How major retailers are using AI to keep brick-and-mortar alive

While the age of the internet began in the last millennium, the ecommerce boom is just reaching its peak. Online retail behemoths like Amazon are easing the shopping process by making products just one click away. Today’s shopping experience can take place anywhere, anytime, even while waiting for coffee or picking up the kids from soccer practice. The time for retailers to adapt is now.

In 2017, 7,000 retail businesses had to cease operations, and 3,800 retail stores have already announced plans to shut their doors in 2018. Without a new strategy in place, retailers risk becoming victims of the “retail apocalypse.”

To survive, retailers must have the right technology in place to derive the right insights. Retailers spend billions of dollars looking for insights, but without analyzing the full network of data, findings will remain fuzzy and incomplete. One way retailers can attempt to keep up with today’s ecommerce giants is to deploy AI, big data analysis, and other emerging technologies to improve customer experiences.

This tailored approach can help keep brick-and-mortar customers happy, while simultaneously facilitating the cost efficiency that drives margins.

Here are a few ways some of the world’s largest retailers are employing AI to keep their brick-and-mortar stores afloat.

Appealing to shoppers’ unique needs is the most effective way to create and maintain customer loyalty. In fact, according to a recent survey, 70 percent of respondents said they would be more loyal to brands that integrated customization into their stores. With machine learning and transactional data at the center of their operations, retailers can track and analyze customer behavior, past purchases, and loyalty cards to glean insights and deliver tailor-made offerings. In fact, machine learning-based solutions can even recommend location-level assortments and predict demand by fulfillment path.

A prime example of this is what Sephora is doing with Color IQ, its exclusive machine learning-driven, in-store product that scans the surface of your skin to provide a personalized foundation and concealer shade recommendation. Since launching this technology in 2012, Sephora stores have generated 14 million Color IQ matches, and the company has created a spinoff, Lip IQ, for lipstick shades. By bringing in-store personalization to the next level, the company found a creative and successful way to increase foot traffic — and other retailers are starting to take note.

With insights into store sales patterns, retailers can reduce safety stock and avoid the industry-standard approach of stocking equally across locations.