The AR-Infused Café of the Future
Huge, in partnership with BRASH coffee roasters, unveils a new and improved mobile order-ahead and pickup experience for customers.
Mobile ordering seems like a dream. You place your morning coffee order using a phone app, walk into your favorite café to find your java waiting, and make it into the office for your first meeting of the day without waiting online or talking with another person before your dose of caffeine. But how often does it work that smoothly? If your experience is like mine, you show up at your allotted pickup time only to huddle with other mobile-app customers, touching each cup placed on the counter to see if it’s yours, or staring at your phone while you wait for the barista to yell your name above the atmospheric din.
Huge, in partnership with BRASH coffee roasters, decided to fix the order-ahead pickup problem in its newly relaunched café in Atlanta. Leveraging computer vision and projection mapping, the coffee house brings the ease and convenience of mobile ordering into the physical retail space. Customers can not only order ahead through the café’s app but will also be visually cued when their drink is ready: Their names are projected onto the counter around their respective orders. “It’s one seamless experience,” says Huge Associate Product Director Neil Caron, “starting with the digital touch point of your mobile app and ending while you’re in the café.”
The frictionless user experience extends to the baristas behind the bar, who no longer have to interrupt their workflow at the espresso machine to monitor new orders coming in. Instead, they’ll be subtly prompted by a Bose Audio AR in-ear headset to check an iPad for the exact order. At the same time as the order appears onscreen, a ceiling-mounted projector creates a circle (indicating the drop zone for the coffee) along with the customer’s name and order facing the barista. A camera hooked up to a computer running an object-detection program recognizes when the barista places a prepared drink in the circle, and the orientation of the projection flips toward the customer for easy reading. After the customer picks up the order, the circle closes.
“The user can walk up and grab their coffee without any awkward moments,” says Huge Executive Creative Director Rich Bloom. Those awkward moments include asking the barista if they’ve received the order, and if so, where it is in the queue. And it leverages technology to solve that problem in an unobtrusive way, without resorting to screens — the all-too-common signal that digital tech is in the room.
The Huge team turned to AR to give customers a moment of delightful discovery. Scattered around the café are coasters with QR codes that, once scanned, generate a web-based AR experience that visualizes where the coffee beans came from and the real-time weather conditions in El Salvador where the coffee is being harvested.
Huge first opened the café in 2015 to serve as an R&D space where the agency could test and showcase its innovative retail concepts to clients, including Lowe’s, Arby’s, and SK-II. “Usually ideas stop at the proof-of-concept stage,” Huge VP of Technology Brian Fletcher says. “The café lets us push technology further and get it in front of people for real.” For Capital One, for instance, Huge used research borne out of the café to show the bank how it could integrate screens in its own cafés to encourage customers to have conversations around their finances. “The Huge Café showed Capital One that we had been putting our money where our mouth was, and that we were in earnest about driving actual value,” Fletcher says.
Even the bathrooms in the café will get a digital upgrade with Hooha, the world’s first smart-tampon dispenser that provides a free tampon to customers when they send it a text message. Developed by Huge Associate Director of Social Marketing Steph Loffredo and launched at SXSW in February, the dispenser is far more reliable than old-school coin-operated models, because it’s equipped with two sensors, one that detects when stock levels are low, the other that detects whether a tampon was successfully dispensed as a way of preventing the classic “jammed” scenario.
Fletcher says that the Huge team will continue to build out its object-detection capabilities by using machine learning to teach its computer model to recognize other food items as the café expands its menu. “What we have right now are very simple but very powerful building blocks that we can use to eventually scale this up in the future,” he says.
Magenta is a publication of Huge.
