Marketing data and identity

Why an identity framework matters more than any single identifier   The challenge facing marketers today isn't a single identifier on a deprecation timeline; it’s the increasing fragmentation of signals and identifiers across browsers, devices, apps, and platforms. This shift introduces complexity into how audiences are reached and measured, as signals behave differently in every environment, and it becomes more complex to piece together a complete view of the consumer. Each environment contributes to its own set of visibility gaps, making identity less predictable and more uneven. The result is a patchwork of inconsistent identity signals rather than a single, predictable decline. While you can’t control how platforms evolve, you can control how you respond to fragmentation. The future won’t be defined by the loss of any single identifier, but by your ability to unify, interpret, and activate the many signals that remain. Marketers who adopt a flexible, identity framework will be best positioned to create consistency in an otherwise fragmented landscape. At Experian, we believe flexibility starts with intelligence. For decades, we’ve used AI and machine learning to help marketers understand people’s behavior more clearly, respect their privacy, and deliver messages that drive business outcomes. Our technology brings identity, insight, and intelligence together, so even as the number of signals grows and becomes more varied across environments, marketers can reach the right people with relevance, respect, and simplicity. This intelligence acts as the connective tissue across fragmented ecosystems, ensuring marketers can recognize and reach audiences consistently wherever they appear. What forces are driving fragmentation in identity and signals? Changes to traditional IDs Since Apple introduced App Tracking Transparency (ATT), access to the Identifier for Advertisers (IDFA) has become inconsistent across apps and devices. Google’s evolving Android privacy roadmap adds another layer of variability, fragmenting mobile addressability. Safari and Firefox have long restricted third-party cookies, while Chrome continues to support them for now. This creates different signal availability across browsers, contributing to an uneven and increasingly fragmented identity landscape on the open web. Shifts in signals IPv4 to IPv6 migration introduces mismatched identity structures that complicate continuity across environments. Platform-driven fragmentation Closed ecosystems and uneven adoption of evolving RTB standards (like OpenRTB 2.6 updates designed to support new identifiers and consent signals) create differences in which identifiers and consent signals are shared in the bidstream. At the same time, the rise of alternative or “universal” IDs—often developed by individual platforms, publishers, or technology companies—means that multiple ID types can appear within the same auction, each with its own structure, rules, and level of support. These differences reduce interoperability across platforms and contribute to a more fragmented activation landscape. Each change creates an identity silo. Together, they form an ecosystem defined by fragmentation rather than absence. Without an identity framework, these environments operate as disconnected identity islands. A multi-ID world requires a unified identity framework Alternative IDs play an important role, but they also expand the number of signals marketers must reconcile. Without a consistent identity layer, more IDs often mean more complexity—not more clarity. Common alternative IDs in use today: UID2: The Trade Desk’s Unified I.D. 2.0, an iteration of their original Unified ID 1.0, which was still reliant on third-party cookies, creates persistent IDs with user-provided email addresses and phone numbers. ID5: This independent identity provider builds an identity infrastructure that powers addressable advertising across channels. It can create an ID based on both deterministic and probabilistic data. Hadron ID: Hadron ID is a unique, interoperable identity system (including first-party, audience-based, contextual, deterministic, and probabilistic) developed by Audigent, now part of Experian, to drive revenue for publishers by making their audience data and inventory actionable for media buyers. Industry reports suggest roughly one-third to two-fifths of open-auction traffic carries alternative IDs, sometimes multiple per request. Among Experian clients, adoption of alternative IDs rose 50% year over year, with a 30% increase in IDs resolved to individuals via our Digital Graph. Identity isn’t disappearing; it’s multiplying. A modern identity framework resolves these identifiers into a single, privacy-safe consumer view. Why CTV makes an identity framework essential Beyond alternative IDs, device-level identifiers also play a major role in today’s ecosystem and add to the fragmentation marketers must navigate. Connected TV (CTV) environments introduce additional fragmentation. CTV IDs A CTV ID is an identifier used to deliver, target, and measure ads on CTV devices, including smart TVs, streaming devices, gaming consoles, and more. Unlike MAIDs, which act as universal device identifiers across apps, CTV environments often generate multiple, platform-specific IDs for the same physical device. Different operating systems, publishers, or streaming platforms may each assign their own identifier—such as Roku ID for Advertisers, Amazon Fire Advertising ID, Samsung TIFA, or Apple IDFA for CTV. As a result, a single household or TV can appear under several distinct IDs, making cross-app or cross-platform recognition more complex and further reinforcing the need for a unified identity framework. Experian’s identity framework is powered by predictive and generative intelligence that makes resolution faster and more human-centered. Our AI models fill gaps where data signals are missing, infer behaviors responsibly, and continuously optimize for accuracy, so marketers can personalize ads responsibly, even in a fragmented ecosystem. More importantly, our framework normalizes signals across disconnected environments, creating a consistent identity spine that follows the consumer through their fragmented digital journey. An identity framework connects online and offline signals Fragmentation extends beyond digital environments. Marketers manage offline data from in-store transactions, loyalty programs, household identifiers, and phone numbers that rarely align cleanly with digital signals. As consumers move between online and offline touch points, an identity framework connects these signals into a coherent view of the individual. This foundation allows marketers to recognize the same consumer across environments that expose different identifiers. Four keys to future-proofing your media with an identity framework 1. Know your customer: Unify and enrich your first-party data First-party data is a marketer’s most durable asset, but it’s often scattered and incomplete. Unify it: Bring CRM records, site interactions, and loyalty data into a single platform to build a holistic customer view. Use Offline Identity Resolution to resolve your first-party offline personally identifiable information (PII) back to a consolidated consumer profile, removing duplication of users in your data set. Enrich it: Append Experian Marketing Attributes to uncover demographics, lifestyle markers, and purchase behaviors you can’t see on your own, and use Offline Identity Append to fill in missing offline data points (such as name, address, phone, etc.) to create a more complete and actionable customer profile. This gives you richer profiles that drive more personalized targeting and messaging. Fragmented ecosystems make unified first-party data even more essential. A connected view allows marketers to anchor identity against a stable, proprietary foundation. As identifiers vary across environments, marketers need flexible, privacy-first ways to understand where their audiences are and how to reach them. 2. Find your customer: Expand how you discover and reach audiences in a fragmented landscape As identifiers vary across environments, marketers need flexible, privacy-first ways to understand where their audiences are and how to reach them. Contextual signals: Experian’s Contextually-Indexed Audiences map content to consumer insights, so you can target intent-rich environments. Geographic insights: Our Geo-Indexed Audiences help you find regions that over-index for specific traits and activate them across your preferred platforms. Syndicated and Partner Audiences: Choose from 3,500+ prebuilt segments or 30+ partner data sources spanning health, retail, travel, and more. Curation: As a full-service curation partner, we enable private marketplace (PMP) deals that are privacy-safe, identity-agnostic, and performance-optimized. Together, these approaches help you confidently reach your audiences - using multiple types of signals that complement your identity strategy and create a clearer picture across fragmented environments. 3. Reach your customer: Maximize scale through interoperability As signals and identifiers proliferate across environments, interoperability is essential to maintain consistent reach. Experian’s Offline and Digital Graphs unify disparate signals (MAIDs, CTV IDs, alternative IDs, IP, and more) so marketers can recognize and engage audiences reliably across channels, devices, and platforms. Interoperability matters because it turns a collection of disconnected identifiers into a coherent identity framework that can actually be activated. The following capabilities demonstrate how that comes to life. Unified identity: Create a consistent view of your audience, even when different environments expose different identifiers. Experian’s identity framework connects these signals into a single, actionable identity spine. Expanded reach: OpenX enriched its supply-side identity graph with Experian’s audiences, making our data available directly across OpenX supply and formats. By matching more of the starting audience and identifying more users in the bidstream, marketers see higher match and activation rates, extending reach in hard-to-address environments like Safari and mobile web. Measure success: Optimize based on outcomes If you can't measure your marketing, you can't improve it. Experian Outcomes, powered by our holistic understanding of the user across online and offline touch points, closes the loop by connecting media exposures to real-world actions (store visits, purchases, or site conversions). With these insights, you can: Prove ROI across digital and TV Attribute success to the right channels and tactics Continuously refine targeting, creative, and spend allocation Outcome-based measurement makes your strategy adaptive, so dollars flow to what drives results. As signals multiply across environments, connecting exposures to outcomes requires a unified identity foundation. Experian closes the loop by unifying exposures across disconnected touch points, enabling holistic attribution and optimization. Our AI-powered simplicity drives continuous improvement. From predictive modeling to agentic workflows that automate optimization, we’re investing in generative AI to help marketers spend less time on manual setup and more time on strategy and outcomes. The Experian identity framework advantage Experian connects fragmented signals into a single, actionable identity framework built for long-term resilience. What our identity framework delivers Interoperability: We support all major identifiers, including alternative IDs, IP address (v4 and v6), contextual signals, and both first- and third-party data. Flexibility: Whether you’re activating syndicated audiences, tapping into partner audiences from 30+ data providers, or curating custom segments through Audigent, our solutions meet you where you are. Scale: With four billion IDs resolved in our Digital Graph and 280 million telephones in our Offline Graph, we deliver unmatched reach across digital and offline environments. AI that makes marketing more human: We bring together identity, insight, and automation through responsible AI, helping marketers see audiences clearly, act with intelligence, and optimize with respect for privacy. Our approach is delivering results across a range of programmatic players. These outcomes demonstrate how a unified identity framework delivers performance in environments where signals, identifiers, and devices operate in silos. Proven results powered by Experian’s identity framework Sonobi increased programmatic addressability across the mobile web by 25% and delivered a 20% lift in impression value through our identity graph, driving stronger campaign connections and greater publisher returns. One DSP used our Digital Graph to match more MAIDs, CTV IDs, and IP addresses to online conversions, enabling increased accuracy of their attribution and measurement. They achieved an 84% synced ID rate and a 9% increase in match rate. For Cuebiq, we significantly increased match rates and resolved data from cookieless environments, such as Safari. By combining separate data streams and resolving 85% of total events to a household, Cuebiq expanded on the household IDs to identify MAIDs that are observed in-store, enabling accurate cross-channel measurement. Our Digital Graph allowed MiQ and their clients to expand the reach of their seed audiences across devices by 51% and cookieless IDs by 64%. As a result, MiQ can provide marketers with future-proofed connected planning, advanced targeting, and precise measurement. We’re your partner in building identity framework that lasts: resilient to change, adaptive to new signals, and focused on outcomes. What comes next for signals and identity? The future isn’t defined by any single identifier. It’s defined by the ability to unify and activate across a fragmented identity ecosystem. The winners will be those who adopt interoperable, outcome-driven identity frameworks today. Those strategies will increasingly be powered by responsible AI, systems that simplify workflows, predict opportunity, and optimize in real time while keeping people at the center. At Experian, we see AI not as automation for its own sake, but as a way to make marketing more human, relevant, and respectful. Your playbook for navigating fragmentation Experian connects the fragmented identity ecosystem, unifying alternative IDs, IP signals, contextual data, and first- and third-party assets into a consistent, actionable identity foundation. With proven lift across partners like Sonobi and new offerings like Contextually-Indexed Audiences, we help you build campaigns that perform in a fragmented landscape. Download our 2026 Digital trends and predictions report to explore how identity, interoperability, and measurement will define the future of advertising. Download About the author Henry Schenker Group Product Manager, Experian Henry has nearly 15 years of experience in Digital Advertising, Social Media Marketing, Data Licensing & Analytics, Front-End Engineering, Technical Architecture & Integrations, Profit & Loss Management, and Enterprise-Level Contract Negotiation across the U.S., EMEA, and Asia Pacific regions. Prior to re-joining Experian, Henry held critical go-to-market and product roles at noted industry-disruptors Media.Monks and Attain. From 2018 - 2020, he served as the Vice President, APAC of Innovid (now publicly traded, NYSE:CTV), leading the company's expansion into Japan, Singapore, and Australia. The preceding 4 years with Tapad (acquired by Experian), allowed Henry to become a seasoned Sales Engineer, grow and lead a global Technical Integrations team, and relocate to Singapore, leading sales and operations in the APAC region. Before beginning his career and learning front-end engineering on-the-job at Wyng (formerly Offerpop), Henry received a dual-major (BA/BS) in Sociology and Economics & Finance from Bard College in New York. FAQs Why is signal and identity fragmentation increasing across digital and offline channels? Signal and identity fragmentation is increasing across digital and offline channels because consumers now engage across more devices, platforms, and environments. Each environment introduces its own identifiers and privacy rules. This growth creates more signals overall, which increases the need for unification rather than reliance on a single ID. How should marketers think about alternative IDs in a multi-signal ecosystem? Alternative IDs add reach and coverage when they connect through a common identity framework. They work best alongside first-party data, device identifiers, and contextual signals. Resolution turns multiple IDs into one consistent view of the consumer. What role does unified identity play in CTV and cross-device media? CTV environments often assign multiple platform-specific identifiers to the same household or device. A unified identity layer links those identifiers together. This approach supports consistent audience recognition across streaming apps, devices, and digital channels. How does unified identity support accurate measurement and attribution? Unified identity connects media exposure to outcomes across digital, TV, and offline touch points. It enables marketers to see how different channels contribute to real actions like visits or purchases. Measurement improves when identity remains consistent across the full journey. Why does an identity strategy matter beyond digital advertising? Identity extends into offline signals such as transactions, loyalty activity, and household data. A unified foundation aligns online and offline interactions into one coherent profile. This connection supports planning, activation, and measurement across the entire customer experience. Latest posts

Experian Audiences help financial marketers serve consumers with very different financial habits, digital behaviors, and spending patterns. Backed by our deep insight into income, debt, and credit, digital behavior, and household dynamics, our approximately 400 financial audiences and 3,500+ syndicated segments give financial marketers the ability to engage consumers with relevance across every life stage, channel, and financial mindset. To help financial marketers build effective, more adaptable programs, in this article, we’ll explore two approaches: Generational: How financial behaviors differ across life stages Seasonal: How consumer financial motivation spikes at key times of year Together, these approaches help financial marketers reach the right consumers with the right message at the right moment. Generational approach Financial marketers face a new kind of challenge: some consumers still visit branches, while others manage nearly every financial task from their phones. That gap reflects more than a channel preference; it signals distinct financial needs, confidence levels, and expectations for how money should work across generations. How do financial behaviors differ across generations? Generational digital behaviors The data below highlights key differences in how younger consumers engage with digital financial tools compared with Boomers. Behavior/metricGen Z and MillennialsBoomersUse peer-to-peer transfer apps (Venmo, PayPal)~50%~20%Use a mobile wallet daily79% (Gen Z), 67% (Millennial)Nearly 70% have never used one Younger generations are driving a mobile-first approach to money management, while Boomers are far less likely to manage their finances this way. They prioritize tools that help them build credit, reduce debt, manage rising costs, and automate everyday tasks. This behavior is reshaping how financial institutions think about acquisition, product relevance, and loyalty. Generational workforce and retirement dynamics As Boomers retire, their focus shifts to protecting accumulated wealth, steady income, and simplified service experiences. These changes are reshaping household finances and long-term planning behaviors across the country. The table below outlines how shifting workforce composition and retirement milestones differ across generations. Behavior/metricGen Z and MillennialsBoomersShare of the U.S. workforceGrowing toward 74% of the global workforce by 2030 (younger generations collectively)~15% of the U.S. workforce and shrinkingRetirement outlookExpected age to retire 67-69~75 million people will have retired by 2030 Marketers need to do more than track trends; they need to act on them with confidence. That’s where Experian Audiences come in. Turn generational insights into action with Experian Audiences Experian Audiences turn complex generational data into actionable marketing segments, helping financial brands reach the right people with the right message across every life stage. We offer approximately 400 financial audiences, each reflecting distinct financial priorities, from debt management to wealth preservation. These audiences are built using privacy-safe data and grounded in our deep understanding of income, debt, and digital behavior. Experian’s financial audiences blend credit, behavioral, and demographic signals to help you connect with consumers based on: Debt profile, including type and overall burden Income tier and earning stage Financial confidence and digital engagement habits How can marketers activate generational insights with Experian Audiences? Each generation has unique financial journeys, needs, and motivations that marketers can address with Experian Audiences designed to reach: Generation Z (Gen Z) Millennials Generation X (Gen X) Baby boomers (Boomers) In addition to these four generational segments, Experian Audiences also includes segments that apply broadly across life stages. These audiences reflect core financial attributes, such as income, capacity, and lifestyle, that are consistently relevant and can be layered onto any generational strategy. Ability to pay Generational income bands  Income Mosaic® USA While Fair Lending regulations prohibit age-based targeting, these groups are not built on age itself. Instead, they’re derived from observable financial behaviors and signals that often align with different life stages; allowing marketers to engage consumers in a compliant, behavior-driven way. We also offer FLA-friendly¹ audience segments when required, alongside expanded options for non-lending campaigns, supporting initiatives such as brand and product awareness, deposit growth, credit union membership, and other programs that don’t rely on credit-based targeting. You can find the full taxonomy paths in the appendix. This generation is young, digitally savvy, and highly engaged. Gen Z is beginning their financial journey with a focus on independence and debt management. Their preference for mobile-first tools and peer-to-peer payments reflects an expectation for simple, accessible financial experiences. Campaigns centered on credit-building tools, savings apps, and financial literacy resources are especially relevant for this group. Behavior/metricGen ZUse peer-to-peer transfer apps80%+Use mobile wallets daily79% Here are seven recommended audiences to target Gen Z:  Credit Card Financial Personality Discretionary Spend: Dining Out Discretionary Spend: Education Discretionary Spend: Entertainment In Market Buy Now Pay Later In Market for Auto Loan or Lease Renter How to use these audiences Financial marketers can activate audiences like Credit Card Financial Personality, In-Market Buy Now Pay Later, and Renter to introduce credit-building tools and mobile-first financial products. Millennials are entering their peak earning years while balancing family, homeownership, and digital convenience. Their preference for digital and contactless payments reflects a broader expectation for seamless, mobile-first financial experiences. Campaigns highlighting mortgage products, family insurance, and digital banking resonate across connected TV, mobile, and display. Behavior/metricMillennialPrefer digital or contactless payments~85% Here are ten audiences to target Millennials:  Deposits Financial Personality Discretionary Spend Education Discretionary Spend Home Furnishings In Market Buy Now Pay Later In Market Real Estate Investable Assets Likely to Move Mortgage Financial Personality New Parents Student Loan Age How to use these audiences Financial marketers can use audiences such as Mortgage Financial Personality, New Parents, and Discretionary Spend: Home Furnishings to reach Millennials navigating homeownership, family growth, and major financial decisions. Gen X leads in household income and prioritizes investments, education, and long-term financial stability. They respond well to data-driven offers for refinancing, college planning, and wealth management, especially across digital video, streaming, and email channels. Behavior/metricGen ZMillennialsGen XBoomersMedian income$71,200~$104,000~$126,000~$54,000 Here are ten audiences to target Gen X:  Discretionary Spend Discretionary Spend Donations Discretionary Spend Entertainment Discretionary Spend Travel Equity Loan Age Insurance Financial Personality Investment Financial Personality Investable Assets Mortgage Loan Age Net Asset Score (Net Worth) How to use these audiences Financial marketers can utilize audiences like Investment Financial Personality, Equity Loan Age, and Net Asset Score to promote refinancing, college planning, and wealth-building solutions. Boomers tend to have lower debt loads and more stable income, but place a high value on security and simplicity. Their channel preferences skew traditional, focusing on direct mail, television, and formats that reinforce trust and familiarity. Behavior/metricBoomerMedian net worth$410,000TV consumption98% watch TV; 77% watch more than 2 hours per dayNewspaper readership50%+ still read print or a mix of print and digital Here are eight audiences to target Boomers:  Charitable Causes Discretionary Spend Discretionary Spend Donations Discretionary Spend Travel Equity Loan Age Home Equity Financial Personality Mortgage Loan Paid Off or “Has Existing” Net Asset Score (Net Worth) How to use these audiences Financial marketers can target audiences such as Home Equity Financial Personality, Mortgage Loan Paid Off, and Net Asset Score to support messaging around wealth preservation, estate planning, and retirement security. Seasonal approach Alongside generation insights, financial advertisers should also capitalize on key seasonal events where financial motivation naturally spikes. Each season brings unique consumer behaviors, and Experian Audiences can be activated to align with these key seasonal moments. Tax season Refunds and debt payoff are top of mind as consumers prepare and file their returns. Experian Audiences you can activate: Household Tax Shelter User Tax Preparation Services and Software Tax Return: Professional Service Prepare User Tax Return: Self Prepare User How to use these audiences Use Tax Preparation Services and Software or Tax Return: Self Prepare User to reach consumers actively preparing returns, paying down debt, or planning how to use their refunds.  Home buying season Mortgage, refinancing, and home equity activity increases as consumers enter the peak home buying window. Experian Audiences you can activate: In Market First Mortgage In Market Home Equity In Market New Mortgage In Market Second Mortgage Refinancing Homeowners How to use these audiences Use In Market First Mortgage or Refinancing Homeowners to connect with consumers exploring first-time home purchases, refinance options, or equity-based borrowing. Back-to-school Household spending increases as families manage education costs, holiday purchases, and year-end budgeting. This period also drives heightened activity around payments, credit usage, and financial planning. Experian Audiences you can activate: Back to School High Spend Back to School Moderate Spend Back to School Spend: PreK through High School College Tuition Geo Index High Spenders Credit Card Age <2 Years Credit Seeking Card Switcher In Market Credit Card In Market Personal Loan Mobile Location > College Students Student Loan Age <5 Years Student Loan Existing How to use these audiences Activate Back to School High Spend, Back to School Moderate Spend, or Back to School Spend: PreK through High School audiences to reach households actively preparing for the school year. Year-end planning (October-December) As Boomers and Gen X plan for retirement or tax optimization, focus on wealth preservation and investment management.  Experian Audiences you can activate: Baby Boomer Household Income $150K–$249K Baby Boomer Household Income $250K–$499K Estimated Household Income Range $500K Gen X Household Income $1M Plus Geo-Indexed Household Income $1M Plus How to use these audiences Use Estimated Household Income Range $500K or Geo-Indexed Household Income $1M Plus to engage consumers focused on financial wrap-up activities. What sets Experian Audiences apart? Our syndicated audiences give you an advantage across channels, offering both scale and accuracy: Experian’s 3,500+ syndicated audiences can be sent to 200+ leading social platforms, such as Meta and Pinterest, TV, and programmatic advertising platforms, and activated directly within Audigent, a part of Experian,  with private marketplaces (PMPs). Reach consumers based on who they are, where they live, and their household makeup. Experian ranked #1 in accuracy by Truthset for key demographic attributes. Access to unique audiences through Experian’s Partner Audiences available on Experian’s data marketplace, within Audigent, a part of Experian, for activation in PMPs, and directly on platforms like DirectTV, Dish, Magnite, OpenAP, and The Trade Desk. You can activate our syndicated audiences on-the-shelf of most major platforms. For a full list, download our syndicated audiences guide. Explore Experian and FMCG Direct’s financial audiences in non-financial campaigns Where can you activate Experian Audiences? Experian Audiences can be activated on 200+ leading destinations or found directly on over 30 platforms, including: Basis  FreeWheel  Magnite  Nexxen  The Trade Desk  Viant  Microsoft Advertising and more Need a custom audience? Reach out to our audience team and we can help you build and activate an Experian audience on the platform of your choice. Want to activate an Experian Audience on Meta, Pinterest, Snap, TikTok or on a platform not listed above? Contact us today. Explore our other audiences that you can activate today Activate Experian Audiences today with Audigent Audigent will build customized deals that combine premium Experian Audiences or Partner Audiences and inventory into a single, streamlined deal ID – tailored to your campaign needs. Plus, our powerful supply-side optimization ensures your campaigns deliver top marks in performance. Connect with the Audigent team today at AudigentAgency_Brands@experian.com to get started. Make every consumer part of your financial strategy From first paychecks to retirement portfolios, every generation has its own financial story, and seasonal moments create predictable spikes in financial behavior. With Experian Audiences, you can plan across life stages and timing to meet consumers when intent is highest, building relationships grounded in trust, relevance, and meas Reach out to us today FAQs What are Experian Audiences? Experian Audiences are pre-built, privacy-compliant consumer segments that help marketers target based on verified demographic, financial, and behavioral data.They’re designed for flexibility across channels and can be activated on 200+ platforms, including major social, CTV, and programmatic partners.Experian ranks #1 in demographic accuracy according to Truthset, and marketers can choose from 3,500+ syndicated audiences that capture signals such as income, spending behavior, household structure, financial attitudes, and ability to pay. These same audiences are also available through partnerships on platforms like DirecTV, Dish, Magnite, OpenAP, and The Trade Desk.For a deeper look at our audience catalog, explore our syndicated audience guide.  How can financial marketers use Experian Audiences effectively? Financial marketers can use Experian Audiences by aligning audience selection with generational priorities, such as digital banking for Gen Z or retirement planning for Boomers, to improve engagement and ROI. Are Experian Audiences compliant with financial marketing regulations? Experian Audiences are designed to meet a variety of needs while respecting different levels of privacy standards. For example, we offer FLA-compliant segments where required, as well as broader audiences for objectives such as brand awareness, promotion, credit union membership growth, and more.Experian’s approach to data is guided by our Global Data Principles, which reflect how we protect and manage information:Data security: safeguarding data against unauthorized access, use, or lossAccuracy: ensuring data is as accurate, complete, and relevant as possibleFairness: collecting and using data responsibly and for legitimate purposesTransparency: being open about the data we collect, how it’s used, and where it’s sharedInclusion: using data to expand financial access and support consumer financial health Where can you activate Experian Audiences? You can activate Experian Audiences are available across 200+ digital and connected TV platforms, including Meta, Pinterest, The Trade Desk, and Audigent PMPs. Can I combine Experian data with my own? Yes, you can combine Experian data with your own. You can combine your own first-party data with Experian’s 3,500+ syndicated audiences and additional segments from multiple Partner data providers, as a custom audience within a Curated Deal or self-service via Audience Engine. Footnote “Fair Lending Friendly” indicates data fields that Experian has made available without use of certain demographic attributes that may increase the likelihood of discriminatory practices prohibited by the Fair Housing Act (“FHA”) and Equal Credit Opportunity Act (“ECOA”). These excluded attributes include, but may not be limited to, race, color, religion, national origin, sex, marital status, age, disability, handicap, family status, ancestry, sexual orientation, unfavorable military discharge, and gender. Experian’s provision of Fair Lending Friendly indicators does not constitute legal advice or otherwise assures your compliance with the FHA, ECOA, or any other applicable laws. Clients should seek legal advice with respect to your use of data in connection with lending decisions or application and compliance with applicable laws. Appendix Generation Z Financial Personalities > Credit Card Financial Personality > Uninterested, Average Credit Card Balance Financial Personalities > Credit Card Financial Personality > Reluctant User, High Credit Card Balance Financial Personalities > Credit Card Financial Personality > Loyal Rewards Enthusiast, Low Credit Card Balance Financial Personalities > Credit Card Financial Personality > Credit Seeking Card Switcher, High Credit Card Balance Financial Personalities > Credit Card Financial Personality > Complacent Card User, Low Credit Card Balance Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $4302-$99999 Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $2084-$4301 Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $0-$2083 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $512-$1227 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $1228-$99999 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $0-$511 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $4607-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $2230-$4606 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $0-$2229 Financial FLA Friendly > In Market > Buy Now Pay Later Financial > In Market > Buy Now Pay Later Financial FLA Friendly > In Market Auto Loan Financial FLA Friendly > In Market Auto Lease Demographics > Homeowners/Renters > Renter Millennials Financial Personalities > Deposits Financial Personality > Uninterested, Average Deposit Balance Financial Personalities > Deposits Financial Personality > Self-Directed Diversifier, Very High Deposit Balance Financial Personalities > Deposits Financial Personality > Hesitant Borrower, Low Deposit Balance Financial Personalities > Deposits Financial Personality > Demanding Advice Seeker, Low Deposit Balance Financial Personalities > Deposits Financial Personality > Conservative Branch Banker, Very High Deposit Balance Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $512-$1227 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $1228-$99999 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $0-$511 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $2602-$99999 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $1272-$2601 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $0-$1271 Financial FLA Friendly > In Market > Buy Now Pay Later Financial > In Market > Buy Now Pay Later Publisher Derived > In-Market: Real Estate > In-Market Real Estate Consumer Financial Insights > Investable Assets > Investable Annual Assets Score Less Than $10000 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $10000-$49999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $50000-$99999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $100000-$249999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $250000-$499999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $500000-$999999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $1000000 Plus Lifestyle and Interests (Affinity) > Movers > Likely to Move Financial Personalities > Mortgage Financial Personality > Uninterested, Slightly Below Average Mortgage Balance Financial Personalities > Mortgage Financial Personality > Secure, Active Refinancer, Above Average Mortgage Balance Financial Personalities > Mortgage Financial Personality > Disciplined, Passive Borrower, Below Average Mortgage Balance Financial Personalities > Mortgage Financial Personality > Conservative, Bank Loyalist, Slightly Below Average Mortgage Balance Financial Personalities > Mortgage Financial Personality > Advice Seeking Refinancer, Slightly Above Average Mortgage Balance Life Events > New Parents > Child Age 0-36 Months Financial FLA Friendly > Student Loan Age > 9 Years Financial FLA Friendly > Student Loan Age > 8 Years Financial FLA Friendly > Student Loan Age > 7 Years Financial FLA Friendly > Student Loan Age > 6 Years Financial FLA Friendly > Student Loan Age > 12 Years Financial FLA Friendly > Student Loan Age > 11 Years Financial FLA Friendly > Student Loan Age > 10 Years Financial FLA Friendly > Student Loan Age > <5 Years Generation X Financial - Analytics IQ > Discretionary Spend > Travel Annual Spend $682-$1364 Financial - Analytics IQ > Discretionary Spend > Travel Annual Spend $1365-$99999 Financial - Analytics IQ > Discretionary Spend > Travel Annual Spend $0-$681 Financial - Analytics IQ > Discretionary Spend > Reading Annual Spend $193-$99999 Financial - Analytics IQ > Discretionary Spend > Reading Annual Spend $102-$192 Financial - Analytics IQ > Discretionary Spend > Reading Annual Spend $0-$101 Financial - Analytics IQ > Discretionary Spend > Personal Annual Spend $993-$99999 Financial - Analytics IQ > Discretionary Spend > Personal Annual Spend $525-$992 Financial - Analytics IQ > Discretionary Spend > Personal Annual Spend $0-$524 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $2602-$99999 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $1272-$2601 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $0-$1271 Financial - Analytics IQ > Discretionary Spend > Entertainment Other Annual Spend $911-$1973 Financial - Analytics IQ > Discretionary Spend > Entertainment Other Annual Spend $1974-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment Other Annual Spend $0-$910 Financial - Analytics IQ > Discretionary Spend > Entertainment AV Annual Spend $952-$1763 Financial - Analytics IQ > Discretionary Spend > Entertainment AV Annual Spend $1764-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment AV Annual Spend $0-$951 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $4607-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $2230-$4606 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $0-$2229 Financial - Analytics IQ > Discretionary Spend > Entertainment Admissions Annual Spend $833-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment Admissions Annual Spend $326-$832 Financial - Analytics IQ > Discretionary Spend > Entertainment Admissions Annual Spend $0-$325 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $512-$1227 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $1228-$99999 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $0-$511 Financial - Analytics IQ > Discretionary Spend > Donation Annual Spend $2568-$99999 Financial - Analytics IQ > Discretionary Spend > Donation Annual Spend $1265-$2567 Financial - Analytics IQ > Discretionary Spend > Donation Annual Spend $0-$1264 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $31619-$99999 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $0-$7900 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $7901-$10930 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $21952-$31618 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $15180-$21951 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $10931-$15179 Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $4302-$99999 Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $2084-$4301 Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $0-$2083 Financial - Analytics IQ > Discretionary Spend > Apparel Annual Spend $2818-$99999 Financial - Analytics IQ > Discretionary Spend > Apparel Annual Spend $1459-$2817 Financial - Analytics IQ > Discretionary Spend > Apparel Annual Spend $0-$1458 Financial - Analytics IQ > Discretionary Spend > Alcohol and Wine Annual Spend $727-$99999 Financial - Analytics IQ > Discretionary Spend > Alcohol and Wine Annual Spend $331-$726 Financial - Analytics IQ > Discretionary Spend > Alcohol and Wine Annual Spend $0-$330 Financial FLA Friendly > Equity Loan Age > 9 Years Financial FLA Friendly > Equity Loan Age > 7-8 Years Financial FLA Friendly > Equity Loan Age > 12+ Years Financial FLA Friendly > Equity Loan Age > 11 Years Financial FLA Friendly > Equity Loan Age > 10 Years Financial FLA Friendly > Equity Loan Age > <6 Years Financial Personalities > Insurance Financial Personality > Uninterested, Below Average Insurance Policy Face Value Financial Personalities > Insurance Financial Personality > Secure Agent-Oriented Loyalist, High Insurance Policy Face Value Financial Personalities > Insurance Financial Personality > Reluctant Insurance Skeptic, Below Average Insurance Policy Face Value Financial Personalities > Insurance Financial Personality > Insurance Averse, Below Average Insurance Policy Face Value Financial Personalities > Insurance Financial Personality > Engaged Advice Seeker, Average Insurance Policy Face Value Financial Personalities > Insurance Financial Personality > Confident, Self-Directed Planner, High Insurance Policy Face Value Financial Personalities > Investments Financial Personality > Skeptical, Fund-Oriented Investor, Low to Medium Investable Assets Financial Personalities > Investments Financial Personality > Savvy Sounding-Board Seeking Investor, Average Investable Assets Financial Personalities > Investments Financial Personality > Price Sensitive, Self-Directed Investor, Very High Investable Assets Financial Personalities > Investments Financial Personality > Cautious Investing Novice, Low Investable Assets Financial Personalities > Investments Financial Personality > Broker-Reliant Delegator, Very High Investable Assets Consumer Financial Insights > Investable Assets > Investable Annual Assets Score Less Than $10000 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $10000-$49999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $50000-$99999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $100000-$249999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $250000-$499999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $500000-$999999 Consumer Financial Insights > Investable Assets > Investable Annual Assets Score $1000000 Plus Financial FLA Friendly > Mortgage Loan Age > 9 Years Financial FLA Friendly > Mortgage Loan Age > 8 Years Financial FLA Friendly > Mortgage Loan Age > 7 Years Financial FLA Friendly > Mortgage Loan Age > 6 Years Financial FLA Friendly > Mortgage Loan Age > 5 Years Financial FLA Friendly > Mortgage Loan Age > 13 Years Financial FLA Friendly > Mortgage Loan Age > 11-12 Years Financial FLA Friendly > Mortgage Loan Age > 10 Years Financial FLA Friendly > Mortgage Loan Age > <4 Years Consumer Financial Insights > Net Assets Score (Net Worth) > Net Asset Score Net Worth $1000000 Plus Consumer Financial Insights > Net Assets Score (Net Worth) > Net Asset Score $2500000 Plus Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score Less Than $25000 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $750000-$999999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $75000-$99999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $500000-$749999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $50000-$74999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Asset Score $5000000 Plus Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $250000-$499999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $25000-$49999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $2500000-$4999999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $100000-$249999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $1000000-$2499999 Baby boomers Lifestyle and Interests (Affinity) > Charitable Causes > Contributes to Private Foundations Lifestyle and Interests (Affinity) > Charitable Causes > Contributes to Political Charities Lifestyle and Interests (Affinity) > Charitable Causes > Contributes to Health Charities Lifestyle and Interests (Affinity) > Charitable Causes > Contributes to Education Charities Lifestyle and Interests (Affinity) > Charitable Causes > Contributes to Charities Lifestyle and Interests (Affinity) > Charitable Causes > Contributes to Arts/Culture Charities Lifestyle and Interests (Affinity) > Charitable Causes > Contributes by Volunteering Financial - Analytics IQ > Discretionary Spend > Travel Annual Spend $682-$1364 Financial - Analytics IQ > Discretionary Spend > Travel Annual Spend $1365-$99999 Financial - Analytics IQ > Discretionary Spend > Travel Annual Spend $0-$681 Financial - Analytics IQ > Discretionary Spend > Reading Annual Spend $193-$99999 Financial - Analytics IQ > Discretionary Spend > Reading Annual Spend $102-$192 Financial - Analytics IQ > Discretionary Spend > Reading Annual Spend $0-$101 Financial - Analytics IQ > Discretionary Spend > Personal Annual Spend $993-$99999 Financial - Analytics IQ > Discretionary Spend > Personal Annual Spend $525-$992 Financial - Analytics IQ > Discretionary Spend > Personal Annual Spend $0-$524 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $2602-$99999 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $1272-$2601 Financial - Analytics IQ > Discretionary Spend > Furnishings Annual Spend $0-$1271 Financial - Analytics IQ > Discretionary Spend > Entertainment Other Annual Spend $911-$1973 Financial - Analytics IQ > Discretionary Spend > Entertainment Other Annual Spend $1974-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment Other Annual Spend $0-$910 Financial - Analytics IQ > Discretionary Spend > Entertainment AV Annual Spend $952-$1763 Financial - Analytics IQ > Discretionary Spend > Entertainment AV Annual Spend $1764-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment AV Annual Spend $0-$951 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $4607-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $2230-$4606 Financial - Analytics IQ > Discretionary Spend > Entertainment Annual Spend $0-$2229 Financial - Analytics IQ > Discretionary Spend > Entertainment Admissions Annual Spend $833-$99999 Financial - Analytics IQ > Discretionary Spend > Entertainment Admissions Annual Spend $326-$832 Financial - Analytics IQ > Discretionary Spend > Entertainment Admissions Annual Spend $0-$325 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $512-$1227 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $1228-$99999 Financial - Analytics IQ > Discretionary Spend > Education Annual Spend $0-$511 Financial - Analytics IQ > Discretionary Spend > Donation Annual Spend $2568-$99999 Financial - Analytics IQ > Discretionary Spend > Donation Annual Spend $1265-$2567 Financial - Analytics IQ > Discretionary Spend > Donation Annual Spend $0-$1264 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $31619-$99999 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $0-$7900 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $7901-$10930 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $21952-$31618 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $15180-$21951 Financial - Analytics IQ > Discretionary Spend > Discretionary Annual Spend Estimate $10931-$15179 Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $4302-$99999 Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $2084-$4301 Financial - Analytics IQ > Discretionary Spend > Dine Out Annual Spend $0-$2083 Financial - Analytics IQ > Discretionary Spend > Apparel Annual Spend $2818-$99999 Financial - Analytics IQ > Discretionary Spend > Apparel Annual Spend $1459-$2817 Financial - Analytics IQ > Discretionary Spend > Apparel Annual Spend $0-$1458 Financial - Analytics IQ > Discretionary Spend > Alcohol and Wine Annual Spend $727-$99999 Financial - Analytics IQ > Discretionary Spend > Alcohol and Wine Annual Spend $331-$726 Financial - Analytics IQ > Discretionary Spend > Alcohol and Wine Annual Spend $0-$330 Financial FLA Friendly > Equity Loan Age > 9 Years Financial FLA Friendly > Equity Loan Age > 7-8 Years Financial FLA Friendly > Equity Loan Age > 12+ Years Financial FLA Friendly > Equity Loan Age > 11 Years Financial FLA Friendly > Equity Loan Age > 10 Years Financial FLA Friendly > Equity Loan Age > <6 Years Financial Personalities > Home Equity Financial Personality > Uninterested, Low Home Equity Balance Financial Personalities > Home Equity Financial Personality > Secure, Savvy Credit User, High Home Equity Balance Financial Personalities > Home Equity Financial Personality > Home Equity Enthusiast, Very High Home Equity Balance Financial Personalities > Home Equity Financial Personality > Home Equity Averse Skeptic, Very Low Home Equity Balance Financial Personalities > Home Equity Financial Personality > Hesitant Borrower, Low Home Equity Balance Financial FLA Friendly > Mortgage Loan Paid Off Financial FLA Friendly > Mortgage Loan Has Existing Consumer Financial Insights > Net Assets Score (Net Worth) > Net Asset Score Net Worth $1000000 Plus Consumer Financial Insights > Net Assets Score (Net Worth) > Net Asset Score $2500000 Plus Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score Less Than $25000 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $750000-$999999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $75000-$99999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $500000-$749999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $50000-$74999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Asset Score $5000000 Plus Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $250000-$499999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $25000-$49999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $2500000-$4999999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $100000-$249999 Consumer Financial Insights > Net Assets Score (Net Worth) > Net Assets Score $1000000-$2499999 Tax season Lifestyle and Interests (Affinity) > Financial Behavior > Household Tax Shelter User Publisher Derived > In-Market: Financial Services > Tax Preparation Services and Software Lifestyle and Interests (Affinity) > Financial Behavior > Tax Return --Professional Service Prepare user Lifestyle and Interests (Affinity) > Financial Behavior > Tax Return - Self prepare user Home buying season Financial FLA Friendly > In Market First Mortgage Financial FLA Friendly > In Market Home Equity Financial FLA Friendly > In Market New Mortgage Financial FLA Friendly > In Market Second Mortgage Financial FLA Friendly > Refinancing Homeowners Back to school Retail Shoppers: Purchase Based > Seasonal > Back to School Apparel - High School Retail Shoppers: Purchase Based > Seasonal > Back to School Moderate Spend Retail Shoppers: Purchase Based > Seasonal > Back to School High Spend - PreK (Early Ed - PreK) Geo-Indexed > Discretionary Spend > College Tuition GeoIndex High Spenders Financial Personalities > Credit Card Financial Personality > Credit Seeking Card Switcher, High Credit Card Balance Financial FLA Friendly > In Market Credit Card Financial FLA Friendly > In Market Personal Loan Consolidated Mobile Location Models > Visits > College Students Financial FLA Friendly > Student Loan Age > <5 Years Financial FLA Friendly > Student Loan Has Existing Year-end planning Demographics > Household Income (HHI) > Baby Boomer Household Income $150K-$249K Demographics > Household Income (HHI) > Baby Boomer Household Income $250K-$499K Demographics > Household Income (HHI) > Estimated Household Income Range $500K Plus Demographics > Household Income (HHI) > Gen X Household Income $1M Plus Geo-Indexed > Demographics > Geo-Indexed Household Income $1M Plus Latest posts

Audigent, a part of Experian, Dun & Bradstreet, and Experian are collaborating to help business-to-business (B2B) marketers target more effectively. Now, B2B marketers can reach verified decision-makers, keep the same audience across channels, and activate on connected TV (CTV) and digital via the Experian data marketplace. Together, Dun & Bradstreet’s trusted business data, Audigent’s curation and Deal ID activation, and Experian’s identity resolution drive efficient, measurable results.

Personalization without context misses the moment Marketers have spent years perfecting personalization — but personalization alone often misses the mark. We’ve all seen it. You shop for a weekend getaway, then get served travel ads weeks later when you’re already home. The data was right. The timing wasn’t. Personalization based only on identity and behavior knows who you are but not when or why you’re ready to act. At Experian, we believe AI should make marketing feel more human. That means understanding people in context, recognizing their environment, mindset, and the moment, to create relevance that feels timely, not intrusive. The context gap: Why identity and behavior aren’t enough Identity and behavioral data can reveal the kind of consumer someone is and the kind of products they may want to buy. But they don’t explain what’s happening right now. The missing layer is context: the dynamic, real-time signal that shows why this moment matters. Context bridges the gap between knowing something about a consumer and understanding their intent. In an era of fragmented signals and stricter privacy rules, context is one of the most reliable ways to stay relevant without over-reliance on personal identifiers. It helps marketers adapt to shifting needs while keeping privacy intact. How Experian interprets context in real-time By context, we mean all the subtle, in-the-moment signals, like time of day, location, or what someone’s watching, that shape what people care about in real-time. At Experian, our technology interprets these in real-time: Temporal signals Time-based patterns such as daypart (morning vs. evening), recency (how fresh a signal is), seasonality (holidays, life events), and micro-moments (split-second intent-driven actions). Environmental signals The media or content environment; what type of program, article, or channel someone is engaging with when they see your ad. Situational intent Signals like browsing behavior or purchase patterns that hint at a person’s stage in the buying journey, from early research to final decision. By layering these signals over verified identity and behavioral data, Experian’s AI-powered technology helps marketers predict not just who will act, but when they’re ready to act. Experian’s approach: Turning context into relevance Consumer behavior changes by the minute, and marketers need to adapt just as quickly. Our technology interprets live bidstream data, device activity, content, and timing to optimize in the moment, ensuring your campaigns deliver meaningful relevance, not just broader reach. Our process combines: Input Clean, accurate identity and audience data anchored in our privacy-first framework. Enrichment Our models fuse household, device, and publisher context to reveal moment-based intent. Activation We're investing in agentic workflows that help marketers plan and execute performance campaigns at scale, activated via our real-time technology that dynamically adjusts deals and surfaces contextually aligned opportunities. Governance Every signal and recommendation follows Experian’s principles of transparency, consent, and ethical oversight. We call this AI-powered simplicity tools that help marketers work more efficiently, with intelligence that feels intuitive and human-centered. How context changes the game for marketers AI without real-time context can only react based on what it already knows. AI-powered by in-the-moment contextual data points enables marketers to anticipate, not just react. A travel brand can shift creative from “dreaming” to “booking” mode when AI detects signals of active planning. A retailer can align promotions with trending content or regional weather shifts in real time. A CPG brand can trigger different product messages based on the context of recipes or household occasions. Adjustments based on contextual signals compound into meaningful gains — higher engagement, better efficiency, and a consumer experience that feels natural rather than intrusive. Context makes AI more human Context introduces empathy into automation. It’s what keeps AI from overstepping, ensuring the message fits the moment. When marketers respect timing, environment, and intent, ads feel like service, not surveillance. Context transforms relevance into respect. At Experian, our vision is to make every signal serve people, not profiles. Because the more our technology (including our AI tools and capabilities) understands context, the more human marketing becomes. At Experian, responsible intelligence is built in Every contextual model we deploy adheres to our standards for transparent and responsible innovation. We validate inputs, monitor model drift, and ensure no context-based variable introduces bias or privacy risk. This is what responsible automation looks like in practice: intelligent, explainable, and ethical. From who to when: Context is the future of AI-driven marketing Identity tells us who someone is. Context tells us when it matters. The next wave of AI-driven marketing will unite privacy-first identity with contextual intelligence to deliver real-time relevance, responsibly. At Experian, we’re building that future now. Our AI-driven capabilities bring identity, insight, and generative intelligence together so brands, agencies, and platforms can reach the right people, at the right moment, with relevance and respect. Get started now About the author Matthew Griffiths SVP of Technology, Audigent, a part of Experian Matthew Griffiths is a seasoned technology entrepreneur and a driving force in advertising technology, data technology, and AI. As the Co-Founder and former CTO (now SVP of Technology) at Audigent, a part of Experian, he plays a pivotal role in shaping the company’s cutting-edge solutions for data activation, curation, and identity management. With years of executive experience across the U.S., Africa, and the U.K., Matthew has a proven track record of leadership in steering the adoption and use of cutting-edge technologies to drive business outcomes. His expertise spans from collaborating with top global corporations and governments to spearheading award-winning technology projects that deliver life-changing impacts in some of the world's most underserved communities. Matthew’s dynamic approach to solving complex business and technology challenges makes him a visionary leader in the AdTech space, consistently driving innovation and performance through technology. FAQs How does context make AI-driven marketing more effective? Context makes AI-driven marketing more effective because it helps marketers understand people in context, recognizing their environment, mindset, and the moment, to create relevance that feels timely, not intrusive. Context helps marketers understand not just who a person is, but when and why they’re ready to act. Experian’s AI-powered technology layers contextual signals over verified identity data to deliver relevance that feels intuitive, not invasive. This approach connects recognition with understanding, making every campaign more effective and more human. What is the context gap in AI-driven marketing? Identity and behavioral data can reveal the kind of consumer someone is and the kind of products they may want to buy. But they don’t explain what’s happening right now. That’s the context gap—the missing link between knowing something about a consumer and understanding their intent.  Context closes this gap by analyzing environmental, temporal, and situational signals that reveal intent—without using invasive identifiers. Does Experian interpret contextual signals in real-time? Yes, at Experian, our technology interprets contextual signals, including temporal, environmental, and situational, in real-time. By layering these signals over Experian’s verified identity and behavioral data graph, marketers can predict when consumers are most receptive, turning data into real-time opportunity. What does responsible intelligence look like in practice? At Experian, every contextual model we deploy adheres to our standards for transparent and responsible innovation. We validate inputs, monitor model drift, and ensure no context-based variable introduces bias or privacy risk. What does Experian’s foundation in responsible automation look like? - Privacy-first clarity: We unify household, individual, device, demographic, behavioral, publisher first-party signals, and contextual data points to build a reliable view of consumers, even when certain signals are missing. This clarity helps marketers personalize, target, activate, and measure with confidence.- Predictive insight: Our models go beyond describing the past. They forecast behaviors, fill gaps with inferred attributes, create lookalikes, and recommend next-best audiences so clients can anticipate opportunity.- AI-powered simplicity: We’re investing in generative AI and exploring emerging agentic workflows to reimagine how marketers work. Our vision is to move beyond basic audience recommendations toward intelligent audience discovery and automated setup, helping teams uncover opportunities they may not have considered, while spending less time on manual work and more time on strategy and outcomes.- Real-time intelligence: Consumer journeys never stand still. Our AI-powered technology interprets live bidstream data, device activity, content, and timing to optimize in the moment, ensuring campaigns deliver meaningful relevance, not just broader reach.- Transparent and responsible innovation: We drive safe, modular experimentation, from generative applications to agentic workflows, always balancing bold ideas with ethical guardrails. We stay at the forefront of evolving legislation and regulation, ensuring our innovations protect consumers, brands, and the broader ecosystem while moving the industry forward responsibly. Latest posts

In the past, first-party onboarding focused on activating a brand’s own customer data, while third-party onboarding allowed advertisers to tap into external audiences. But the rise of commerce media networks (CMNs) — which now influence over 14% of all digital ad spend — has blurred those once-clear lines. CMNs, retail media ecosystems, and brand partnerships are reshaping how data is shared, accessed, and activated. Today, the question isn’t just who owns the data but why it’s being used. Whether to strengthen customer relationships or create new revenue opportunities, intent now shapes how data must be governed, shared, and measured. ​​For brands with strong first-party data, this shift creates opportunities to deliver more personalized, privacy-safe campaigns to their own audiences and to extend that data’s value by enabling partners to reach new segments. In this connected ecosystem, data onboarding enables brands to activate, scale, and monetize their data responsibly, turning first-party insights into privacy-led growth opportunities. Trusted onboarding partners like Experian can help marketers activate first-party audiences with accuracy while scaling and connecting those audiences across the ecosystem for compliant, revenue-generating collaboration. What is data onboarding? Data onboarding moves offline consumer data — like CRM records, loyalty details, or transaction histories — into digital environments for activation and measurement. It connects real-world insight with digital engagement across display, social, search, connected TV (CTV), and commerce media. Data onboarding is now a strategic pillar for marketers managing signal loss, disconnected data, and rising privacy expectations. The approach you take and who owns the data determine what kind of onboarding it is: First-party onboarding: A brand activates its own customer data across digital platforms. Third-party onboarding: A brand enables others to use its data, often monetizing it — common in CMNs or commerce media ecosystems. Experian helps marketers succeed in both models. With AI-driven identity resolution, persistent identifiers, and privacy-first infrastructure, we make onboarding accurate, compliant, and scalable, regardless of who owns the data. Why do marketers need data onboarding? Even the most data-rich brands often have a limited view and reach when it comes to their audiences. They’re confined to the data they collect directly and to the owned channels they use to engage those people. Customer files may reveal who’s already in the ecosystem, but not always where those people spend time, how they behave across channels, or why they make certain decisions. Onboarding bridges that gap. It transforms offline data into digital activation power, allowing marketers to connect insight with action. Experian makes this possible at scale with trusted identity resolution, data ranked #1 in accuracy by Truthset, audience modeling expertise, and seamless data integration across platforms, helping marketers activate confidently and compliantly. With Experian’s onboarding solutions, marketers can achieve: Unified customer identity across devices, channels, and touchpoints. Cross-channel personalization with consistent, relevant messaging wherever customers engage. Scaled, privacy-compliant reach beyond owned channels without sacrificing control or consent. Better insights and audience creation by blending first-party and Experian Marketing Data for a deeper understanding. Cross-channel activation with deep integrations into the advertising ecosystem. Core steps in the onboarding process While onboarding can vary across use cases, the core process remains consistent. Experian’s AI-enhanced identity infrastructure streamlines every stage of data migration and activation, making each step safer and faster: Data ingestion: Transfer the data into the onboarding environment using privacy-safe encryption and consented parameters to protect sensitive information responsibly from the start. Transformation: Cleanse, standardize, and format records to align with digital identifiers. This eliminates inconsistencies and makes every record easier to recognize and activate later. Identity resolution: Link offline identifiers (names, emails, addresses) to hashed digital equivalents like mobile advertising IDs (MAIDs), CTV IDs, and universal IDs via Experian’s Offline and Digital Graphs. Identity resolution connects customers to their digital presence without exposing personal information. Identity matching: Match hashed emails, MAIDs, and device-graph identifiers to activation partners for each audience across demand-side platforms (DSPs), social, and CTV platforms. This expands your audience reach while maintaining accuracy and privacy. Activation: Deliver privacy-safe audiences to DSPs, social, search, or CMN shelves from third-party data providers (not the CMN’s own data) — or directly to an advertiser’s seat for immediate activation. You’ll turn insights into action and be able to reach the right people with relevant, compliant messaging. Behind this flow is Experian’s identity graph, which links 250 million U.S. individuals, 900 million hashed emails, and 4.2 billion digital identifiers refreshed weekly. It’s the foundation that keeps onboarding accurate as the signal landscape shifts. First-party vs. third-party onboarding Every digital marketing data point has a story, but whose story it tells depends on who’s using it. That distinction defines the difference between first-party and third-party onboarding. Both are essential to modern marketing, but they carry different expectations for control, consent, and accountability. First-party onboarding: Activate your own data safely and strategically First-party onboarding starts with the data a brand earns directly from its own customers through trusted relationships. This data belongs to the brand, as customers have given consent, and the brand has the responsibility (and opportunity) to use it well. That data might include: CRM records Loyalty-program data Purchase or transaction histories Website or app interactions Email subscribers or reward members How first-party onboarding works in practice The onboarding process connects this offline data to digital identity so marketers can reach their existing customers across channels. For example, a credit card company might take its CRM file of cardholders, hash the email addresses, and upload that file to a DSP via Experian’s Audience Engine. Experian’s identity graph resolves those emails to privacy-safe digital identifiers like MAIDs, CTV IDs, or universal IDs. The result is a ready-to-activate audience that can be reached on CTV, social, and display without exposing raw personally identifiable information (PII). Why control matters in first-party onboarding The advantage of first-party onboarding is control; the brand decides what to share and how to use it. It’s a powerful way to: Personalize messages for known customers Re-engage lapsed buyers or loyalty members Suppress existing customers from prospecting campaigns Measure performance with closed-loop attribution Doing first-party onboarding responsibly That control comes with responsibility. Even consented customer data that has been consented to can pose risks if handled carelessly or shared with unverified partners. Experian’s First-Party Onboarding sits on a privacy-first identity foundation, governed by decades of compliance leadership under laws like the Gramm-Leach-Bliley Act (GLBA) and Fair Credit Reporting Act (FCRA). We connect data and identity responsibly, so marketers can activate with confidence while protecting consumers. Why first-party onboarding matters First-party onboarding is the cornerstone of responsible marketing. It allows brands to deepen relationships they already have, using data that customers have freely shared. And with Experian’s secure First-Party Onboarding, that data stays encrypted, compliant, and under the brand’s control from start to finish. Third-party onboarding: Share and monetize data responsibly Third-party onboarding begins when a brand allows someone else to use its data. It’s how data providers, publishers, and especially CMNs monetize their audiences — turning first-party customer insights into addressable, privacy-safe segments that advertisers can buy and activate across digital channels. How third-party onboarding works in practice Think of it as data collaboration at scale. Let’s say a retailer collects first-party shopper data like product purchases, loyalty card usage, and store visits. Then, they partner with Experian to make that audience available to outside advertisers, such as a consumer packaged goods (CPG) brand. Through Experian Third-Party Onboarding, those audiences are resolved, privacy-protected, and distributed to integrated destinations such as The Trade Desk, Magnite, or NBCUniversal for activation. To the retailer, it’s their first-party data. To the CPG, it’s third-party data they can use for targeted campaigns. To Experian, it’s an opportunity to ensure the entire exchange is accurate and compliant. Why scale matters in third-party onboarding The benefit of third-party onboarding is scale. It enables data owners to monetize their insights, while giving advertisers access to richer audiences they couldn’t build on their own. It’s the engine behind CMNs, commerce media, and the growing data-sharing economy. With a partner like Experian, that scale becomes even more powerful. Our advanced modeling and identity solutions help brands expand their audiences responsibly using lookalike and predictive modeling to identify high-value segments, increase reach, and maximize performance across every activation channel. The responsibilities of data sharing in third-party onboarding As data ecosystems grow, so does the opportunity to collaborate responsibly. Once data leaves its original owner’s ecosystem: Consent obligations become more complex. Control over downstream usage can blur. Regulatory oversight increases, especially around transparency and consumer rights. With the right governance in place, these responsibilities can help strengthen partnerships, protect consumers, and create a foundation for sustainable growth. Experian’s ethical enablement role in third-party onboarding Experian’s enablement role is both technical and ethical. Our deep expertise enables us to partner with brands and support their monetization efforts, helping them derive new value from their data while maintaining the highest standards of privacy and compliance. Meanwhile, our infrastructure ensures third-party data onboarding happens securely and transparently: Identity resolution expands reach without overexposing identifiers. Data verification and governance ensure partners meet strict privacy standards. Revenue-share structures maintain fairness without hidden costs. Cross-channel integrations enable you to onboard your data once and activate it everywhere (programmatic, CTV, or social) through Experian’s 30+ direct and 200+ indirect destination partnerships. Why third-party onboarding matters Third-party onboarding is the foundation of modern data collaboration. When done through Experian, it becomes a trusted extension of your brand’s identity governed by the same privacy, consent, and accuracy standards that strengthen your first-party ecosystem. We help brands uncover new opportunities for growth, partnership, and responsible innovation. When first-party onboarding turns into third-party onboarding When data ownership shifts, privacy expectations change, and the rules of onboarding start to look a little different. This stage can feel complex, but with the right approach, the crossover becomes clear. It’s a natural evolution that helps brands connect data more effectively and collaborate confidently. Here’s what that can look like in practice. A retailer uses its own first-party data to engage loyal shoppers through its website, app, or email program. The data is secure, consented, and fully under the retailer’s control. Then comes collaboration. The retailer decides to partner with a brand, like a CPG company, to reach those same shoppers across connected TV or the open web. In that moment, the retailer’s first-party data becomes the CPG’s third-party data. Ownership doesn’t really change, but accountability does, along with new privacy and compliance considerations. This “crossover moment,” when first-party onboarding turns into third-party activation, is a small shift with big potential that can lead to new reach, deepen collaboration, and strengthen customer connections across the marketing ecosystem when managed responsibly. Why clarity matters in the crossover between first- and third-party onboarding When data starts flowing beyond owned channels, questions naturally come up. Marketers want to know things like: Who “owns” the audience once it’s shared with a partner or DSP? Whose privacy notice applies — the retailer’s, the brand’s, or both? How do we keep match accuracy without overexposing PII? Who’s responsible for opt-outs and suppression compliance downstream? These are the right questions to be asking, and they’re signs of a mature, data-driven strategy. Asking them is what helps brands strengthen governance, build trust, and get more value from collaboration. With the right framework in place, what could feel complicated becomes clear, opening the door to more confident growth across CMNs and other shared-data environments. How Experian brings clarity and control to the first- and third-party onboarding crossover As a neutral, privacy-first partner, we provide the infrastructure that keeps data secure, compliant, and meaningful wherever it flows. Our onboarding solutions help both sides of the partnership — retailers and advertisers — maintain trust through: Clear ownership and consent management: Experian enforces data-handling rules that preserve each party’s control. Every record is matched and activated in accordance with strict consent parameters and Global Data Principles that exceed industry standards. Accurate, privacy-safe identity resolution: Our Offline and Digital Graphs connect people to their devices, households, and behaviors using hashed identifiers, ensuring match precision while protecting individuals. AI-powered contextual intelligence: Experian’s AI models analyze real-world behavior and contextual signals to enhance match quality and extend reach without reliance on cookies. For CMNs, that means better off-site activation, targeting the right shoppers in the right environments while maintaining compliance. Trusted integrations and transparent reporting: With direct integrations into 30+ programmatic and TV destinations, Experian delivers consistent match rates and unified measurement through solutions like Activity Feed and Experian Outcomes. This is how Experian transforms complex data challenges into seamless, scalable collaborations that give marketers the confidence to expand responsibly into commerce media and commerce ecosystems. The new standard of responsible AI and commerce media Commerce media represents the future of audience activation, but only if the transition is managed responsibly. As the lines blur between data ownership and activation rights, Experian’s AI-driven, privacy-first identity framework acts as the connective tissue between retailers, brands, and platforms. We help CMNs: Enrich shopper data with Experian Marketing Attributes for deeper insights. Extend addressability off-site using privacy-safe identity resolution. Optimize activation through real-time, contextually aware audience expansion. Measure results transparently through privacy-compliant feedback loops. In short, we ensure that when your first-party onboarding becomes third-party activation, trust and performance stay intact. Why choose Experian's onboarding solutions? Many view onboarding as a data transfer, but we treat it as a trust process where accuracy, privacy, and performance align. Here’s why marketers choose us: 1. Unmatched data and identity foundation When brands struggle with incomplete or siloed customer data, Experian’s unified foundation connects fragmented records into a single, accurate identity. Our Offline and Digital Graphs link households, individuals, and devices with persistent accuracy. Updated weekly and built on decades of historical data, our graphs maintain 97% household coverage across the U.S., even through signal loss. 2. Privacy-first and compliance-led Given tightening regulations and growing consumer expectations, privacy compliance is essential. With decades as a regulated data steward, we apply the same rigorous controls from our financial operations to marketing data. Every data partner is verified for transparency and compliance with consent requirements, and all consumer data is governed by Experian’s Global Data Principles, which exceed industry standards. We help brands meet their privacy and consent obligations confidently while maintaining the data integrity that drives results. 3. Real-time, contextual activation Experian’s industry-leading Offline and Digital Graphs are widely adopted across the advertising ecosystem, powering identity resolution and audience activation for the world’s top marketers. Our integrations span 30+ direct and 200+ indirect activation platforms, including leading DSPs, CTV networks, and commerce environments. With real-time, AI-driven contextual intelligence, Experian enables privacy-safe targeting even in signal-limited environments through solutions like Contextually-Indexed Audiences that deliver reach without reliance on cookies or personal identifiers. 4. Platform flexibility Modern marketing requires interoperability. Experian’s onboarding framework is technically integrated across multiple platforms, offering brands and data providers the freedom to activate where they choose. Whether through self-service onboarding in Audience Engine for first-party data or managed onboarding for third-party monetization, Experian scales with your organization, providing transparent pricing, seamless delivery, and dedicated support teams to ensure every connection performs. 5. Human-centered innovation Marketing should strengthen relationships and build trust. Our AI-driven identity systems are designed to protect privacy, respect individuals, and create real human value — helping brands connect with people meaningfully. They aren’t built to collect more data but to make better use of the data you already have by connecting insights responsibly and ethically.  Every innovation at Experian is guided by the principle of balancing personalization with compliance. Top use cases for Experian’s onboarding solutions Our onboarding solutions are transforming how brands operate across industries every day. Whether you’re deepening loyalty, expanding reach, or proving performance, Experian helps connect data responsibly to drive measurable results. Here’s where we make the biggest impact: Automotive: Connect purchase intent data with digital identifiers for more efficient targeting. Commerce media: Use both first- and third-party onboarding — first-party for on-site activation and owned marketing, third-party for off-site activation and monetization — all while maintaining compliance and accurate attribution. CPG: Activate shopper data through retailer partnerships to drive off-site reach and stronger brand collaboration. Data providers: Monetize audience segments across Experian’s programmatic and TV integrations. Financial services: Deliver compliant, personalized cross-channel offers with unified identity. Healthcare: Use National Provider Identifier (NPI) onboarding to reach healthcare professionals compliantly. Retail: Power loyalty personalization, partner monetization, and CMN audience activation. Across each use case, Experian’s privacy-first identity foundation turns data onboarding into a trusted driver of growth and stronger customer relationships. Navigate the new data economy with Experian Data onboarding has come a long way, mirroring the changes in marketing itself. We’ve moved from relying on third-party cookies to empowering first-party data, and now to building collaborative ecosystems like CMNs. At Experian, we’re right in the middle of that evolution. With decades of data expertise, privacy leadership, and AI-driven activation, we help marketers connect more responsibly, measure what matters, and grow with confidence. Want to see what that looks like for your brand? Let’s build safer connections together. Start connecting responsibly Data onboarding FAQs What is Experian First-Party Onboarding and Third-Party Onboarding? Experian First-Party Onboarding helps brands take the customer data they already own, like CRM lists or loyalty files, and use it safely across digital channels for targeting, personalization, and measurement. Experian Third-Party Onboarding helps retailers, publishers, and data providers share or monetize their audiences responsibly with partners through secure, privacy-first activation.Both are powered by Experian’s trusted identity foundation that keeps every connection accurate, compliant, and privacy-safe. What’s the difference between first-party and third-party data onboarding? The difference between first- and third-party onboarding is who’s using the data. First-party means a brand is activating its own customer information, while third-party means that data is being shared or used by another advertiser or partner. When does first-party onboarding become third-party onboarding? First-party onboarding becomes third-party onboarding most often in CMNs or commerce media. When a retailer monetizes its first-party shopper data for use by CPGs or advertisers, the use case shifts to third-party onboarding. Why do marketers need both first- and third-party onboarding? First-party onboarding helps brands reach and understand their existing customers, while third-party onboarding helps expand reach, enable partnerships, and monetize data responsibly. Latest posts

If you buy media today, you’re already feeling the shift: the best results don’t always come from broad, open auctions or static “safe site” lists; they’re coming from deals that combine the right data with the right inventory and let algorithms optimize in real time. That’s curation. And when it’s done right, it reduces data and media waste for buyers and raises eCPMs (effective cost per thousand impressions) and win rates for publishers.  As part of our Cannes Content Studio series, leaders from Butler/Till, Index Exchange, OpenX, PubMatic, and Yieldmo discuss how curation cuts waste and lifts results. What is real curation? Real curation isn’t “packaging inventory.” It’s a strategic framework built on three pillars:  1. Unique data Privacy-compliant and accurate. 2. Strong supply connections Access to quality inventory from publishers at scale. 3. Optimization tools To measure, refine, and improve performance throughout the campaign lifecycle. Why it matters: Manual approaches hit a ceiling. They can’t react quickly to shifting content, identity signals, or auction dynamics. That’s where technology partners come in, keeping the optimization loop running continuously. Intelligence at every touchpoint Curation isn’t about shifting control between platforms. It’s about better brand decisions, connecting opportunity-rich supply to the brand’s preferred buying platform and enriching each buy with audience data. In practice, supply-side platforms (SSPs) are ingesting richer signals to route inventory more effectively and support frequency caps and deal prioritization, in collaboration with demand-side platforms (DSPs). "I think we’re seeing a shift toward bringing more DSP capabilities into the SSP, like supply-side targeting and data driven curation. Advancements in areas like CTV are enabling targeting based on content signals, and SSPs are pulling in more data to inform which supply is sent to the DSP, helping with things like frequency caps."Matt Sattel Why page-level targeting beats static lists Static domain lists were a useful first step for quality control. The intent was sound, but the approach was too cumbersome for today’s signal-rich buying. Today, AI and contextual engines read the page, not just the site, and adapt in real time. Page-level logic delivers three key benefits:  Accuracy by targeting high-intent, page-level content.  Relevance by matching the creative to both the content and the audience context. Speed by enabling campaigns to move away from underperforming pages in real time, without waiting for a manual trafficking change.  "AI-driven contextual engines evaluate the page, not just the domain, to curate inventory in real time. That moves curation from static allowlists to adaptive logic for greater accuracy, relevance, and speed."Sophia Su Partnerships broaden who influences the buy Curation works when publishers, agencies, data partners, and platforms share signals and KPIs.  Horizontal curation (across multiple SSPs) assembles broader, higher-quality reach and resilience, ideal for scale and diversity of supply.  Vertical curation (an SSP’s in-house product) provides deep controls within a single exchange, useful for specific inventory strategies.  Creative and data now shape supply and demand: better creative decisioning, tested against richer signals, improves outcomes.  DSPs remain central for activation and pacing. But the sell-side’s growing intelligence means more accurate inventory routing and signal application before a bid ever fires.  "Curation will continue to evolve through deeper data partnerships and expanded use across publishers and agencies, with more sophisticated types of optimization. DSPs will remain critical to activation, even as sell-side decisioning plays a larger role in identifying and shaping the supply to select."Mike McNeeley Curation delivers access and measurable performance Here’s what curated deals are delivering. For buyers ResultType of result36-81%savings on data segments10-70%lower cost per click (CPCs)1.5-3xhigher click-through rates (CTRs)10-30%higher video completion rates For publishers ResultType of result20%bid density118%win rate10%revenue on discovered inventory25%eCRM on incremental impressions Why it works: When data, supply, and optimization are integrated, you reduce waste, surface better impressions, and let algorithms compound your advantage. That’s why curated private marketplaces (PMPs) have grown at ~19% compound annual growth rate (CAGR) since 2019.  "Publishers using supply-side curation see ~15% more diverse buyers and 20–25% better performance than buy-side-only targeting. Smarter packaging and signal application tighten auctions and strengthen outcomes."Howard Luks Holistic curation streamlines planning and outcomes Curation adds the data layer earlier in the buying process, starting at the supply-side. This creates more opportunities to reach the right audience and improves scale and performance. By replacing multiple line items with a single curated deal, campaign setup becomes faster and less error-prone. Curated deals also simplify measurement by including the necessary context for accurate attribution, while dynamic adjustments ensure campaigns remain optimized without requiring manual updates. "Publishers using supply-side curation see ~15% more diverse buyers and 20–25% better performance than buy-side-only targeting. Smarter packaging and signal application tighten auctions and strengthen outcomes."Gina Whelehan It’s much more streamlined, bringing more pieces together so we’re thoughtful and holistic. Adding the audience and data element creates more scale and strategy in how we curate supply and data, and ultimately better results for clients. The bottom line Curation has matured from buzzword to performance system. DSPs still anchor activation and pacing, but better sell-side pipes now pre-route inventory and apply signals before any bid starts, making the whole system faster and more accurate. When you combine unique signals, tight supply connections, and always-on optimization, you gain addressability, reduce waste, and achieve better business outcomes for both buyers and sellers.  Curation isn’t just a trend; it’s where programmatic advertising is headed. Start testing curated PMPs today to see the difference for yourself. Explore curated PMPs with Audigent Curation FAQs What is curation in performance marketing? Curation in performance marketing is the process of combining data, inventory, and optimization to deliver better results. Audigent supports curated strategies through privacy-safe data and advanced integrations. How does curation benefit marketers? Curation reduces wasted spend by targeting high-quality impressions and optimizing campaigns in real time. Audigent’s solutions help marketers achieve higher click-through rates, lower costs, and better engagement across channels. What are curated PMPs, and why are they important? Curated PMPs are deals that use curated data and inventory to deliver measurable results. They help buyers save on data costs, improve ad performance, and achieve better video completion rates, while publishers see higher win rates and revenue. How does Audigent support curated strategies? Audigent provides unique data assets, privacy-safe integrations, and optimization tools that help marketers and publishers create curated deals. Our solutions ensure campaigns are more efficient, targeted, and effective from start to finish. What’s the difference between horizontal and vertical curation? Horizontal curation combines inventory across multiple platforms for broader reach and diversity, while vertical curation focuses on deep control within a single platform. Both approaches can be tailored to specific campaign goals with Audigent's expertise. Latest posts

How third-party data has changed and why it matters in 2025 For years, third-party data operated in an expansive, lightly regulated marketplace: fast-moving, high-growth, and filled with players eager to capitalize on digital marketing’s demand for audience insights.   That era is over. Regulatory scrutiny, stricter compliance standards, and rising consumer expectations have already transformed the market. Today, third-party data belongs to partners with proven expertise and built-in compliance. This isn’t a space for opportunistic newcomers; it’s one that rewards long-term commitment and trust.  Even the rapid rise of retail media networks (RMNs) reflects this shift. These platforms are built on long-standing, trusted relationships between brands, retailers, and data partners, utilizing that foundation in new ways to reach audiences responsibly and effectively. The best providers have already made this transition; those still “shifting” are catching up. From growth to governance: A market defined by accountability The third-party data ecosystem has matured. After years of rapid expansion and recalibration, the market has stabilized around a new standard: data quality and regulatory accountability. Third-party data enriches first-party insights with attributes such as income, gender, and interests that round out the customer view. But when the industry grew unchecked, unreliable providers diluted quality and trust. This resulted in a decline in the overall value and reliability of the third-party data marketplace. That breakdown led directly to today’s privacy laws, now active across more than 20 U.S. states and numerous countries worldwide. These regulations reflect a permanent consumer expectation: relevance delivered responsibly. Consumers aren’t rejecting personalization; they’re rejecting how it’s been done in the past. They still want relevant, tailored experiences, but they expect brands to deliver them through ethical, transparent data practices. Does third-party data still matter in a privacy-first era?  Third-party data isn’t disappearing, if anything, it’s become more important. Brands will always need additional insight to deepen customer understanding; first-party data alone only reflects what’s already known. The industry has entered a mature phase where data quality and compliance are table stakes. The companies leading today built their data infrastructure on rigorous standards, regulatory foresight, and transparent governance. That same foundation powers the next wave of innovation, including the explosive growth of RMNs. RMNs rely on responsibly sourced third-party data to enrich shopper insights, validate audiences, and extend addressability beyond their own walls. Trusted data partners make that expansion possible, connecting retail environments with broader media ecosystems while maintaining privacy and accuracy. High-quality, compliant third-party data remains essential because it: Fills knowledge gaps Good third-party marketing data complements first-party insights with demographic, behavioral, and transactional context, providing the missing puzzle pieces to complete the full customer profile.  Improves accuracy Filling in gaps in customer understanding helps you identify, reach, and engage your customers more effectively. This helps improve the delivery of relevant messages and offers to your customers and prospects across channels.  Builds connections Third-party data helps brands build loyalty with consumers by speaking to their interests, and intent behind purchases.  Fuels prospecting Third-party data can help you find your best prospects. By enriching customer files, you can understand who your best customers are, and how to find more of them. By modeling this data, you can determine who your best customers are and source prospects similar to them.  Advancements in AI and machine learning are reshaping how this data is used across the ecosystem. What was once primarily a buy-side tactic is now expanding into the sell-side, where publishers and platforms are using data to curate, package, and activate audiences more intelligently. As AI enhances modeling accuracy and automation, third-party data will play an even greater role in connecting brands and consumers in more meaningful, privacy-conscious ways.  The bottom line: it’s not about having more data; it’s about having better, verified data you can trust. How can you spot a trustworthy data partner?  The strongest third-party data partners demonstrate accountability through experience, infrastructure, and integrity. Swipe right on the perfect data partner Look for providers that: Operate with clear data principles  Trustworthy partners publish and follow codified data principles that guide every step of data handling. Experian adheres to a set of global data principles designed to ensure ethical practices and consumer protection across all our operations. Treat new privacy regulations as routine  For mature providers, evolving privacy laws are routine, not disruptive. At Experian, privacy and compliance have long been built in. Every partner and audience goes through Experian’s rigorous review process to meet federal, state, and local consumer privacy laws. Decades of experience have shaped processes that emphasize risk mitigation, transparency, and accountability. Stay deeply connected  Leading data companies maintain deep relationships with technology partners and industry and regulatory groups to ensure that ethical data practices are put into practice and their customers are aware of platform-specific regulations. Experian's relationships with demand-side platforms (DSPs), supply-side platforms (SSPs), and even social platforms like Meta, ensures we are aware of any platform-specific initiatives that may impact audience targeting. We’re also active participants in many trade groups to ensure that the industry puts ethical data practices in place to ensure consumers still receive personalized experiences but their data usage and collection is opt-in, transparent and handled with their privacy at the center of the transaction. Have a proven track record in the industry  Longevity matters in a regulated and compliance-driven industry. Providers that have thrived through economic cycles and regulatory shifts are the ones equipped for the future. The ability to source high-quality third-party data is core to their business, not an afterthought. Our data is ranked #1 in accuracy by Truthset, giving our clients confidence that every decision they make is backed by the industry’s most reliable insights. Why the future of third-party data depends on accountability  The third-party data industry has already crossed the threshold from expansion to accountability. The companies leading this era have established their credibility through governance and proof. The future belongs to providers that:  Build with regulatory foresight  Maintain rigorous quality assurance  Prioritize partnership over profit The Wild West days are long gone. The third-party data ecosystem is now defined by stability, transparency, and shared responsibility. Partner with Experian for data you can trust and results you can prove  When accuracy and accountability define success, you need a partner built on both. Work with the company that’s setting the standard for responsible data-driven marketing and helping brands connect with people in meaningful, measurable ways.  Get started About the author Jeremy Meade VP, Marketing Data Product & Operations, Experian Jeremy Meade is VP, Marketing Data Product & Operations at Experian Marketing Services. With over 15 years of experience in marketing data, Jeremy has consistently led data product, engineering, and analytics functions. He has also played a pivotal role in spearheading the implementation of policies and procedures to ensure compliance with state privacy regulations at two industry-leading companies. Third-party data FAQs What is third-party data? Third-party data is information collected by organizations that don’t have a direct relationship with the consumer. It supplements first-party data by adding demographic, behavioral, and interest-based insights. Why are privacy regulations reshaping data practices? Privacy regulations are reshaping data practices because consumers expect control over how their information is used. That expectation led directly to today’s privacy laws, now active across more than 20 U.S. states and numerous countries worldwide. These regulations reflect a permanent consumer expectation: relevance delivered responsibly. Consumers aren’t rejecting personalization; they’re rejecting how it’s been done in the past. They still want relevant, tailored experiences, but they expect brands to deliver them through ethical, transparent data practices. Laws like the CCPA and state-level privacy acts enforce this expectation, holding brands and data providers accountable for the ethical use of data. Can brands still use third-party data safely? Yes, brands can still use third-party data safely when sourced responsibly. Partnering with established, compliant providers like Experian ensures both legal protection and data accuracy.  How does Experian ensure compliance with evolving privacy regulations? Experian adheres to a set of global data principles designed to ensure ethical practices and consumer protection across all our operations. At Experian, privacy and compliance have long been built in. Every partner and audience goes through Experian’s rigorous review process to meet federal, state, and local consumer privacy laws. Decades of experience have shaped processes that emphasize risk mitigation, transparency, and accountability. Experian's relationships with demand-side platforms (DSPs), supply-side platforms (SSPs), and even social platforms like Meta, ensures we are aware of any platform-specific initiatives that may impact audience targeting. We’re also active participants in many trade groups to ensure that the industry puts ethical data practices in place to ensure consumers still receive personalized experiences but their data usage and collection is opt-in, transparent and handled with their privacy at the center of the transaction. What should marketers look for in a data partner? Marketers should look for transparency, longevity, and evidence of compliance when looking for a data partner. The best partners can clearly explain how their data is sourced, validated, and maintained. Read Experian's guide on how you can swipe right on the perfect data partner here. Latest posts

What makes data “good” in the age of AI? In AI-driven marketing, data quality now defines success. “Good data” in AI isn’t about volume; it’s about the balance of accuracy, freshness, consent, and interoperability. As algorithms guide decisions, they must learn from data that’s both accurate and ethical. At Experian, we believe good data must meet four conditions: 1. Accurate Verified and anchored in real human identity. 2. Fresh Continuously updated to reflect today’s consumers. 3. Consented Collected and governed transparently. 4. Interoperable Easily integrated across platforms through a secure, signal-agnostic identity spine, enabling seamless data activation. This is the data AI can trust and the data that keeps marketing relevant, predictive, and privacy-first. Listen to InfoSum's Identity Architect's podcast for more on AI, outcomes, and curation Why does data accuracy matter more than ever? AI models are only as intelligent as their inputs. Incomplete or inconsistent data leads to bad predictions and wasted spend. As the industry moves toward agentic advertising, where autonomous systems handle campaign buying and optimization, data accuracy becomes even more critical. If your ad server or audience data is flawed, these new AI agents will simply automate bad decisions faster. Experian applies rigorous quality filters and conflict resolution rules to ensure our data is both deterministic and accurate. Deterministic signals alone don’t guarantee accuracy; they must be verified, deduplicated, and contextualized. Our identity resolution process anchors every attribute to real people, giving brands and platforms the confidence that every insight stems from truth, not noise. Our data is ranked #1 in accuracy by Truthset, giving our clients confidence that every decision they make is backed by the industry’s most reliable insights. See how Experian's Digital Graph improved attribution accuracy for a demand-side platform (DSP) with 84% of IDs resolved Just because it is deterministic, doesn’t mean it’s highly accurate. You still need to refine and validate your data to make sure it tells a consistent story. You need to anchor your data around real people. Calculate the real impact of data accuracy Why does AI need fresh data? Outdated data can’t predict tomorrow’s behavior. AI thrives on recency. At Experian, our audiences are refreshed continuously to mirror real-world signals, from purchase intent to media habits, so every campaign reflects what’s happening now, not six months ago. And we don’t just advocate for fresh data, we rely on it ourselves. Our own AI-powered models, used across our audience and identity platforms, are continuously retrained on the most current, consented signals. This allows us to see firsthand how freshness drives better accuracy, faster optimization cycles, and more relevant outcomes. But freshness alone isn’t enough. With predictive insights, our models go beyond describing the past. They forecast behaviors, fill gaps with inferred attributes, and recommend next-best audiences, helping you anticipate opportunity before it happens. Fresh and predictive data means you’re reaching people in the moment that matters and shaping what comes next. With AI, that’s what defines performance. Explore Experian's most popular audiences, ready to activate now How do consent and governance build trust in AI? Responsible AI starts with responsible data. With 20 U.S. states now enforcing privacy laws, data compliance isn’t optional, it’s operational. At Experian, privacy and compliance are built in. Every data signal, attribute, audience, and partner goes through our rigorous review process to meet federal, state, and local consumer privacy laws. With decades of experience in highly regulated industries, we’ve built processes that emphasize risk mitigation, transparency, and accountability. Governance isn’t just about regulation, it’s also about innovation done right. We drive transparent and responsible innovation through safe, modular experimentation, from generative applications to agentic workflows. By balancing bold ideas with ethical guardrails and staying ahead of evolving legislation, we ensure our innovations protect consumers, brands, and the broader ecosystem while moving the industry forward responsibly. Compliance and governance aren’t just boxes to check; they’re the foundation that gives AI its license to operate. How does interoperability enable AI’s full potential? AI delivers its best insights when data connects seamlessly across fragmented environments. Our signal-agnostic identity spine allows data to move securely between platforms (connected TV, retail media networks, and demand-side platforms) without losing context or compliance. Interoperability isn’t just about moving data between systems; it’s about connecting insights across them. When signals connect across environments, AI gains a more complete view of the customer journey revealing true behavior patterns, intent signals, and cross-channel impact that would otherwise remain hidden. This unified perspective allows AI to connect insights in real time, improving predictions, performance, and personalization while protecting privacy. Where do AI and human oversight meet? AI can make marketing more predictive, but people make it meaningful. At Experian, our technology brings identity, insight, and generative intelligence together so brands, agencies, and platforms can reach the right people with relevance, respect, and simplicity. Our AI-powered models surface connections, recommend audiences, and uncover insights that would take humans months to find. But our experts shape the process, crafting the right inputs, ensuring data quality, reviewing model outputs, and refining recommendations based on industry knowledge and client goals. It’s this partnership between advanced AI and experienced people that turns predictions into actionable, trustworthy solutions. What “good data” looks like in action “Good data” becomes most powerful when it’s put to work. At Experian, our marketing data and identity solutions help brands and their partners connect accurate, consented, and interoperable data across the ecosystem, turning insight into measurable outcomes. Learn more about Experian's data solutions Learn more about Experian's identity solutions When Windstar Cruises and their agency partner MMGY set out to connect digital media spend to real-world bookings, they turned to Experian’s marketing data and identity solutions to close the attribution loop. By deploying pixels across digital placements and using Experian’s identity graph to connect ad exposure data with reservation records, we created a closed-loop attribution system that revealed the full traveler journey, from impression to confirmed booking. The results were clear: 6,500+ bookings directly tied to digital campaigns, representing more than $20 million in revenue, with a 13:1 ROAS and $236 average cost per booking. Attributed audiences booked $500 higher on average, and MMGY’s Terminal audience segments powered by Experian data achieved a 28:1 ROAS. This collaboration shows that responsible, high-quality data and AI-driven insights don’t just tell a better story; they deliver measurable business performance. Download the full case study How to choose the partner built for responsible AI Why the future of AI depends on “good” data The next phase of AI-driven marketing won’t be defined by who has the most data, but by who has the best. Leaders will: Operate with clear data principles grounded in transparency and truth Build consent and compliance into every workflow Keep data accurate, current, and interoperable Pair automation with human oversight   AI success starts with good data. And good data starts with Experian, where accuracy, privacy, and purpose come together to make marketing more human, not less. Partner with Experian for AI you can trust About the author Budi Tanzi VP, Product, Experian Budi Tanzi is the Vice President of Product at Experian Marketing Services, overseeing all identity products. Prior to joining Experian, Budi worked at various stakeholders of the ad-tech ecosystem, such as Tapad, Sizmek, and StrikeAd. During his career, he held leadership roles in both Product Management and Solution Engineering. Budi has been living in New York for almost 11 years and enjoys being outdoors as well as sailing around NYC whenever possible. "Good" data in AI FAQs What defines “good data” according to Experian? At Experian, we define "good data" as the balance of accuracy, consent, freshness, and interoperability. We apply rigorous governance, validation, and cleansing across every signal to ensure that AI systems learn from real-time behaviors, not assumptions. This approach turns data into a foundation for reliable, ethical, and high-performing intelligence. How does Experian ensure AI-ready data accuracy? Experian ensures AI-ready data accuracy through advanced cleansing, conflict resolution, and human anchoring. Experian ensures AI models rely on verified, high-quality inputs. Experian's data is ranked #1 in accuracy by Truthset. Can Experian help brands stay compliant with privacy laws? Yes, Experian can help brands stay compliant with privacy laws. Experian’s privacy-first governance framework integrates ongoing audits, legal oversight, and consent management to ensure compliance with all federal, state, and global privacy laws. Compliance isn’t an afterthought; it’s embedded in every step of our data lifecycle. How does Experian make AI more human? Experian makes AI more human by pairing innovation with human oversight to ensure AI helps marketers understand people, not just profiles. At Experian, we believe the future of marketing is intelligent, respectful, and human-centered. AI has long been part of how we help brands connect identity, behavior, and context to deliver personalization that balances privacy with performance. Our AI-powered solutions combine predictive insight, real-time intelligence, and responsible automation to make every interaction more relevant and ethical. Where can marketers access Experian’s high-quality data? Marketers can activate Experian's high-quality data directly in Experian’s Audience Engine, or on-the-shelf of our platform partners where Experian Audiences are ready to activate. Built on trusted identity data and enhanced with partner insights, it’s where accuracy meets accessibility, helping brands power campaigns with confidence across every channel. Latest posts

Artificial intelligence (AI) is becoming a bigger part of modern advertising, changing how brands connect with people. At Experian, we believe this technology should make marketing more human, not less. We use AI to help marketers understand consumer behavior, respect privacy, and deliver messages that matter. As part of our latest Cannes Content Studio series, we spoke with leaders from AdRoll, MiQ, OpenX, Optable, PMG, PubMatic, and Yieldmo. Their insights show a clear path forward; one where technology supports human strategy to create more meaningful connections.  1. How does AI help you see audiences more clearly? AI decodes complex behavioral signals to reveal the values and mindsets behind decisions, and increasingly, it predicts what audiences will care about next. This allows marketers to deliver timely, relevant messages that resonate with audiences. At Experian, we help brands use these insights to connect more meaningfully and ethically. Takeaway: Experian’s tools help brands uncover audience insights, enabling more meaningful and ethical connections. 2. Where does AI actually save time, and improve results? Running campaigns is time-consuming. Solutions like Agentic AI now orchestrate end-to-end campaign workflows, audience building, trafficking, QA, pacing, and routine optimizations, so teams focus on strategy and creativity. Many leaders (94%) are investing broadly in AI to drive efficiency and impact, and 49% of marketers use it daily for image and video generation, shifting repetitive tasks from people to tools. By quickly combining past and current performance data, AI can pre-optimize before launch and refine mid-flight, while marketers steer the message and experience. "AI uses past campaign data to optimize performance before launch, continues learning during the campaign, and refines strategies based on the insights it generates, driving better results over time.”Howard Luks Takeaway: Experian’s solutions streamline campaign workflows, allowing marketers to focus on creativity and strategy while improving results. 3. How do AI and human strategy work together in real time? AI handles real-time data analysis and optimization, freeing marketers to focus on strategy, messaging, and creativity. By defining audiences once and activating them across platforms, teams can adapt quickly and confidently. At Experian, we combine machine intelligence with human insight to deliver smarter, more agile campaigns. “AI analyzes data, pulls insights, and automates optimizations, allowing marketers to focus on strategy, messaging, and creativity instead of spending time digging through numbers and data."Lizzie Chapman Takeaway: Experian solutions empower marketers to adapt quickly and confidently, combining human strategy with insights. 4. What does privacy-first look like now? Relying on simple, static data points is no longer enough. A modern approach to identity blends deterministic data (like known identifiers) with modeled components, ensuring data remains de-identified where possible. Clear, transparent guardrails, permitted-use policies, retention limits, sensitive-category blocks, and audit trails, help brands balance personalization with privacy, build trust, and respect user choice. "A new blend of identity systems combines deterministic data, known identifiers, and model driven components, creating fresh ways to address identity and activate campaigns with precision.” Vlad Stesin Takeaway: Experian’s privacy-first identity solutions help brands balance personalization with safety, ensuring trust and compliance. 5. Which new data signals matter, and why? AI is unlocking a new generation of data signals, like content context, sentiment, emotional tone, suitability, attention, and commerce intent, that go beyond legacy identifiers like cookies and demographics. These signals can help brand messages appear in the most relevant environments and by high-value audiences. Used well, they improve relevance, avoid placements near unsuitable or off-brand content, and drive stronger campaign outcomes. "Unlocking new data sets (like emotion, sentiment, and context), AI is creating innovative ways to connect client content with advertising opportunities and rethink how we approach the market.” Sam Bloom Takeaway: Experian’s solutions use advanced data signals to help marketers create more effective and innovative campaigns. Why Experian for human-centered AI? We deliver on the promise of AI-powered marketing through five pillars: See audiences clearly across households, individuals, and devices. Recommend next‑best audiences and automate setup for faster execution. Adapt in real‑time to keep relevance high. Innovate responsibly with strong governance and transparency. Plan, activate, and measure campaigns on one unified platform. The future of intelligent marketing AI will keep accelerating, but the goal stands: make marketing more human. Teams that blend privacy‑first identity, predictive insight, AI‑powered simplicity, and real‑time intelligence will earn trust and drive outcomes. Experian helps you bring those pieces together so every campaign moves from assumptions to clarity, and from activity to measurable results. Talk to Experian about building human-centered AI into your marketing strategy AI marketing trends FAQs How does AI help marketers understand audiences better? AI analyzes complex signals, behaviors, values, and mindsets to provide a clearer picture of what matters to audiences. That clarity makes messaging feel personal and relevant. Learn more about Experian’s Digital Graph and how it can help marketers understand audiences better.  Where is AI improving campaign efficiency today?   Automation reduces manual setup and reporting, so teams focus on strategy and creative. Nearly half of marketers (49%) use AI daily for image and video generation, reflecting this shift.  What does “smarter activation across platforms” mean? Smarter activation across platforms means defining audiences once, then carrying them across channels with live feedback, so relevance and suitability stay high. See how Experian enables smarter activation with our data and identity solutions.  How is AI changing identity?  Privacy‑first identity blends deterministic and modeled components, keeping data de‑identified where possible. Experian’s solutions balance personalization with safety. Learn about Experian’s identity solutions is changing identity.  Why is structured data important for AI‑driven marketing?   AI systems rely heavily on brand‑managed sources. 86% of citations come from websites, listings, and reviews, so clean, accurate, structured data makes your answers and your brand more discoverable. Discover how Experian supports structured data for AI-driven marketing.  Latest posts