Elevating Apple Health with Intuitive Data Visualizations for Wellness Insights
As a student specializing in data analytics & visualization with a background in product design, I am constantly seeking ways to integrate my skill sets in my projects. I’ve also observed significant overlaps in methodologies and principles between the two disciplines.
In a recent project, I actively searched for companies that highlighted the synergy of product design, data analytics, and data visualization in their job postings. During this search, I came across an enticing job listing at Apple, specifically seeking a data visualization specialist for one of their product design teams.
Upon reading the responsibilities and competencies outlined for this role and aligning them with the metrics and guidelines for my final project, I recognized a fitting opportunity. Considering both the company’s expectations and my personal objectives, I decided to focus in on one of their flagship products, and channel my efforts into enhancing data visualizations within Apple’s Native Health Application for mobile.
With a clear vision of my personal and professional goals, I eagerly entered the research phase, driven to develop a project that not only aligns with my interests but also serves as a new and exciting endeavor for me to undertake.
Data-Driven Design Framework
I crafted a data-driven design framework to seamlessly merge methodologies from both disciplines into my workflow.
The initial phase involved discovery, where I delved into understanding user needs and data insights. Following that, the analysis and synthesis phase aimed to transform those user and data insights into tangible design goals. Moving into the ideation phase, I translated these goals into low-fidelity wireframes and concepts.
Transitioning to the design refinement stage, I integrated user feedback and data considerations, incorporating user testing into my workflow. The final phase centered on the implementation plan, where I bridged design and technical considerations to create a high-fidelity prototype showcasing improvements to Apple’s Health application features. Towards the conclusion, I will reflect on the project and discuss future areas of focus and development.
Discovery:
I embarked on two distinct research approaches to kick off the research phase. First, I conducted a survey targeting individuals using health and fitness apps, seeking insights into their preferences, usage patterns, and expectations from these applications. Simultaneously, I manually analyzed reviews, focusing specifically on one and two-star ratings from the past year and a half sourced from the Apple App Store. This qualitative examination aimed to uncover the specific challenges faced by Apple’s Health application users as expressed in their reviews on the platform.
For the survey, I employed survey creation tools to generate and collect data. I used a combination of manual methods and software to consolidate and extract information from the reviews. Initially, I captured screenshots from the App Store. Subsequently, I leveraged Apple’s optical character recognition (OCR) feature to extract text from images. This allowed me to transfer the reviews (text) to an Excel sheet where I compiled all the critical feedback for Apple’s Health application. By cross-referencing both datasets, derived from surveys and App Store reviews, I aimed to identify areas for improvement through a comprehensive analysis.
Analysis and Synthesis:
Numerous Apple Health users and participants in my survey expressed similar concerns. Synthesizing this feedback revealed a common desire among users to have more control over the visualizations they encounter, emphasizing the importance of customizable graphs. A prominent issue with the Apple Health application was the absence of a standardized dashboard, resulting in scattered information that varied for each user, depending on the data collection settings. Users found the multitude of features overwhelming, particularly the inclusion of irrelevant blogs and third-party app extensions that consumed valuable space and were seldom used.
Additionally, users reported that the application was cumbersome and challenging to navigate, given the abundance of data and difficulty in locating specific features. An interesting observation was the difficulty some users faced in comprehending graphs, indicating a need for more user-friendly and straightforward visualizations. This insight highlighted the diversity in users’ proficiency in interpreting complex visual data.
Ultimately, users experiencing challenges with the application sought alternatives to fulfill their needs, often resorting to other applications or managing their health data through multiple platforms.
Ideation:
Following my analysis and synthesis phase, I delved into the ideation stage, creating diverse personas based on the insights gleaned from the data. Recognizing the challenge of fitting everyone into a single category, I crafted three distinct personas representing different types of individuals commonly using health applications.
Meet Sarah, an avid marathon runner. She relies on health apps to monitor fitness goals, track biometrics, and ensure proper training. Individuals like Sarah are meticulous about tracking various metrics consistently throughout the day, prioritizing their health and fitness goals by diligently inputting relevant information.
Next is Alex, a regular health tracker who may have a couple of other fitness applications. Unlike Sarah, Alex checks the Apple Health app once or twice a day, primarily to assess sleep patterns and daily step counts. While Alex may not have specific goals, periodic app use reflects a subtle awareness of personal well-being, with the potential to engage more consistently in the future.
Lastly, we have Angie, a casual user who may not be aware of the app’s existence. She might stumble upon it occasionally and check her statistics from time to time. However, complex data and visualizations could pose a challenge for Angie, leading her to find the app less helpful or potentially too intricate to understand. This complexity may deter Angie, unfamiliar with extensive data and visualizations, from utilizing the app regularly.
To prioritize metrics, I focus on understanding specific health preferences of personas. By grasping user needs and data significance, I create visualizations catering to diverse individuals for a consistent experience.
Bar graphs, pie charts, and line charts stand out as the most prevalent and universally recognized visual aids, equipped with labels for enhanced accessibility, ensuring a straightforward user experience. Empathetic design for diverse skills is imperative to maintain consistency across a broad user spectrum.
User challengrs:
Here’s the initial experience when you open the Apple Health application. The first screen displays a summary of your health data, showcasing information you manually inputted or automatically gathered from your phone. You can click “Show All Health Data” to explore various metrics or choose “Show Health Trends” at the bottom. The navigation bar lets you view health stats, share data, or explore reblogs and third-party applications. For my iteration, I decided I’ll focus on the starting dashboard and the sleep metric.
Clicking on the “sleep” metric provides a week overview. The top section of the screen offers a toggle for day, week, month, or six months, along with displaying time in bed on the right axis using a stacked bar chart. Apple uses this visualization to depict when you’re in bed or sleeping, with different metrics for light and deep sleep. The bottom axis covers the last seven days, with an option to view more sleep data. Users can manually add data or adjust alarms and schedules as they scroll down.
The toggle option on top lets users choose the timeframe. All graphs are histograms with vertical bars, except for the current day visualization, which is a horizontal single bar chart. Colors remain consistent for day, week, month, and six months. Understanding daily sleep hours is challenging, requiring users to click on each bar for details. Many reviewers expressed frustration about the inability to zoom in on graphs, indicating a need for more detailed insights not provided by the initial display.
Now, continuing on with the ideation concept phase, my next goal was to identify opportunities from Apple’s competitors. I explored the App Store to discover popular health and fitness applications, focusing on the top six with features similar to Apple’s Health app. Drawing inspiration, I contemplated certain features to enhance Apple’s application. Additionally, I adhered to Apple’s design system and human interface guidelines while designing and updating the current app.
In consideration of similar applications featuring dashboards, graphs, and visual-based metrics, I began creating low-fidelity wireframes for the main dashboard. I started with four options: a 3x4 grid, rectangles in a row, 2x3 larger squares, and a mix of differently sized rectangles and squares. As I worked on these wireframes, I dropped the first design, realizing it would overwhelm users. The three remaining designs allowed for both visualizations and metrics, catering to different preferences.
Continuing with high-fidelity wireframes, I integrated insights from user surveys and reviews. These designs were tailored to suit the preferences of each persona, with an ideal scenario allowing users the flexibility to customize dashboards for both creativity and personalized data viewing. I created three different versions of what the initial dashboard could look like.
The left design caters to someone like Angie, who prefers a quick and straightforward glance at a few key stats without delving deep into health data. It provides an overview of essential metrics such as sleep and steps. The middle design is geared towards Sarah, providing a comprehensive snapshot of all crucial metrics with a single click, including finer details like sleep duration, bedtime, changes in sleep patterns, and the commencement of physical activities. The right design suits Alex, offering a visually engaging interface with pertinent information, avoiding information overload.
In my updated dashboard design, once a user clicks on the apple health application, they encounter their standard dashboard. This is advantageous because users won’t need to navigate elsewhere to access additional information. On the homepage, they can swiftly view metrics such as sleep duration, steps, state of mind, mood, active energy, calories burned, blood oxygen levels, and walking speed. This streamlined approach allows for a quick and effortless overview. The design incorporates a visual hierarchy, ensuring that all essential metrics are presented in the initial dashboard, fulfilling the needs of all three personas with the necessary information.
Moving on to the sleep metric, the current setup involves visualizations utilizing stacked bar charts, depicting details such as time spent in bed and time asleep. Applying consistent design principles and insights gained earlier, coupled with features observed in high-performing apps, I developed an enhanced version of the sleep mode.
In my redesigned version, users now have the convenience of encountering only two primary visuals. The first screen offers a comprehensive view of daily and weekly sleep metrics, while the second screen delves into the monthly sleep data. This streamlined approach provides users with the necessary information in a clear and user-friendly manner.
Let’s explore the before-and-after versions and discuss the modifications I’ve implemented, taking into account factors such as hierarchy, color schemes, and metrics. I made adjustments like enlarging and bringing the sleep section to the forefront, placing the data button in close proximity for a seamless transition. In response to user feedback, I updated the visualization, incorporating familiar graphs and designs, including a calendar view that starts from the beginning of the week for a cleaner representation.
Now, with just a glance, users can easily see their daily and weekly sleep durations. The graph illustrates sleep start and end times, adopting both Z and F reading patterns for quick and effortless data interpretation. Average metrics are conveniently positioned beneath the graph for those who prefer textual interpretation. This design eliminates the need to click on individual bars or zoom in, providing users with all the necessary information at a glance. Additionally, users can set sleep goals, enhancing inclusivity by allowing them to access vital information without scrolling, zooming, or unnecessary clicks.
The next design focuses on the monthly sleep metrics, featuring a calendar format that is both easily recognizable and aesthetically pleasing. This design choice adds a pleasant touch and enhances user experience, leveraging the universal familiarity of calendar formats displaying days of the week. Users can effortlessly track their monthly sleep duration at a glance, aided by a color-coded legend for each day.
Additionally, this design incorporates statistics and numerical data, enabling users to discern the frequency of various sleep durations throughout the month. A quick overview reveals specific patterns, such as three days with 11+ hours of sleep, one day with 0 to 4 hours of sleep, and the majority of the month with 8 to 10 hours of sleep daily. The bottom bar visually represents the percentage distribution of sleep durations, offering comprehensive insights.
To further enhance usability, an average sleep duration for the entire month is provided, and users can easily toggle between different durations by clicking on the month. This one-screen solution empowers users to grasp multiple insights effortlessly, eliminating the need for scrolling, extra clicks, or zooming in on graphs.
These serve as my final designs for the revamped Apple Health main dashboard and sleep metrics. The aim was to elevate user experience by offering a visually appealing, user-friendly interface that caters to diverse preferences and needs.
I streamlined the initial homepage, introducing a standardized, easily digestible dashboard that users can personalize to their liking. A quick glance provides all the essential information, and I reoriented x and y axes to align with familiar graph standards, enhancing readability.
Additionally, I integrated average metrics, showcasing daily sleep duration, start times, and total hours on a single screen, eliminating the need for scrolling, zooming, or additional clicks. The month graph, utilizing a calendar layout, employs color-coded days for a clean design. Starting with a traditional week and day structure, users can easily interpret the hours slept per day. A legend accompanies the calendar, offering a quick reference, and metrics at the bottom provide an overview of average sleep time during the month of December.
Looking ahead to future endeavors, I am enthusiastic about the ongoing development of this project. My plans involve continual refinement and the introduction of new designs tailored to various health metrics. User testing will be a crucial step to identify potential enhancements based on real-world interactions.
I envision incorporating customization features, allowing users to personalize visualizations to their preferences. This not only fosters engagement but also serves as a motivational tool. Exploring social integration and the idea of users sharing their customized visualizations on social media platforms with friends adds a layer of community and motivation to the application.
