FoodCourt
AI-Driven Meal Plans for Healthier Living
ROLE
Lead Product Designer
TEAM
Product Manager, Business Analyst
DELIVERABLES
UX Research, User Flows, High Fidelity Design, Design System
Defining the Problem
Numerous Nigerians, particularly health-conscious individuals and busy professionals, find it challenging to sustain healthy lifestyles due to limited time, a lack of tailored guidance, and difficulties in staying motivated. To tackle these issues, an innovative approach is essential to deliver accessible, personalized, and inspiring fitness and wellness solutions. By empowering Nigerians to prioritize their health and well-being, their overall quality of life can be significantly enhanced.
My Role
I have the responsibility for the end-to-end design of the meal planning feature. I focused on creating a user-friendly experience that would help users achieve their fitness goals by providing personalized meal plans. To ensure a smooth integration with FoodCourt’s operations.
Design Decision
To develop a successful digital meal planner tailored to the Nigerian market, I incorporated the following AI-driven,
user-focused design decisions:
Advanced Dietary Recognition: Leveraging AI to precisely identify and accommodate a wide range of dietary preferences and restrictions, such as vegetarian, vegan, gluten-free, and specific cultural or religious requirements.
Intelligent Recipe Recommendations: Implementing a sophisticated recommendation system that learns from user input, dietary needs, and past meal choices to provide highly personalized recipe suggestions.
Design Success Metrics
User Interaction Efficiency: The goal is to enable users to create personalized meal plans with minimal clicks, ensuring the process is simple and intuitive. This can be measured by metrics such as the average number of clicks required to create a meal plan and the time spent on the task.
User Satisfaction: The use of AI and machine learning should provide tailored meal plans that match user preferences and dietary needs. A metric for this could be user feedback scores on meal plan relevance and personalization.
Competitive Differentiation: To confirm that FoodCourt stands out from competitors, benchmark comparisons could be used to track unique features such as automated meal personalization and the speed of meal plan creation.
Product Deliverables
Learnings
By utilizing AI and machine learning, FoodCourt can stand out from competitors and fulfill a crucial market demand. The competitive analysis reveals that the market is ready for innovative solutions that encourage healthier eating habits. Through offering automated, customized meal plans, we can help create a healthier and more efficient workforce.