With knowledge, comes power. In an age of sensors, smartphones and big data, it’s possible for people to gain more knowledge about themselves than ever before to improve their lives. However, the growing self-tracking industry has no clear industry winners yet; the devices that will come out on top are the ones that best meet the needs of real people. The next generation of self-tracking devices will support meaningful and positive impact by pushing and aligning the technological possibilities, business implications and user needs.
A Golden Age of Self-Tracking
Since the first Fitbit tracker was released in 2009, startups and large corporations alike have developed devices, apps and wearables. With the Apple Watch and Health app announcements in September 2014, Apple becomes the latest entrant to the health-focused, self-tracking device industry.
Research shows that these devices offer a “one-size fits all” solution focused on a narrow set of health metrics. But, trackers have unique personal attitudes about self-tracking, and technology is broadening what can be tracked. The right self-tracking device tailored to a tracker’s mode of tracking encourages adoption and generates more meaningful insights.
My team and I designed Links for target-focused self-trackers. Links is a tracking platform comprised of a customizable, modular band with individual sensors and informational “links” that track progress and offer suggestions that help users achieve their goals. I am currently in the progress of developing interactive wireframes and a visual design for the mobile Links app.
The Journey to Links
This project built on top of previous research and my team’s task was to synthesize those learnings in a robust solution. Our process was deeply focused on articulating new user flows and solution scenarios.
Documenting the Self-Tracking Landscape
I had never tracked my steps or calories, even though I was well aware of the 10,000 step goal and calorie consumption goal of 1,200 (or was it 2,000?) calories. To begin my tracker immersion, I wore a Nike Fuelband and Lark, experimented with health and fitness apps, and digested any media stories I could find. It was quickly apparent how similar all the consumer devices and apps seemed. Most devices had limited functions, relied on the same activity and sleep metrics, and looked like sporty medical devices. Data analysis was difficult because only a third-party apps made it possible to review multiple data streams at once.
Articulating User Needs
In previous work with the self-tracking community, IIT Institute of Design students identified four user modes of self-tracking: target-focused, performance-seeking, life mission, and experimenting. My team and I analyzed this research for design principles that could guide our solution tailored for target-focused trackers.
We learned that target-focused trackers aim for key numerical targets as a means of achieving their goals; such as, defining their active lifestyle by achieving a daily goal of 10,000 steps. These trackers typically begin tracking health-related goals with one or two tracking devices, focusing on metrics that they know the devices can easily manage. Target-focused trackers aren’t interested in lengthy setup processes or manual data entry because tracking is a means to an desired end result; trackers don’t draw joy from the process of self-tracking.
Pain Points in the Self-Tracking Journey
In the process of selecting a device, tracking metrics and achieving goals, we saw many opportunities for failure. At the time of our research, current solutions did little to keep target-focused users on the right track.
- Target-oriented trackers focus only on the metrics that they can easily track, thereby ignoring metrics that might have a significant impact in reaching their goal. If they can’t track it, they can’t change it.
- Trackers are deterred from tracking if setup, data syncing, or tracking itself takes a considerable amount of time. They won’t track manually, tackle technical issues or take time away from their families or careers to track.
- Data visualizations are limited to trends and medals, encouraging trackers to focus solely on the numbers and not on overall trends or behavioral context.
- If there’s no progress in the bigger goal, tracking might be seen as pointless. If users reach their daily step counts, but don’t lose weight, they may lose all incentive to track or change their behavior.
Design Principles for Target-Focused Trackers
One of the most important design attributes of a self-tracking system is a clear relationship between goals, sub goals and tactics that self-trackers set to achieve success. For example, target-focused trackers focus on their calories consumed and weight in order to institute a habit of eating less. By committing to a habit of eating less, these trackers feel closer to achieving their big goal of losing weight. Daily metrics represent the tactics that target-focused trackers use to measure their habits. These habits, or sub goals, work together to support a overall vision, or big goal, that trackers are trying to achieve.
While numerical targets motivate target-focused trackers, current devices encouraged a piece-meal approach and short-term goals. My team and I believe that any future device should encourage trackers to take a long view toward healthy living. Devices should encourage a shift from reaching 10,000 steps every day to achieving behaviors that are part of an active life. These future designs must also:
- Provide a way to track multiple goals at once.
- Show data dependencies as they support goals at multiple levels.
- Support the need to see quantifiable metrics while encouraging a more holistic view.
- Encourage daily use by integrating the device into day-to-day activities.
- Offer meaningful and actionable advice at key moments.
Because goal-focused trackers have such a tenuous relationships with tracking devices, it’s important that a future solution offers goal customization, data sharing, automation, meaningful notifications, future-proofing and fashion. By making it easy to reach for bigger goals, these devices could encourage usage and progress.
Links: A Customizable Self-Tracking Platform
Our final solution, Links, is a tracking system that users customize to their goals. Links combines modular sensors and informational “links” on a wearable chain with a companion mobile app for deep data analysis.
The Links platform is comprised of sensor “links” that track and notify trackers of related metric clusters. These sensor links can be purchased individually and assembled into sets on the wearable band. Via the band’s embedded screen, trackers can view metric progress, alerts and receive tips. Links provide alerts through a unique interaction language featuring unique vibration patterns and LEDs.
The companion mobile app provides rich data visualizations that callout suggestions, tips and data insights; trackers can review individual data sets or combine diverse data types into a single visualization. Tips provide their own context, referencing commonly accepted scientific research as justification for the recommendations.
Shopping Experience and App Wireframes
To visualize the user flow through the mobile native app, I brainstormed multiple wireframes for each key screen or screen flow. Wireframes circled in red represent my initial hypothesis of a user flow and screen layout; these choices were made based on considerations and limitations of screen real estate, a prioritization of tips and at-a-glance interpretations of link metrics, and an aim to streamline processes on a mobile device.
Wireframes designated in red are currently being developed as Axure interactive wireframes.
A Robust System
In order to support the diversity of goals and technological knowledge, trackers might purchase Links at staffed retail spaces, kiosks and online. At retail spaces, staff could provide support in selecting Links for achieving the trackers goals; the kiosk and online store would provide ways of selecting Links or advising trackers’ on their goals. The draft service blueprint below reveals some of the complexity to supporting this multi-channel tracking solution for positive, long-term behavior change.