Walmart Taps AI to Add Personalization to Holiday Shopping Experience
Walmart is touting its AI capabilities as it prepares for the holiday shopping season.
The retail giant on Wednesday (Oct. 30) announced several ways it would use artificial intelligence (AI) and generative AI (GenAI) to help consumers, such as helping to offer personalized shopping suggestions.
“In the U.S., if a customer previously searched for board games, they may be shown deals, new game releases or gift ideas,” the company said in a news release. “In the coming year, the company will use this same technology to create even more relevant and customized homepages for each shopper.”
On the international level, Walmart says it has a new GenAI-based personalization feature for shoppers in Mexico, offering a wider range of product recommendations. In addition, Walmart says it is using artificial intelligence to identify and vet influencers before sharing their content on the company’s website.
Other AI features include Walmart’s continued expansion of its generative AI-powered shopping assistant, and the use of AI-driven exit technology at its Sam’s Club locations.
PYMNTS noted in a report earlier this year that Walmart and rival Amazon were both competing to harness AI to improve their retail operations and customer experiences.
“Both are using the technology to gain a competitive edge, but their approaches highlight distinct strategies and priorities,” that report said, adding that Walmart was focused more on how the technology impacts the shopper journey.
On an earnings call in August, CEO Doug McMillon stressed the importance of AI in refining the retailer’s massive product catalog.
“We’re finding tangible ways to leverage generative AI to improve the customer, member and associate experience,” McMillon said. “We’re leveraging data and large language models from others and building our own. One example is that we’ve used generative AI to improve our product catalog.”
In related news, PYMNTS wrote earlier this week about the use of small AI models in retail, marking a shift towards a more streamlined system that can process purchase orders, receipts, and shopping data with the same accuracy as massive language models while cutting computing costs.
“Smaller AI models can level the playing field between large retailers and small/medium businesses (SMBs) by providing cost-effective solutions for inventory management and customer service automation,” Steven Sermarini, senior director of engineering, data and analytics at eCommerce logistics and payments company Radial, told PYMNTS. “These models enable SMBs to optimize stock levels, predict demand, and automate reordering while enhancing operational efficiency.”
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