3 Ways to Improve the Retail Customer Experience With AI

Customer experience is quickly becoming the brand differentiator, and there’s no customer experience game-changer potentially bigger than artificial intelligence (AI).

In a recent market analysis from UBS, retail ranked among the top industries predicted to be most impacted by AI. It's easy to see why. While online giants like Amazon.com and online disruptors such as Stitch Fix dominate headlines, 85 percent of retail still takes place offline.

As such, there’s untold opportunities to merge online and offline experiences, connect what shoppers browse online or offline with personalized offers, and deploy AI and machine learning in ways that boost both in-store and online experiences.

Retailers will want to seize the potential. Half of consumers say customer experience is what drives their decision to make a purchase, beating both quality and price. As retailers gear up for the next holiday season, here are three ways that AI will impact the customer experience by making it:

More Personal

A full 91 percent of consumers are more willing to make a purchase from a company that remembers them and provides relevant offers or recommendations. Few in retail do this better than Amazon.com or online styling service Stitch Fix. Stitch Fix is remaking retail with algorithms and data science that match people with clothes that hit their style, fit and price points — all without a single trip to a brick-and-mortar store. Stitch Fix Chief Algorithms Officer Eric Colson said it best when he told Fast Company that the retailer should almost “pay” its customers because the data they provide enables such personalization.

Most legacy retailers didn’t start as digital natives, as Stitch Fix did, but they still have reams of consumer data. Rather than distribute mass coupons that are rarely personal, they’ll continually move closer to Stitch Fix’s capability with data. For instance, they’ll use what consumers purchase to suggest similar items, like Spotify recommends songs, and deliver the information via phone while the consumer is still in-store. Discounts will be more appropriately targeted based on past purchases. All of this will create a retail environment that's more “context aware,” thus personal. AI is driving the same kind of personalization in the contact-center industry, which is often linked to the retail customer experience, in that agents are increasingly aware of consumer needs based on purchases, browsing patterns and past interactions.

More Convenient

Today’s consumers shop across a sea of touchpoints. They research online, purchase offline, browse in stores, via mobile devices, and buy online. They don’t think about “channels.” They just do what’s convenient. As such, retailers need to make it as easy as possible for them to switch between channels and create an omnichannel experience. Beauty products retailer Sephora, for instance, merged its in-store and digital retail teams to create one “omniretail” department, CB Insights notes. Sephora customer profiles now include online and in-store purchases, and the company delivers personalized product recommendations based on what consumers browsed online and in-store. Also, after in-store makeovers, makeup artists download beauty products to a customer’s profile, which customers can then use to shop online or in-store. Removing friction from where and how consumers shop and buy will be critical to remaining competitive because other retailers will make it easier and easier. AI and machine learning will enable these efforts.

More High Touch

The fitness industry is all about high touch. You hit the gym, check in and the gym knows that you're there, that you do yoga, but haven’t done it in three days. Right then, someone can see that data, engage with you and drive a deeper customer experience. In low-end retail, human interaction most often occurs only at the end of the experience when you check out. In high-end retail, humans are more involved throughout the process. AI will enable more high-touch encounters across the retail spectrum — even if they’re not exactly human. Lowe’s, for instance, created the LoweBot to help customers find their way around the store and get the items they need. Look for more such nonhuman, human-like helpers in all kinds of retail encounters, including online and offline.

AI will also continually drive high-touch interactions that make shopping more experiential vs. simply transactional. As Macy’s CEO Jeff Gennette told market researcher McKinsey, “A store needs to be broader than just a place of transaction. It needs to be a place where people gather, and if you don’t bring in experience and education and entertainment, you’re not going to do as well.”

Jafar Adibi is head of AI and data science at Talkdesk, an enterprise cloud contact center that helps IBM, Trivago and 1,800-plus other enterprises improve customer satisfaction and agent productivity.