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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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Marketing without segmentation is a lot like shouting into a crowded room and hoping the right person hears you. Without a clear way to communicate in a noisy marketing environment, your message gets lost in the mix. With segmentation, you can identify your target audience, speak to their needs, and deliver the right message at the right moment. Companies that use segmentation are 130% more likely to understand customer motivations, resulting in more effective campaigns and deeper audience relationships. In this article, we’ll break down four of the most effective customer segmentation methods, when to use each, and how Experian’s audience solutions can help. What is segmentation in marketing? Segmentation is the process of splitting a large audience into smaller groups that share similar traits, like demographics, location, behavior, or firmographic characteristics. As a marketer, these segments enable you to choose channels, messaging, and offers that resonate with each group. Whether you’re targeting new homeowners in Texas, loyalty shoppers in retail, or small business decision-makers in finance, segmentation helps you stand out to them and get results. Why should marketers segment their audiences? Effective audience segmentation fuels accuracy, performance, and personalization at scale. Here's why you should invest your time and marketing budget in honing your audience segments. Maximize your marketing ROI Nobody wants to waste money talking to the wrong crowd. Using various methods of segmentation, you can focus on those who want to hear from you — and the payoff can be huge. For marketing channels like email, segmentation can drive up to 760% more revenue than non-segmented campaigns. The more targeted your message, the better the return. Create a unified omnichannel strategy Segmentation helps ensure that every channel, from email and social media to display, SMS, and direct mail, operates from the same playbook. Once you define your target audience segments, you also need a trusted identity partner to sync them across platforms and environments. This ensures you can deliver consistent, personalized experiences at every touchpoint and your audience receives the same message in the proper context, regardless of where they engage. Strengthen customer loyalty Roughly 75% of consumers are loyal to brands that “get” them. When you strive to understand your customers, they’re more likely to stay. Segmentation enables you to personalize communications based on your target segment’s values, behaviors, or preferences, encouraging repeat business. Expand into new markets With segmentation, you can analyze existing customers to identify common traits and use that data to pinpoint similar groups in new regions or markets. For example, if your top customers are middle-class parents in suburban areas, you can target lookalike segments in other cities with tailored messaging. This makes it easier to expand with confidence, knowing you're reaching people who are more likely to convert. Lower customer acquisition costs Rather than forcing you to cast a wide net, segmentation enables you to focus your budget on high-potential audiences across channels, reduce acquisition costs, and minimize wasted spend on low-intent audiences. Four segmentation methods and examples Let’s look at four different methods of market segmentation. We’ll define each, share when to use them, and give real-world examples to help you apply them. 1. Demographic segmentation Demographic segmentation breaks your audience into groups based on gender, income, age, education, marital status, occupation, and household size. It’s one of the most foundational segmentation methods because it’s easy to implement and often tied directly to buying behavior. Demographic data makes it easier to get the tone, offer, and channel right from the start. And when you combine demographic segmentation with other segmentation methods, such as behavior or location, the impact multiplies. When to use it Use demographic segmentation when your product or service is clearly more relevant to people in a specific life stage, income bracket, or household type. Among all methods of market segmentation, demographic data is often the easiest starting point. It’s especially effective for industries such as financial services, healthcare, education, retail, and others, where consumer needs change based on demographics. Examples As a real-world example, a health supplement company used Experian data to segment its ambassador program audience into four demographic groups based on lifestyle and household makeup. These included younger singles, value-seeking families, high-income spenders, and older empty nesters. Applying these insights at registration allowed the brand to deliver personalized, channel-specific communications that boosted acquisition and retention. The approach led to stronger engagement and more meaningful customer connections. 2. Geographic segmentation This method of market segmentation categorizes people by location, including country, region, state, city, zip code, or even climate. It’s a simple yet effective way to tailor your marketing, as location often influences everything from lifestyle and language to shopping habits and product needs. It’s most often used among brands with physical locations or region-specific campaigns. Whether you're promoting snow boots in Colorado or sunscreen in California, geographic segmentation helps you stay relevant to the local context. When to use it Geographic segmentation is ideal when your offer or message changes depending on climate, culture, availability, or local regulations. It’s also helpful for planning market expansion or testing the performance of different methods of market segmentation across regions. Examples One home furnishings retailer partnered with Experian to understand how customer needs varied across store locations. Using a mix of client data and Experian demographics, we segmented stores based on their surrounding customer base, like urban, white-collar shoppers in metro centers versus lower-income households in more remote cities. These insights enabled the retailer to tailor inventory, marketing strategies, and ad copy for each store type, resulting in more relevant customer experiences. 3. Behavioral segmentation Behavioral segmentation centers on how people live their lives — their interests, habits, and decision-making patterns. It includes factors like past purchases, engagement frequency, brand loyalty, product usage, browsing patterns, and responsiveness to offers or promotions. Among all of the segmentation methods, this one provides insight into intent, helping you go beyond who your audience is to understand what they do. You can use behavioral insights to re-engage former customers with relevant offers, reward loyal buyers with personalized perks, or guide high-intent shoppers toward conversion with timely nudges. When to use it Behavioral segmentation is best when you want to personalize based on intent, habits, or engagement stage. It's particularly useful for retention, reactivation, or cross-selling strategies. Examples In practice, a national big-box retailer partnered with Experian to better understand customer behavior during grocery store visits. The goal was to identify distinct “trip missions” that could drive category trial and increase basket size. We analyzed everything from basket contents to customer composition and segmented visits into 11 unique missions. For example, the “All Aisles Online” segment represented large households (often homeowners with families) stocking up on household staples through online orders. In contrast, the “Marketable Mission” segment captured smaller, likely renter households making quick trips for non-essentials. These behavioral insights empowered the retailer to adjust promotions based on the intent behind each visit, strengthen customer relationships, and drive growth. 4. Firmographic segmentation (B2B) Firmographic segmentation is like demographic segmentation for businesses. It groups B2B audiences based on attributes such as annual revenue, location, company size, industry, and organizational structure. You can also segment by job title or decision-maker role to better target key stakeholders. This method is great for aligning your messaging, sales strategy, or product offerings with the unique needs of various business types. A startup in the tech sector will likely respond to a very different pitch than an enterprise manufacturer, and firmographic data helps you speak to both with precision. When to use it Use firmographic segmentation when marketing to other businesses, especially when your product or service has different benefits depending on business size or sector. Examples Recently, a B2B client partnered with Experian to gain a deeper understanding of the revenue potential of their existing business customers. Using firmographic data, we segmented the client’s customers into distinct groups based on the characteristics most strongly tied to spending behavior. For each segment, we calculated potential spend, defined as the 80th percentile of annual spend within that segment. This allowed the client to identify high-value accounts with untapped growth potential. For example, one customer, ABC Construction, had spent $4,750. But based on their segment’s profile, their annual potential was $9,000. That insight revealed a $4,250 opportunity to deepen the relationship through more targeted marketing and sales efforts. Best practices for market segmentation Regardless of the segmentation method you use, the following best practices will help you maximize the benefits of your efforts. Start with clean, reliable data Segments are only as good as the data behind them. If your data is outdated, inaccurate, or incomplete, your segments will result in ineffective targeting and a wasted budget. Utilize accurate, compliant, up-to-date sources like Experian Marketing Data, ranked #1 in accuracy by Truthset, to ensure your targeting is on point. Test and refine segments continuously Business goals, market conditions, and behaviors are constantly changing. What worked last month or even last week might not work today. By adjusting your segments over time, you make sure your marketing stays relevant, focused, and effective. Use A/B testing, performance metrics, and audience analytics to iterate on your segments and improve results over time. Align segments with personalized messaging and offers Each segment has distinct needs, preferences, and motivations, which means generic messaging won’t resonate effectively. Once you’ve built your segments, personalize your creative, copy, and offers to appeal to each group and increase the likelihood of engagement and conversions. Integrate segmentation across all platforms If someone sees one message in an email and a completely different one in an ad or on your website, it creates confusion and weakens trust. From CRMs and email platforms to ad tech and analytics tools, make sure your segmentation method is applied consistently across every channel to improve performance and build a cohesive brand experience. Segment your audiences with Experian Effective audience segmentation is at the heart of every successful marketing strategy, but in this fragmented, privacy-conscious landscape, grouping your audience into meaningful, actionable subgroups is more challenging than ever. That’s where we come in. With coverage of the entire U.S. population, Experian helps marketers define and categorize broad audiences into precise segments using rich data on demographics, behaviors, financial profiles, and lifestyle traits. These insights make it easier to personalize messaging, optimize media spend, and drive better outcomes. From ready-to-use syndicated audiences to custom segments and even Contextually-Indexed Audiences that align targeting with content, Experian offers flexible segmentation solutions that perform across digital, TV, programmatic, and social channels. In our most recent release, we introduced over 750 new and updated audience segments across key categories, including a brand-new category for Experian, giving marketers more accurate, behavior-based targeting options than ever before. 135+ new CPG audiences, a brand-new category for Experian, built from opt-in loyalty card and receipt scan data 240+ new automotive audiences covering ownership and in-market shoppers 100+ new high-spending behavior audiences focused on specific merchant categories 24 new wealth and income segments with refined household net worth tiers 13 new lifestyle-based housing audiences for family- and household-focused targeting 250+ refreshed financial segments with improved naming conventions for better discoverability and clarity Together, these segments give marketers more accuracy to reach high-intent consumers based on real-world behaviors, spending patterns, and financial capacity. Audience solutions powered by consumer insights Experian Marketing Data, one of the most comprehensive and accurate consumer databases in the U.S., is the core of our segmentation capabilities. Backed by over 5,000 demographic and behavioral attributes, it helps you understand not just who your customers are but how they live, shop, spend, and engage, too. Each audience segment is built with privacy and precision in mind, using a blend of demographic data, financial behaviors, lifestyle signals, and media habits. With these consumer insights, we’ll help you uncover meaningful patterns that lead to smarter strategy. Experian’s pre-built audiences Our syndicated audiences are pre-built, ready-to-activate segments based on shared characteristics from age and income to purchase behavior and lifestyle indicators. When speed and scale are a priority, these segments offer a fast, effective way to reach your target audience. Experian’s 2,400+ syndicated audiences are available directly on over 30 leading television, social, and programmatic advertising platforms, as well as within Audigent for activation within private marketplaces (PMPs). Here’s what’s new from our August 2025 release: CPG shoppers by category (e.g., Frozen Food Shoppers, Multi-Vitamin Shoppers) Luxury EV owners and auto brand shoppers (e.g., Rivian, Polestar, Cadillac) High spenders in specific categories (e.g., men's grooming and women's accessories) Ultra high-net-worth households (e.g., Net Worth $50M+) and likely home sellers Young Family Homeowners and Growing Family Apartment Renters Custom audiences for specialized targeting Need a custom audience? Reach out to our audience team, and we can help you build and activate an Experian audience on your preferred platform. Additionally, work with Experian’s network of data providers to build audiences and send to an Audigent PMP for activation. Contextually-Indexed Audiences Experian’s Contextually-Indexed Audiences offer a privacy-safe way to reach relevant consumers in the moments that matter without relying on identity signals or third-party cookies. These segments combine Experian’s consumer insights with page-level content signals, enabling you to align targeting with intent and mindset, even in cookieless or ID-constrained environments. Want to take your segmentation strategy to the next level? Let’s talk. We’ll help you define your audience in ways that drive real results. Talk to our team about your segmentation methods today Latest posts