Whether a retailer is creating hyper-convenient checkout options, digital self-serve wayfinding solutions, or autonomous mobile service robots, AI technologies can transform data into consumer-focused strategies. But deciding where to use the technology can be challenging.
For example, Retail Express can use AI to predict customer demand for different products across their stores’ geographic locations. They can also use it to optimize pricing based on market conditions. This type of predictive analytics helps retailers avoid stockouts and connect customers with the right product at the right time.
Smart Shelves and Virtual Assistants: How AI is Reshaping the In-Store Shopping Experience
Other retail applications of AI include smart self-checkout systems that scan products and automatically charge the purchase to a shopper’s account. Automated loss prevention can reduce theft in fully automated stores. For instance, Amazon’s Just Walk Out system tracks what shoppers take off shelves with cameras and charges their payment cards after they leave a store without stopping at a cash register.
Another popular application of AI is recommendation AI, which uses machine learning to suggest products that are likely to interest a given customer. It’s often used in voice assistant apps like Amazon’s Alexa or Apple’s Siri, but it’s also available in the form of web browsers that suggest product results based on previous searches and page visits.
And in the e-commerce space, intelligent visual search technology powered by AI allows users to look for products using images or descriptions. And generative AI models can power chatbots and virtual assistants that answer questions directly and make purchase suggestions based on customer preferences or previous purchases.
