As a recent Times article describes, shopping plazas are now using cell-phone tracking technology to map shoppers’ activities and movement patterns. The "Path Intelligence" hardware used to track the movements works like this:
- A cell-phone-wielding shopper enters the shopping plaza.
- Path Intelligence monitors mounted throughout the plaza detect that a new mobile phone is in the vicinity and log its IMEI code.
- As the shopper moves around the mall, his or her movements are continuously triangulated by the multiple Path Intelligence units, allowing movements to be mapped and saved for later analysis.
The good news: it’s totally private, there isn’t any (automated) way to map a particular record in the Path Intelligence logs to an actual person. The resulting logs can be analyzed for shopping patterns (where people go after visiting a certain store, peak hours of traffic, most popular regions, etc.) later on, providing valuable intelligence and allowing for improvements.
The bad news: The Path Intelligence logs — in-conjunction with other monitoring techniques such as cashier timestamps, credit card log, video surveillance, etc. — can result in the identification of the persons associated with logged behavior in the system; posing a real and tangible privacy/Big Brother concern.
The weird news: Everything in the above scenario can be directly mapped to an exact counterpart in the current web-tracking solutions in use:
- Shopper -> Visitor to a site
- Mall/Shopping Plaza -> Website
- IMEI code -> IP Address (unique, but not personally identifying on its own)
- Path Intelligence -> One of the many web-statistics companies
Everything from the tracking techniques used to the information gathered to the way its analyzed and used is directly taken from the way cyber traffic has been logged and analyzed for years. After all, why not?
Web monitoring solutions have proven to be reliable metrics for understanding the userbase of any given site; and more importantly, the number one tool to improving conversion rates and increasing the visits-to-sales ratio. If there are technologies that have proven invaluable to boosting the online commerce economy, it makes sense for people to attempt to apply these same methods to everyday life in the real world as well.
It’s somewhat of an epiphany to consider the amount of information available in cyberspace and how easy it is to obtain and analyze when compared to the physical world we live in. The quantity, quality, and pervasiveness of the data available to online far exceeds anything in the real world, and the use that it can be put to are truly amazing – and scary when extended to our normal lives.
Imagine for an instance the typical data available to a website owner enlisted with one or more of the web statistics services and just how useful such knowledge would be in the real world:
- Referrals. Who came from where, how people came across your store, and what they’re most interested in.
- Popularity Ranking. Know what stores in each mall are the most popular, down to the last customer. Find out exactly what sections of each store get the most attention (then compare it with sections are currently getting the most sales and try to maximize sales in those departments).
- Shopper Characteristics. As the Times article explains, the IMEI number can be traced back to the country the shopper comes from. In high-tourist areas (think New York, Las Vegas, London, Chicago, etc.) this kind of intelligence can provide great insight…
Basically, the real world is starting catch up with the online one (not the other way around, folks!), and there’s a lot it has to learn and a lot it has to benefit.