Internet of Behavior (IoB) — Quick Insights

From IoT to IoB:

Internet of Things (IoT) is a network of objects that collect and exchange information and data over the Internet. IoT is constantly changing and changing depending on its complexity, i.e. the way the devices are connected, the statistics that can be processed by these devices independently and the data stored in the cloud are changing in a complex way.

Data collection (BI, Big Data, CDP, etc.) provides important information about customer behavior, interests, and interests, and is now called the Internet of Behavior (IoB). IoB seeks to understand the data collected from online user interactions through behavioral psychology. It seeks to answer the question of how to understand information, and how to use that knowledge to create and market new products, all from a personal point of view.

IoB then refers to the process by which user-controlled data is analyzed from a moral point of view. With the results of this analysis, there are new ways to create user experience (UX), user search information (SXO), and how to market end products and services offered by companies.

Because of this, for a company to use IoB technically is simple, but intellectually complex. It requires the study of mathematical studies that reflect daily habits and practices without fully disclosing consumer privacy for ethical and legal reasons.

In addition, IoB incorporates existing personal-focused technologies such as face recognition, location tracking, and Big Data. It is therefore a combination of three disciplines: technology, data analytics, and behavioral psychology.

The purpose of the IoB is to capture, analyze, understand and respond to all forms of human behavior in a way that allows to track and interpret that human who use new technologies and developments in machine learning algorithms. The real thing about IoB is that it not only defines (behavioral analysis), but it works (to find out what variables can influence a particular outcome).

IoB influences consumer choice, but it also creates a value chain. While some users are reluctant to provide their personal information, many others are happy to do so as long as it adds value — the value driven by the data. Hypothetically, data can be collected from all parts of the user’s life, for the greater purpose of performance and quality.

IoB and its ethical usage:

With Big Data, data can be accessed from multiple social networks. This allows you to test the CX from start to finish, so you know where the customer’s interest in the product starts, its shopping trip, and the method used to purchase. This gives you the ability to build multiple touchpoints to better engage with the customer. This customization is key to app performance. The more the app works, the more the user will continue to interact and change their behavior as a result.

IoB benefits:

• Analyze customer acquisition practices across all platforms.
• Read previously inaccessible data on how users interact with devices and products.
• Get detailed information about the customer’s location at the time of purchase.
• Provide real-time POS notifications and identification.
• Solve problems quickly to close sales and keep customers happy.

The potential problem with this technology is not technical. IoB faces the challenge of how data is collected, stored, and used. Google, Facebook, or Amazon continue to receive the software that can bring a user from a single app to any online environment, without their consent. This poses a serious legal and security risk to privacy rights, which also vary among authorities around the world.

Behavioral data can allow cyber makers to access sensitive information that reflects customer patterns, collect and sell access codes, delivery routes, and bank codes. These criminals can take the crime of stealing sensitive information to another level by creating high-level scams, designed for individual users’ practices, thus increasing the chances of users cheating. It is therefore important that you have a secure platform, data storage, and processing using tools such as Confidential Computing, E2E encryption, or SDP tools.

Conclusion:

Undoubtedly, A / B testing, SWOT analysis, and many other strategies have helped companies for years to build their own product and marketing strategies to create and inform potential buyers. IoB will take this practice to the next level, and is set to generate significant momentum in developing the retail industry.

According to Gartner, technology may still exist in its early days, but by the end of 2025, more than 50% of the world’s population will be exposed to at least one IoB system, either in government or in the private sector. It will be an ecosystem that explains how human behavior in a growing digital world.

For this reason, it will be important to strike a balance between personalized offers and interruptions to avoid negative customer reactions. Any company that chooses to adopt an IoB approach to its strategy must ensure that it has strong cybersecurity to protect all such sensitive data.

Author: Starlin Daniel Raj