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

IoT growth predictions

The Internet of Things (IoT) has opened up new avenues for businesses to connect with consumers by linking devices and enabling data exchange. Now, an emerging concept called the Internet of Behaviors (IoB) is taking IoT to the next level. It utilizes behavioral data to provide insights into consumers‘ motivations and influence their actions.

In this comprehensive 3500+ word guide, we will explore what exactly IoB is, why it is critical in 2024, its key benefits for businesses and consumers, as well as the main challenges it faces.

What is IoB?

IoB can be considered an integration of three key elements:

  • IoT: Provides continuous streams of consumer data such as location, daily routines, health metrics, and more.
  • Consumer psychology: Seeks to understand motivations behind consumer actions and decisions.
  • Data analytics: Leverages algorithms on IoT data and psychology insights to identify behavioral patterns and influence opportunities.

IoB concept

Image source: Science Direct

IoB combines the vast amount of granular data from IoT devices with principles from psychology to gain deep understanding of what motivates human behavior. Sophisticated AI and machine learning algorithms then derive actionable patterns from this data to guide or "nudge" consumers towards targeted behaviors and choices.

For example, let‘s consider a consumer attempting to stick to a healthy diet plan but facing temptations from junk food options. IoB systems can identify this individual through analyzing their search engine history, smart fridge data, or inputs to a diet tracking app. When this person enters a shopping mall filled with unhealthy eating spots, geo-location data from their phone triggers a customized notification nudging them towards the healthy restaurant options instead.

In summary, IoB aims to influence and enhance consumer behaviors by making use of IoT data, human psychology, predictive analytics, and targeted real-time nudges. It takes IoT connectivity to the next level by understanding users deeply and guiding their actions.

Why is IoB Critical in 2024?

There are several key drivers making adoption of IoB-powered solutions a top priority for businesses in 2024:

  • IoB was highlighted as one of the top 10 strategic technology trends for 2021 by Gartner.
  • Over 50% of the global population is predicted to be impacted by IoB programs by 2025 as per Gartner analysis.^1
  • IoB enables granular personalization for superior marketing, sales, and customer experience optimization.
  • It empowers mutually beneficial "nudges" to improve consumer decision making aligned with their aspirations.
  • IoB provides detailed insights into consumer preferences for data-driven strategy and investment decisions.

Fundamentally, IoB enables next-generation personalization and customer understanding using AI-powered analytics on behavioral data. Companies can evolve from generalized demographic segmentation to ultra-targeted interactions with each individual.

For consumers, IoB opens up new possibilities for personalized coaching and motivation to improve their well-being. In essence, it can steer consumer behavior in ways that benefit both businesses as well as their customers.

The rich insights into human psychology combined with predictive power make IoB pivotal for enterprises and consumers moving forward.

Key Business Benefits of Adopting IoB

There are three main areas where IoB adoption can provide tangible business value:

1. Enhanced Customer Understanding

The better a company can understand its customers at an individual level, the better it can serve and retain them. IoB enables marketers to build a detailed profile of each customer with their specific preferences, behaviors and motivations.

For instance, research has shown that algorithms analyzing Facebook activity can actually know users better than their own families in some cases. IoB amplifies this with data from smartphones, wearables, smart homes, automobiles and more.

With these insights, companies can hyper-personalize marketing outreach including:

  • Customized pricing based on consumer willingness to pay
  • Tailored products and services matching user needs
  • Contextual engagement across the right channels
  • Personalized messaging that resonates

IoB enables marketers to understand micro-trends in consumer behavior and adapt quickly based on live data. Personalization can happen at the segment-of-one level.

2. Optimization of Marketing Processes

Previously, gauging campaign effectiveness relied on high-level aggregate metrics like clicks, traffic, and conversions. However, IoB provides detailed consumption and behavioral data to evaluate granular components of marketing and sales funnels.

For example, a smartwatch company need not just look at sales figures when launching a new model. Instead, they can analyze:

  • Detailed in-app usage patterns after rollout
  • Features users are most responsive to
  • Impact on activity levels and other health metrics

These insights allow for rapid iterations and optimizations to maximize engagement, satisfaction, and retention. Marketing ops powered by IoB offer the capacity for continuous improvement through monitoring of behavioral signals.

3. "Nudging" Users to Beneficial Actions

Humans often act in ways misaligned with their long-term interests due to lack of self-control or focus. IoB enables carefully tailored nudges and interventions to guide consumers towards better choices.

For instance, location data from a user‘s phone can identify when they enter a mall filled with unhealthy fast food options. A customized reminder about their health goals can nudge them towards better meal decisions.

This benefits the consumer in achieving their diet or fitness objectives. For companies, it builds brand affinity through being perceived as caring for the user‘s well-being.

Additional examples of potential "nudge" scenarios enabled by IoB include:

  • Retailers nudging customers from high-cost impulse purchases to more considered buys
  • Banks advising consumers on spending behaviors to better manage savings
  • Learning apps motivating students to complete courses once started
  • Insurance providers nudging for safer driving through real-time feedback

When designed ethically, IoB-enabled nudges can create "win-win" situations improving outcomes for both businesses and their customers.

IoB business value drivers

Image source: Medium

Tangible Business Value Generated by IoB

The granular behavioral insights and nudging capabilities of IoB translate into concrete financial value drivers for enterprises:

  • Increased revenue:

    • More relevant and personalized customer experiences drive higher purchase conversion rates. McKinsey estimates this can increase sales by 5-15%.
    • Higher customer lifetime value thanks to improved retention and loyalty. Bain & Company research found a 5% boost in retention can increase profits by 25-95%.
  • Lower costs:

    • Optimized marketing and sales processes reduce wasted spend and investments in ineffective channels. Altimeter suggests personalization can deliver five to eight times the ROI on marketing spend.
    • Higheroperational efficiency and lower customer support costs through meeting needs proactively before issues arise.
  • New revenue streams:

    • Opportunities for value-added services and information offerings leveraging IoB data and platforms.
    • Emergence of data brokerage allowing consumer insights to be packaged as products.
  • Risk management:

    • Granular visibility into emerging customer trends and pain points enables proactive mitigation of reputation risks.
    • Analysis of operational IoT data spots problems before they impact customers.

As per McKinsey, experience personalization alone could drive $700 billion to $900 billion in incremental value worldwide across retail, healthcare, and financial services. IoB exponentially expands personalization capabilities for businesses.

Consumer Behavior Principles Relevant to IoB

To deliver effective solutions, IoB needs to be grounded in an understanding of human psychology and factors that drive consumer actions. Some relevant principles include:

  • Present bias: Humans tend to prefer smaller short-term gratification over larger long-term rewards due to limitations in self-control and delayed discounting.

  • Ego depletion: Consumers have limited cognitive resources. Once exhausted, they switch to more impulsive automatic behaviors.

  • Anchoring effect: Initial exposure anchors perceptions, causing consumers to rely more on that reference point subsequently.

  • Optimal stimulation level: People seek to maintain an ideal level of mental stimulation. Too much or too little prompts actions to change the stimulus.

  • Hyperbolic discounting: The value of a reward decreases rapidly with delay to delivery of that reward.

These core effects shape day-to-day consumer behaviors. IoB aims to account for them and deliver timely interventions targeted to overcome innate human limitations.

IoB Use Cases to Benefit Consumers

While businesses gain significantly, there are also several ways responsible deployment of IoB can benefit consumers:

  • Personalized coaching apps: IoB can power mobile or virtual assistant apps that act as digital coaches using personalized nudges and motivation tailored to the individual. For instance, guiding the user on healthy lifestyle choices or prudent spending habits.

  • Value alignment: Companies can better align their product design, pricing strategies, and messaging with consumer aspirations thanks to granular IoB insights. This enables delivery of greater perceived value.

  • Win-win nudging: Behavioral interventions oriented towards mutual benefit of businesses and users. For example, nudging book readers towards more reading time by recommending captivating titles.

  • Curated recommendations: Detailed IoT behavioral trails combined with preference data allow platforms like Netflix, Spotify, and Amazon to offer superior personalized recommendations.

  • Optimized product experiences: Usage telemetry from sensors on smart products helps companies continuously refine and enhance their performance, usability, and capabilities.

  • Responsible consumption: IoB nudges can guide consumers to more mindful consumption – eg: buying sustainable goods, moderating energy usage, reducing waste.

Case Study: Optimizing Health Through IoB

John, a busy 40-year old executive, decides to enroll in a digital health program to address long-ignored fitness and dietary goals.

The program leverages IoB to optimize John‘s journey:

  • John‘s fitness tracker provides real-time data on activity, sleep, heart health, etc.

  • His smart scale measures weight changes and nutrition tracking app monitors calorie intake.

  • Location data, schedule, and restaurant spending reveal behavior patterns.

Combining these IoT data streams with health knowledge and behavioral science, the program guides John‘s progress through personalized nudges such as:

  • Reminder to take stairs instead of elevator when arriving at office.

  • Suggesting walking meeting when multiple back-to-backs scheduled.

  • Recommending healthy meal choices when near office fast food outlets.

  • Motivating messages when progress data indicates fatigue setting in.

  • Tips for better sleep habits based on sleep tracker patterns.

The adaptive IoB-powered nudges help John stick to his goals and form long-term healthy behaviors. He gets fitter while the digital health company gains a loyal customer.

Regional Adoption Trends

IoB adoption is surging ahead globally, with China and North America leading the way as per a research study published in the Sensors journal:

Regional IoB adoption trends

Image source: MDPI Sensors Journal

Key factors driving IoB development across regions include:

  • Expanding IoT connectivity with increasing consumer adoption of smart devices and wearables.
  • Growing volumes of consumer behavioral data from digital platforms and e-commerce.
  • Advances in big data pipelines, AI, and machine learning analytics capabilities.
  • Rising niche use cases tailored to localized needs and priorities.
  • Favorable government policies and regulations, with countries like China taking the lead.
  • Accelerating rollout of 5G networks enabling real-time behavioral insights.

These trends point to massive headroom for growth in IoB globally as the foundational IoT, cloud, and analytics infrastructure evolves across regions.

Key Challenges Facing Mainstream IoB Adoption

While promising, IoB faces some crucial challenges and barriers on the path to mainstream adoption:

Privacy and Ethical Concerns

The extensive behavioral data collection and manipulation capabilities of IoB raise critical concerns:

  • Data privacy: Granular data on consumers‘ lives could expose sensitive details if not anonymized and secured properly. Although solutions like differential privacy and federated learning allow extracting insights from data while protecting individual privacy.

  • Informed consent: Are consumers fully aware of how their data is used? Consent needs to be explicit and transparent.

  • Manipulation: Failsafes are needed to prevent misuse of behavioral nudges to overly influence vulnerable segments like teens or those with addictive tendencies.

  • Algorithmic bias: With greater reliance on ML systems, accountability for algorithm outputs and avoiding baked-in bias is crucial.

IoB adoption necessitates careful balancing of personalization potential with ethical data usage and oversight.

Building Consumer Trust

Many consumers are apprehensive of technologies that involve pervasive monitoring and modifying behaviors. To drive adoption, consumers must fully comprehend the benefits they receive in exchange for data sharing. Transparent consent flows and communication are vital.

Companies leveraging IoB need to proactively address consumer concerns around privacy invasion, manipulation, and loss of control. Responsible and ethical utilization of data is the key to building requisite trust.

Technical Limitations

While IoT capabilities have grown tremendously, fully realizing the vision of pervasive behavioral data access will require overcoming some technology limitations:

  • Interoperability : IoT devices today use fragmented communication protocols. Lack of compatibility and standards hampers aggregation of cross-device behavioral data.

  • Analytics at edge: Running advanced AI/ML on terabytes of IoT data is still challenging. Edge analytics is needed for low-latency insights and nudges.

  • Weak security: Billions of IoT devices with lax security greatly increase the attack surface for hackers. Robust endpoint hardening and encryption is critical.

  • Digital divide: Lack of affordable network coverage and smart devices limits IoB benefits for lower-income demographics. Accessibility challenges need addressing.

Maturing IoT infrastructure with 5G, improved analytics architectures, and global technology standards will help tackle these technology roadblocks.

The Road Ahead

As consumer adoption of smart devices and digital engagement explodes in 2024 and beyond, we are firmly entering the era of IoB. The companies that harness its potential while mitigating the risks will gain lasting competitive advantage. They will also play a key role in shaping the evolution of IoB as a trusted mechanism for mutually beneficial behavioral change.

For consumers, IoB presents an opportunity to take control of their technology usage and consciously direct it towards their own well-being and self-actualization by selecting services that resonate with their values. The future of relationship between brands and users will be defined by this interplay of granular personalization with purposeful and ethical application of behavioral insights.

IoT growth predictions

Image source: McKinsey

Exciting possibilities lie ahead as IoB matures to its full potential based on emerging research in recommender systems, computational psychology, and behavioral economics. But prudent regulation, responsible corporate policies, and giving users control over their own data will be crucial in shaping an IoB landscape that benefits all stakeholders.

^1: McHug, B. “Gartner’s IT Automation Trends for 2022.” ActiveBatch. Revisited June 30, 2023.

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