Ai Nutrition Tracker
This project focuses on designing a fitness tracker app with a strong emphasis on AI-powered nutrition tracking.
Role
UX Research
Tools
Figma | FigJam
Challenge
Problem
Users find existing fitness apps complicated, time-consuming, and overwhelming — especially for nutrition tracking.
Project Goal
Design a mobile app that seamlessly combines fitness tracking and nutrition logging into one easy-to-use, motivating system that helps users stay on track despite busy schedules and everyday stress.
Methods
1. Research
Methods: Competitor analysis (8 apps), online survey (n=52), 6 in-depth interviewsPurpose: Understand user needs, pain points, and market standards
2. Synthesis
Methods: Affinity mapping, persona development, user journey mappingPurpose: Structure insights, define the core user
3. Ideation
Methods: How-Might-We questions, brainstorming, feature prioritizationPurpose: Develop solution concepts
4. Design
Methods: Wireframes, prototyping in Figma, 2 feedback roundsPurpose: Test and refine usability
5. Validation
Methods: Usability testing (5 participants), UX writing optimizationPurpose: Remove usage barriers, improve clarity and tone of voice
Key Findings
74%
cited lack of time as their biggest challenge.
68%
wanted faster meal logging (photo/barcode scan).
63%
said gamification (badges, challenges) would boost motivation.
56%
already use wearables but complained about poor integration.
Results
- Developed a functional mid-fidelity prototype with optimized navigation and tracking flow
- 80% faster meal logging in usability tests
- +30% increase in motivation score compared to baseline
- Positive feedback on clarity, speed, and enjoyment of use
