The birth and never ending iterations of mobile devices have created a rat race for mobile-related softwares and technologies, from mobile apps to payment platforms, and from cameras to music players. All of these pieces of software not only provide us with incredibly practical services that help to simplify our lives, but also keep us connected and engaged.
What was the first thing you thought about when you realized how “smart” your smartphone is? If you’re like most people, your immediate thought was, “You mean Apple can track my location?” It was kind of creepy at first. But then you realized how practical the ability to track your location and movement was – “I can track the distance of my runs!” “I know the fastest route home!” “I know where my kids are 24/7!” You may be surprised to know that the first patents of location-based software were approved almost 20 years ago. Why then, is location still the first thing that comes to mind when we think of a mobile user’s “context”?
The more useful the app is, the more we likely we are to use it and grow comfortable with sharing our personal information. As a result, the app can begin to understand the user’s behaviour and become smarter. We all witnessed the beginnings of this form of machine-learning with features like “iTunes Genius,” where iTunes would pick up on our music preferences and curate playlists for us. Today’s apps work in much in the same way, with algorithms baked into the backend that enable the app to understand the user and catering to their preferences and needs. This in turn keeps the user coming back – they find the app useful, intuitive and effortless to use.
We get so hung up on location, forgetting that it’s just one of the several types of data app users provide. Each time we interact with our mobile device, we are helping the app get to know us better – our spending patterns, our workout habits, our music preferences. We are comfortable in giving this information to our mobile app providers because they are providing a useful service to us and creating a meaningful experience. Smartphones are not just miniature computers in our pockets; they are powerful machines that carry massive amounts of data on our everyday transactions and with sensors tracking our movement patterns.
Although mobile apps learn from and improve based on data, enterprises across all industries are still trying to figure out how exactly to make use of it in a way that generates revenue for the business and delights their customers. Before mobile apps existed, big data and analytics were captured from legacy systems and big clunky databases, and would lead to targeted offers via direct mailers and other traditional marketing and advertising streams. Today, with the Internet, mobile and IoT, new data sources of data are created each day, piling on additional layers of complexity to traditional datasets. Enterprises, often hindered by legacy data management systems, struggle to make sense of all the different types and sources of data they have and convert it into something meaningful. And yet the first thing that comes to mind when it comes to understanding the digital context of their customers’ and mobile users’ is location. It’s an interesting observation.
Maybe one of the reasons enterprises are having trouble making sense of their proprietary data is because it’s really only a partial view of who their customer is. A bank, for example, can see transactional history, but do they know all of the loyalty programs their customers belong to, or how often they exercise? The real power comes in tapping into other sources of data in order to get a comprehensive understanding of the mobile user, their true “contextual” circumstances; being able to extrapolate the data and understand it, and analyze it in a way that enables enterprises to make inferences of their customers’ needs and wants. Seeing and tracking a customer’s location and proximity is simply not enough.