IoT and Behavioral Analytics: A Perfect Marriage of Big Data

Big data is about to get even bigger. As the Internet of Things (IoT) grows – connecting everything from our cars to our FitBits, inventory pallets to coordinated networks, and everything in between – so does the need for sophisticated data analytics processes, such as behavioral analytics.

First, it’s worth noting that IoT places the onus on dynamic analysis. Think about what it is that we like so much about self-driving cars. They process information instantaneously to produce the most efficient, and safest, outcome possible for the rider.

The days of gathering data to inform next quarter’s business decisions are over. Today companies need a direct input analysis and output vector in order to achieve business outcomes with the least amount of digital touches required from the customer. After all, customers are expecting instant satisfaction, or else they’ll move on to anther site as quickly as they came.

Additionally, machines today are better at predicting not only large-scale outcomes (like the state of the traffic on your local interstate), but also individual human behavior. That’s what a team of MIT professors proved last year in an experiment that compared how a computer system fared in creating predictive algorithms for an unfamiliar dataset. The computer finished ahead of 615 human teams out of 906, and worked exponentially faster. It even produced better results in predicting human behavioral outcomes (such as dropout rates) by selecting more relevant data than its human competitors.

This is all good news, because not only will IoT make behavioral analytics processes stronger by increasing the data pool by several orders of magnitude. It will also make it more valuable.

Take FitBit, for example. After the company has gathered ten years of data on millions of users, imagine what a sophisticated algorithm will be able to infer from your heart rate, monitored hour by hour, day after day. FitBit will have enough information to create advanced counterpart identification models to not only diagnose a user’s health problems, but also estimate what they are at risk for. Another example, is at Tesla Motors, where acquiring 1 billion miles of customer driving behavioral data will allow engineers to design and feed data into smarter, autonomous vehicles.

That’s the beauty of behavioral analytics, synced to IoT. It should make your heart race with excitement.