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Hyper-Local and Predictive Marketing

Location systems that enable you to avoid traffic and get to where you want to go are nothing new. Some applications of location technology are emerging however, that may usher in an entirely new era of hyper-local, micro-personal and predictive consumer marketing.

TechCrunch released a study this past week showing how the Google Location History system tracks one’s movements throughout the course of a given time frame. Google Location History is made possible by an ‘opt-in’ system on Google devices such as Android phones that allows Google to collect and store location history information. This level of data aggregation and Google’s ability to glean meaningful information out of a truly huge set of data highlights some very interesting possibilities for local marketing strategists.


Knowing Where You’ve Been
During the set up sequence consumers endure when setting up their Google mobile devices, the user is asked whether or not they would allow Google to identify their location. In the haze and confusion of the set up procedure, many users may not realize the significance of answering ‘yes’ to this prompt.

A ‘yes’ answer allows Google to know where you are and where you’ve been. What does this mean?  If you spend time at the pub on your way home and tell your wife that you worked a bit late, this information might make one’s personal life more difficult. In a partnership with Google, one’s wife could easily discover your whereabouts and uncover the deception.

Hyper-Local Marketing
Aside from throwing a wrench into one’s home life, combining location information with consumer preference data is hugely valuable to marketers and of course to Google. The ability to associate these different sets of behavioral data enables the holders of this information to construct a reasonably predictive micro-consumer model.

If you only stop by the pub on the way home on Thursdays, the model would be able to reasonably predict your consumption habits for upcoming Thursdays. If you spent an hour or so at a particular address that corresponded to that of a local Irish bar, Google will know about it. Further, if you recently viewed Guinness Beer advertisements on YouTube or have the Guinness Brewery in your Google+ circles, one could conclude fairly strongly that you prefer to consume that beverage at an Irish bar to take the edge off your workweek.

Why might these bits of information be important? Competing Irish themed establishments along this consumer’s route home might earn some new business by reaching out directly to this individual with a special promotions positioned to fit the consumer’s existing tastes and habits. Technology currently exists to cause an advertisement to appear on a consumer’s mobile device as he/she passes within a certain distance of the seller’s location. These messages can be micro-targeted to an individual consumer to offer specials on Guinness or other preferred products.

Micro-Personal Profiling
Identifying a consumer’s area of interest can also be fairly accurately estimated by monitoring one’s Internet activity. The number of ‘likes’ or ‘plusses’ or ‘follows’ for certain product pages strongly reflects a consumer’s tastes and preferences. Companies already follow individual consumers they consider to be ‘trendsetters’ or ‘influencers.’ Google is taking this to a new level however, by observing and storing as much of this online interaction as is possible. If your favorite department store has you in their Google+ circles, Google is also able to determine something about your consumer preferences.

Predicting Behavior
Collecting personal information like gender, age, income, work location, college degree, home location and consumer preferences allows sellers to build complete consumer profiles. Merging this with where the consumer actually is at certain points in time enables marketers to construct and deliver messaging that will be perfectly timed to coincide with both the consumer need and consumer location. As the consumer’s location is important to his ability to consume, applying geographic data to consumer preference profiles can make marketing data very “actionable.”

At this point, much of this information gathering is done with the acquiescence of the device user. But, with new ways of gathering data constantly emerging, it might not be much of a stretch to imagine data being collected without the specific approval of the consumer. It will be interesting to see the limits that Google and its advertisers push in making use of their ability to match consumer preferences with location.

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