How Walmart’s Indian IT team used AI to predict customer preferences

Online orders skyrocketed at Walmart, the largest retailer in the US, when the pandemic hit, making more work for in-store employees. At the same time, demand for certain products led to frequent stock outages.

While Walmart’s ordering app allowed customers to indicate their preferred substitutes for out-of-stock products, customers usually skipped this step. This forced the Walmart employees who pick and pack items on behalf of the customer to make the decision themselves.

As a result, dissatisfied customers returned one in ten substitute items, leaving Walmart to refund the full amount of the product and pick up the cost of restocking.

To reduce the number of returns and the accompanying losses, and to improve customer experience, the company’s innovation hub, Walmart Global Tech India (WGTI), rolled out an AI system to learn customers’ preferences. It uses data to predict consumer behaviour, preferences, and needs.

“The AI-driven system learns individual preferences of every customer over a period of time and gives the pickers hints to what the customer likes if a particular item is not available,” says Rohit Kaila, WGTI’s vice president of US tech.

Further adding to the workload of in-store employees assembling online orders for delivery, a few thousand Walmart stores added the option of curb-side pickup to reduce customers’ exposure during the pandemic.