Foodie Buddy
A personalized dining assistant for optimizing dietary decision-making
UX solution that utilizes a conversational agent and user data logging to provide highly personalized and balanced food recommendations in real-time dining scenarios.
Role
Product Manager
Visual Designer
Team
1 Product Designer
1 UX Researcher
Timeline
Sep 23 - Dec 23
Problem
Restaurant diners frequently make impulsive or uninformed food choices
due to the overwhelming effort required to analyze menu options
Opportunity
How might we help diners make faster, better decisions?
Generic menu information fails to integrate personalized factors such as specific nutrient deficiencies, dietary restrictions and preferences, or current emotional state (mood) into on-the-fly food recommendations.
Solution
A holistic, multi-phase experience granting diners control via continuous data recording and personalized recommendations
Personalization is initiated before eating via recording details and matching preferences for recommendations. Transparency is achieved during eating with automatic nutritional tracking. Finally, the after eating phase captures essential feedback, refining the system for improved Supervision in the next dining choice.
– Research breakdown –
Research insights
Qualitative interviews and synthesis defined the user's "Desire vs. Effort" gap
Initial interviews confirmed that while users want healthy diets, they are constrained by the limited time and willingness to personally manage their complex eating habits. Further generative research identified the critical need for a personalized system providing known ingredient details and better control, validating the core solution pillars of Personalization, Transparency, and Supervision.
Interview Affinity Diagram
Generative Study
User Flow Storyboard
ui revamp
After the project finished, I personally further developed the branding for “Foodie Buddy” because I felt a missing connection between making this application more approachable for our target users.
