Daily

PERSONAL SHOPPER

A.I. tech helps consumers shop

Just over one in 10 young consumers around the world have used a personal shopper, with Trendsetting Zs in the U.S. nearly twice as likely to have done so, but new A.I. services are changing the scene. These artificial intelligence-backed virtual assistants provide insight, support, and personalization during the shopping experience.

FASHIONAI

Despite the popularity of online shopping, young consumers are still drawn to storefronts for the real life experience they offer—particularly when such experiences are innovative and personal, like that provided by FashionAI. Installed in 13 stores in China by e-commerce giant Alibaba, FashionAI uses artificial intelligence and machine learning to not only catalog the store’s available merchandise to present to consumers, but also learn a user’s tastes and act as a fashion consultant. Sales on Single’s Day last year, a Chinese shopping festival started by Alibaba, set a record, and the company hopes technology such as FashionAI will drive even more in-store sales moving forward.

SUE

Developed by Chinese A.I. technology firm Emotibot, Sue, an artificial intelligence shopping assistant, was debuted by Chinese retailer Suning at CES 2018. Innovations in A.I. have given such technology the ability to detect human emotion, and Sue uses facial expression, voice emotion, and conversation to detect 22 emotional states. Also able to recognize individual shoppers based on 22 facial attributes, Sue can provide consumers with product information, recommendations, consultations, and post-purchase customer service. Suning plans to deploy Sue in its brick-and-mortar stores across China this year.

RESTB.AI

After presenting their technology in front of a panel of judges made up of entrepreneurs, venture capitalist investors, and innovation experts, the co-founders of Restb.ai were one of the final winners in the Horizon 2020’s European Innovation Council program, landing a €1.7 million investment. Restb.ai uses artificial intelligence and machine learning to identify, categorize, and deliver results on real estate property-related images, helping real estate companies provide the best user experience to interested consumers visiting their websites to find their dream home.