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How the AI revolution is transforming the future of commerce

Published: September 10, 2024 by Experian Marketing Services

The widespread adoption of AI in commerce

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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Combined with our identity and modeling capabilities, this expands match rates and unlocks up to 76% net-new reach, so campaigns reach patients and caregivers in critical health moments. As a result, healthcare brands can launch campaigns that are privacy-first, highly targeted, and proven to drive meaningful impact. Audio People use audio while commuting, working out, and even folding laundry. It can be one of the hardest channels to track because of how frequently listeners switch between apps, stations, and devices. Experian’s identity resolution partnerships with Audacy and DAX change the game: Audacy helps tie scattered listening into a single view, so advertisers can follow audiences across devices and keep ads relevant in the moment. DAX pairs Experian’s 2,400+ syndicated audiences with its audio network, enabling brands to target precisely and launch impactful campaigns at scale. These partnerships turn audio into an accurate channel where ads feel personal, privacy-safe, and measurable. Gaming Gamers don’t stick to one platform. Player data gets scattered across mobile, console, and PC, so it’s tough to keep track of individuals. Experian helps stitch those signals together so publishers can finally see the whole picture, personalize gameplay, and keep players coming back. With enriched profiles, publishers can deliver offers that resonate and unlock fresh revenue by packaging high-value gaming audiences for advertisers outside the industry. Unity, a leading gaming platform, is tapping into Experian’s syndicated audiences to gain player insights and help advertisers reach gamers across mobile, web, and CTV. For global publishers, unifying player data with Experian has driven higher engagement and stronger ad ROI. Discover how to unlock revenue with unified player data How should I evaluate identity resolution providers? When choosing an identity resolution partner, look for: Data scale and quality: The value of identity resolution depends on how complete and accurate the underlying data is. The right provider should bring together a wide range of identifiers from online and offline sources, maintaining high accuracy so your customer profiles are broad and reliable. Match accuracy and recency: The best partners also refresh their data regularly and can blend deterministic (exact, one-to-one matches) with probabilistic (pattern-based matches) methods. That way, you get the accuracy of “this email is definitely that customer” with the reach of “this device likely belongs to the same person.” Privacy and compliance readiness: Compliance can’t be an afterthought. Your identity partner should be ready for GLBA, FCRA, GDPR, CCPA, and the latest state-level rules with built-in tools for opt-outs, corrections, and deletions. Integration flexibility: A good provider fits into your world, not the other way around. Look for pre-built integrations with your customer data platform (CDP), demand-side platform (DSP), or marketing tech (MarTech) stack so you can get up and running without the heavy IT lift. Data analytics capabilities: You need proof that identity resolution drives ROI. Look for closed-loop measurement that ties unified IDs directly to campaign performance, so you can see what’s working and optimize with confidence. How Experian enables enterprise-grade identity resolution Experian delivers identity resolution at the scale, accuracy, and compliance required by the world’s largest enterprises. Our solutions are: Built on trust: Backed by 40+ years as a regulated data steward and rated #1 in data accuracy by Truthset, so you can act with confidence. Powered by our proprietary AI-enhanced identity graph: Combining breadth, accuracy, and recency across four billion identifiers, continuously refined by machine learning for maximum accuracy. Seamlessly connected: Pre-built data integration with leading CDPs, DSPs, and MarTech platforms for faster time to value. Always up to date: Frequent enrichment and near-real-time identity resolution through Activity Feed for timely personalization and more responsive customer engagement. Privacy-first by design: Compliance with GLBA, FCRA, and emerging state regulations baked in at every step, supported by rigorous partner vetting. The bottom line Identity resolution turns fragmented signals into connected, measurable, and compliant experiences. From retail to gaming, brands using it see stronger personalization, engagement, and ROI. With Experian, you get the data, trust, and responsible AI innovation to make identity resolution work across every channel. Our approach uses AI to connect identities, predict behaviors, and deliver personalization that balances privacy with performance. If you’re ready to turn fragmented data into growth, now’s the time to start. The world’s leading brands trust us to power identity resolution at scale. See how we can do the same for you. Identity resolution FAQs What’s the difference between deterministic and probabilistic matching? Deterministic uses exact identifiers (like an email) for accuracy, while probabilistic uses signals and algorithms to expand reach. Best-in-class providers usually combine both. How does identity resolution improve ROI? Identity resolution helps with personalization by unifying scattered signals into one profile. It reduces wasted spend and increases match rates, which means bigger addressable audiences and higher ROAS. Can identity resolution work without third-party cookies? Yes. With first-party data and hashed PII, brands can still maintain addressability and personalization. What industries benefit most from identity resolution? Retail, finance, travel, media, gaming, and audio all use identity resolution to personalize, attribute sales, and improve efficiency. How is Experian different from a CDP? A customer data platform unifies the data you already own. Meanwhile, we add depth, scale, and higher match rates by layering in our identity graph and data enrichment. Is Experian identity resolution privacy-compliant? Yes. Experian is GLBA/FCRA compliant, GDPR/CCPA ready, and supports consumer opt-outs and corrections to ensure responsible personalization. Latest posts

Oct 22,2025 by Experian Marketing Services

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At Experian Marketing Services, we use data and insights to help brands have more meaningful interactions with people. As leaders in the evolution of the advertising landscape, Experian Marketing Services can help you identify your customers and the right potential customers, uncover the most appropriate communication channels, develop messages that resonate, and measure the effectiveness of marketing activities and campaigns.

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