WIFI Tracking using your smartphone who's doing it and why?

Privacy advocates have an entirely new worry to keep them awake at night.
National retailers like Nordstrom and Home Depot, working with a company called Euclid Analytics, have devised a method for tracking shoppers in their stores. The service identifies shoppers' smartphones by requests the devices make for Wi-Fi, even if they aren't connecting to the store's network.
UPDATE: Thursday, 4:30 p.m. -- According to spokeswoman Tara Darrow, as of May 8, Nordstrom is no longer using Euclid for data collection in their stores. Said Darrow in an email to The Huffington Post, "We've said all along that Euclid was a test for us. We had it in select stores since September. We felt like we learned a lot and got great feedback from our customers."
Previously:
According to Euclid, 40 to 70 percent of all shoppers are equipped with a smartphone that can be used to determine specific departments a shopper visits and how long a shopper may spend there. Thus, any person with a Wi-Fi-enabled phone is automatically tracked as he moves through the store. Shoppers looking to go un-tracked have to turn off their Wi-Fi or power down their handsets, a point that has some critics livid.
"I think it's outrageous," John Soma, executive director of the University of Denver Privacy Foundation, told Denver's ABC7. "What are they going to do with that data? Are they going to keep it forever? Are they going to aggregate it? Are they going to sell it to 'affiliates?' We just don't know. That's what's so troubling to me."
John Fu, Euclid’s director of marketing, told Texas-based news outlet CBS DFW that the company's client list includes a wide variety of establishments, from "mom & pop stores and coffee shops to large department stores."
Nordstrom, one such retailer that uses Euclid in some of its stores, told CBS DFW the anonymous reports they receive give them "a better sense of customer foot traffic."
In a piece published earlier this year, The New York Times speculated that retailers could use the data to alter their placement of high- and low-margin items based on who walks by them. In the not-so-distant future, the service could single out specific shoppers, pointing customers who choose to be personally identified toward items they may be interested in.