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Internet of Behaviors (IoB): Its Nature & Importance in 2024

Cem Dilmegani
Updated on Feb 22
4 min read

IBM and McKinsey estimate that there will be ~10 intelligent devices (IoT) per person by 2030. IoT is a connection of devices that continuously exchange data with one another. Companies are leveraging IoT to enhance their operational efficiency.

Nowadays, Internet of Behaviors (IoB) is emerging as a new concept, where companies can use big data collected through IoT as a tool to influence people’s behaviors. Gartner expects that over half of the global population will be a part of the IoB program by the end of 2025.1 

Source: McKinsey

What is IoB?

IoB is a use case for IoT that focuses on nudging customers to improve selected outcomes (e.g. IoT provider profitability, sustainability, societal well being etc.). One can view IoB as an intersection of three pillars:

  • IoT: Provides customers’ data such as location, daily routine, health condition, etc.
  • Consumer psychology: Seeks to understand the motivation behind an individual’s actions.
  • Data analytics: Algorithms can use IoT data and findings from psychology to identify behavior patterns and recommendations.

IoB is the natural extension of IoT where these three components are used to achieve long-term customer satisfaction and greater profits. Companies have used big data to understand their customers’ wants and needs. However, by augmenting big data with psychology and powerful AI/ML-driven data interpretation models, it is possible to understand the reasons behind customers’ decisions and achieve greater profits by nudging customers’ behaviors.

For example, people who are on a diet often abandon diets for short-term satisfaction by eating unhealthy food. Places like shopping malls and streets full of restaurants are a source of danger in this respect. Thanks to IoB, a restaurant chain that is located in the mall and offers diet food can

  • identify customers on a diet and flag them as target customers. Customers’ search engine queries or data from other IoT devices like smart fridges can be used for this identification
  • when target customers enter the mall, the restaurant can send them customized advertisements reminding them to stay faithful to their diet. Of course, for this to work, customers need to have allowed businesses to reach them via notifications

Consequently, the restaurant increases its profit and the person increases their long-term benefit.

A picture of a pyramid as a metaphor for IoT and IoB integration. Data fuels the IoB.
Source: Science Direct

Why is IoB important now?

IoB is one of the top 10 trends identified in Gartner’s strategic technology report for 2021 and it can drive significant value generation. The data produced by IoT devices can be used by marketing teams to drive sales which falls under the IoB topic.

Also, IoB might guide entrepreneurs and business leaders to make more data-driven investment decision since IoB provides more insights about customers’ preferences. For example, an auto insurance company can choose its rates based on a customer’s driving style by adjusting the customer experience at a personal level.

How can IoB be beneficial to businesses and consumers?

There are three main advantages of IoB:

  • Know your customer: By analyzing your customers’ data, a company can more accurately determine the demand for its products.
  • Marketing optimization: Thanks to the IoB organizations can optimize campaigns.
  • A nudging opportunity: Consumers can benefit from IoB if IoB is utilized to help them improve their well being.

Know your customer

The better you know your customers, the better you can grow as a business.

Researchers at Cambridge and Stanford Universities found that an algorithm that evaluates individuals’ Facebook activity knows them better than their friends and families. Today, even a mass-produced device like a smartphone can track our online movements and geographic location depending on the permissions that are given. As a result, businesses have the potential to know us better than anyone else. With this knowledge, companies can customize every aspect of their marketing (e.g. price, product, channel, message, timing) effectively and track trend changes more closely.

Explore know your customer automation in more detail.

Marketing optimization

Before recent technological developments, the success of a campaign relied on high level numbers like clicks, sales etc. With IoB, companies can use detailed consumption and behavioral data to identify the success of their campaigns. For example, a smart watch company would not only rely on the sales numbers of its smartwatch to understand the success of its new product. It can rely on detailed usage data to understand how users interact with the smart watch. These insights can be used to tailor campaigns.

A nudging opportunity

Humans have problems with self-control. For example, we tend to prefer small short-term gains over larger long-term ones. As a result, we tend to spend more, eat more, drink more, and work or study less than we intended. Therefore, we all sometimes need a control mechanism for our own benefit. IoB offers a lot in this regard and could increase the number of apps that offer personal coaching. For example, an app could remind you to go exercise if you stay stationary for long periods of time.

What are the key challenges of IoB?

So far, we have focused on the positive sides of the IoB. However, there are some issues that need to be considered as follows:

  • Manipulation by malevolent actors:
    • Manipulation for profit: Let us consider again the example of a person who wants to be faithful to his diet. What if this person has a perfectly healthy body, but is manipulated by a healthcare provider to start a diet? For example, those with excessive concerns about their health could be manipulated to spend more on healthcare.
    • Manipulation for control: Governments or political parties can rely on IoB to manipulate citizens (e.g. during elections)
  • Privacy concerns: Storing and analyzing big data in the name of maximizing profits can be problematic because it involves a large amount of private data. Use of private data is increasingly getting regulated but there are also technologies which allow data processing without exposing private data. Read more on data privacy.
  • Laws and regulations: Regulations lag behind technological development. There are remaining legal problems that need to be solved. For example, there is limited standardization of data security measures.
  • Threat of cyberattacks: The more we rely on digital technologies for our daily tasks, the more vulnerable we become to cyberattacks. Despite the increasing number of cybersecurity tools and even cybersecurity insurances, people need to consider such risks.
  • Convincing users of data sharing: Some people may not want to disclose their personal data. Let’s take a look at the case of car insurance. According to Deloitte, 47% of drivers don’t want to share their driving data. Driving data is information such as driving speed, average driving time, number of full brakes per kilometer, driving routes, etc. IoB means adding more data, such as internet browsing history. For example, the premium price for you could be higher if you search for “how to drive fast”.

If you need more information regarding IoB, contact us.

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Cem Dilmegani
Principal Analyst
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Cem Dilmegani
Principal Analyst

Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.

Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.

Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.

He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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