What is IoB? Internet of Behaviors in a nutshell

Internet of Behaviors (IoB) is an area of research that strives to understand the role of psychology in product development and consumer purchase decisions.

DefinitionThe Internet of Behaviors (IoB) is a concept that involves the use of technology to collect and analyze behavioral data from various sources, such as sensors, devices, social media, and online activities. It aims to understand and influence human behavior by leveraging data insights. IoB combines data analytics, behavioral psychology, and technology to provide organizations and governments with insights that can be used to improve services, enhance decision-making, and optimize user experiences. It raises ethical and privacy concerns due to the extensive data collection involved.
Key ConceptsData Collection: IoB relies on the collection of behavioral data from multiple sources, including wearable devices, online interactions, and physical sensors. – Behavioral Analysis: The core of IoB involves analyzing and interpreting behavioral data to derive insights into human actions, preferences, and patterns. – Influence and Feedback: IoB can be used to influence behavior by providing feedback, recommendations, or interventions based on data analysis. – Privacy Considerations: Due to the sensitive nature of behavioral data, privacy and ethical considerations are central to IoB implementations. – Customization: IoB enables the customization of experiences, products, and services based on individual behavior.
CharacteristicsData Integration: IoB integrates data from various sources, creating a comprehensive view of an individual’s behavior. – Predictive Analytics: It often employs predictive analytics to anticipate future behavior or preferences. – Feedback Loop: IoB systems create a feedback loop by providing users with recommendations or interventions to influence behavior. – Real-Time Insights: It can provide real-time insights, enabling immediate responses or adjustments. – Ethical Challenges: Ethical challenges related to data privacy, consent, and security are central to IoB implementations.
ImplicationsBehavioral Insights: IoB can provide valuable insights into customer behavior, helping businesses tailor their products and services. – Enhanced Decision-Making: Organizations and governments can make more informed decisions based on behavioral data. – Privacy Concerns: The extensive data collection involved raises privacy concerns and requires robust data protection measures. – Ethical Considerations: Ethical issues, such as consent and data ownership, must be carefully addressed. – Regulatory Compliance: Organizations need to comply with data protection regulations when implementing IoB.
AdvantagesPersonalization: IoB allows for personalized experiences and recommendations, increasing user satisfaction. – Efficiency: Organizations can optimize processes and resources based on behavioral insights. – Predictive Capabilities: It offers predictive capabilities that can anticipate user needs and trends. – Competitive Edge: IoB can provide a competitive advantage by staying ahead of market trends and customer preferences. – Public Services: Governments can use IoB to improve public services and policy decisions.
DrawbacksPrivacy Risks: Extensive data collection and analysis can infringe on individuals’ privacy if not handled properly. – Data Security: There is a risk of data breaches and cyberattacks, given the sensitive nature of behavioral data. – Algorithmic Bias: IoB systems may exhibit bias in their recommendations or interventions if not carefully designed and trained. – Ethical Dilemmas: The use of IoB for behavioral influence raises ethical dilemmas about manipulation and consent. – Regulatory Challenges: Complying with evolving data protection regulations can be complex.
ApplicationsRetail and Marketing: IoB is used to personalize shopping experiences, recommend products, and optimize supply chains. – Healthcare: It aids in remote patient monitoring, early disease detection, and medication adherence. – Smart Cities: IoB contributes to urban planning, traffic management, and energy efficiency. – Education: It can enhance personalized learning and improve educational outcomes. – Public Policy: Governments use IoB to inform policy decisions related to public health, safety, and transportation.

Understanding IoB

Much has been said about the Internet of Things (IoT) and how the trend has made consumer lives more seamless and convenient. However, businesses can also benefit from the recent proliferation of IoT devices.

Internet of Behaviors is a way for these businesses to analyze user-controlled IoT data in the context of behavioral psychology.

These analyses yield crucial information that can be used to influence consumer behavior in customer experience management (CXM), search engine optimization (SEO), eCommerce, and healthcare, to name just a few applications.

IoB lies at the intersection of three areas:

  1. IoT – the source of myriad consumer behavior data in areas such as location, health, interests, desires, preferences, and routines.
  2. Behavioral science – which seeks to understand the motivations behind consumer behavior, and
  3. Data analytics – where machine learning algorithms evaluate IoT data and psychology insights to identify behavioral patterns and make recommendations.

IoB is an emerging field that is likely to grow significantly in the years to come. Gartner, who was credited with devising the term “IoB”, estimates that around 40% of internet users will have their behavior tracked by 2023. Gartner also named IoB in its top ten strategic technology trends in 2021.

IoB industry applications

Below we have listed a few broad applications of IoB in different industries.


The most obvious application of IoB in business is advertising.

Audiences are segmented according to their behavior and served hyper-targeted ads, while smartphones track user locations and serve ads for businesses located nearby.

Google, YouTube, and Facebook are also well versed in serving ads on their platforms based on user behavior.

In fact, academics at Stanford and Cambridge University found that Facebook’s behavioral algorithms enabled the company to know its users better than their friends and families.

Insurance and logistics

The insurance industry has also been utilizing some form of IoB for years. Technology that monitors a user’s driving habits is used by insurance companies to adjust their premiums.

A driver who brakes and accelerates within an acceptable range, for example, may be rewarded with a discount while those prone to speeding may be charged more.

Cprime Studios also offers telematics for commercial vehicle fleet management.

In this case, data on driver behavior in addition to route and location information can be used to reduce a company’s transport-related costs.

Healthcare and fitness

Some healthcare providers are also using IoT and IoB to manage their patients remotely. 

IoT devices collect data on metrics such as blood pressure, sleep patterns, temperature, and heart rate which can be later analyzed using software.

Based on this data, IoB apps can alert patients of impending health problems or remind them to take preventative medication. 

Those interested in building their fitness may also receive personalized recommendations to an associated device based on their exercise behavior.

Key takeaways:

  • Internet of Behaviors (IoB) is an area of research that strives to understand the role of psychology in product development and consumer purchase decisions.
  • Internet of Behaviors lies at the intersection of IoT, data analytics, and consumer behavior and is an emerging field that is likely to grow significantly in the years to come.
  • Industries where IoB is relatively well established include healthcare, fitness, insurance, social media, and online advertising.

Key Highlights

  • Definition of Internet of Behaviors (IoB):
    • IoB is an emerging research area that explores the impact of psychology on consumer behavior and product development.
    • It leverages data from the Internet of Things (IoT) devices to analyze user behavior in various contexts.
  • IoB Components and Intersection:
    • IoB intersects three key areas: IoT, behavioral science, and data analytics.
    • IoT provides data on consumer behavior, such as preferences, interests, and routines.
    • Behavioral science seeks to understand the motivations behind consumer behavior.
    • Data analytics involves using machine learning to analyze IoT data and behavioral insights to identify patterns and make recommendations.
  • Growth and Importance of IoB:
    • Gartner coined the term “IoB” and predicts that about 40% of internet users will have their behavior tracked by 2023.
    • IoB is considered one of the top ten strategic technology trends, highlighting its significance in various industries.
  • Applications of IoB:
    • Advertising: IoB is applied to advertising by segmenting audiences based on behavior and serving hyper-targeted ads. Platforms like Google, YouTube, and Facebook use behavioral algorithms to personalize ads.
    • Insurance and Logistics: IoB is used in the insurance industry to monitor driving habits and adjust premiums. Telematics in commercial fleet management utilizes data on driver behavior, routes, and location to reduce transport costs.
    • Healthcare and Fitness: IoB is employed in healthcare to remotely monitor patients’ metrics such as blood pressure, sleep patterns, and heart rate. IoB apps can alert patients about health issues and offer personalized recommendations for fitness.
  • Key Takeaways:
    • IoB focuses on understanding psychology’s role in consumer behavior and product development.
    • It combines IoT data, behavioral science insights, and data analytics to analyze and influence behavior.
    • IoB applications span industries such as healthcare, insurance, advertising, and more.

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