At A Glance
AI learns what your data teaches in 2025, "good data" in AI means accurate, current, consented, and easy to connect, or your models lose relevance and your investments underperform. Experian is leading this next era of responsible data where trust, transparency, and innovation come together to make marketing more human, not less.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:
This is the data AI can trust and the data that keeps marketing relevant, predictive, and privacy-first.
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.
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.
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Outdated data can’t predict tomorrow’s behavior.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.
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.
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.
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:
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
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.
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.
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.
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.
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

Retail media networks (RMNs) are on the brink of a major shift. While they are poised to capture over 20% of ad spend in 2025, on-site monetization won't be the growth driver it once was. With advertisers consolidating spend among just six or seven RMNs on average, including giants like Amazon and Walmart, it’s hard for smaller RMNs to compete. Off-site retail media ad spend is projected to grow 42.1% in 2025 – nearly three times the rate of on-site growth (15.1%), according to eMarketer's November 2024 forecast. This dramatic shift underscores that while on-site placements are maturing, off-site is where the momentum (and money) is heading. To remain competitive, RMNs must move beyond traditional, on-site placements and embrace a broader, more integrated approach to media activation. The future of retail media is about utilizing enriched first-party data to drive performance across the open web, connected TV (CTV), and other digital channels. Break free from your owned and operated properties Historically, RMNs have limited ad placements to their own digital properties. While this approach has delivered high-margin returns – on-site ad margins can reach 70-90%, compared to 20-40% for off-site – it’s also inherently limiting. Retailers only have so much owned inventory to sell, and advertisers demand greater scale and flexibility. As brands push for more reach, RMNs must extend their impact beyond owned-and-operated (O&O) properties. Omnichannel retail media ad spending is forecast to hit $61.2 billion in 2025. Brands are looking beyond retail sites to build integrated, multi-channel strategies that drive results across the funnel.eMarketer Off-site doesn’t just mean digital. Walmart’s recent expansion of its Fuel and Convenience stations – planning to open or remodel 45 in 2025, bringing the total to 450 – shows how physical spaces are also becoming extensions of a retailer’s media network. These locations create new touchpoints where advertisers can engage shoppers with timely, context-aware messaging while they fuel up or grab a snack. These quick-stop environments are ideal for limited-time offers or impulse-triggering messages – especially since 68% of U.S. adults say discounts contribute to their latest in-store impulse purchase. Maximize the value of first-party data One of retail media’s biggest promises is the power of first-party data for precision targeting. While on-site ads are inherently lower-funnel, off-site activation allows advertisers to move up the funnel and apply retailer customer data holistically across the open web. For example, DoorDash and Macy’s now offer self-service audience data to advertisers via The Trade Desk, allowing brands to target consumers programmatically. Meanwhile, Walmart is taking a different approach – cloning The Trade Desk’s technology to maintain its walled garden. These moves demonstrate how retailers are rethinking data monetization strategies to scale beyond O&O limitations. Drive new revenue streams with off-site activation Off-site activation enables RMNs to drive incremental reach on channels where audiences are actively engaging, including CTV, programmatic display, and social media. This expansion allows brands to connect with consumers beyond retail websites. Retailers are also utilizing non-endemic advertising opportunities in environments like gas stations and kiosks. Unlike traditional grocery or apparel aisles, these spaces are brand-neutral, allowing advertisers who don’t sell products in-store to still activate campaigns using retailer data. In fact, 53% of brands have already partnered with a retailer that doesn’t carry their product, and that number is expected to grow as advertisers seek new ways to tap into retail media’s rich targeting capabilities. Retailers looking to extend the value of their data beyond O&O inventory have two primary off-site opportunities: First, they can use an identity graph to resolve customer identifiers into addressable IDs that can be enriched with additional attributes and activated across channels like the open web and CTV. This allows retailers to find and reach known customers with relevant messaging outside of their owned platforms. For example, a grocery RMN can identify lapsed snack buyers and deliver streaming TV ads that reengage them on CTV platforms. CTV retail media ad spending alone is expected to grow 43.1% this year, reaching $4.86 billion, highlighting the appetite for video-based upper-funnel strategies. Second, RMNs can broaden reach by activating first-party audiences, syndicated segments, or custom-built audiences through onboarding capabilities. These audiences can be sent to a variety of programmatic and CTV destinations, enabling advertisers to engage shoppers in high-impact environments. For example, a home improvement retailer can send its audience segments to programmatic ad exchanges, ensuring DIY shoppers see relevant offers even while browsing unrelated sites. Together, these approaches allow retailers to monetize their data more effectively while giving brands the ability to reach consumers in moments that matter beyond just retail websites and apps. Scale and measure success with data partnerships For smaller RMNs to compete with larger players, they need more than just inventory – they need the ability to scale campaigns and prove performance. Data partnerships play a critical role in both expansion and measurement. Measurement remains one of the biggest challenges for RMNs moving off-site. On-site retail media offers closed-loop attribution, but off-site activations introduce complexity. Retailers can work with an identity resolution partner like Experian to connect ad exposures to actual retail outcomes, such as store visits or purchases, across digital and physical environments. Whether it's through pixels placed on campaign ads or TV impression logs, these connections help RMNs demonstrate real impact. This approach helps unify disparate data – such as a CTV ad exposure and a subsequent online or in-store purchase – into a clear, measurable outcome. These insights not only show what’s working, but help RMNs optimize future campaigns and provide advertisers with transparent, third-party-validated reporting. As retailers like Walmart integrate loyalty programs like Walmart+ into their physical extensions, they gain valuable behavioral insights into how customers shop across formats – from fueling up to filling carts. These data signals help refine identity graphs and improve measurement across increasingly hybrid consumer journeys. Beyond ads: The data monetization opportunity Smaller RMNs may struggle to scale ad-supported revenue, but there’s another path forward: Data-as-a-Service (DaaS). Providing anonymized, privacy-compliant audience insights to brands offers a high-margin, scalable revenue stream. In fact, some retailers are already embracing this model by licensing their data to programmatic platforms. A playbook for smaller RMNs to win off-site The future of retail media belongs to those who harness data to influence consumer behavior across all digital marketing channels. To succeed, RMNs should focus on: Moving beyond owned inventory: Activate first-party data across CTV, social, and programmatic channels to meet advertisers where their audiences are. Expanding reach through partnerships: Collaborate with identity resolution providers to maximize match rates and campaign effectiveness. Building a full-funnel offering: Position off-site retail media as a brand-building play, tapping into ad budgets that traditionally fund upper-funnel campaigns. Monetizing data, not just ads: Explore DaaS models to generate passive revenue. The time to move off-site is now Retailers that wait too long to embrace off-site activation risk falling behind. Those that expand beyond their owned inventory, invest in off-site data strategies, and build strategic partnerships will be the ones that shape the future of retail media. Experian isn’t just part of the RMN conversation. We’re driving it. Let’s talk. Connect with our team Latest posts

Not all customers are the same, so why waste your budget marketing to them like they are? McKinsey research shows that 71% of consumers want personalized shopping experiences, and 76% get frustrated when they don’t have them. That’s where demographic segmentation comes in. But what is demographic segmentation, exactly? We define it as a process that helps you categorize your audience into meaningful demographic groups so you can reach the right people with impactful custom messages. Businesses across industries are partnering with Experian to power smarter decisions and better results through solutions like demographic segmentation — but what does this look like in action? This article breaks down five real-world demographic segmentation examples, showing how businesses have worked with us to drive measurable success so you can see exactly how it can work for you. What is demographic segmentation? Demographic segmentation involves dividing your audience into smaller, more specific groups based on shared demographics like income, education, gender, job, family status, and more to gain a more granular understanding of your brand’s target segments. The better you know your audience, the better you speak to their unique needs — and the more effective your campaigns will be, as you’ll be able to target each segment with highly personalized content that resonates. For instance, a company might market a new tech gadget to young adults in one way while promoting the same product to families with young children in a completely different way, ensuring the message speaks to each group’s lifestyle and priorities. Demographic segmentation attributes Some of the most common attributes used in demographic segmentation include: Age Each age group has different wants and needs. A new video game might catch the eye of teenagers, while a retirement plan is more likely to appeal to someone in their 50s or 60s. Gender Gender impacts preference for certain products, from fashion to gadgets, so knowing who you’re talking to helps make your marketing more relevant. Income Someone with a higher income might be more likely to purchase premium products, while someone on a budget will respond better to discounts or value-based offers. Education The level of education a person has can influence what kind of messaging will resonate with them, whether it’s complex or more straightforward. Occupation A marketing message targeting busy professionals might differ from one aimed at students or retirees. Occupation can tell you what’s important to a person in terms of their needs and lifestyle. Family Status A family with young kids likely has different priorities than a single person or a couple without children. You can adapt your messaging to be more relevant to what matters most to them, like convenience or value. Benefits of using demographic segmentation Demographic segmentation offers several valuable benefits for marketers. Here’s why it’s one of the most commonly used and effective ways to target audiences: Improved targeting and personalization: Demographic segmentation powers highly customized campaigns so you can cater to different income levels, family structures, job types, and so forth. B2C brands can provide offers based on factors like age, income, and gender, while B2B brands can target by occupation to reach decision-makers. Better product and service development: Understanding which demographics use your product or service is a great way to inform future improvements. Higher engagement: With highly customized content, you can speak directly to specific demographic groups and increase engagement. Cost efficiency: As you target the most relevant segments, you optimize your spending around the most likely buyers and will see better returns. Increased conversion and retention: Relevant, targeted messaging leads to higher conversion rates, and when people feel understood, they’ll want to keep coming back. Clearer customer insights: Demographic data provides precise, actionable insights for refining your marketing strategy. Simplicity and effectiveness: Demographic insights are immediately actionable and easy to implement, which gives you a great starting point for focused campaigns. When to use other segmentation types While demographic segmentation provides valuable consumer insights, there are times when other approaches may offer a more effective strategy: Your business provides location-dependent services. If you strictly serve a local area, geographic segmentation would be more effective in targeting customers based on location. You have access to detailed behavioral data. If you collect data on customer behavior (like browsing history or purchase patterns), behavioral segmentation would allow for more personalized targeting than demographics. You're selling high-end luxury products. While income is a useful demographic variable, factors like values, aspirations, and lifestyle better capture the desires of luxury consumers. Your target audience shares similar behaviors, regardless of demographic factors. Behavioral segmentation might offer more insight if your customers engage with your product or service based on shared behaviors rather than demographic traits. Your product or service targets specific needs or pain points. Segmenting by need or issue rather than traditional demographic variables would likely yield better results if you're offering a solution to a particular problem (like a health-related product). How our customers are using demographic segmentation to produce tangible results Demographic segmentation is about knowing your audience and using data to create marketing strategies that drive measurable outcomes. Let’s look at some real-world use cases from brands like yours that have been successful in this effort, working with Experian to translate demographic insights into significant business growth. Use case #1: Identifying customer spending potential to boost growth for a retail chain Objective A large retail chain wanted to understand the spending potential of each customer in their stores. Their goal was to uncover and maximize untapped spending potential. Solution The large retail chain licensed Marketing Attributes to identify the top demographic factors that drove spending in the retail store the previous year. The four key drivers were: Age Income Family structure (household composition) Location/region Results By combining these attributes to create custom segments, we uncovered two valuable annual estimates: Potential spend: A conservative estimate of how much a customer could spend if they reached the top 20% of spenders within their specific demographic segment (based on data from the highest spenders). Unrealized spend: The difference between a customer's annual potential spend and their current spend. An estimate of how much more they could be spending each year. These demographic segments provided the marketing strategy the retail chain used to target $1.1 billion in unrealized spend. This revealed how much additional revenue could be captured by targeting the right customers with tailored marketing and offers through demographic segmentation. Use case #2: Helping a financial institution identify regional DE&I opportunities Objective A large financial institution needed help identifying regional diversity, equity, and inclusion (DE&I) opportunities. They wanted to better prioritize their outreach to underserved communities in the Los Angeles area. Solution We provided the data and insights to pinpoint specific areas needing attention. We used three key indices to analyze the region: Income index: Measured each underserved economic group by comparing the percentage of low-to-moderate income consumers against the entire L.A. area. Ethnicity index: Measured the percentage of consumers by ethnicity, such as African-American, Hispanic, Asian, and others, against the entire L.A. area. Credit index: Identified potential credit disparities by looking at the average FICO score and the percentage of customers with credit accounts against the entire L.A. area. Results Our client received an analytics dashboard to track and report these metrics, providing clear, traceable data to prioritize DE&I outreach. This dashboard helped them measure progress toward more inclusive practices. Use case #3: Segmenting a health supplement ambassador program for enhanced engagement Objective A health supplement company wanted to identify specific segments within their ambassador program to provide better support and increase engagement. Solution We developed tailored customer segments to address specific needs and behaviors. These segments included: Young and independent: Younger, lower-income singles or starter households who are just beginning to establish their own lives. Families with ends to meet: Young and middle-aged families with kids who are budget-conscious, often using coupons and enjoying fast food. High-end families: Middle-aged families with kids and high incomes, financially secure big spenders who also give to charities. Empty nesters: Older households with no kids who focus on cooking at home and may have more disposable income. Results Segmenting at registration allowed for more effective communication and engagement with prospects. Customized messaging, guided by customer demographics and purchasing behaviors, improved acquisition and retention by helping the right messages reach the appropriate individuals through their preferred channels. Use case #4: Comparing customer bases: Insights for a retailer across two cities Objective A national retailer with locations in two major cities (their home base city and a recent expansion city) wanted to understand how different their customer base was in each city. They aimed to uncover key demographic and behavioral differences to refine their marketing strategies and ensure each location received the most relevant messaging and promotions. Solution We analyzed each city’s customers across a wide range of characteristics:. Demographics: The expansion city had a younger population with more families, while the home base city had an older and more established customer base. Purchasing behavior: Customers in the expansion city spent more per transaction than those in the home base city. Preferred marketing approach: Customers in the home base city were likelier to be Brand Loyalists, responding well to familiar, trust-driven messaging. Shoppers in the expansion city were Savvy Researchers who responded better to value-based content and product comparisons. Results Using these insights, the retailer tailored its marketing approach to align with each location’s customer base: Home base city: Focused on maintaining loyalty by emphasizing brand trust and highlighting long-term customer benefits. Expansion city: Positioned marketing to appeal to younger, family-focused consumers to showcase high-value purchases and competitive pricing These adjustments led to improved engagement and higher sales in both cities. Use case #5: Optimizing direct mail to help a nationwide retailer maximize impact on a limited budget Objective Facing a shrinking marketing budget, a nationwide retailer needed to refine their direct mail strategy to reach the right customers while reducing costs. Solution We developed a comprehensive dashboard summarizing two dozen recent direct mail campaigns, which allowed the retailer to: Understand the demographic composition of high-response customers across different regions. Identify key patterns in response rates, helping them pinpoint the most receptive audiences. Discover that the Power Elite Mosaic Group representing affluent, high-spending households comprised only 17% of their mailed audience but accounted for 47% of responses. Results With these insights, the retailer restructured their direct mail strategy to target the highest-performing segments. Changes like these led to a 30% reduction in mailing costs while retaining 92% of sales, proving that strategic segmentation can drive efficiency without sacrificing revenue. Explore demographic segmentation with Experian Now that we’ve defined demographic segmentation and provided real-world examples, it’s time to explore how Experian data can help you better understand and connect with your audience. Experian’s Marketing Attributes provide rich, privacy-conscious insights into consumer demographics, lifestyles, and behaviors. These insights empower marketers to personalize experiences, refine targeting strategies, and make more informed decisions. With a deeper understanding of who your customers are, you can create more meaningful, impactful campaigns that drive stronger engagement and results. Connect with us today to see how our data and expertise can improve your targeting, personalization, and campaign performance. Connect with us Latest posts

In our Ask the Expert series, we interview leaders from our partner organizations who are helping lead their brands to new heights in AdTech. Today’s interview is with Brian Mandelbaum, CEO and Co-Founder at Attain. About Attain Built for privacy — with visibility across all retailers, verticals and purchases — Attain provides solutions for the modern marketer. Its real-time measurement and optimization solutions coupled with high-fidelity audiences and proprietary insights enable marketers to drive valuable business outcomes. The power of transaction-based audiences Attain’s real-time transaction data provides a 360-degree view of consumer behavior. What makes this approach more effective than traditional demographic or behavioral targeting? Attain is the industry’s most trusted source of live purchase data, powered by a robust panel of 8 million fully permissioned consumers. Our platform delivers unmatched, real-time visibility into consumer purchase behavior across retailers, industries, and payment methods. Marketers gain deep insights — such as in-store vs. online purchases, payment methods, purchase frequency, cart contents, and average transaction value — enabling more precise audience targeting and media strategies. With Attain’s rich, transaction-based data, marketers can optimize campaigns with direct, actionable sales signals. Ensuring data accuracy and relevance Attain curates audiences using real-time transaction data, but advertisers often ask whether this data is deterministic or probabilistic. Can you clarify your methodology, and if probabilistic, how do you ensure accuracy and representation across the entire US population? Our transaction data comes directly from the largest live purchase data panel in the U.S. Covering over 10,000+ merchants and $600B in cumulative spend, our dataset offers a complete and dynamic view of real-world purchase behavior. Using advanced machine learning, we scale this data to represent the entire U.S. population with unmatched accuracy, ensuring a balanced and unbiased reflection of consumer spending patterns. Our rigorous methodology eliminates outliers, continuously optimizing for precision and stability, so marketers can trust our insights for better targeting, measurement, and optimization. Privacy-first data practices Attain is built on a privacy-first, consumer-permissioned model. There are many ways to capture purchase data—why did Attain choose a panel-based approach, and how does this method compare to other collection strategies in terms of accuracy, scale, and compliance? Attain’s panel-based approach is the foundation of our privacy-first, consumer-permissioned model. By capturing real-time transaction data directly from our opted-in consumer panel, we ensure unmatched accuracy and ethical data sourcing — paramount in today’s privacy-conscious world. In exchange for sharing their data, consumers receive valuable benefits like early wages, savings tools, and shopping rewards, with no hidden fees. Unlike legacy third party data providers, our directly sourced transaction data provides deeper, more precise insights, enabling highly granular and actionable audience segments. Our continuously growing panel reflects a broad cross-section of U.S. consumers while maintaining strict privacy and compliance standards. We fully adhere to regulations like CCPA and GDPR, giving both consumers and advertisers confidence in the responsible use of data. Attain’s approach delivers the ideal balance of accuracy, scale, and compliance—while prioritizing consumer trust. Cross-channel addressability With brands activating audiences across display, mobile, and CTV, how does Attain’s purchase data help advertisers refine their cross-channel strategies? Attain’s purchase data empowers advertisers to refine cross-channel strategies with smarter, data-driven insights. Our real-time transaction-based audiences enable scalable activation across display, social, online video, and addressable TV — ensuring campaigns reach high-intent buyers more likely to convert. By applying purchase-based audiences across all channels, marketers are utilizing the strongest signals possible, which enables a more effective holistic strategy to drive to that ultimate sales outcome. Whether through social media, TV/CTV, mobile, or programmatic platforms, Attain helps brands connect with consumers at key moments in their buying journey, maximizing media impact with real behavioral insights instead of proxies. With an expansive and growing network of media partners, Attain ensures brands reach their audiences wherever they are, delivering consistent, high-impact messaging. Whether optimizing for brand awareness or performance, our data helps marketers make smarter decisions to drive superior results. Proven performance with live purchase feedback Attain moves beyond traditional proxy metrics by providing live purchase data. How does this help advertisers optimize campaigns while they’re still running? What sets Attain’s audiences apart isn’t just the data fidelity and holistic coverage of consumer behavior, it's that they’re built and validated using live, privacy-safe purchase signals. Advertisers can execute campaigns confidently, knowing that they’re reaching real consumers based on recent, real-world transactions, not outdated models or inferred, probabilistic behaviors. Attain’s ability to measure sales lift across a wide range of inputs means that marketers can easily understand which audiences are driving actual sales outcomes during flight. This unlocks smarter mid-campaign optimizations, discovering new audiences, and fine-tuning targeting — to ensure audience performance continually improves against real revenue goals. Attain’s closed-loop approach gives advertisers a faster path from targeting to transaction, helping brands maximize the value of every impression. Industry-specific use cases Beyond CPG, Attain supports industries like QSR, retail, and financial services. Can you share a compelling example of how brands in these verticals are utilizing your audiences? Attain’s audiences provide a comprehensive view of the consumer, capturing all aspects of their purchase behaviors — from travel and dining to TV content consumption and shopping habits. This broad perspective offers brands a far richer set of buying signals than ever before, enabling them to make more informed decisions across the entire consumer journey. Quick service restaurants (QSR): With a comprehensive view across all transaction types (cash, credit, debit) – Attain enables QSRs to capture a full picture of customer spend at their nationwide locations. Ensuring these brands have holistic coverage across all sales channels, powered by a direct relationship with the consumer, Attain captures transactions both in-store, online, and through 3P delivery apps like UberEats and Grubhub. This powers Attain’s deep insights, which QSRs can use for intelligent, precise targeting- including frequent visitors, competitive share, products purchased, and more. QSRs can use this data to solve a variety of business objectives, like retention/growth, competitive conquesting, and more. Retail: In retail, Attain provides a wide range of audience segments, including loyalty shoppers, in-market buyers, competitive shoppers, and even adjacent buyers who may be interested in similar products. By combining these segments, retailers can optimize their campaigns to target real-time shoppers with the highest intent, rather than relying on outdated or generalized profiles that other providers might offer. Additionally, with our industry-leading refresh rate, brands benefit from the most up-to-date data, ensuring their campaigns are always aligned with the latest consumer behaviors. Financial services: In the financial services sector, Attain’s purchase data helps identify consumers who are actively considering financial products such as credit cards or loans. By understanding their purchasing behaviors, marketers can deliver highly personalized and relevant offers to those already displaying intent, leading to better conversion rates and more effective acquisition strategies. Integration with Experian's marketplace Attain is now available through the Experian marketplace. How does this integration make it easier for advertisers to activate and scale your audiences? Attain’s integration with Experian marketplace makes it easier than ever for advertisers to activate our purchase-based audiences across TV, social, and programmatic. This partnership makes Attain’s data even more accessible, supporting our mission to build the most comprehensive and trusted consumer data ecosystem. With direct access to our real-time audiences within Experian’s marketplace, advertisers can more efficiently launch campaigns at scale and make more precise, data-driven decisions. As one of Experian’s inaugural partners, we’ve already seen strong adoption and demand, reinforcing the value of this partnership. The future of transaction-based targeting As the use of transaction data in advertising continues to grow, what changes do you anticipate in how brands will apply it for targeting and measurement? And how is Attain evolving its approach to support those shifts? As transaction data reshapes advertising, brands can shift from targeting probabilistic audiences to reaching high-intent consumers for greater ad relevance and conversions. Purchase data also unlocks highly accurate incrementality measurement, closing the loop and revealing which tactics and channels drive true incremental sales. Attain’s platform is built for outcomes-driven advertising, capturing data across the entire media cycle to continuously optimize performance. As we continue to make investments in AI and machine learning into our platform, our insights will become even more actionable and efficient — helping brands maximize impact, drive incrementality, and fuel long-term growth. Thanks for the interview. Any recommendations for our readers if they want to learn more? To explore our audience segments, visit the Attain website or contact your Experian account representative to schedule your free match test. Contact us today About our expert Brian Mandelbaum, CEO and Co-Founder, Attain Brian Mandelbaum, a veteran entrepreneur and investor, is the co-founder and CEO of Attain, North America’s largest opt-in purchase platform. Prior to Attain, Brian founded Clearstream TV, a data-enabled video distribution platform acquired by Engine Group in 2015. He brings over 20 years of experience in data-driven digital media, collaborating with top agencies and major brands. Latest posts







