The @WSJ covers the quickly developing hyper location market, including @EuclidAnalytics and @getTurnstyle. A fascinating read that raises all sorts of privacy questions. It's already in market, with data coming from proprietary wifi signal detectors and licensed carrier data. Again, the law is trying to catch up, both in the US and Canada.
Mr. Zhang is a client of Turnstyle Solutions Inc., a year-old local company that has placed sensors in about 200 businesses within a 0.7 mile radius in downtown Toronto to track shoppers as they move in the city.
The sensors, each about the size of a deck of cards, follow signals emitted from Wi-Fi-enabled smartphones. That allows them to create portraits of roughly 2 million people's habits as they have gone about their daily lives, traveling from yoga studios to restaurants, to coffee shops, sports stadiums, hotels, and nightclubs.
Turnstyle's weekly reports to clients use aggregate numbers and don't include people's names. But the company does collect the names, ages, genders, and social media profiles of some people who log in with Facebook FB -1.77% to a free Wi-Fi service that Turnstyle runs at local restaurants and coffee shops, including Happy Child
Even as they covet the data, stores and businesses recognize it is a touchy subject. "It would probably be better not to use this tracking system at all if we had to let people know about it," says Glenna Weddle, the owner of Rac Boutique, a women's clothing store that is a Turnstyle client. "It's not invasive. It might raise alarms for no reason."
Viasense Inc., another Toronto startup, is building detailed dossiers of people's lifestyles by merging location data with those from other sources, including marketing firms. The company follows between 3 million and 6 million devices each day in a 400-kilometer radius surrounding Toronto. It buys bulk phone-signal data from Canada's national cellphone carriers. Viasense's algorithms then break those users into lifestyle categories based on their daily travels, which it says it can track down to the square meter.
For example, by monitoring how many times a consumer visits a golf course in a month, Viasense can classify her as a casual, intermediate or heavy golfer. People whose cellphones move at a certain clip across city parks between 5:30 and 8:30 every morning are flagged by the algorithm as "early morning joggers." The company identifies "youth" by looking at phone signals coming from schools during school hours and nightclubs, and home locations by targeting the places phones spend each night.