In this article…

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.
Contact us
Latest posts

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

As privacy regulations, signal loss, and consumer expectations change, marketers face growing challenges in creating meaningful connections. In our latest Ask the Expert segment, Tom Wolfe, SVP at Viant, and Ali Mack, VP of AdTech Sales at Experian explore how first- and third-party data strategies, advancements in connected TV (CTV), and AI tools empower marketers to build smarter campaigns tailored to modern demands. Identity-driven advertising built on first-party data With the decline of traditional third-party signals and the rise of privacy-first advertising, first-party data is more important than ever. By collecting data directly from customers, marketers ensure they have accurate, user-consented data to fuel personalized advertising. Viant’s identity graph takes these first-party signals—such as email addresses, household locations, and phone numbers—and connects them with additional attributes in a privacy-safe way. This approach empowers marketers to build precise audience segments without relying on cookies, which Viant phased out over a decade ago. Combining first-party data and privacy-first solutions to build trust By combining first-party data strategies with privacy-first solutions, marketers can build long-term success while earning consumer trust. The Viant Household ID eliminates reliance on cookies while enabling secure, compliant campaign management. Additionally, Viant's partnerships with cleanrooms further protect their clients' data integrity and ensure smooth collaboration between trusted parties. Beyond safeguarding consumer information, the Viant ecosystem allows their clients to integrate data seamlessly from audience segmentation to campaign activation and reporting. How first and third-party data work together While first-party data is crucial for precise, personalized advertising, it isn’t always sufficient—especially for smaller or emerging brands that haven’t yet amassed audience data. Third-party data plays a pivotal role in these scenarios by supplementing first-party insights, offering a broader view of consumer behavior, leading to new growth opportunities. Viant collaborates with partners like Experian to help marketers seamlessly merge their customer information with additional consumer insights. Viant and their clients benefit from Experian's identity data to match various identifiers such as hashed emails, device IDs, or other platform-specific tags and map them back to a single consumer profile. With a unified view of the consumer, marketers can refine targeting, expand their reach, and maintain consistency across channels. By utilizing first- and third-party data solutions, marketers can build well-rounded, effective campaigns that resonate with diverse audiences. “Our clients have embraced the Viant Household ID because it powers a comprehensive, seamless flow from segment creation to targeting, activation, and measurement.” Tom Wolfe, SVP Business Development, Viant CTV as a core marketing channel CTV is emerging as the core platform for immersive and effective advertising by merging the visual storytelling power of traditional TV with the precision of digital tools. Viant helps marketers optimize CTV capabilities by building connections between premium publishers and data, allowing marketers to personalize experiences. Whether it’s tailored ads for families watching a live sports event or pinpointing niche interests, CTV enables marketers to reach diverse audiences with meaningful ads. Beyond awareness, Viant drives results for their clients and monitors that performance across each stage of the funnel. Marketers can use the key insights to optimize their media buys on CTV and achieve even higher ROI. Viant takes CTV performance a step further with its direct access programs. Stronger data matching via publisher partnerships improves accuracy, helping marketers connect with their ideal audience. Viant’s recent data shows that campaigns incorporating CTV achieve a conversion rate of 12.89%, outperforming campaigns lacking it by a wide margin. This dramatic improvement highlights the power of precise targeting combined with Viant’s advanced CTV tools. For marketers, this translates to impactful storytelling supported by tangible results. “CTV drives high-level brand awareness via sight, sound, motion, and emotion, but it also powers activity through the funnel.” Tom Wolfe, SVP Business Development, Viant AI is streamlining marketing from start to finish AI is transforming advertising by automating tasks like performance tracking and audience segmentation, allowing marketers to focus on strategy and creativity. At Viant, AI is part of the company’s DNA, helping marketers drive more efficient and effective campaigns. With real-time data insights and streamlined processes, teams can quickly refine messaging and optimize budgets. This efficiency not only saves time but also empowers marketers to channel their energy into creating impactful strategies that resonate with their audiences. The integration of AI into Viant’s ecosystem also simplifies overall workflows, optimizing campaign execution from start to finish. With performance tracking made easier and segmentation automated, marketers can rely on data accuracy and actionable insights to make confident decisions. How Experian and Viant work together Experian's syndicated audiences—demographic, auto, TV, FLA (Financial Fair Lending Act), and more—are available within Viant's platform. Experian's partnership with Viant enables the deployment of custom audiences specifically designed to meet distinct campaign objectives. Together, Experian and Viant provide solutions that support first-party data strategies, third-party data integration, CTV optimization, AI-driven insights, and identity resolution, creating a cohesive and privacy-forward marketing ecosystem. “At Viant, we focus on the sensible, scalable, impactful opportunities.” Tom Wolfe, SVP Business Development, Viant Watch the full Q&A Visit our Ask the Expert content hub to watch the full conversation with Tom and Ali and learn more about Viant’s scalable identity solutions. Contact us About our expert Tom Wolfe, SVP Business Development, Viant As SVP of Business Development at Viant, Tom and his team forge strategic business partnerships that fuel the company's growth and business strategy. He is a seasoned industry veteran with more than 25 years of expertise in content distribution, advertising, and technology, particularly in CTV. Throughout his career, Tom has played a pivotal role in establishing and managing multiple businesses at major companies such as Roku, TiVo, YuMe, and Comcast. Additionally, he has provided valuable advisory services to organizations including VIZIO, Vice Media, and many others across the ecosystem. Tom holds a B.A. in Political Science from Lehigh University and has shared his knowledge as a guest lecturer at both New York University and Drexel University. Latest posts

At this year’s Shoptalk, one thing was crystal clear: Retailers are no longer just competing on price or product—they’re competing on experience. And in that race, customer expectations are not just the starting line—they’re the finish line, too. Over three days of discussions, demos, and side conversations, Shoptalk 2025 delivered a fresh look at how brands and advertisers are adapting to an increasingly blended retail environment. The show spotlighted not just what's new in retail media and AdTech—but how the industry is rethinking the entire shopper journey. What we heard again and again on the ground was this: there is no one-size-fits-all playbook anymore. Every retailer is navigating their own unique mix of identity, data, tech, and consumer needs. The winners will be those who stay nimble while staying connected to what customers actually want. Experience is everything Across sessions and show floor chats, the core message was this: customers expect more—and retailers must rise to meet that moment. Whether it’s a personalized in-store interaction or a seamless connected TV (CTV) ad experience, people want value, inspiration, and storytelling wherever they shop. That means digital and physical channels must work together effortlessly. Retailers aren’t just “digitizing” the in-store experience anymore—they’re rethinking how to make the entire shopping journey feel easy, consistent, and enjoyable. This shift isn’t just about touchpoints. It’s about changing the way retailers think about the customer experience. Loyalty isn’t a program, it’s every interaction Loyalty emerged as a major theme—one that goes well beyond points and perks. Speakers from Wayfair, DSW, and Lowe’s emphasized that every customer interaction, not just formal programs, should be viewed as an opportunity to build emotional loyalty. Sarah Crockett, CMO of DSW, shared that emotional tactics resonate more deeply than transactional rewards—echoing a broader shift toward customer-centric, experience-driven engagement. “Loyalty today isn’t just about perks. It’s about trust, connection, and knowing your customer on a deeper level. Every interaction is a chance to build that relationship.”Sam Zahedi, Sr. Enterprise Partnerships Manager Retail media gets real Retail media networks (RMNs) took center stage, but the tone is changing. With so many players flooding the space, retailers and advertisers alike are asking tougher questions: How do you stand out? How do you prove value? And perhaps most critically—how do you build trust? Standardization came up in several sessions, but as Harvey Ma from Sam’s Club MAP pointed out, standardization alone won’t fix what's been lost: foundational trust and transparency. Advertisers want more than impressions—they want insights, outcomes, and measurement they can count on. “There’s no one playbook—nor should there be. Every retailer, every RMN, and every customer is different. Success comes from building strategies as unique as the audiences they serve.”Anne Passon, Sr. Director, Sales, Retail Many brands came to our team asking how Experian can help extend their audiences into new environments like social and CTV. Here’s how we do it: We work with our RMN partners to take their organized, clean, complete, and highly usable customer records and expand them to include other digital identifiers. By adding digital IDs such as hashed emails (HEMs), mobile ad IDs (MAIDs), CTV IDs, and Universal IDs like Unified I.D. 2.0 (UID2) or ID5, we ensure that the retailer's entire customer base can be reached. On their own, RMNs only know the digital identity of a portion of their customer base. With Experian's help, they can add digital IDs to their entire customer base. As a result, marketers can reach all of an RMN's customers, including those whose identities were previously unknown. They can reach these customers both onsite and offsite, thanks to the array of addressable IDs we provide. This increase in addressability leads to higher revenue for the RMN. Moving at the speed of people One of the most thought-provoking moments came from Nikki Laughlin from McClatchy Media during a Brand Innovators session. She asked a simple but powerful question: How can we move at the speed of people if we’re always looking backward at data? It’s a challenge we’re hearing more often—marketers want to be proactive, not just reactive. That requires faster insights, cleaner connections between signals, and a shift from static audiences to living, evolving ones. Experian's identity and data solutions aren’t just about better targeting—they’re about helping brands activate smarter, faster, and with more confidence across the full media ecosystem. A marketplace of possibilities The best part of Shoptalk? The spontaneous moments. The side conversations where ideas turned into opportunities. We had several discussions that signaled new partnerships on the horizon—some with current clients, others brand new. What united them was a desire to co-create: to build something more tailored, more agile, more customer-first. Of course, there were also shared challenges. Retailers are navigating how to stay customer-centric while grappling with complex, sometimes controversial tech—from AI to influencers to evolving data privacy norms. But if there was one consistent thread, it was this: retailers are hungry for clarity and collaboration. Forget the playbook, follow the customer Shoptalk 2025 reminded us that while tech and trends come and go, the most successful retail strategies still start with one thing: knowing your customer. That’s what fuels smarter activation, stronger measurement, and more meaningful experiences—whether online, in-store, or across emerging media channels. If you're rethinking your retail strategy or want to explore how Experian can support your goals across identity, retail media, or CTV, let’s talk. Let's connect and explore what's possible Latest posts