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.

Executives in the automotive sector believe that machine learning can help them achieve their marketing goals, but that doesn't necessarily mean they invest in that ambition. In the automotive industry, machine learning (ML) is most often associated with product innovations, such as self-driving cars, parking and lane-change assists, and smart energy systems. But ML is also having a significant effect on the marketing function, from how marketers in the automotive sector establish goals and measure returns on their investments to how they connect with consumers. ML is poised to become as much an organizing principle as an analytic ingredient for sophisticated marketing campaigns across industries. This is especially true in the automotive industry, a capital-intensive, high-tech sector riven by disruption.