The Role of Internet of Behaviors (IoB) in Digital Marketing

Introduction

Gothe Nyman, who is a professor of psychology, first proposed the concept of collecting precise data on users' habits and routines in relation to the IoT in 2012. Many researchers saw this as the beginning of the Internet of Behavior (IoB). Understanding the three key fields that take role in the implementation of IoB is necessary. The first is the Internet of Things (IoT). It is a network of physically connected objects that communicate with one another and share data and information through the use of computer networks. IBM (2016) defines IoT as a “vast network of connected devices and individuals that collect and share data about their use and surrounding environment.” The second area is behavioral science, which encompasses the study of human behavior in social contexts and includes fields like psychology, sociology, and anthropology. Third, there's data analytics, which involves looking for trends and conclusions in large amounts of data from various sources. By bringing together the IoT's technical infrastructure, the insights into human behavior provided by behavioral science, and the analytical power of data analytics, IoB offers a comprehensive method for doing so. The IoB has risen to prominence as a topic of conversation because of advancements in IoT, big data analytics, and AI. Because of these developments, IoB has emerged as a major movement in the fields of data analysis and IT/behavior integration.

Smart devices that are interconnected via the Internet of Things (IoT) are becoming increasingly common today, including mobile phones, watches, voice assistants, smart homes, and even smart shoes. People can use this connectivity to collect and analyze data in useful ways, such as tracking fitness, sleep patterns, and blood oxygen levels. The IoB takes this a step further by analyzing user data using behavioral psychology to identify patterns and behaviors (Rahaman, 2022). IoB harnesses the advantages of the three fields outlined above to derive valuable insights from data collected through interconnected physical objects. This data can provide crucial information about individuals' behaviors, needs, interests, and preferences. By analyzing purchasing patterns, consumption behaviors, and demographic interests, IoB uncovers hidden patterns in consumer behaviors. Therefore, IoB refers to the collection of data through sensors and computing devices that provides crucial information about a user's behavior, interests, and preferences (Elayan et al., 2022). Basically, IoB aims to analyze the information gathered from individuals' online behavior using the lens of behavioral psychology. (Halgekar et al., 2021). This field aims to comprehend how, when, and why individuals use technology to make decisions about purchasing or using a product or service.

The pyramid model in Figure 1 can be used to illustrate the relationship between IoT and IoB (Afor & Sahana, 2022; Sun et al., 2022). IoT forms the foundation of the pyramid and collects data, which is then transformed into information in the second layer. The third and fourth layers, which belong to the IoB architecture, show how relevant background knowledge and technology are used to turn this information into knowledge and wisdom. IoB is a larger network architecture that uses data from IoT to attach it to specific human behaviors and turn it into knowledge. To obtain wisdom at the top, complex technologies like artificial intelligence, machine learning, and behavioral psychology are used. This demonstrates that the IoB builds upon the foundation provided by the IoT to transform data into valuable insights.

Figure 1.

The connected pyramid of IoT and IoB