Metaplaces: Sense Networks
I thought one of the most interesting and informative speakers at Metaplaces was Tony Jebara from Sense Networks. While I have posted about Sense Networks in the past, Tony did a great thorough, and mechanical walk through of his company that provided some interesting new insights.
He describes the company as an analytics company, like Nielsen, with a particular focus on segmentation analysis, and importantly one that doesn’t deliver anything directly back to a single end user, but rather allows its business customers to have a better understanding of aggregate customer behaviors.
Sense Networks pulls together call data and location data from 10 million devices, and slices and dices the data in a variety of different ways to provide, what it hopes, is a useful analysis for companies. The subscriber location and call usage data is almost all consumer opt-in, gathered directly from wireless subscribers, and is limited just to lat, long, time and call details.
But Sense Networks uses this information, to among other things look at similarities between the behaviors of people who ‘co-locate’ (visit the same place at the same time) and to draw out information on commutes and distances traveled based on changes in location. They also combine the location and call data in with other information sources that paint a picture of the places/geography around us that allow them to make inferences about people based on their visits to certain geographic areas.
The output from Sense Network could be used as stand alone “research” or could also be integrated into other corporate services or platforms like the mobile ad serving solution, Ad Orchestrator, from Ericsson for example.
Needless to say, the company has gone to great lengths to protect the identity of the individual customers behind that data and purposely does not receive any personally identifiable details or ID numbers tied back to a particular mobile device.
As I have said in previous posts, I believe that there is something potentially very big here, particularly for marketers, in a deeper analysis and understanding of actual human behavior around the places we all visit. Do people tend to go to ice cream parlors after sitting for 2 hours in a movie theatre? How do most people who arrive by airplane get from LGA to Manhattan? Does it vary by time of day? Where do fans go after a day game at Yankee stadium? How long and far are they traveling to see a game?
I was a bit surprised to learn that at the moment Sense Networks seems quite focused on serving the wireless carriers themselves, with a significant focus on reducing subscriber churn, which presumably digs as much into the call data as anything else. But the potential behind the location data just seems enormous, so I’d hope and expect to see more on that front in the months and years to come.
