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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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Centralized data access is emerging as a key strategy for advertisers. In our next Ask the Expert segment, we explore this topic further and discuss the importance of data ownership and the concept of audience as an asset. We're joined by industry leaders, Andy Fisher, Head of Merkury Advanced TV at Merkle, and Chris Feo, Experian’s SVP of Sales & Partnerships who spotlight Merkle's commitment to centralized data access and how advertisers can use our combined solutions to navigate industry shifts while ensuring consumer privacy. Watch our Q&A to learn more about these topics and gain insights on how to stay ahead of industry changes. The concept of audience as an asset In order to gain actionable marketing insights about your audience, you need to identify consumers who are actively engaged with your brand and compare them against non-engaged consumers, or consumers engaged with rival brands. Audience ownership Audience ownership is a fundamental marketing concept where marketers build, define, create, and own their audience. This approach allows you to use your audiences as an asset and deliver a customized journey to the most promising prospects across multiple channels. With this strategy, you enhance marketing effectiveness and ensure ownership over your audience, no matter the platform or channel used. Merkle enables marketers to own and deploy said asset (audience) so that marketers can have direct control over their audience. With audience strategy, you can tie all elements together – amplify your marketing reach, while maintaining control of your audience. Merkle connects customer experiences with business results. Data ownership Data ownership refers to the control organizations have over data they generate, including marketing, sales, product, and customer data. This data is often scattered across multiple platforms, making it difficult to evaluate their effectiveness. Alternatively, owning this data, which is typically housed in a data warehouse, allows the creation of historical overviews, forecasting of customer trends, and cross-channel comparisons. With advertisers and publishers both claiming ownership over their respective data and wanting to control its access, there has been a growing interest in data clean rooms. Data clean rooms The growing interest in data clean rooms is largely due to marketers increasing preference to maintain ownership over their audience data. They provide a secure environment for controlled collaboration between advertisers and publishers while preserving the privacy of valuable data. Data clean rooms allow all parties to define their usage terms – who can access it, how it is used, and when it is used. The rise in the use of data clean rooms strengthens data privacy and creates opportunities for deeper customer insights, which leads to enhanced customer targeting. Data clean rooms unlock new data sets, aiding brands, publishers, and data providers in adapting to rapidly changing privacy requirements. Why is centralized data access important? Centralized data access is crucial for the effective organization and optimization of your advertising campaigns. It involves consolidating your data in one place, allowing for the identification of inconsistencies. Merkle’s Merkury platform The concept of centralized data is a key component of Merkle’s Merkury platform, an enterprise identity platform that empowers brands to own and control first-party identity at an individual level. A common use case involves marketers combining their first-party data with Merkury's data assets and marketplace data assets to build prospecting audiences. These are later published to various endpoints for activation. The Merkury platform covers three classes of data: Proprietary data set – Permissioned data set covering the entire United States, compiled from about 40 different vendors Marketplace data – Includes contributions from various vendors like Experian First-party data from marketers – Allows marketers to bring in their own data Merkury's identity platform empowers brands to own and control first-party identity at an individual level, unifying known and unknown customer and prospect records, site and app visits, and consumer data to a single, person ID. This makes Merkury the only enterprise identity platform that combines the accuracy and sustainability of client first-party data, quality personally identifiable information (PII) data, third-party data, cookie-less media, and technology platform connections in the market. End-to-end management of data Data ownership and management enables you to enhance the quality of your data, facilitate the exchange of information, and ensure privacy compliance. The Merkury platform provides a comprehensive, end-to-end solution for managing first-party data, all rooted in identity. Unlike data management platforms (DMPs) that are primarily built on cookies, the Merkury platform is constructed on a person ID, allowing it to operate effectively in a cookie-free environment. A broader perspective with people-based views The Merkury platform is unique because it contains data from almost every individual in the United States, providing a broader perspective compared to customer data platforms (CDPs) which only contain consumer data. The platform provides a view of the world in a people-based manner, but also offers the flexibility to toggle between person and household views. This enables you to turn data into actionable insights and makes it possible to target specific individuals within a household or consider the household as a whole. How Experian and Merkle work together Experian and Merkle have established a strong partnership that magnifies the capabilities of Merkle's Merkury platform. With Experian’s robust integration capabilities and extensive connectivity opportunities, customers can use this technology for seamless direct integrations, resulting in more effective onboarding to various channels, like digital and TV. "Experian's role in Merkury's data marketplace is essential as they are considered the gold standard for data. It significantly contributes to our connectivity through direct integrations and partnerships. Experian's presence in various platforms and technologies ensures easy connections and high match rates. Our partnership is very important to us."andy fisher, head of merkury advanced tv Through this partnership, Merkle can deliver unique, personalized digital customer experiences across multiple platforms and devices, highlighting their commitment to data-driven performance marketing. Watch the full Q&A Visit our Ask the Expert content hub to watch Andy and Chris's full conversation about data ownership, innovative strategies to empower you to overcome identity challenges, and navigating industry shifts while protecting consumer privacy. Tune into the full recording to gain insights into the captivating topics of artificial intelligence (AI), understanding how retail networks can amplify the value of media, and the growing influence of connected TV (CTV). Dive into the Q&A to gain rich insights that could greatly influence your strategies. Contact us today About our experts Andy Fisher, Head of Merkury Advanced TV As the Head of Merkury Advanced TV, Andy's primary responsibility is driving person-based marketing and big data adoption in all areas of Television including Linear, Addressable, Connected, Programmatic, and X-channel planning and Measurement. Andy has held several positions at Merkle including Chief Analytics Officer and he ran the Merkle data business. Prior to joining Merkle, Andy was the EVP, Global Data & Analytics Director at Starcom MediaVest Group where he led the SMG global analytics practice. In this role, he built and managed a team of 150 analytics professionals across 17 countries servicing many of the world’s largest advertisers. Prior to that role, Andy was Vice President and National Lead, Analytics at Razorfish, where he led the digital analytics practice and managed a team of modeling, survey, media data, and business intelligence experts. He and his team were responsible for some of the first innovations in multi-touchpoint attribution and joining online/offline data for many of the Fortune 100. Andy has also held leadership positions at Personify and IRI. Andy holds a BA in mathematics from UC Berkeley and an MA in statistics from Stanford. Chris Feo, SVP, Sales & Partnerships, Experian As SVP of Sales & Partnerships, Chris has over a decade of experience across identity, data, and programmatic. Chris joined Experian during the Tapad acquisition in November 2020. He joined Tapad with less than 10 employees and has been part of the executive team through both the Telenor and Experian acquisitions. He’s an active advisor, board member, and investor within the AdTech ecosystem. Outside of work, he’s a die-hard golfer, frequent traveler, and husband to his wife, two dogs, and two goats! Latest posts

Bridging disparate data in a fragmented world In today's world, consumers engage with brands across multiple platforms, including social media, online marketplaces, in-store experiences, and customer service touchpoints. However, the main challenge for marketers and advertisers is the fragmentation of customer data across these different channels. Each platform generates its own set of data, which is stored in different databases and formats. Integrating these various data sources to create a unified view of the customer is a complex task involving technology and understanding customer behavior across different digital and physical channels. Businesses must link these data fragments to avoid creating a disconnected customer experience. For example, a person may browse products on a mobile app, ask questions through a customer service chat, and eventually purchase in an online marketplace. 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Start collaborating About the authors Kalyani Koppisetti, Principal Partner Solution Architect, AWS Kalyani Koppisetti is a technology leader with over 25 years of experience in the Financial Services Industry. In her current role at AWS, Kalyani advises financial services partners on best-practice cloud architecture. Kalyani works closely with internal and external stakeholders to identify industry technical trends, develop strategies, and execute them to help Financial Services Industry partners build innovative solutions and services on AWS. Technical and Solution interests include Cloud Computing, Software-as-a-Service, Artificial Intelligence, Big Data, Storage Virtualization and Data Protection. Matt Miller, Business Development Principal, AWS In his role as Business Development Principal at AWS, Matt drives customer and partner adoption for the AWS Clean Rooms service specializing in advertising and marketing industry use cases. Matt believes in the primacy of privacy-enhanced data collaboration and interoperability underpinning data-driven marketing imperatives from customer experience to addressable advertising. Prior to AWS, Matt led strategy and go-to-market efforts for ad technologies, large agencies, and consumer data products purpose-built to inform smarter marketing and deliver better customer experiences. Tyler Middleton, Sr. Partner Marketing Manager, Experian Marketing Services Tyler Middleton is the Partner Marketing Lead at Experian. With almost 20 years of strategic marketing experience, Tyler’s focus is on creating marketing strategies that effectively promote the unique value propositions of each of our partners’ brands. Tyler helps our strategic partners communicate their mutual value proposition and find opportunities to stand out in the AdTech industry. Tyler is an alumnus of the Seattle University MBA program and enjoys finding new marketing pathways for our growing partner portfolio. 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The holiday season is just around the corner, and retailers and marketers are gearing up for the busiest shopping period of the year. It's crucial to understand how consumer behavior is evolving and what emerging trends to expect. Experian's 2023 Holiday spending trends and insights report analyzes recent trends, consumer spending habits, and anticipates what's to come in 2023 to help you deliver a top-notch shopping experience this holiday season. In this blog post, we'll cover three key insights from our report. 1. Consumers are shopping earlier It's no secret that December has always been the go-to month for consumers when it comes to holiday spending. However, holiday shopping now starts earlier, particularly with online sales. This can be attributed to a surge in promotions and deals, enticing shoppers to open their wallets ahead of time, giving a significant boost to holiday sales. Notably, Cyber Week sales have proven to be an influential factor, accounting for 8% of total consumer holiday spending. Experian tip Reach the right shoppers with your promotions with sell-side targeting. This powerful approach gives you control over where your ads are placed while ensuring maximum visibility through direct connections with publishers. Whether on mobile, web, or CTV, this seamless ad experience will engage your audience effectively. 2. Online sales are on the rise The popularity of online holiday sales is continuously growing, surpassing in-store shopping. There has been a consistent 1% year-over-year increase in online sales, while in-store sales have seen a 1% decrease. "It’s easier for consumers to comparison shop for large ticket items online that they might find at a mass retailer or office supply store. Consumers prefer to have larger, bulkier items shipped directly to their home for minimal cost. By shopping online, consumers can save time since they don’t need to wait in checkout lines." Anna Liparoto, Sr. Account Executive, Retail & CPG Although online sales currently make up only one-third of all holiday shopping, there is immense potential for further expansion. Mass retailers and office, electronics, and games industries particularly excel in online holiday sales. While in-store purchases remain the primary choice for holiday shoppers, consumer online and offline activities intersect before the final purchase. Experian tip Take advantage of the surge in online shopping by diversifying your marketing channels. An agnostic identity graph can bring together device and media data, capturing valuable user insights. By gaining a holistic view of your target audience, you'll be able to optimize your ad spend and allocate resources effectively, ultimately boosting your return on investment. "Omnichannel targeting during the upcoming holiday season will continue to prove to be the best way to reach scale and maximize ROI across all marketing channels."Joe Ligé, Head of Enterprise Demand Partnerships 3. 2023 holiday spending will be on par with 2022 During the holiday season in 2022, consumer spending showed an anticipated increase, although the growth rate was slightly lower compared to previous years. October saw a surge in average consumer spending, indicating a swift response to early discounts and promotions offered by retailers. As the holiday season progressed, holiday spending gradually slowed down and reached a level similar to that of the previous year. Overall, there was a modest 2% growth. Looking into the future, if economic conditions remain stable in the second half of 2023, we can expect holiday spending to align with the figures from last year. Experian tip To truly maximize impact, consider data enrichment. By diving deeper into your target audience's preferences and behaviors, you can better tailor your strategies and seamlessly integrate the enriched data across various channels. This allows you to unlock the true potential of your ad inventory, creating more meaningful connections with your audience. Download our new 2025 report Get ready for the holiday shopping season with Experian's 2025 Holiday spending trends and insights report, in collaboration with GroundTruth. Inside you'll find: When shoppers plan to buy Why stores still drive results Where marketers are placing their bets How AI is shaping discovery To access to all of our predictions for this year's holiday shopping season, download our 2025 Holiday spending trends and insights report today. Download now Contact us today Latest posts