There’s a big push in the analytics space for increased mobility, and “Mobile Analytics” (or any variation on the term) is becoming a hot commodity. But what does it mean for things like Business Intelligence, or working in the data space in the retail business? A recent post from Wired offers an interesting take on the phenomenon of “Location Analytics,” and it is a good read. What really stands out is this focus on location as a parameter for measurement, the idea that analytics can benefit from knowing the “where” of a person’s purchase. At first glance, this might not seem relevant to mobile analytics — that is, the field of analytics that is concerned with analysis via mobile devices. But if we think about it for a second, something like location analysis becomes incredibly important to the mobile analytics user — in this case, a retailer. The great promise of mobile analytics is the freedom of it: you can gain real insights into problems from anywhere, whether at your desk, out in the field, or in a client’s office. Mobile analytics is all about knowing something right now, and in fact that is iVEDiX’s own belief. When it comes miVEDiX, our own mobile analytics platform, we want you to “Know why. Know how. Know now.” And that’s the key, really. That’s the advantage. Mobile analytics is all about that flexibility, so there is no waiting on report generation, and no need to be tied to a desk to get the work done. Location analytics, then, is a natural fit to the mobile driven analysis a company will do because location analytics is itself such an immediate process. For example, collecting the information from a person buying a car at a dealership doesn’t require any real heavy lifting. The location data is contained in the transaction itself — Uncle Bob’s Used Cars sold XYZ number of vehicles, and their address is (hopefully for Uncle Bob!) not changing. More importantly, you can’t yet buy a car on your mobile device. But let’s say you want to know where a person was when they bought windshield wipers for their car. That’s something you can do from your phone or your tablet, and from an analytics standpoint, it can tell us a lot. Did you buy the wipers from your house? Or did you place the order from the parking lot of your local big-box retailer because you went in, looked around, and didn’t find what you wanted? Now we’re seeing how valuable location analytics can really be! The retail implications for location analytics, combined with the speed offered by mobile analytics, are absolutely huge. The dovetail into mobile analytics is easy to see, as mobile analytics as a field is evolving precisely because of growing pervasiveness of mobile technology. But this leaves us wondering — what, exactly, changes with mobile analytics? It requires a few things, not the least of which is a group of technology users who are willing to learn a new skill. The the good news is, mobile analytics are an extension of mobile technology, something that a great many people are already extremely familiar with. The common gestures of a tablet or a phone — the swipe, the pinch, the tap, the hold, etc — are all put to use in a mobile analytics platform. The transition should be fairly painless for most people. The back-end solution can be a little more complicated. Some systems require new hardware or software in order to interact with a mobile device. Other systems, like miVEDiX, are designed to be extremely compatible with a wide range of existing technology solutions, so the BI user doesn’t have to invest in a completely new stack to start using their new mobile analytics tool. Retail is often considered one of the best hot-bed test cases for BI and analytics, because the BI being conducted is helped in large part by the process of retail itself — sales and data collection are already happening at the same point, so extracting the data to make meaningful decisions is already that much easier. It remains to be seen how mobile analytics will affect retail, but it feels obvious that it will have a large impact.