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.
Latest posts

The holiday season is almost here, and knowing how each generation plans to shop can give your holiday advertising campaigns the edge you need. Our recent survey of 1,000 U.S. consumers reveals 2024 holiday shopping trends for each generation and key insights into their anticipated spending levels, preferred shopping categories, and how they look for gift ideas. In this blog post, we'll explore three 2024 holiday shopping trends across generations: Projected consumer spending Top categories on shoppers' lists Preferred channels for researching gifts 1. Projected consumer spending Over 1 in 3 Gen Z and Millennials are gearing up to increase their holiday budgets this year, while Gen X and Boomers are likelier to stick to last year's budget. 36% of Millennials and Gen Z plan to spend more this holiday season 45% of Gen X and 52% of Boomers expect their spending to remain consistent with last year What this means for marketers These insights highlight the importance of tailoring your messaging. For Gen Z and Millennials, emphasize value and unique offerings that justify increased spending. For Gen X and Boomers, focus on trust and reliability, reinforcing their confidence in your brand. How Experian can help you target these audiences Experian’s custom and syndicated audience segments, including Holiday Shopper High Spenders and Holiday Shopper Moderate Spenders, enable you to connect with these diverse consumer groups. Our audiences are available on-the-shelf of leading ad platforms to help you reach people across social, TV, and mobile. The election effect U.S. holiday retail sales saw 4.1% YoY growth in 2016 and 8.3% YoY growth in 2020 following presidential elections. There’s a chance that holiday spending increases after the 2024 election, regardless of the outcome. Experian has 240+ politically relevant audiences that you can activate across major ad platforms ahead of the upcoming election. 2. Top categories on shoppers' lists Different generations have distinct preferences when it comes to what they plan to buy. Gift cards top the list for Gen X and Boomers, while Gen Z leans toward clothing. Millennials are looking to splurge on toys, electronics, and experiences. 69% of Boomers and Gen X plan to purchase gift cards 72% of Gen Z will buy clothing 45% of Millennials will buy health and beauty items 25% of Millennials will buy tickets and 22% of Millennials will buy experiences What this means for marketers Align your product offerings and promotions with each generation's preferences to capture their attention. For example, highlighting versatile gift cards may resonate more with older generations, while showcasing trendy apparel and tech gadgets will appeal to younger consumers. How Experian can help you target these shoppers We offer audience segments like Holiday Shoppers: Apparel, Cosmetics & Beauty Spenders, and Toys Shoppers that you can activate to connect with consumers primed to purchase in these categories. We recently released 19 new holiday shopping audiences we recommend targeting to drive engagement and conversions. Download our audience recommendations here. 3. Preferred channels for researching gift ideas When it comes to finding the perfect gifts, Gen Z turns to social media, while Millennials prefer online reviews and video content. Boomers and Gen X are more inclined to visit physical stores for hands-on product evaluations. 29% of Gen Z and 26% of Millennials will look for gift ideas on social media 44% of Millennials will rely on video reviews and product demos on platforms like YouTube 49% of Gen X and Boomers plan to visit physical stores to evaluate products in person What this means for marketers Understanding where each generation looks for inspiration can guide your content and ad placement strategy. To engage Gen Z, focus on social media campaigns and influencer partnerships. For Millennials, consider investing in video content and reviews. For older generations, ensure your in-store experience is optimized to convert browsing into purchases. How Experian can help you engage these shoppers Our TrueTouchTM audiences can help you pair the perfect messaging styles with the right channels and calls to action. Our Social media channel and content engagement audiences can help you reach Gen Z who are likely to be active users on major social platforms and are Black Friday shoppers. For a full list of Experian’s syndicated audiences and activation destinations, download our syndicated audiences guide. Download our report for five 2024 holiday shopping trends by generation Understanding 2024 holiday shopping trends by generation can help you tailor your targeting, messaging, media planning, and creative based on the generation you’re targeting. In addition to the insights covered here, download our 2024 Holiday spending trends and insights report to learn: When consumers plan to shop (hint: they're already shopping) Where they plan to shop (online vs. in-store) Download our full report to access all five of our predictions by generation, so you can address the diverse needs of this year's holiday shoppers. Download now When you work with Experian for your holiday shopping campaigns, you’re getting: Accurate consumer insights: Better understand your customers’ behavioral and demographic attributes with our #1 ranked data covering the full U.S. population. Signal-agnostic identity solutions: Our deep understanding of people in the offline and digital worlds provides you with a persistent linkage of personally identifiable information (PII) data and digital IDs, ensuring you accurate cross-device targeting, addressability and measurement. Secure connectivity: Bring data and identity to life in a way that meets your needs by securely sharing data between partners, utilizing the integrations we have across the ecosystem, and using our marketing data in flexible ways. Make the most of this holiday shopping season with Experian. Contact us today to get started. Contact us Source Online survey conducted in June, 2024 among n=1,000 U.S. adults 18+. Sample balanced to look like the general population on key demographics (age, gender, household income, ethnicity, and region). Latest posts

Today, Experian is excited to introduce our Offline Graph as a standalone product that clients can license, marking a significant step in our commitment to powering data-driven advertising through connectivity. Offline Graph empowers advertisers and advertising technology companies to build and refine consumer profiles, contributing to data connectivity, more offline audience reach, and improved offline measurement accuracy. As a result of consumers engaging with content across more channels, there are more disparate data points than ever before. When you couple that with ongoing signal loss, the need for a unified identity solution has never been greater. Experian’s Offline Graph offers companies a license of stable offline data points, like name, address, phone number, email, geographic information, date of birth, and additional attributes that provide a complete view of household and individual identities. The Offline Graph integrates known offline identity information from reliable deterministic sources like property ownership records, public records, and marketing data to provide access to all United States consumers and households. How customers can use the Offline Graph A big box retailer fills in the blanks of their existing customer data and builds a database of prospects. A media platform more effectively onboards advertisers’ segments, enabling advertisers to reach more of their customers. A retail brand better understands their customer’s demographic and behavioral make-up, by licensing Offline Graph with Marketing Attributes. A connected TV (CTV) manufacturer increases audience reach and accurately quantifies the campaign impact for their advertising partners. Experian’s Offline Graph is already driving value across industries. Here’s some in-depth client success stories: Fusion92 licenses Offline Graph to help their clients transform their marketing Fusion92 is a marketing partner that fuels business transformation in today’s digital economy and delivers exponential returns for brands. Fusion92 licenses Experian’s Offline Graph to power their strategy: from research and discovery to audience creation, activation, and measurement. With access to our Offline Graph, Fusion92 ensures their clients get the insights, targeting, reach, and measurement they need to achieve their business goals. "At Fusion92, we are always pushing the envelope to develop solutions that lead to success for our clients. Our desire to innovate pushed us to find an industry-leading partner in data and identity. This led to us licensing Experian’s Offline Graph product, which we use to build more complete audience profiles for our clients. In doing so, we help brands target, activate, and measure their marketing campaigns more effectively, leading to superior results.”dave nugent, executive vice president of data and analytics, fusion92 Using Offline Graph to deliver relevant messaging to multiple audience cohorts A leading direct-to-consumer (DTC) company with strong customer relationships built a robust first-party data set, enabling effective customer retention. To attract new customers, they partnered with Experian to access offline identity data from Experian’s Offline Graph. The Offline Graph provides them with the data needed to validate their first-party data and with the keys to unlock new customers. With this data, the DTC company delivered the right message to both sets of consumers: existing customers and new prospects. By integrating Experian’s Offline Graph they broadened their reach, personalized their messaging, and improved their marketing. What sets Experian’s Offline Graph apart from the competition Stability of data: With data from deterministic sources, our Offline Graph ensures that your view of consumers – and your ability to connect with them – is stable over time. Connected digital and offline data: Seamlessly connect offline data with digital identifiers through our Digital Graph, enabling a holistic approach to marketing, while ensuring consumer privacy is prioritized. Tailor made for your use cases: Build the Offline Graph to fit your specific needs, selecting the exact offline identity information required for your campaigns. Expanded consumer insights: Connect more data points to enrich your understanding of consumer demographics and behavior, using Experian’s Marketing Attributes and Audiences data. Offline Graph: Your gateway to consumer connectivity As signals fade, there is a large emphasis on procuring and having accurate consumer data. Experian’s Offline Graph delivers the connectivity and insights necessary to stay ahead. Whether you aim to strengthen your existing data or access entirely new data sets, Experian’s Offline Graph offers a solution tailored to your needs. Transform your data strategy with Experian’s Offline Graph — your gateway to a unified consumer identity solution. Get started today Latest posts

Ditch the cookie, not the data with the next evolution of contextual targeting Today, we're excited to announce Contextually-Indexed Audiences, a game-changer in contextual targeting. Experian’s new solution offers advertisers a powerful, privacy-safe solution that combines the precision of deterministic audience targeting with the flexibility of contextual targeting. Powered by real-time analysis from two million websites, access to 1,400 trusted audience segments, and easy activation through the top demand-side platform’s contextual marketplace or Audigent private marketplaces (PMPs), this solution offers advertisers a scalable way to reach their target consumers. With this solution, advertisers can reach consumers on websites that over-index for visitors with the demographics, behaviors, or interests, they are looking to target. For example, an automotive brand can select Experian’s “Contextually-indexed in-market for a luxury electric car” audience segment and reach consumers when they are browsing websites that often attract that exact segment. Best of all, this is done in a privacy-safe way since it’s not reliant on cookies, mobile ad IDs (MAIDs) or other user identifiers. How Contextually-Indexed Audiences work Contextually-Indexed Audiences harness advanced machine learning technology to move beyond traditional keyword-based strategies. The solution works in three steps: First, it analyzes traffic from over two million websites and mobile apps to identify the types of frequent visitors to those platforms. Next, using Experian’s Digital Graph, it resolves the identities of those visitors and maps them to more than 1,400 of Experian’s Syndicated Audiences, determining which audiences are most overrepresented on each site. Finally, the relevant audiences are assigned to those sites, allowing advertisers to deliver ads to people in those audiences while they are actively browsing the websites — without relying on user identifiers. Customer success story A leading auto manufacturer was among the first clients to activate this new solution while we were in beta. The goal was to identify new contextual targeting solutions that focus on privacy while maintaining scale and performance. The client identified two key target audiences: first-time vehicle buyers and experienced buyers. The initial campaigns using this new solution were highly successful. Even as the campaign scaled to twice the original volume, it continued to deliver three times the targeted click-through rate (CTR) goal. “Partnering with industry leaders like Experian, we're pushing the boundaries of contextual targeting with innovative data strategies that offer buyers greater flexibility and improved performance. These advanced contextual solutions are exciting as they not only drive results but also have the same privacy safeguards as traditional contextual targeting.”Matt Griffith, CTO & Co-Founder, Audigent Benefits of Contextually-Indexed Audiences Accurate consumer reach: Real-time integrations with over two million websites and apps coupled with machine-learning indexing technology ensure audience segments are constantly refreshed, which means advertisers reach consumers based on their latest habits. Privacy-safe audience targeting: These audiences are not reliant on cookies or any other user identifiers for targeting. Audience customization: Create the right audience segment for your campaign by using a combination of over 1,400 audiences across 12 data categories like demographics, politics, health, travel, finance, and TV. Flexible activation: Activate these audiences instantly in the top demand-side platform’s contextual marketplace or utilize our partnership with Audigent to create a custom private marketplace (PMP), where they can be activated across any media buying platform. When using a PMP, advertisers benefit from additional performance optimization capabilities. Experian’s Contextually-Indexed Audiences offer advertisers a powerful solution that combines the precision of audience targeting with the flexibility of contextual targeting. With real-time analysis of over two million sites and access to 1,400 trusted audience segments, advertisers can reach consumers based on their exact behaviors and interests. This is done in a privacy-safe, yet scalable way since it’s not reliant on cookies or other user identifiers. Whether activating instantly through the top demand-side platform or customizing through Audigent PMPs, this is the future of audience targeting. Ditch the cookie, not the data, and elevate your strategy today. See how these audiences can work for you Latest posts