Retail companies that neglect machine learning do so at their peril.

The name 1-800-Flowers.com is a charming legacy anachronism: These days, most of the gifting brand’s customers don’t dial a phone number, and a clear majority order more than bouquets. In fact, the now 40-plus-year-old parent, 1-800-FLOWERS.COM Inc., is today primarily an e-commerce business whose revenue, since its acquisitions of brands such as Harry & David, Cheryl’s Cookies, Wolferman’s, and The Popcorn Factory, comes largely from food-related gifts.

Its floral origins notwithstanding, the company has been on the cutting edge when it comes to using machine learning (ML) to enhance customer experience. Since 2016, 1-800-FLOWERS.COM Inc. has launched several noteworthy marketing innovations to enhance the customer experience. Partnering with IBM Watson, the company introduced the AI-powered personal gift concierge GWYN (Gifts When You Need) to customize suggestions to online shoppers. In addition, customers can order gifts via chatbots and voice.

Amit Shah, CMO of 1-800-Flowers.com, is committed to furthering machine learning in the organization. While ML technologies are still in the nascent stage at the company, the innovative uses of ML are already “training the muscle memory of the organization very deeply,” Shah says. “I think what we will find, five years down the road, is that the people who took the early bets in artificial intelligence actually achieve the learning that cannot be copied. I don’t think you can short-circuit your way the way you can with other channels.”

Shah is hardly unique among innovative retail marketers in taking ML seriously. Research conducted for our global executive study of strategic measurement, “Leading With Next-Generation Key Performance Indicators,”1 reveals that retail executives believe that ML can improve their KPI outcomes and they are investing in the technology for marketing at high levels. Notably, even those retail executives who don’t believe strongly in the importance of ML report investments in the technology at relatively high rates. They are evidently aware that there are strategic risks to falling behind the competition.