Wearable Device Companion Mobile App

Project Description

Note: Basis was acquired by Intel. This project sought to create a more useful companion app to the Basis Peak fitness wearable device.  The current app collected incredibly accurate data, but customers were having difficulty making sense of how their data could best be used to facilitate behavioural changes.

Project Details

Client: Intel (Formerly Basis)
Role: User and Market Research, UX, UI, User Testing, Design Management


Information is accurate but not actionable.
The Basis Peak device is one of the most accurate on the market. When it comes to the companion app however, users have difficulty understanding the data and harnessing it for growth.

Who is Maria?

Through analyzing current and future sales projections in the wearables sector – our business analysts honed in on our target demographic.

  • Maria is a 29 year old Customer Service Team Leader.

  • She lives with her boyfriend and 6 month old in Austin, TX.

  • Their household income is $75K.

  • She recently finished her degree and has a 9-5 job.

  • She enjoys moving once she can get motivated.

I don’t know how sleep relates to the amount of exercise I’m getting, I feel like exercise has a negative impact on my sleep.

I want to be informed of my progress & acheivements.

I think really the big thing is schedule and then just being tired after work and not setting aside time for it. And I think that’s why I opted with doing the trainer, things like that, because I wanted structure because I wasn’t very good at being accountable, like finding times to exercise when I had other stressors.

I want to be educated to help me improve my sleep, stress, rest, diet and activity (incl. exercise) patterns.

Maria’s Activities

  • WALKING 100% 100%
  • HIKING 45% 45%
  • SWIMMING 33% 33%
  • CYCLING 33% 33%

Reasons Maria Exercises

  • LOSE WEIGHT 50% 50%
  • FEEL STRONG 30% 30%


  • TOO TIRED 39% 39%
  • DOESN’T FEEL LIKE IT 34% 34%
  • LACK OF TIME 28% 28%

What Patterns Form Habits?

Our team researched strategies of coaches and behavioral scientists to better understand what factors and behaviors lead to habit formation and goal achievement.

Our most influential takeaways were:

Tiny tiny goals

Running a 5K is hard. Running for 2 minutes is more manageable. A tiny goal can present a smaller barrier to getting started. Once you’ve started, you are often likely to go a little further. The low starting threshold helps get started. Little successes breed confidence!

Understand your underlying motivation

What will accomplishing your goal signify or satisfy within you? What will the absence of that mean?

Fit your goal into your regular routine

Get off the train one stop early, park a few block further away from your destination, do your yoga while you watch nightly TV. Fitting goals into your regular daily structure results in a higher percent of adoption.

Just 2 weeks

Experts disagree on the time needed – but if you can do the new habit consistently for 2 weeks, it is statistically more likely to stick.


Brainstorming Maria

In brainstorming the dashboard, we quickly realized our dashboard objectives were becoming too broad, trying to hit all Maria’s needs in one place. Our ideas were lacking direction and glanceability.

Maria needs to understand her overall wellness in a context relatable to her, see how her biometric inputs are effecting this, and be presented with appropriate actions based on her wellness and preferences.

App Purpose Redefined

Always answer for the user:  “Where am I? Where can I go? How can I get there?”

Numbers alone don’t drive change. Data must have context, goals must be personal and attainable, and insights actionable and relevent. We aim to link sleep, stress and physical activity as equal contibutors to overall wellness.

Guiding Principles: Simplicity, Clarity and Actionability

Design for action

Data is visualized with narrative and provides the insight needed to create actionable goals.

Provide Context

Context is provided by relating your data to personal and demographical averages, or other familiar paradigms.

Design for the frequency and immediacy

Design for short bursts of interaction. The app is glanceable and provides immediate details and intuitive navigation.

Directly address the user’s needs.

The interface puts the user’s needs and habits at its core. It is designed to learn their desires, motivations and limitations – and gives them options to customize their experience whenever possible.

Clarity and insight

Simplicity and clarity are prioritized in data visualization.

Mental Model

This  model follows the user’s thought cycle as they understand their motivations, assess their status, and plan/analyze/iterate their behavior to improve performance.The interactions in the interface will assist the user through this process.


Translating Desires and Motivations into actionable steps

This is a small sample of the larger list of features we brainstormed to address Maria’s needs and desires

Mapping the App

App Mapping