AI Platter
PROJECT OVERVIEW
I designed an AI-powered meal planning app to simplify meal prep and save time through features like ingredient scanning, personalized meal plans, and automated grocery delivery. My role included creating a user-friendly interface, researching, and developing prototypes to ensure the app met diverse user needs.
My Role UI/UX Designer
Tools Figma
Deliverables Wireframes, User Experience, and User Interface
DESIGN PROCESS
The Design Sprint
I applied the Double Diamond Model and User-Centered Design Thinking to develop the AI Platter UX design. By deeply understanding user needs, defining key challenges, and iterating through ideation, prototyping, and testing, I ensured that the final design provides an intuitive and seamless user experience.
PROBLEM
For dual-income parents raising children, meal planning can be an exhausting task.
Busy parents struggle to find time for meal planning and grocery shopping. With hectic schedules, they often visit multiple stores, forget what they already have, and feel overwhelmed by daily meal preparation.
Quotes:
"After work, I have to pick up my kids, and it's already late by the time we get home. There's no time to plan or cook a proper meal."
"I have to go to multiple stores—Costco, Whole Foods, Trader Joe’s, and an Asian market—to get everything I need. It takes hours."
"I always forget what I already have at home and buy duplicates."
SOLUTION
How Can We Solve Meal Planning Challenges?
Our solution automates ingredient tracking, personalizes meal plans, and streamlines grocery delivery to simplify meal planning, helping busy families save time and reduce stress.
01: Smart AI Food Scanner
Camera Scanning – Scan your fridge or pantry with a camera.
AI Recognition – AI automatically detects and logs ingredients into the app.
Manual Input – Users can add missing items AI couldn't detect.
03: AI-Powered Grocery Auto-Delivery
02: AI-Powered Meal Suggestions
Smart Recipe Recommendations – AI suggests meals based on available ingredients.
Personalized Choices – Users can select preferred dishes from AI’s recommendations.
Quick Recipe Access – View short video guides or text-based recipes.
Seamless Cooking Experience – Get step-by-step instructions for easy meal prep.
Automatic Cart Filling – AI detects missing ingredients and adds them to your cart.
Seamless Home Delivery – Groceries are delivered straight to your doorstep.
Personalized Selection – Choose between organic or budget-friendly options, and AI selects the best brands accordingly.
USER RESEARCH PROCESS
Where do people struggle in the current experience?
Through multiple surveys and interviews, I identified user pain points and gained valuable insights.
Step 1: Listening to Users' Stories
In the first step, I conducted open-ended interviews to understand users' cooking habits and motivations. Key questions included:
How do you start cooking?
Why do you cook?
What matters most to you in meal preparation?
Findings: Users value home-cooked meals for their family's health, but they struggle with the time and effort required.
Step 2: Digging Deeper
To explore this issue further, I conducted in-depth interviews with targeted questions:
How do you currently plan your meals?
What challenges do you face when creating a meal plan?
What options would you want in a meal planning app (e.g., diet preferences, allergies)?
Findings: Many users want a quick meal preparation method based on personal preferences and available ingredients.
Step 3: Synthesizing Insights
Using Affinity Diagrams and 2x2 Prioritization Frameworks, I categorized patterns from the research.
A User Journey Map helped identify points of frustration and joy in the meal planning process.
Step 4: Validating & Refining the Scope
Through target audience interviews and validation, I refined the problem scope using "Start at the End" and "Map Stages" frameworks.
This phase focused on defining a clear solution to address user challenges.
KEY INSIGHT
Most participants wanted to use a service that combines meal planning and delivery. (76.2%).
People struggle with the entire process from meal planning to cooking due to a lack of time.
90% of users struggle with meal prep due to time constraints. Through surveys and interviews, I identified key pain points: lack of time, ingredient tracking, and limited meal options. I used affinity mapping and user journey analysis to design an AI-powered solution that simplifies meal planning and grocery shopping.
GOALS
Balancing work, family, and meal planning is a challenge for busy households. Our solution simplifies meal prep, streamlines grocery shopping, and helps families spend more time together by leveraging AI-powered automation.
Simplify Meal Planning: To make meal planning easier by automatically generating weekly menus based on the ingredients users already have at home.
Efficient Grocery Shopping: To save users time by delivering missing ingredients directly to their door, reducing the need for multiple store visits.
Promote Family Time: To help busy families spend less time on meal prep and more time enjoying quality moments together.
TARGET USERS
PERSONA
Over 90% of participants reported experiencing frustration with meal preparation. (90.4%).
Streamlining Meal Planning, Shopping, and Family Time
The target users are busy individuals, particularly working parents, who want to provide healthy, home-cooked meals for their families but struggle with time constraints and the complexity of meal planning. They value convenience, personalization, and efficiency, often needing solutions that accommodate dietary preferences, cultural cuisines, and family-specific needs. These users are looking for a seamless way to plan meals, shop for ingredients, and save time in their daily lives.
A Day in Her Life
Minji, a dedicated nurse and mother of two, starts her day early, balancing patient care at the hospital while constantly thinking about her family's needs. After a long shift, she rushes to pick up her kids and faces the challenge of planning dinner. She prefers cooking healthy Korean meals but struggles with time-consuming grocery trips to multiple stores.
By the time she gets home, she's exhausted, yet she still needs to figure out what to cook, track ingredients, and prepare meals. The mental load of meal planning, shopping, and cooking takes away from precious family time.
Minji dreams of a solution that simplifies meal planning and grocery shopping—something that can automatically suggest recipes based on available ingredients, organize grocery lists, and even arrange delivery. With such a system, she could spend less time worrying about meals and more time enjoying dinner with her family.
USABILITY TEST + IMPROVEMENTS
3 Major improvements in my design
Based on various feedback from 5 other peers + mentor feedback, I continually iterated my design with 3 major improvements:
Iteration 01
Improved Navigation & Structure
Shifted from a basic list view to a structured calendar-based meal planner.
Clearer meal categories (Breakfast, Lunch, Dinner) for easier selection.
Iteration 02
Simplified Step-by-Step Flow
Replaced a long, overwhelming form with a guided, step-by-step interaction, making it easier to complete.
Upgraded toggle switches and dropdowns to interactive buttons, improving clarity and user engagement.
Iteration 03
Clearer Ingredient Organization
Categorized ingredients with icons and visuals, making it easier to browse and track available items.
Emphasized user inventory, enhancing engagement and usability.
THE FINAL SCREENS
The final product
WRAP UP
Takeaways
🔍 Balancing Depth and Efficiency
User research required extensive data collection and analysis, making it challenging to balance depth with efficiency. Iterative testing helped streamline insights without overcomplicating the process.
🛠 Overcoming Uncertainty in Ideation
At times, selecting the right direction felt overwhelming due to the abundance of possible solutions. Using structured ideation techniques and validation frameworks helped narrow down the most effective ideas.
⚡ Navigating User Feedback Loops
User feedback was invaluable, but it also required multiple iterations and refinements. Managing conflicting opinions and determining which insights to prioritize was a key challenge that required careful analysis and testing.