IN DEVELOPMENT
FITRADIO AI Mood
FITRADIO is a top performing mobile fitness app with millions of daily users, they offer innovative DJ-curated workout mixes, audio-guided workouts, tempo-matching technology, and much more.
Challenges
FITRADIO users are struggling to navigate an overwhelming selection of workout categories and types, making it challenging to quickly find a mix that matches their mood and activity. This ongoing issue is impacting user satisfaction and engagement.
My Role & Collaboration
I collaborated with FITRADIO to create their first AI-powered feature, AI Mood Mix, which aims to enhance user engagement by delivering personalized workout mixes based on the users current mood, activity, and genre preferences. This feature combines FITRADIO’s DJ expertise with AI to streamline the mix selection process, helping users quickly find the perfect soundtrack to elevate their workout experience.
Research
I researched several competitors including Spotify, Endel, Chosic, and others to compare their AI-generated features with FITRADIO’s AI MIX. I examined user customization, playlist creation, and the overall experience. This helped highlight FITRADIO’s unique strengths and inspired future improvements.
Optimizing User Flows
To better understand how users interact with the AI experience, I mapped a high-level user flow highlighting key decisions and system behavior.
The feature uses two AI layers:
A tag-based recommendation engine to surface content based on user input
A machine learning model that personalizes results by learning from user actions and behavior over time
Integrating AI Mood into the existing player
I designed several exploratory concepts to integrate the new AI features into the existing player screen. The challenge was to enhance functionality without straying too far from the current experience, ensuring it remained intuitive for users.
Hi Fidelity Designs
A/B Testing the entry point
I conducted an A/B test to determine the best placement for the entry point, ensuring users could easily discover the feature. After testing, the navigation bar achieved a 12% adoption rate, demonstrating the highest level of user engagement.
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