High-quality user experience (UX) design means reacting to feedback and preferences. The traditional ways to learn about users' wants and needs have included studies, surveys and data analysis — reliable methods, but relatively slow and reactive. Today, there's a new option.

Due to the wide range of inputs that are now recordable and usable, it's possible to interpret user behavior and provide shifting, hyper-personalized experiences that give each person a unique view of an app. This ability to turn real-time behavioral data into a custom UX is called the Internet of Behaviors (IoB), and it's changing the way developers think about apps.

Deep customization powered by the IoB goes beyond what's possible with experiences segmented by user personas. By enabling this new approach to UX, the IoB can be the key to capturing and keeping user attention.

Understanding IoB mechanics

The first question before getting involved in IoB design is a fundamental one: What is IoB? IoB is related to a similarly named and related concept, the Internet of Things (IoT). The term IoT describes the network of sensors at work in devices of all kinds, from home automation systems to fitness wearables and even industrial robots.

The IoT represented a deepening of the possibilities for data collection and personalization, with new ways to monitor activity and create automated responses. The vast amount of information being exchanged allowed developers to respond to patterns and inputs that were previously difficult to monitor.

Research published in the IEEE Internet of Things Journal describes how the IoB represents an expansion of the ideas behind the IoT. The IoB applies this concept to information generated by a user's interaction patterns within a specific context. IoB-based technology is about understanding those patterns of use and making changes based on the resulting analysis.

The researchers noted that the ultimate goal of an IoB-informed UX is to either predict user behavior or actively influence it. The input from those users' reactions will provide fuel for ever-improving automatic customization.

Musts for IoB development

To enable effective IoB performance, organizations need to rethink the way they're organizing their teams, as well as the priorities they're placing on various systems and functions. Some requirements for putting IoB principles into practice include:

• Multidisciplinary teams: Developing an IoB-informed UX requires a new approach to personnel management. UX designers, engineers and data scientists have to break out of their departmental silos to collaborate on responsive, intelligent end-to-end experiences and data models that allow the targeting of individual users.
• Proliferation of sensors: Generating a nuanced picture of user behavior requires ample input from those users. This means sensors in wearable devices, smart homes, vehicles and more. Smartphones are especially valuable, as they capture everything from location and app interactions to typing patterns.
• High-quality data collection and analysis: The analytics algorithms underlying IoB customization need to be powerful and capable of processing patterns of behavior. Technology including machine learning (ML) is an important element in this process, which needs to focus on analyzing the right data rather than a cache of undifferentiated information.

The IoB can be the key to a new generation of app experiences that react to exactly what users want to see. Understanding and respecting the new requirements that go into creating these experiences are essential steps in making the IoB work.

UX design for solutions with IoB inputs

In practical terms, IoB-based UX design is all about removing guesswork. With the influx of new data generated by everyday user interactions over time and across multiple touchpoints, it's possible to create experiences that are right on target.

Since each user is different, with their own opinions and preferences, UX design must be adaptable and flexible. Serving a hyper-personalized version of a software experience to each individual is a powerful IoB outcome, one that can help users across groups all have positive reactions to a product.

How do developers apply these principles to their UX design practices?

Important concepts include:

• Hyper-personalization: Apps designed from the ground up to be highly reactive are important parts of the IoB ecosystem. This means making major changes to push individuals toward content they'll enjoy. These experiences have already found popular success — for example, the Netflix homepage is entirely based on recommendations based on users' past activity. The content is refreshed often to react to new input and analysis.
• Needs anticipation: In addition to serving a layout based on user data analysis, IoB-powered experiences should also provide answers, tips and suggestions that suit a given user's anticipated path. This prevents frustration and encourages continued, satisfying interactions by creating a smooth, helpful experience.
• Frictionless interaction: IoB data is good for more than just serving up positive experiences for clients. It can also predict points of friction that could derail the user journey. Designers can use this intelligence to remove all potential roadblocks and make sure users have an easy path to all the features they'll most want to use.
• Privacy and consent: There is a potential problem around IoB design: To work, the process requires a constant stream of rich, detailed user data. If users' data is being taken without their consent, or if information is inadvertently revealed or stolen, trust and satisfaction can plummet. IoB designers must be scrupulous about governance, consent and data security. In addition to being IoB-related focus areas, data privacy and protection are common topics of discussion in the design of AI-based experiences.

These design decisions are intimately connected with both data science and development, proving the necessity of multidisciplinary work. Rather than working in isolation, teams need to be united in both the objectives of their IoB efforts and the methods they'll use to achieve them.

Development considerations for IoB-powered solutions

On the development side of the coin, working with IoB data requires a new mindset. Rather than creating one app experience with some customized elements, engineers need to fully internalize the concept of creating applications that are driven, nearly in real-time, by users' activity and preferences.

There is a complexity to working in this new realm, in terms of the data being analyzed as well as the ways that information affects the apps themselves. As long as engineers can embrace this depth of analysis and work with it instead of trying to mitigate it, they're on the right path for IoB solution development.

Specific considerations include:

• Accommodating hyper-personalized frontends: Building applications to support shifting, flexible design is a process that requires engineers' input. The software should have personalization as a fundamental building block, rather than simply letting it be a skin on top of the application.
• Designing data collection methodologies: Data collection is an essential element of development for IoB apps, as the depth of user input available determines the quality of the resulting insights. This process needs to suit the application — for instance, acquiring user data from consumer-facing apps is relatively simple compared to arranging employee data usage in a business-to-business (B2B) context.
• Adopting specific tool sets: Developing apps that take advantage of IoB input requires specialized tools and libraries designed to deal with massive, fast-moving data sets. Fortunately for engineers, these optimized technologies are widely available within the developer community as focusing on hyper-personalization becomes a more common goal.
• Embracing imperfect data: Some of the standard assumptions about the best ways to process user data don't apply to IoB applications. Developers will have to become comfortable using information that is complex, incomplete or otherwise doesn't live up to the standards they're accustomed to. This information, despite its fragmentary and unsorted nature, is the key to IoB hyper-personalization.

The idea behind the IoB is an intuitive evolution of a few trends powering software development — prominently including personalization and the IoT. With that said, creating IoB solutions isn't an automatic process. Designers, developers and data scientists need to unite around a new set of best practices to make the most of this methodology.

Ready to incorporate the Internet of Behaviors into your products?

Rather than just being one branch of UX design, the IoB is poised to become the dominant trend powering the next generation of software. This comes from a desire to serve frictionless, intelligent and highly customized experiences to users. For organizations starting down the path of IoB development, an engagement with third-party experts can provide the transformative power.

If your business is pondering the IoB, Transcenda can help you achieve your aims. Working with Transcenda's experts is a way to quickly add hands-on experience in IoB design and development, while also upskilling your personnel. By learning from the collaborative work, your own designers and engineers can grasp the best practices of the IoB and put that knowledge to work on valuable UX improvements.

‍Contact Transcenda to get started or learn more.