. Additionally, work with Experian’s network of data providers to build audiences and send to an Audigent PMP for activation.
Contextually-Indexed Audiences
Experian’s Contextually-Indexed Audiences offer a privacy-safe way to reach relevant consumers in the moments that matter without relying on identity signals or third-party cookies. These segments combine Experian’s consumer insights with page-level content signals, enabling you to align targeting with intent and mindset, even in cookieless or ID-constrained environments.
Want to take your segmentation strategy to the next level? Let’s talk. We’ll help you define your audience in ways that drive real results.
Talk to our team about your segmentation methods today
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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. 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 AdTech 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. 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 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