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Technology is pushing the boundaries of commerce like never before. Artificial intelligence (AI) is one of the primary driving technologies at the forefront of the commerce evolution, using advanced algorithms to revolutionize marketing and personalize customer experiences. As of 2024, AI adoption in e-commerce is skyrocketing, with 84% of brands already using it or gearing up to do so.
This article explores the AI revolution coming to commerce, focusing on what makes AI a driving force for e-commerce in particular, and the ways it’s reshaping how businesses engage with consumers.
Understanding the AI revolution in commerce
AI is quickly reshaping commerce as we know it by democratizing access to sophisticated tools once reserved for large corporations, breaking down functional silos within organizations, and integrating data from multiple sources to achieve deeper customer understanding. It’s paving the way for a future where every brand interaction is uniquely crafted for the individual, powered by AI systems that anticipate preferences proactively.
AI is a broad term that encompasses:
- Data mining: The gathering of current and historical data on which to base predictions
- Natural language processing (NLP): The interpretation of human language by computers
- Machine learning: The use of algorithms to learn from past experiences or examples to enhance data understanding
The capabilities of AI have significantly matured into powerful tools that can improve operational efficiency and boost sales, even for smaller businesses. They have also fundamentally changed how businesses interact with customers and handle operations. As AI continues to develop, it has the potential to provide even more seamless, personalized, and ethically informed commerce experiences and establish new benchmarks for engagement and efficiency in the marketplace.
Four benefits of the AI revolution coming to commerce
Major commerce players like Amazon have benefited from AI and related technologies for a while. Through machine learning, they’ve optimized logistics, curated their product selection, and improved the user experience. As this technology quickly expands, businesses have unlimited opportunities to see the same efficiency, growth, and customer satisfaction as Amazon. Here are four primary benefits of AI adoption in commerce.
1. Data-driven decision making
AI gives businesses powerful tools to analyze large amounts of data more quickly and accurately than a person. Through advanced algorithms and machine learning, AI can sift through historical sales data, customer behavior patterns, and market trends to uncover insights and suggest actions that might not be immediately obvious to human analysts. By transforming raw data into actionable insights, AI empowers businesses to make more informed decisions, reduce risks, and capitalize on opportunities.
As a real-world example, Foxconn, the largest electronics contract manufacturer worldwide, worked with Amazon Machine Learning Solutions Lab to implement AI-enhanced business analytics for more accurate forecasting. This move improved forecasting accuracy by 8%, saved $533,000 annually, reduced labor waste, and improved customer satisfaction through data-driven decisions.
2. A better customer experience
AI is set to make customer interactions smoother, faster, and more personalized by recommending products based on preferences and behaviors, making it easier for customers to find what they need.
When consumers visit an online store, AI also provides instantaneous help via a chatbot that knows their order history and preferences. These AI-powered assistants offer real-time help like a knowledgeable store clerk. They give the appearance of higher-touch support and can answer basic questions at any hour, provide personalized product recommendations, and even troubleshoot issues. Chatbots free up human customer service agents for more complicated matters, and these agents can then use AI to obtain relevant information and suggestions for the customer during an interaction.
3. Personalized marketing
Data-driven personalization of the customer journey has been shown to generate up to eight times the ROI, as data shows 71% of consumers now expect personalized brand interactions. Until AI came around, personalization at scale was complex to achieve. Now, gathering and processing data about a customer’s shopping experience is easier than ever based on lookalike customers and past behavior.
Many businesses have adopted AI to glean deeper insights into purchase history, web browsing, and social media interactions to drive better segmentation and targeting. With AI, advertisers can analyze behavioral and demographic data to suggest products someone is likely to love. Consumers can now browse many of their favorite online stores and see product recommendations that perfectly match their tastes and needs.
AI can also offer special discounts based on purchasing habits, and send personalized emails with products and content that interest customers to make their shopping experience more engaging and relevant. This personalization helps businesses forge stronger customer relationships.
Personalization across digital storefronts
Retail media involves placing advertisements within a retailer’s website, app, or other digital platform to help brands target consumers based on their behavior and preferences within that environment. Retail media networks (RMNs) expand this capability across multiple retail platforms to create seamless advertising opportunities throughout the customer journey. Integrating AI into RMNs can improve personalization across digital storefronts with personalized, relevant ads and custom offers in real time that improve the customer experience.
4. Operational efficiency
AI can also be beneficial on the back end, enabling more efficient resource allocation, pricing optimization, efficiency, and productivity.
Customers can be frustrated when they visit a store for a specific product only to find it out of stock or unavailable in a particular size. With AI, these situations can be prevented through algorithms that forecast demand for certain items. Retailers like Amazon and Walmart both use AI to predict demand, with Walmart even tracking inventory in real time so managers can restock items as soon as they run out.
AI can automate and streamline operational tasks to help businesses run smoother, faster, and more cost-effective operations. It can:
- Offload tedious data entry, scheduling, and order processing tasks for greater fulfillment accuracy.
- Analyze historical data and market trends, predicting demand to help businesses optimize inventory, reduce waste, track online and in-store sales, and prevent shortages.
- Forecast demand levels, transit times, and shipment delays to make better predictions about logistics and supply chains.
- Improve data quality using machine learning algorithms that find and correct product information errors, duplicates, and inconsistencies.
- Adjust prices based on competitor pricing, seasonal fluctuations, and market conditions to maximize profits.
- Pinpoint bottlenecks, identify issues before they escalate, and provide improvements for suggestions.
Future trends and predictions
If you want to stay ahead in e-commerce, it’s just as important to know what’s coming as it is to understand where things are today. Here are some of the trends expected to shape the rest of 2024 and beyond.
Conversational commerce
Conversational commerce allows real-time, two-way communication through AI-based text and voice assistants, social messaging apps, and chatbots. Generative AI advancements may soon enable more seamless, personalized interactions between customers and online retailers. This technology can improve customer engagement and satisfaction while providing helpful insights into preferences and behaviors for better personalization and targeting.
Delivery optimization
AI-driven delivery optimization uses AI to predict ideal routes for each individual delivery, boosting efficiency, reducing costs, promoting sustainability, and improving customer satisfaction throughout the delivery process.
Visual search
AI-driven visual search is quickly improving in accuracy, speed, and contextual understanding. Future developments may integrate seamlessly with augmented reality (AR) so shoppers can search for products by pointing their devices at physical objects. Social media and e-commerce platforms may soon incorporate visual search more prominently, allowing users to find products directly from images.
AI content creation
AI is already automating and optimizing aspects of content production:
- Algorithms can generate product descriptions, blog posts, and social media captions personalized to specific customer segments.
- AI tools also enable the creation of high-quality visuals and videos.
- NLP advancements ensure content is compelling and grammatically correct.
- AI-driven content strategies analyze consumer behavior and refine messaging to meet changing preferences and trends.
This automation speeds up content creation while freeing resources for strategic planning and customer interaction.
IoT integration
Integrating AI with Internet of Things (IoT) devices could help make the ecosystem more interconnected in the future. AI algorithms can use data from IoT devices like smart appliances, wearables, and sensors to gather real-time insights into consumer behavior, preferences, and product usage patterns. This data enables personalized marketing strategies, predictive maintenance for products, and optimized inventory management. AI-driven IoT data analytics can also streamline supply chain operations to reduce costs and inefficiencies.
Fraud detection and security
There will likely be an increased focus on the ethical use of AI and data privacy regulations to strengthen consumer trust and transparency. AI-powered systems will get better at detecting and preventing fraud in e-commerce transactions, which will heighten security measures for both businesses and consumers.
Chart the future of commerce with Experian
AI has changed how marketers approach e-commerce in 2024. With AI-driven analytics and predictive capabilities, marketers can extract deeper insights from extensive data sets to gain a clearer understanding of consumer behavior. This enables refined segmentation, precise targeting, and real-time customization of messages and content to fit individual preferences.
Beyond insights, AI automates routine tasks like ad placement, content creation, and customer service responses, freeing marketers to concentrate on strategic planning and creativity. Through machine learning, marketers can predict trends, optimize budgets, and fine-tune strategies faster and more accurately than ever. The time to embrace AI is now.
At Experian, we’re here to help you make more data-driven decisions, deliver more relevant content, and reach the right audience at the right time. Using AI in your commerce marketing strategy with our Consumer View and Consumer Sync solutions can help you stay competitive with effective, engaging campaigns.
Contact us to learn how we can empower your commerce advertising strategy today.
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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. Unify identity and engage B2B audiences With Audigent, Dun & Bradstreet, and Experian working together, you get one dependable way to recognize the same companies and roles everywhere you run. Dun & Bradstreet's D-U-N-S® Number, serves as a stable company identifier, so offline business details map to the right digital profiles, and you can reach verified decision-makers with confidence. Through Audigent and Experian, you can access 400+ Dun & Bradstreet B2B audience segments, matched to a Deal ID and activated via Audigent’s curation engine and Experian’s data marketplace. This provides real-time B2B targeting across connected television (CTV), display, native, audio, and online video (OLV). Utilize differentiated data Dun & Bradstreet audiences are built on verified offline signals (e.g., company, industry, size, role, seniority) linked to the proprietary D-U-N-S® Number for deterministic matching. High-quality firmographic attributes become actionable segments you can activate in leading programmatic platforms. The result: privacy-compliant, performance-driven campaigns with omnichannel B2B targeting. Unmatched scale Dun & Bradstreet’s Data Cloud spans over 600 million businesses across industries and regions, offering unparalleled depth for B2B targeting. Verified business identity The D-U-N-S® Number links verified offline business data to digital environments, enabling accurate and scalable activation. Privacy-first design Data undergoes rigorous validation and is compliant with major global regulations (General Data Protection Regulation (GDPR), California Consumer Privacy Act (CCPA)), enabling responsible activation. Trusted by the enterprise Over 85% of Fortune 500 companies rely on Dun & Bradstreet B2B data for its depth, accuracy, and broad coverage of small and medium-sized businesses (SMBs). Three ways unified B2B identity improves media performance Target with accuracy: Use deterministic firmographics. Dun & Bradstreet’s D-U-N-S® Number anchors a consistent way to recognize the same company, linking offline signals to authenticated business entities. Reduce waste: Activate curated PMPs for efficient spend. Audigent’s curation engine packages those audiences into Deal IDs and routes through cleaner, more predictable supply paths, so more budget reaches the buyers that matter. Publishers see up to 75% net revenue increase after fees, while brands save 36–81% on data segments and achieve 10–30% higher video completion rates. Stay consistent: Maintain identity across all channels. Use the same audience criteria across CTV, display, native, audio, social, and OLV to improve match consistency without relying solely on third-party cookies. Improve addressability with Experian's Digital Graph Advertisers can use Dun & Bradstreet’s off-the-shelf segments to target specific audiences accurately across channels. By connecting Experian’s Digital Graph with Dun & Bradstreet’s company and contact data, marketers gain a clear advantage: one durable identity that improves match rates, keeps reach consistent across CTV and digital, and aligns targeting with measurement. What that means in practice: Higher match rates without third-party cookies. Expect consistent reach across CTV and digital with one audience anchored to the same identity. Cleaner measurement because activation and identity stay in sync. Suggested use cases Below are simple ways to put this to work, using Dun & Bradstreet business data and Audigent Deal IDs so the same audience runs and measures the same everywhere. Target key decision-makers Reach professionals in Finance, Sales, Healthcare, and IT/Technology by job role, company size, and industry, driving awareness and consideration across complex buying committees. Reach SMB owners Target companies with fewer than 50 employees to connect with small-business owners and operators. Activate across channels via Audigent Deal IDs for consistent delivery and measurement. Achieve more with Audigent, Dun & Bradstreet, and Experian Together, Audigent, Dun & Bradstreet, and Experian allow marketers to activate high-quality B2B audiences with confidence, delivering relevant and efficient campaigns. By pairing Dun & Bradstreet’s trusted business data and proprietary D-U-N-S® Number with Audigent’s curation engine, you get deterministic, privacy-compliant targeting at scale, now boosted by Experian’s identity for consistent cross-channel reach. Ready to activate your next B2B audience? Talk to an Experian expert today FAQs What makes Dun & Bradstreet's data unique for B2B targeting? Dun & Bradstreet's data is anchored by the D-U-N-S® Number, a persistent business identifier that links offline signals like company size, industry, and role to digital environments. This ensures accurate, scalable, and privacy-compliant targeting. How does Experian enhance cross-channel reach? 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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? 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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