DEFINING THE DIRECTION
The story beings on a treadmill. Headphones on, Lady Gaga blasting. I was racing towards my long term goal of completing a marathon, but for today: 5 miles. After finishing my daily run, I turned my attention to my Apple Watch, hoping to get a better idea of my athletic performance— however, I wasn’t able to view multiple data types simultaneously or in correlation to each other for an accurate overview. In an effort to find out if others felt similarly, I began this case study.
Apple Health users want a comprehensive view of their health and activity but can’t because information is segmented and hard to collectively understand.
I want to pinpoint key opportunities in the Health App’s capacity to:
Efficiently communicate information
Display multiple data sets simultaneously
Create a comprehensive view of health statuses
After doing a bit of research to identify the Health App’s target Audience, I found that its users were segmented into three sectors of the activity scale:
Working to become more active
I utilized in-person interview methods to get a deeper understanding of current pinpoints and opportunity areas. During these sessions, my goal was to gain a better understanding of their current viewpoints.
After investigating users’ experiences, I refined my observations into several key findings to identify the most notable problem spaces. Users expressed that while using the Apple Health app it was:
Difficult to initially understanding visual information
Laborious to compare data sets (too much clicking involved to navigate in and out of separate pages to view separated information)
Hard to gauge goals and progress towards achieving them
Weaving together observations, findings and insights.
Diving into opportunity areas and problem spaces.
Playing with proportions, spacing & low level concepts.
High Fidelity Explorations
Differing opacities show data behind each other
Allows for 2+ data sets to be viewed simultaneously
Color coordination to numerical metrics beneath
Overlapping opacities may be confusing with more than 3 colors
Units to increment scaling may conflict
Highlights progress towards a goal (fostering motivation within the user to achieve it)
Colors correspond to the numerical metrics below to increase
Time of day is not included/shown
Clearly cites numerical metrics
Displays different data in coordination
Deeper the color, the more important to the users
Does not showcase evolution or changes over time
Could get confusing if too many data types are added
Familiar; similar to current interface
Color coordination to metrics below reinforce clarity
Displays changes in activity effectively
Bars may disappear below each other
Confusion increases with the addition of more data
Screen may be overwhelming (and therefore unreadable) if too many data sets are included.
Displays two correlated sets of data
Shows differing intensities over time
Focused on evolution of data instead of increments
No way to see data if back set is below the front
Differing units may not fit on the same incremental scale (on the right side)
Apple Watch experimentations
Shows visual indicator of progress
Integrates into current visual aesthetic
Opaque bars indicate progress towards goals designated by the bars of lower opacity
Numerical percentages to reinforce exact status
No gauge of progress distribution over time
Simultaneously displays multiple data sets (color coordinated)
Displays activity/data progression over time
Ineffective given spacial constraints
Clear percentages towards goals to illustrate users’s progress
Colors correspond to specific data types
Readability issues due to small labels
Time-related information not included
Efficient readability of percentage metrics
Clear focus on current information type
Singularly shows one set of data
Visual representation of progress in real time
Color coordination to data types
No solution to the case of the user achieving their goal by over 100%
Opaque bar overlaying a bar of reduced opacity to indicate advancement towards goal as a motivator
No exact metrics
Activity-time relationship not incorperated
By doing this case study, I learned how to create screens for comprehensive data visualization. The biggest challenge of this was to find a balance between readability and clarity while combining different types of information. Upon reflection, I would like to have done a deeper dive into researching the most popular types of information to the three main user types (active, becoming active, non-active). In the future, I hope to explore more dynamic ways to show health data in real time; using animations and other interactive systems.
Thanks for reading! 💓