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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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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

In our Ask the Expert Series, we interview leaders from our partner organizations who are helping lead their brands to new heights in AdTech. Today’s interview is with Ben Smith, VP of Product, Data Products at Infillion. Adapting to signal loss What does the Experian–Infillion integration mean for advertisers looking to reach audiences as signals fade? As cookies and mobile identifiers disappear, brands need a new way to find and reach their audiences. The Experian integration strengthens Infillion’s XGraph, a cookieless, interoperable identity graph that supports all major ID frameworks, unifying people and households across devices with privacy compliance, by providing a stronger identity foundation with household- and person-level data. This allows us to connect the dots deterministically and compliantly across devices and channels, including connected TV (CTV). The result is better match rates on your first-party data, more scalable reach in cookieless environments, and more effective frequency management across every screen. Connecting audiences across channels How does Experian’s Digital Graph strengthen Infillion’s ability to deliver addressable media across channels like CTV and mobile? Experian strengthens the household spine of XGraph, which means we can accurately connect CTV impressions to the people and devices in that home – then extend those connections to mobile and web. This lets us plan, activate, and measure campaigns at the right level: household for CTV, and person or device for mobile and web. The outcome is smarter reach, less waste from over-frequency, and campaigns that truly work together across channels. The value of earned attention Infillion has long championed “guaranteed attention” in advertising. How does that philosophy translate into measurable outcomes for brands? 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This evolution brings greater accountability and next-generation audience engagement to an increasingly automated, intelligent media landscape. Our goal is to help brands connect more meaningfully with audiences while holding every impression – and every outcome – to a higher standard of transparency and effectiveness. Driving impact across the funnel What is a success story or use cases that demonstrate the impact of the Experian–Infillion integration? We recently partnered with a national veterans’ organization to raise awareness of its programs for injured or ill veterans and their families. Using the Experian integration, we combined persistent household- and person-level identifiers with cross-device activation to reach veteran and donor audiences more precisely across CTV, display, and rich media. The campaign achieved standout results – industry-leading engagement rates, a 99% video completion rate, and measurable lifts in both brand awareness (3.6 % increase) and donation consideration (13.7% lift). It’s a clear example of how stronger identity and smarter activation can drive meaningful outcomes across the full funnel. Contact us Identity resolution FAQs Why is identity resolution critical for CTV and cross-channel campaigns? Identity resolution ensures accurate connections between devices, households, and individuals. Experian's Offline Identity Resolution and Digital Graph strengthen these connections for improved targeting and consistent measurement across CTV, mobile, and web. What strategies help address the loss of cookies and mobile IDs? Solutions like Experian's Digital Graph enable brands to connect first-party data to household and person-level identifiers, ensuring scalable reach and compliant audience targeting legacy signals fade. How can engagement translate into measurable results? Focusing on earned attention (where audiences actively choose to engage) leads to stronger completion rates, improves on-site behavior, and drives measurable increases in brand awareness and consideration. What makes cross-channel targeting more effective? By linking CTV impressions to households and extending those connections to mobile and web, Experian's identity solutions ensure campaigns work together seamlessly, reducing over-frequency and improving overall reach. About our expert Ben Smith VP Product, Data Products, Infillion Ben Smith leads Infillion’s Data Products organization, delivering identity, audience, and measurement solutions across the platform. Previously, he was CEO and co-founder of Fysical, a location intelligence startup acquired by Infillion in 2019. About Infillion Infillion is the first fully composable advertising platform, built to solve the challenges of complexity, fragmentation, and opacity in the digital media ecosystem. With MediaMath at its core, Infillion’s modular approach enables advertisers to seamlessly integrate or independently deploy key components—including demand, data, creative, and supply. This flexibility allows brands, agencies, commerce and retail media networks, and resellers to create tailored, high-performance solutions without the constraints of traditional, all-or-nothing legacy systems. Latest posts

Audigent, a part of Experian, was named Microsoft Advertising’s Curator of the Year. The honor recognizes Audigent’s leadership for advancing privacy-safe, sell-side curation that packages high-quality audiences with premium supply for measurable campaign performance. Once only a buzzword, curation has become a mainstream strategy for activating advertisers’ first-party data and streamlining programmatic buying. To recognize this shift and the leaders driving it, Microsoft introduced Curate and established the Curator of the Year award to celebrate excellence in this category. Audigent was recognized for: End-to-end curation from audience planning through activation for outcomes-based, closed-loop programs. Breadth of deal and supply types using unique datasets, real-time supply connections and always-on optimization. Data-driven activation with curation across a large publisher footprint that utilizes Experian marketing data, first-party data, and partner audiences. Audigent’s unique, contextual, and predictive audience data solutions are built into all programmatic media buying. The combination of Audigent’s Real-Time Data and Curation Platform and first-party data, along with Experian identity and optimization, turns real engagement into ready-to-activate audiences. These audiences are available within Microsoft Curate and across omnichannel buying. "Audigent is proud to be named Microsoft Advertising’s Curator of the Year. This is a clear validation of the work our team has done to make curation the new standard in data-driven programmatic activation. We will continue to set the standard by expanding curated deals in Microsoft Curate. This will help maximize efficiency across the bidstream.”Chris Meredith, Head of Supply Side Partnerships Together, Experian and Audigent connect identity to inventory, enabling advertisers to reach the right audiences with precision and scale. By harnessing Experian identity and audience solutions and activating Audigent-curated deals in Microsoft Curate, brands can unlock new levels of efficiency and performance across every programmatic channel. This recognition sets the stage for even greater innovation, collaboration, and results in the year ahead. Ready to design your curated library? Let's connect Latest posts