By David Loshin
Location is meaningful when it comes to analyzing customer behavior. The old
adage “birds of a feather flock together” can be adapted to customer centricity.
Simply put, individuals tend to congregate in areas populated by others with
similar characteristics and interests. People interested in boating and fishing
are more likely to live near the water than the mountains.
Wealthy people live in wealthy neighborhoods. In fact, geo-demographic
segmentation has been around for a long time, in which the primary demographic
characteristics of individuals living in different geographic regions are
analyzed and then used to provide descriptive segmentation in relation to where
each individual lives.
The value of geo-demographic segmentation is that once you can link a location
to the individual, you have a starting point for marketing strategies especially
along the traditional media channels such as television, radio, print
advertising, or even highway billboards. For example, a luxury car manufacturer
might want to situate a highway billboard advertisement close to the exit
nearest the wealthy neighborhoods.
Contact information is traditionally used for determining location, but there
are two factors that are poised to upend this reliable apple cart. The first,
which we started to look at last time, is the encroaching inaccurate use of
previously reliable location data sources such as area codes.
As individuals transition away from landline telephones to mobile or virtual
phones (whose “area” codes are irrelevant and untrustworthy for location
specification), the usability of that data diminishes as well.
The second factor is a transition in the way that people communicate among
themselves. In today’s connected world, people are as likely (if not more so!)
to interact virtually via the internet than by telephone.
Email, instant messages, Facebook, Twitter, LinkedIn, Foursquare – these are
just a few examples of the channels within individuals with similar interests
hang together. But what does this imply when it comes to location analysis and