*This version is edited. If you'd like to check out the full case study, please check it out on my Medium page.
EXPLORING A PROBLEM SPACE
Tracking our golf game statistically is normal. If you've been playing steadily for a few years, you'll eventually want to start tracking your stats during outings on the golf course. It's one thing you can do to improve your game along with improving your swing. You can track things like fairways hit, greens-in-regulation, and putts. As a human-centered design exercise, and with the help of General Assembly's UX design course, I set out to see if I can learn and build at the same time.
BY THE NUMBERS
The U.S. golf economy is worth an estimated $70 billion, and the equipment segment is about $3.4 billion. 'Game improvement' is a growing segment within the training aids category. Stat-tracking is one of the growing categories, and it seems ripe for the taking. This has created an ecosystem of products that miss the point of the category, but the bigger issue is that users end up settling for half-baked products.
Currently, the market is flooded with seemingly ‘useful’ stat tracking products and websites for golfers. The categories break down to:
A stand-alone product — A hardware with built-in GPS tracking, added features to keep your score, and few stat-tracking features. Popular for GPS functionality. Can connect with a dedicated website and gives you dashboards of records.
App — Via smartphone. It’s similar to a standalone device, utilizing the phone’s GPS functionality as well as keeping your scores and your stats.
Website — Mostly used by golfers who track their scores and stats. Typically accessed after their day on the course.
A spreadsheet — Many golfers track their statistics by manually recording their scores and stats by using spreadsheets, then break them down manually.
Studious golfers have no access to insightful data to improve their game.
By giving golfers access to enhanced information through machine learning, they will gain insightful information from their data. We will know this to be true when we see the app and the website being used by golfers of all levels (high and low handicappers).
FINDINGS FROM THE INTERVIEWS
After surveying six golfers and four phone interviews, I grouped the data into specific categories, informed specific feelings and pain points about the end users. Certain patterns did emerge:
Better players were seeking better information for specific categories. In order to eliminate mistakes and tendencies, they need to know specific data about their game. Without this information it feels like a waste of time.
Create an ecosystem where golfers can analyze their statistics easily with a digestible overview, and pair it with detailed statistics where insights are displayed and discovered.
The objective for the user is to be able to track their stats right away without initial onboarding. It is essential that the app starts logging the user's rounds quickly, and with repetition, the user will accumulate their rounds on the app.
The IA works on both the desktop version of the site and the native mobile version to maintain consistency. Any additional pages in the future can easily scale pending on expansion.
SKETCHES + IDEATION
Wireframes were built for both the native app on mobile and for desktop website. The result of the exercise was to focus first on users tracking their scores and stats on the mobile app. This allows the user and the app to collect data. If we onboard the users with effective round tracking capabilities, they will naturally want to look at the statistics, all of which informed the features to be prioritized.
The mid-fidelity prototype further refined our focus on visual representations of the user's statistics and how a user inputs data (magenta) for a round of golf (left). By using card-style navigation, we establish design consistency. Overview (middle) information is meant for a glance with minimal input, while for detailed statistics (right) there are more filters.
A consistent design system keeps the user engaged with familiar icons and visualizations, and puts only the necessary information and input options for each section. The card system seems to be useful and preferred during usability testing.
Colors play an important role in establishing the functionalities of each sections. By separating each sections into its own color family, we established familiarity of those sections and diffused any confusion that may be created.
Let's go back to the beginning. We wanted to solve a problem for golfers: Improve their golf game more effectively.
Providing one place to track their scores and statistics seamlessly through the entire game minimizes the golfer's use of multiple products.
By displaying their statistics in a visually digestible way, we enhance the experience and eliminate multiple information touch-point clutter.
By using machine learning to provide complicated information to remember, we give golfers the advantage of improving their golf game by maximizing the information provided.
NEXT STEPS: MORE TESTING
With a small set of testing and user feedback more testing is necessary, and further refinement is essential in improving the experience, both on and off the course. Initial testing indicated further clarity in information, and the colors seem to confuse general users.
TO BE CONTINUED...