The convergence of three retail technology trends—AI, 5G connectivity and IoT-connected devices—is poised to change the customer experience.
The Internet of Things has already made its way into the lives of consumers, and edge computing isn’t far behind. But the next chapter of retail may involve a convergence of technologies whose sum is more powerful than each individually.
Consider the alliance at work with these retail technologies: Internet of Things (IoT)-connected sensors and smartphones pushing large volumes of data onto the Web, augmented by processing power with 5G wireless, the latest iteration of cellular technology, and artificial intelligence (AI) in the marketplace. Wi-Fi 6, also a next-generation wireless standard, will play an important role alongside 5G, boosting speed and performance of wireless networks.
Together, these technologies have changed the way customers make purchases. Edge computing—which puts data processing closer to the devices and users that need it—also aids the retail experience by enabling more immediate data flow. Mobile devices, video and voice-activated technologies benefit from this improved speed and performance. And 5G, the new networking standard, promises an increase in data transfer speed of tenfold or greater. These enhancements open doors in customer experience—not just in impressive technology, but in helpful services.
E-commerce and immersive digital experiences offer customers new mediums and tools with which to shop: Virtual reality-enabled tools help consumers “virtually” try on clothes or design a new kitchen; voice-activated assistants like Amazon Alexa help customers order online with only voice commands.
Over the next several years, the convergence of IoT, 5G and AI will continue to introduce new experiences but also a data deluge that must be managed. These changes will be significant. Cash is already passé in a world of digital transactions; sales, specials, and inventory information are often discoverable by smartphone while walking in the door; even coupons are now cell phone-based.
For a full generation, manufacturing, warehousing, shipping and retail have steadily become intertwined into a single ecosystem, and consumers have likewise been adapting to Internet-based purchasing and the power of the smartphone. The pieces that were missing in generating a completely digital marketplace have been AI and the speed to make it work.
A smart mirror may be the most science fiction-like—but also ready—addition to retail environments. A smart mirror can enhance a customer’s shopping experience by providing digital extras in the browsing experience—providing suggestions on additional styles, colors and accessories. It becomes possible to try on clothes without physically putting them on in a dressing room, or to digitally design a new dress.
Smart mirrors that can make size, color and style suggestions are already here. 3-D motion-tracking cameras that can sense an individual’s location in a store are here as well. With 5G and edge computing resources, retail stores can deploy smart mirrors as a matter of course, and now many do in either pop-up locations or flagship stores.
Oddly, the most obvious issue with this technology is easy to overlook: privacy. For such a system to work well, a lot of personal customer data must be gathered and used. Should it be stored? Are the shopper’s sizes something that belong in its customer profile database? Questions like these will require some governance.
The combination of edge computing, AI and 5G won’t just be visual; the digital marketplace is about to get more conversational as well. We’ve all driven around town, trying to pick a place to eat. With enhanced AI in the field, advanced speech analytics becomes possible—AI plus speech-to-text conversion plus Google Maps. This means breaking a deadlock among a group of friends on where to eat by asking the car, “Is there a sit-down steakhouse somewhere close by?” and the car responding with options, following up with distance and directions—and no one has to do a search on a phone.
Of course, arguing in the car over where to eat or what club to head for is a learned skill, and one that human beings take for granted. An AI in a vehicle will need to be spoken to explicitly in the course of such a debate to be effective—and for people, that will take some getting used to.
Most shoppers are familiar with the experience of needing help in a retail store and not being able to find an employee. When AI makes its way into a store, a store can not only track customers’ location as they shop, it can sense how they’re feeling, through facial recognition, body language and motion. Put another way, it becomes possible for an aisle camera to spot a customer wandering aimlessly, puzzled, unable to find what she’s looking for—and dispatch an employee. The customer doesn’t even have to ask.
In this scenario, a human employee isn’t required. It’s just as feasible to have the store’s app on your smartphone and have it guide you to the product you’re looking for—the in-house system interfacing with the phone.
Emotion detection has already been applied in other domains. Smart bots can detect emotion in customer service calls, sensing frustration, anger or confusion and adapting their behavior accordingly, to soothe the customer. This can happen only when AI is part of the mix, and edge resources are present to bolster speed and performance.
A downside is smart bots of this type are the byproducts of machine learning—and the range of human emotional expression is vast. It will be a while before emotional tracking seems truly personal to the customer.
In December 2016, Amazon pioneered checkout-free grocery shopping, known as Just Walk Out technology—a store where a customer can select items that automatically check out, eliminating the need to stand in line as a clerk rings up purchases. This experience is enabled by a combination of computer vision, in-store sensors, a smartphone app and machine learning—IoT, edge computing and AI working together.
To shop, customers need the app, which selects items for purchase to a running list when they are removed from the shelf (and it’s smart enough to delete items if they are put back). A customer’s account is charged once she leaves the store.
While consumers may save time not having to stand in line, some problems need to be ironed out. What happens when an item is returned to the wrong shelf, or when an item on the wrong shelf is chosen? If a camera misidentifies a shopper, does the wrong person get charged? What about re-acquiring a shopper after a mistaken ID? In-store cameras tracking shoppers may also mistake certain behavior for shoplifting.
While a no-checkout store seems straightforward, there’s a lot of technology in the background and a lot of customer and product data floating around—so it may not happen overnight. IT departments need training in the technology and network management and security practices become critical.
Retail isn’t the only marketplace where AI, edge and 5G are making their mark. Augmented reality (AR)—virtual reality systems that can provide digital enhancements in a 3-D space, as a smart mirror can do in a stationary role—are now enlisted for a variety of retail activities, from home renovation to office remodeling. New furniture can be visualized, and new fixtures can be swapped out in a 3-D simulation and even manipulated to gauge ease of use.
What’s most impressive about this new level of consumer decision support is its scale; it’s one thing to change the experience of the shopper in the store, and another to play out the renovation of company headquarters, or to construct a new fast food restaurant layout to be instituted in 4,000 locations—with the ability to study the efficiency and ergonomics of the layout in AR throughout the process, simultaneously evaluating how it will look and feel to the customer. That’s an experience of a whole new order—and, again, made possible by a convergence of AI, edge computing and 5G.
The importance of customer data privacy becomes even more critical as these retail technology trends become integral to customer experience. AI in the marketplace will present more than its share of challenges. The supporting technologies all come with their own quirks and shortcomings, and getting them to work well together will take time.
But the end results will be worth the pain, as the marketplace becomes more efficient but also more agreeable to the consumer. Edge computing and AI will help, bolstering data management capacity to meet the challenge. But as with all emerging technologies, there will be a learning curve.
Lauren Horwitz is the managing editor of Cisco.com, where she covers the IT infrastructure market and develops content strategy. Previously, Horwitz was a senior executive editor in the Business Applications and Architecture group at TechTarget;, a senior editor at Cutter Consortium, an IT research firm; and an editor at the American Prospect, a political journal. She has received awards from American Society of Business Publication Editors (ASBPE), a min Best of the Web award and the Kimmerling Prize for best graduate paper for her editing work on the journal article "The Fluid Jurisprudence of Israel's Emergency Powers.”
Scott Robinson is an enterprise architect and AI consultant with a 25-year history in business intelligence, analytics, and content management in the healthcare and logistics industries. He is currently CIO of the GlenMill Group, a research consortium providing new AI technology and infrastructure for enterprise applications and services.