How FlavorFind Simplified Cooking with AI-Powered Ingredient Scans
A case study on making meal planning stress-free with user-centered design.
FlavorFind
FlavorFind is an AI-powered mobile app designed to simplify home cooking and meal planning. It empowers users to scan or input ingredients, discover creative recipes, and plan meals effortlessly, transforming everyday cooking into an engaging experience.
My Role
UX Researcher,
Usability Tester,
Information Architect
Project
Self Initiated
Timeline
2 Weeks (2022)
Tools Used
Figma, Google Forms for surveys
The Problem
“What’s for dinner?” – The everyday question that creates unnecessary stress.
Scenario:
Imagine standing in your kitchen, staring at a mix of random ingredients and struggling to decide what to cook. This frustration resonates with countless home cooks who juggle busy schedules and limited meal ideas.
Core Question:
Could an app transform cooking from a chore into a creative experience?
The Research
What I Did:
1. Talked to friends and family who regularly cook at home.
2. Conducted informal surveys to identify common frustrations:
- Lack of quick and easy meal ideas.
- Difficulty knowing how to use ingredients before they spoil.
- Little knowledge about ingredient substitutions.
Created personas to represent different user types.
Key Insights:
Users wanted a tool that combined convenience, creativity, and ease of use while reducing food waste.
Based on the user research, I developed 3 personas representing typical users of FlavorFind:
User Persona
Empathy Map
Key Insights:
Pain Points: Decision fatigue, lack of creativity with available ingredients, food waste, and the stress of meal planning.
Opportunities: FlavorFind can alleviate these issues by providing easy, AI-powered recipe suggestions based on scanned or inputted ingredients, offering alternatives, and helping users create meals with minimal effort.
Emotions: Users feel a combination of frustration, guilt, and anxiety about meal planning, but they also express excitement when presented with creative and efficient solutions.
Affinity Map
Competitive Analysis
Discovery
User Pain Points:
"I don’t have time to search for recipes that fit my ingredients."
"I end up wasting food because I don’t know how to use it."
"I get overwhelmed with too many recipe options that don’t match what I have."
Re-frame Problem:
How might we empower home cooks to make quick, informed, and enjoyable decisions about their meals?
The Solution
Enter FlavorFind:
A mobile app designed to address these pain points using AI-driven recipe suggestions and ingredient-based cooking tips.
Ingredient Scanning: Users upload or scan their available ingredients for tailored recipe suggestions.
Smart Substitutions: Offers creative ingredient swaps for items users are missing.
Simple Navigation: Focused on minimal steps to reduce cognitive load for users.
Design Process:
Built wireframes to visualize the user flow.
Iteratively improved the design based on mock feedback from peers.
Example Story
Case:
Rahul, a working professional, had leftover zucchini, tomatoes, and pasta. Using FlavorFind, he scanned his ingredients and was delighted to discover a quick recipe for pasta primavera.
Outcome:
Rahul saved time and felt confident creating a dish that minimized waste while meeting his taste preferences.
WireFrames
(Iteration1)
Feedback on Complexity:
Users found the meal planning feature redundant, mentioning it added unnecessary steps.
The recipe recommendation of the day was perceived as too generic and not personalized to their needs.
Suggestions for Simplification:
Many users emphasized that they wanted the app to focus solely on recipe suggestions based on available ingredients to streamline its functionality.
Some users expressed that additional features like meal planning and daily recommendations created a cluttered experience.
Overall Impressions:
Users appreciated the concept of scanning ingredients and getting recipes but requested a simpler and faster workflow with fewer distractions.
Usability Test Results
To simplify the FlavorFind app further and avoid including meal planning and help screens, here’s an updated set of screens:
Welcome Screen
A brief introduction to the app's features with a "Get Started" button.
Home Screen (Dashboard)
Central hub featuring options for Input Ingredients and Discover Recipes.
Ingredient Input Screen
Users can either scan or manually add ingredients.
Recipe Recommendation Screen
Displays personalized recipes based on the input ingredients.
This streamlined approach reduces the app to its core functionality while keeping it user-friendly and efficient. The simplicity makes it easier to develop and ensures a smooth user experience.
(Iteration2)
Prototype
What I learned?
Feedback from Initial Prototypes:
- Users loved the simplicity of the ingredient scanner.
- Some wanted more detailed recipe options for dietary restrictions.
- A few suggested incorporating meal-planning features for future updates.
Iterate
Enhancements Based on Feedback:
- Simplified the onboarding process for first-time users.
- Refined the ingredient scanner’s interface to make it more intuitive.
- Added placeholder functionality for meal planning (future feature).
Impact
What Users Said:
"I feel like this app understands what I need as a home cook."
"It makes cooking feel creative rather than stressful."
Takeaways
Empathy First: Listening to user frustrations is key to designing solutions that resonate.
Start Simple: Focus on solving one core problem effectively before expanding features.
Iterate Quickly: Feedback, even in small-scale testing, can highlight key areas for improvement.
What’s next?
Adding meal planning for weekly schedules.
Incorporating global recipe suggestions for diverse cuisines.
Exploring integration with grocery delivery services to streamline shopping.