The interconnection of devices within the “Internet of Things” (IoT) creates new data sources. Companies can now better observe people’s choices and test the effectiveness of different mechanisms to activate and retain more customers. It may also help policymakers overcome one of the most frequent problems of policy design: the lack of personalized content. We argue that the IoT not only disrupts the way we track our actions and monitor our goals, but also allows the identification of effective methods to alter our behavior. This is optimized by the combination of IoT, data analytics and behavioral science.
One of the main contributions of behavioral economics to the study of consumers is its empirical focus on observed behavior. Hence, behavioral specialists in the areas of marketing, economics and public policy should be aware of the possibilities that new technologies create for the analysis of consumer behavior. Today’s consumers produce (directly and indirectly) an abundance of data. Optimal commuting decisions and advertisement locations can now be inferred from call details and “over-the-top” digital records produced by more than a billion cell phones that emit 18 exabytes (1 billion gigabytes) of data every month. The web and mobile apps, which can track anything from dietary choices to banking transactions, have the potential to replace a large number of existing self-reported consumer surveys. Data collection capacity is added to more and more objects found in the physical world. Sensors are now positioned in our cars, (smart) homes, and even our clothes (wearables). This movement from the world of the Internet of People (IoP) to the Internet of Things (IoT) exponentially increases the data that is being generated.
Source : Behavioral Economics