This story first appeared in the March/April issue of Supply Chain Xchange, a journal of thought leadership for the supply chain management profession and a sister publication to AGiLE Business Media & Events’ DC Velocity.
Consumers are increasingly seeking shopping experiences that are specifically tailored to their unique preferences and needs. According to the 2024 study ”
The State of Customer Service and CX” conducted by CX consultant Shep Hyken, 81% of customers prefer companies that offer a personalized experience. The consumer intelligence company NielsenIQ has also found that consumers demand richer, more informative, and more personalized online experiences.
To meet these demands for hyper-personalized shopping experiences that are both convenient and engaging, companies are increasingly turning to technology solutions that are powered by artificial intelligence (AI). The latest MIT Annual Omnichannel survey, which explored how companies use AI in omnichannel retailing, highlights this trend. According to the research, AI is becoming a critically important enabler of retailers’ efforts to customize omnichannel shopping and improve key capabilities related to these efforts, such as inventory management. (For more background on the study, please see the sidebar, ”
About this study.”)
AI’s growing impact
The 2024 survey found that the most common use of AI in omnichannel retailing was for personalized product recommendations (see Exhibit 1). Seventy-one percent of respondents are either already using or planning to use AI applications this way. For example, in October 2024, Walmart.com launched a new platform leveraging AI technology to gain deeper insights into customer behavior. The platform includes a generative AI-powered tool that predicts the types of content customers are most likely to engage with. This innovation enables Walmart to create personalized homepages for each shopper, enhancing the online shopping experience.
AI is also being applied in customized marketing campaigns (41%) and customer segmentation (38%), according to the survey. Starbucks and Nike exemplify these two personalization trends. Starbucks uses AI-driven insights from its loyalty program to segment customers based on visit frequency, purchase behavior, and preferences. This enables the delivery of personalized offers and rewards, fostering customer retention. Similarly, Nike leverages AI analytics within its app ecosystem to analyze customer data, including browsing patterns, product preferences, and fitness activity. This allows Nike to identify customer segments more precisely and design targeted marketing strategies, improving sales conversion rates and reinforcing customer loyalty.
Another increasingly popular way to use AI to customize the customer experience is via “try-on apps” that allow shoppers to virtually try on a retailer’s products. According to the survey, 54% of retail businesses, including companies like Nike and Zara, are already using or planning to implement AI for this purpose. These apps provide a digital representation of how the items will look or fit, helping customers make informed purchasing decisions without needing to visit a physical store. AI enhances the functionality and effectiveness of these apps by leveraging user data, preferences, and previous purchases to recommend products that match their style, size, and fit. Additionally, machine learning models analyze patterns in user feedback, returns, and size charts to suggest the best-fitting products, reducing sizing errors, returns, and exchanges.
Supply chain implications
As AI-powered applications revolutionize omnichannel retailing, their influence extends beyond the shopping journey. These innovations are also impacting the supply chain. According to our study, AI-driven personalization is driving the need for improvements in real-time information on product availability (55% of respondents) and inventory accuracy (47% of respondents) to better support the supply chain (see Exhibit 2).
Companies were already making advances like these a critical part of their omnichannel strategies, as they aimed to deliver a seamless customer experience across multiple platforms. However, increasing personalization—ensuring the right product is available at the right time through the preferred channel—has introduced greater complexity to the supply chain’s back-end operations. Additionally, a higher level of personalization can increase supply chain costs by raising restocking frequency and the number of stock-keeping units (SKUs) per order. On the positive side, our survey results show that 21% of respondents report a reduction in returns due to the increased use of AI tools, such as try-on apps.
Tech tools and strategies
Companies are using different supply chain technologies to overcome the new fulfillment challenges. The most common one, according to the survey, is real-time inventory management solutions, with 75% of respondents finding these options a highly relevant way to increase inventory visibility (see Exhibit 3). This focus on inventory management technologies makes sense as inventory allocation has been identified as a key pain point for omnichannel fulfillment in previous years’ surveys. The focus on improving inventory visibility and management is a clear response to the increasing complexity of omnichannel operations.
Companies are following several different strategies for managing the implementation of technologies to address omnichannel fulfillment (see Exhibit 4). Seventy-one percent of survey participants reported partnering with tech companies, and 60% said they were developing in-house tools for this purpose. In many cases, these two strategies are being followed in parallel. For example, in February 2024, Kroger partnered with Intelligence Node, an AI retail analytics firm, to enhance its online shopping experience. At the same time, the grocery company has also been developing its own AI solutions, such as Kroger Precision Marketing, which uses machine learning to deliver personalized promotions and optimize inventory management. Similarly, in April 2024, The Coca-Cola Company announced a five-year strategic partnership with Microsoft to boost its cloud and generative AI capabilities, integrating these advancements into marketing and supply chain management to drive efficiency and innovation. While working with Microsoft, Coca-Cola is also continuing to develop its own in-house AI systems, including AI-driven predictive analytics for supply chain optimization and AI-based personalization for its digital channels, ensuring more tailored customer experiences in product offerings and marketing.
AI’s advance to continue
As companies look to boost their competitiveness in omnichannel retailing, we anticipate that they will increasingly turn to technology, especially AI applications, to personalize customer experiences. This trend toward greater personalization will have a significant impact on the supply chain, driving a greater need for inventory visibility and accuracy. While personalization may cause greater complexity in terms of inventory management and fulfillment, more tailored recommendations may lead to greater customer satisfaction. This could, in turn, have a positive effect of reducing returns.
To operate effectively in a highly personalized retail environment, supply chains will need to implement technology that enables real-time inventory visibility and efficient fulfillment practices. To accomplish this, many leading companies are partnering with outside technology companies while also developing their own in-house tools.
About this study
The 2024 edition of the annual “How Is Omnichannel Transforming Retailers’ Supply Chains?” study was conducted by Dr. Eva Ponce and Laura Allegue of the Omnichannel Supply Chain Lab at the Massachusetts Institute of Technology (MIT) Center for Transportation & Logistics. This year’s survey asked companies how technology-related innovations like AI have helped them reshape their omnichannel fulfillment strategies over the past 12 months. Conducted In November 2024, the study surveyed 238 logistics, warehousing, and supply chain professionals from various industry sectors.
Retailers (some 30%) and manufacturers (25%) were the most represented business types in the survey. Transportation and warehousing was the most represented industry sector (35%), followed by food and beverage (27%) and fashion (20%). Most of the study’s companies (47%) were large enterprises with greater than 5,000 employees.
The survey has been conducted for the past four years. More information on previous years’ results can be found in “AI in omnichannel retailing: A revolution in the making” from the May/June 2024 issue of Supply Chain Xchange and “Six defining challenges of omnichannel fulfillment” from the Q2 2023 issue of
CSCMP’s Supply Chain Quarterly.
To learn more about the study and results, contact Dr. Ponce at
eponce@mit.edu.
