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Artificial intelligence (AI) and connected TV (CTV) have a perfect synergy that’s revolutionizing how advertisers connect with their audiences. CTV serves as a medium for streaming content, while AI acts as a sophisticated technology that improves the performance of CTV advertising campaigns. The integration of these two technologies has paved the way for advertisers to reach their target audience more effectively, making CTV advertising a powerful and efficient tool.
In this blog post, we’ll dive into how these technologies work together —and why you should jump on board with AI for CTV advertising if you haven’t already.
Why AI and CTV are a great match
CTV and AI are transforming how advertisers connect with their audiences and improving the performance of their advertising campaigns in the CTV space. They work together to make advertising smarter and more enjoyable for everyone involved. AI uses sophisticated computer programs to analyze and understand data, while CTV refers to the streaming services that consumers use at home. But what makes them a great match in advertising?
AI uses data to determine which TV ads are most exciting and relevant to certain people, and it can even adjust ads in real time to ensure viewers are always getting the most personalized experience. AI can provide suggestions to viewers based on previously watched content to help them find what they’d enjoy watching next. To sum it up, AI allows for:
- Precise targeting: AI uses data to determine which TV ads are most exciting and relevant to certain people.
- Personalization: AI can adjust ads in real time to ensure viewers are always getting the most personalized experience.
- Effective ad insertion: AI can provide suggestions to viewers based on previously watched content to help them find what they’d enjoy watching next.
CTV facilitates these AI-driven strategies for enhanced user engagement and satisfaction.
The rising popularity of CTV
CTV has become increasingly popular as people change the way they watch TV. Instead of the traditional approach, more viewers are now choosing CTV platforms for their entertainment. One of the main reasons for this shift is that CTV offers greater flexibility and lets viewers watch content at their convenience. The ability to skip ads on many CTV platforms also improves the experience.
CTV offers a great opportunity to interact with your target audience in a more engaging way. CTV allows for highly targeted advertising capabilities so you can reach specific demographics and households with tailored messages. Additionally, CTV provides valuable data insights that enable you to measure campaign effectiveness accurately.
If you haven’t embraced this advertising channel yet, you may be missing out on a growing and engaged audience. Here are three reasons you should add CTV to your advertising strategy.
Global video ad impressions
As a global platform, CTV has the unique ability to reach audiences worldwide. Unlike traditional TV, CTV transcends geographical boundaries and brings marketers a global audience, which makes it an ideal channel for global ad campaigns. No matter your target audience, they’re consuming content on CTV. In fact, a recent study showed that 51% of global video ad impressions came from CTV in 2022.
This abundance of global video ad impressions generates vast amounts of data, which AI can process in real time to help you make data-driven decisions and optimize your campaigns for diverse international audiences. AI can analyze viewer data from various regions, identify audience preferences and behaviors across borders, and tailor ad content accordingly. These data analysis capabilities ensure your ads get in front of the right viewers.
Viewers prefer ad-supported CTV
In 2020, the viewing time of ad-supported CTV surged by 55% while subscription video on demand decreased by 30%, according to TVision Insights. Viewers have a well-established preference for ad-supported CTV due, in part, to cost-effective access to premium content. Viewers are more engaged and less resistant to ads, as AI tailors ad content to viewer preferences and behavior to enhance ad relevance.
AI-powered insights can also aid in viewer retention and help you optimize your CTV campaigns. By accommodating viewers’ preference for ad-supported CTV and harnessing AI to improve the ad experience, you’re more likely to be successful in your marketing efforts.
CTV outpaces mobile and desktop for digital video viewing
eMarketer recently reported that U.S. adults spend 7.5+ hours each day on CTV —more than half of their digital video viewing time. Comparatively, they only spend 37.5% of their viewing time on mobile and 10% on desktops and laptops. These statistics demonstrate that CTV has become the preferred platform for digital video consumption, as viewers enjoy larger screens with superior quality for an immersive experience.
It’s important to note that AI is an essential CTV marketing tool, as it allows for precise targeting and content optimization. By utilizing AI on CTV, you can take advantage of this trend and deliver more engaging and effective campaigns to a growing and engaged audience.
How is AI already being used in CTV?
CTV has been integrated with AI across various facets and has revolutionized the television landscape. Here’s a look at how AI is already shaping the CTV experience:
Generative AI ads
Generative AI ads are taking CTV personalization to a whole new level. These innovative ads are customized versions of the same CTV ad to suit individual viewers. Some AI tools can generate several versions of the same CTV ad — swapping the actor’s clothing and voiceover elements like store locations, local deals, promo codes, and more — and can create up to thousands of personalized iterations in just a few seconds. Such capabilities are a game-changing approach to connecting with your audience.
Next, we dive into the advantages and impact of generative AI ads, and explore their transformative role in CTV advertising.
Contextual ads vs personal data
Generative AI ads use personal data, such as viewing history and demographics, to create highly personalized ad experiences. This sets them apart from contextual ads, which rely solely on the content being viewed. Using AI to harness this data, you can move beyond traditional contextual targeting and ensure your ads connect with viewers on a more individualized level.
Generative AI ads can be used to A/B test
Generative AI ads are not just about personalization; they also open the door to A/B testing. Being able to create several versions of one ad quickly allows you to experiment with various ad elements, such as messaging, visuals, and calls to action, to identify what works best for different segments of your audience and drives the best performance. This flexibility is especially valuable for refining ad campaigns and maximizing their impact.
What’s next for AI-generated ads like this?
The potential of AI-generated ads is exciting. As AI technologies constantly advance, we can expect even more personalized and automated CTV advertising. It’s a good idea to keep up with the latest AI-driven innovations to create more effective ad campaigns in the fast-evolving CTV space. The possibilities are endless, and you’ll likely find the most success when you embrace AI in CTV advertising.
Optimize streaming quality
AI helps viewers enjoy more seamless CTV experiences. By assessing network speed and user preferences, AI optimizes video quality in real time to reduce buffering interruptions. For instance, streaming platforms use AI to adjust video settings based on a user’s connection speed. This guarantees an uninterrupted and enjoyable viewing experience.
Review content for compliance
AI also has a part to play in quality assurance and compliance management. It assesses content alignment with technical parameters and moderates compliance with local age restrictions and privacy regulations. This means AI can identify and filter out unsuitable content to provide a safer and more enjoyable viewing environment for audiences while safeguarding brands from association with undesirable material.
Voice command
AI-powered voice command technology is increasingly used to control CTV viewing. This technology is embedded in streaming devices and smart TVs and allows viewers to interact with their CTV content through voice-activated commands. This personalizes the viewing experience and improves convenience, as it eliminates the need for remote controls.
CTV-integrated voice assistants like Google Assistant, Amazon Alexa, Apple Siri, and Samsung Bixby offer a more human-like interaction with the television, allowing users to give commands and receive tailored responses.
Content recommendations
AI can offer content recommendations that provide viewers a more personalized and engaging experience. Major over-the-top (OTT) services like Netflix, Hulu, and Amazon Prime use AI-driven data analysis to deliver tailored content suggestions to their audiences. By analyzing user habits in detail, AI can recommend content based on factors such as actors, genres, reviews, and countries of origin. This personalized approach helps viewers discover content that matches their preferences and enhances their viewing experience.
Advertising
Programmatic ad buying, driven by AI, automatically matches ad placements to specific audience segments based on behavioral patterns. It improves ad delivery by moving away from gross rating points (GRP) to more intelligent and targeted placements. This benefits marketers by ensuring ads are seen by the right people at the right time. It’s also cost-effective for publishers, as it maximizes the sale of ad spots to suitable buyers.
Automatic content recognition (ACR) technology, which AI powers, is integrated into smart TVs and streaming devices to improve ad relevance. It provides contextual targeting and extends the reach of ads across multiple devices. For example, platforms like Roku use ACR data to display ads to viewers who haven’t seen them on traditional TV. Similarly, Samba TV retargets mobile users based on IP address and aligns their viewing habits with their smart TVs.
Demand-side platforms
CTV advertising relies heavily on demand-side platforms (DSPs) to efficiently manage and optimize ad campaigns. These platforms use machine learning and AI in several important ways:
Using machine learning and AI to address data fragmentation
Data is abundant but fragmented when it comes to CTV advertising. DSPs are flooded with a massive amount of data, including information about households, viewer behavior, and viewing patterns. This data is far too much for manual analysis to handle effectively, which is where AI comes in.
By integrating machine learning algorithms into DSPs, AI can harmonize this fragmented data and provide valuable insights and a holistic view of your audience. AI can process zettabytes of data in real time, which streamlines the decision-making process and empowers you to compete quickly for limited CTV impression opportunities.
Predicting advertising outcomes with AI
AI is quickly changing the way we predict and optimize advertising outcomes. TV buying and optimization platforms are now using AI to improve ad performance. With machine learning, these platforms can anticipate which ad creatives will produce the best results based on various non-creative factors. These include the context of the ad, the audience’s profiles, the time of day it is displayed, and the frequency of the ad display.
By relying on AI to make these predictions, you can make sure your campaigns are highly optimized for success and deliver more relevant, compelling ads to viewers.
Optimizing generative ads
AI is also driving optimization in generative ads. These personalized versions of the same CTV ad can be tailored to suit individual viewers. By utilizing AI-driven analytics, DSPs can process extensive amounts of data in real time and optimize generative ads to ensure they align with viewers’ preferences and behaviors. This level of personalization is a game-changer in CTV advertising that boosts engagement and delivers content that truly resonates with the audience.
Add AI to your CTV strategy today
Integrating AI into your CTV strategy can help you stay competitive and ensure your ad campaigns are effective and engaging.
At Experian, we’re ready to help you elevate your CTV advertising and implement AI as part of your strategy. Our solutions, such as Consumer View and Consumer Sync, provide valuable audience insights, enhance targeting capabilities, and optimize engagement on TV. Plus, our partnerships with leading media marketing solutions can help you achieve greater success through effective advanced television advertising.
As you incorporate AI into your CTV strategy, you’ll be able to make more data-driven decisions, deliver more relevant content, and reach the right audience at the right time. Explore Experian’s TV solutions and empower your CTV advertising with AI today.
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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

Retail media networks (RMNs) are on track to capture over $128 billion in ad spend by 2028, growing nearly 25% year over year. But behind this rapid expansion, RMNs face a challenge that could slow their momentum: they lack the complete picture of their customers. Retailers sit on a goldmine of first-party data—loyalty programs, online purchases, and in-store transactions—but their customer view is often fragmented, incomplete, or entirely anonymous. Without a strong identity foundation, RMNs struggle to: Scale advertiser reach beyond logged-in users Seamlessly match audiences across channels (CTV, programmatic, social) Deliver the precise targeting and measurement that advertisers demand The reality? Data is only valuable if it’s usable. And right now, too many RMNs are leaving value on the table. The identity challenge: If you can’t see it, you can’t monetize it Retailers have two types of customers: Known customers: Logged-in or self-identified users with purchase history and identifiable attributes. Unknown customers: Shoppers who browse, purchase in-store, or check out as guests—leaving behind only partial or anonymous data. Although many retailers have a loyalty program, it’s unlikely they are capturing a full view of all of their customers, especially outside of their four walls. When retailers don’t know their customers, they can’t effectively: Understand what messages will resonate with what audiences Extend their audiences beyond their owned platforms Provide advertisers with the reach and addressability they demand Accurately measure media performance and prove ROI But this challenge isn’t unsolvable—it’s an identity problem, and Experian is built to fix it. The missing link: Clean, enriched, and connected data Assuming your data is ready to activate is a costly mistake. Too often, RMN data is messy, siloed, and incomplete, making it difficult to deliver the precision and performance advertisers expect. Experian flips the script—helping RMNs transform fragmented signals into a complete, connected picture of their audience. Here’s how Experian helps RMNs go from fragmented to first-class Clean and optimize We organize messy customer data, removing duplicates and filling in gaps. Enrich and enhance Our insights add depth to profiles with demographics, behavior, and purchase intent signals. For example, an RMN may know a shopper recently bought a car seat—but not that they lease a luxury SUV. That auto data is critical to securing auto ad dollars, and it’s exactly the kind of insight Experian provides. Expand and connect Using digital identifiers like hashed emails (HEMs), mobile ad IDs (MAIDs), and connected TV (CTV) IDs, we help extend audience reach across every channel advertisers care about. The result? A complete and addressable audience picture that RMNs can activate confidently—on-site and off. We partnered with one of the largest RMNs in the world to overhaul its first-party shopper data ahead of industry changes. By anchoring its data to stable digital IDs, addressability skyrocketed by nearly 300%. That’s the Experian difference—turning guesswork into confidence. Retailers who master identity will win the RMN race In an increasingly competitive RMN landscape, identity isn’t optional—it’s everything. Advertisers demand scale, accuracy, and measurable impact. Only RMNs with a robust identity foundation will rise above the competition. RMNs that prioritize identity resolution and data enrichment will: Drive more revenue by increasing the size of their addressable audience Keep advertisers engaged with better targeting and measurement Capture RMN market share by offering scale and accuracy Don’t just compete—lead. Ready to transform? Experian will show you how Fixing data inside the RMN ecosystem is just the beginning. In part two, we’ll cover: Why RMNs should be activating their enriched first-party data across CTV, programmatic, and social. Why off-site expansion is the future of maximizing revenue. How Experian’s data and identity solutions power off-site activation. Experian isn’t just part of the RMN conversation. We’re driving it. Let’s talk. Connect with our team Latest posts