Knowing Customers Before They Know You
The technology that lets you identify them— literally—is here
your favorite ice cream: “Nick, Bosco Café has fresh chocolate ice cream waiting for you. Show your screen for a free second scoop.” Sound like a horrific invasion of privacy? Perhaps. But consider how much of our personal data we’ve already given out in the name of convenience: We now willingly share our fingerprints with our devices.
Other emerging recognition technologies will help you hear what no one else can, participate in a conversation when you’re not in the room, and know who’s come in your front door. An early example was SceneTap, which in 2010 offered an app that helped bar hoppers track, in real time, how many people were at a favorite hangout, their average age, and the male-to-female ratio in that room. SceneTap morphed into DoorStat, a service for retailers, which collects and analyzes customer data, including gender, age, ethnicity, and even mood, in real time. It lets retailers observe shoppers’ behavior in their stores and, for instance, move merchandise to better locations, or deploy staff who have more (or less) outgoing personalities.
SceneTap preceded similar startups, like Density, whose sensors measure customer movement and trigger preprogrammed commands. It’s used by some restaurants in Sacramento. When Density senses that foot traffic has been slow for a specified period, discounted menu prices are triggered and customers are notified of the temporary changes. Another service—Placemeter—quantifies the volume and movements of pedestrians, cars, and bicycles, giving an instant snapshot of how many people pass a storefront and how many walk into the store.
Some new software can even identify people in the dark. German researchers have discovered how to recognize faces by using infrared technology and pattern recognition—and in less than 35 milliseconds, regardless of lighting or facial expressions.
And if your customer wears a heat-signature-blocking helmet? (Hey, it could happen.) KnuEdge has built a platform that recognizes individual voices, even in noisy environments. Founded by a former administrator at NASA, KnuEdge recently hired world-class voice impersonators to see if they could fool the system. The technology prevailed every time.
Soon, such technologies will meld with artificial intelligence and neural nets—those huge computer networks built and trained to “think” like a human. With them, you’ll not only recognize Nick and know how much he likes chocolate ice cream; you’ll also know when there’s a 90 percent chance that he’ll walk by your store, and how likely he is to want ice cream when he does. When that day comes, it will be up to you to use your superpowers wisely. F YOU HAD JUST ONE SUPERPOWER, would you rather fly or be invisible? If you chose the latter, start thinking of a superhero name.
Developers in Russia recently launched an app called FindFace, which lets users scan a stranger’s face in a crowd and identify her. FindFace relies on VKontakte—Russia’s Facebook—to reveal, reportedly with 70 percent accuracy, who someone is, as well as personal details scraped from that social network: who her friends are, who she’s married to, what sports teams she follows, what she likes to eat. FindFace’s founders plan to market their recognition technology to highly sophisticated professionals who need to identify and track people: retailers.
Here’s how it could work. Imagine walking past Bosco Café, on the edge of Red Square in Moscow. As you approach, a discreetly mounted camera would recognize your face, ping a database, and learn that you just chatted with a friend about dessert. You’d hear a beep and look down at your mobile phone to find a notification about