A fitness app that uses AI to pull stats from a user's fitness tracker and recommends workouts based on their needs.

UI/UX Designer & Researcher

Ideation

Design

Hi-Fis

Prototyping

Reflection

RaringTrainer is an innovative fitness application that caters to users of all levels, leveraging artificial intelligence to curate personalized daily regimens based on their physical stats and self-reported well-being.

The project focused on the challenge of interpreting and utilizing fitness tracker data for users who workout and use fitness apps. Users often find themselves overwhelmed with the raw data collected by their devices, uncertain about how to turn these statistics into actionable insights.

The main problem lies in making the data understandable and beneficial for achieving their fitness goals, with a particular interest in exploring how artificial intelligence can enhance this process.

RaringTrainer's design system was already in place, and I enhanced it by adding a few components, variants, colors, and features. I also followed their established user flows:

"AI Recommendations" for low-intensity workouts

"AI Recommendations" for high-intensity workouts

"Pair a Third Party Application" where users can connect any tracker to the app and customize the data for AI

The goal was to leverage artificial intelligence to help users make sense of their collected data, enabling them to make informed decisions about their fitness routines and achieve their health goals. To achieve this, I adapted high-fidelity designs based on the existing screens and developed a prototype for each flow. I created distinct styles for the two AI prompts so users could easily identify whether they were getting low or high-intensity workout recommendations.

I was given all three user stories as part of the project. The user stories helped me focus on what the app was missing and reflect the users' needs:

Pair with a Third Party Application. When the user wants to connect a third-party app like Fitbit or Oura Ring to RaringTrainer and choose which information they'd like to share.

AI Recommendation for High-Intensity Workouts. Based on your stats for the day, if AI pulls the user's data and believes they have high energy and the power for an intense workout, it will suggest those types of exercises to the user.

AI Recommendation for Low-Intensity Workouts. When AI pulls the user's data and it senses they need a recovery day, it will suggest lighter workouts

For the "AI Recommendations" user flows, I introduced new colors to make them stand out from the existing grey and teal palette. I wanted these colors to reflect the energy of each flow. For high-intensity workouts, I chose light and dark yellow to evoke positivity, energy, and enthusiasm. The low-intensity flow got a light and dark purple treatment, bringing a sense of calm, focus, and thoughtfulness. The client requested new components, buttons, and category boxes to highlight these AI prompts with their fresh color schemes.

To allow users to choose which data they want to share, I created toggle switches for the settings. These additions not only improved functionality but also maintained visual consistency throughout the app.

For this flow, I built upon the existing high-fidelity designs by incorporating new AI elements. When a user's data indicates high energy levels, the app greets them with "Fittz" (AI-powered notifications) upon opening. This greeting includes a higher Workout Power Score and more strenuous workouts highlighted in bright yellow to match the user's elevated energy levels.

Fittz goes beyond just notifications; it intelligently highlights suggested workouts based on the user's current stats, encouraging them to capitalize on their high energy. More challenging exercises, such as HIIT, cardio, and weight training, are prominently featured. The vibrant yellow color scheme reflects the intensity and vigor behind these workouts, creating a visual cue that aligns with the user's energetic state.

I designed a series of high-fidelity screens to illustrate the process of pairing RaringTrainer with an Oura Ring, which serves as an example for connecting any third-party app. The flow was crafted to be familiar and efficient, minimizing user drop-off and overwhelm.

As opposed to starting from scratch, designing within an existing brand framework required a balance between innovation and brand consistency.