PROJECT OVERVIEW
This project began with a simple but powerful insight: working parents are exhausted. In every conversation with friends, I heard the same struggle: trying to cook balanced meals while managing careers, kids, and the chaos of everyday life. I set out to design a solution that not only saves time but also lifts the emotional weight of daily meal decisions. The result is an AI-powered app that simplifies meal planning through ingredient scanning, smart weekly menus, and automated grocery delivery.
Responsibility
UI/UX Design
User Research
Prototype
Tool
Figma
Photoshop
Project Type
Personal Project
PROBLEM
For dual-income parents raising children, meal planning can be an exhausting task.
SOLUTION + FINAL DESIGN
How Can We Solve Meal Planning Challenges?
Preferences Setup
This onboarding flow helps us understand your tastes, dietary needs, and family size to create the perfect meal plan.
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Meal Suggestions
Smart Recipes – AI-based meal suggestions
Your Picks – Choose your favorites
Quick Guides – Video or text recipes
Easy Steps – Simple cooking flow
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Smart AI Food Scanner
Camera Scan – Snap your fridge or pantry.
AI Detect – Auto-recognizes and logs items.
Manual Add – Fill in anything AI misses.
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Grocery Auto-Delivery
Auto Cart – Missing items added for you
Home Delivery – Groceries to your door
Smart Picks – Organic or budget, your choice.
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.
Most participants wanted to use a service that combines meal planning and delivery. (76.2%).
Over 90% of participants reported experiencing frustration with meal preparation. (90.4%).
KEY INSIGHT
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.
Streamlining Meal Planning, Shopping, and Family Time
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.