They say everyone’s favorite thing to hear is their own name. That’s why sales people are trained to learn your name quickly and use it a few times in conversation, to build rapport and trust. 

Emails and websites use your name to show they recognize who you are and to give a sense of personalization. And it generally works, even though anyone who spends more than a few seconds to think about it knows their name is just a variable in a highly automated or programmatic system, and it’s not really hand-written just to them. Regardless, simple personalizations do have the desired effect. 

In our work, we think about a deeper level of personalization, pushing beyond the superficial things like showing your name and photo. We like to think about putting the content or features you care about most up front, and moving the stuff you don’t care about out of immediate view. We see social media platforms do this all the time with content, but what about with features and functionality of an application?

Adaptive UIs create a more focused and tailored experience, enabling people to accomplish the tasks they care about with less friction. One project we’re working on is focused on customizing the UI of the app to the person using it, dynamically. We know who logged in, we look at their role in the organization, and can analyze their previous work to understand which parts of the application they use and make those more prominent next time they log in. It’s a learning interface that gets more useful the more you use it. This isn’t new tech. We did it in the software we built at my previous company, too. While it’s not a new concept, it is relatively rare to see in the wild, and that’s because it’s hard to do.

Modern AI and ML algorithms are changing that. Combined with the available computing power these days it’s much easier to analyze and act on vast amounts of data and make adaptive experiences as a result.

McKinsey is (unsurprisingly) looking at this, too. In a recent article, they start to explore how AI/ML are changing the face of current products and services and creating opportunities for things we hadn’t previously thought possible. 

Empathy—the ability to relate to and understand another person’s emotions—is the basis of strong relationships. Understanding social cues and adapting to them is how people build trust. That’s not easy to do digitally or at scale.

Machine learning is changing that, or at least getting much better at reading and reacting to emotional cues. More sophisticated algorithms are allowing programs to interpret new kinds of data (visual, auditory) and extrapolate emotions much more effectively than in the past. Amazon has patented new features that will enable its Echo device to detect when someone is ill—such as nasal tones that indicate a stuffed nose. It will then offer a suitable recommendation, such as a chicken-soup recipe or cough drops, some of which could then be purchased over the device for at-home delivery.

This is fascinating, and a little creepy, but the creepy feeling will fade with time just as it has with the concept of a little hockey puck listening to everything you say (I see you, Alexa).

Obviously, this has far-reaching implications. It will most likely be exploited by marketers first, then once the economies of scale make it more affordable, you’ll start to see apps and services using more adaptive UI in an effort to make you more comfortable using them (and loyal to the platform).

As you’re thinking about your products and services, what kind of small personalizations or customizations could you offer that would elevate the experience? Is it rearranging the navigation, or placement of different information on a dashboard, maybe changing the steps in a workflow for people with high proficiency? AI and ML will undoubtedly change the way we build interfaces. Will your company take advantage of it, or be taken advantage of by the competition?