Walking Around Money


A young company called Placed is deep into Big Data analytics, but with a twist: it marries customer data with its own proprietary data to yield insights into customer behavior. Essentially, Placed wants to provide context around how customers use the mobile applications of its clients, for example, when do they use the app and where do they use it?

The “where” part of the analysis is what’s interesting. Placed could simply spit back to its clients that its customers are in certain ZIP codes or other dry demographics – interesting, like so many analytics reports are, but not particularly useful.

Instead Placed marries customer location with its own proprietary database of places – named stores, major buildings, points of interest. By connecting the two, Placed can tell its clients where mobile use of its app is occurring. For example, if a client’s customers utilize its mobile app in a competitor’s store, it might suggest competitive price comparisons. Knowing its customers frequent Starbucks and nightclubs might influence the clients’ marketing strategy or advertising campaign design. Knowing that the app is used most often when someone is walking (yes, Placed can tell you that) can be important for user interface design – you get the idea.

And therein lies an important insight. There are an endless number of companies offering Big Data analytics capabilities. But almost all of them expect their customers to bring both the problem and the data. That’s a sure recipe for commoditization, and as analytics software evolve, it’s also certain that the companies with the biggest analytics needs will decide to do the work themselves.

Solution? Big Data analytics players should bring proprietary data to the party. Placed is a perfect case study. It differentiates itself by providing answers others can’t. It adds value to its analytics by integrating proprietary and licensed data with customer data and its own optimized analytical tools. As I discussed in my presentation at DataContent 2012, there are lots of ways publishers can profit from the Big Data revolution -- even if they don't have big data themselves.

In a market where companies like Placed can make money by tracking people walking around, it behooves data publishers to walk around to some of these Big Data analytics players and suggest data partnerships that will help them stand out from the crowd.

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