mād is a cooking app for saving recipes, learning cooking skills, meal prep, and understanding balanced eating.
THE PURPOSE
mād aims to boost kitchen confidence and excitement while preventing over-buying. It achieves this through learning modes, personalized recommendations, and tools for visualizing and customizing weekly meals.
Although some apps allow users to store recipes, they often lack the educational component designed to be accessible and easy to understand for new cooks who may lack the necessary tools or knowledge about food.
RESEARCH
Found some research to better educate myself on the topic of meal prep and food waste, to help inform my decisions throughout the rest of the project.
Sources:
https://www.everydayhealth.com/diet-nutrition/scientific-benefits-of-meal-prepping/
https://hdsr.mitpress.mit.edu/pub/wjrl1qsq/release/3
BENCHMARKING
PAPRIKA 3
No limit to the number of recipes stored
Dated user interface + confusing navigation
Directions and ingredients can only be viewed one at a time
Need a third party scanner or transcribe steps manually
MOODBOARD
YUMMLY
Can’t edit recipes or add personal recipes
Grocery list sorts ingredients by the aisle they are found in
Redirects to third-party sites for URL recipes
Ingredient scanner to quickly log what’s in the pantry
SAMSUNG FOOD
Collaborate with others to create collections
Redirects to third-party sites for URL recipes
Shop directly from the grocery store site
Asks about diet and allergies upon registration
ECOSYSTEM MAP AND OPPORTUNITIES
The creation of an ecosystem map allowed me to understand how my users would interact with the app both physically and digitally. Here, I was able to consider how to break down a recipe, tips, or learning points in the most digestible way for a mobile app.
I also questioned how third-party data and user-inputted data would change the experience.
Could the app recommend recipes based on preferences on other apps or recipes they save externally?
Could there be an onboarding form asking about dietary restrictions or liked/disliked foods?
How does personalization work when a user adds notes, star ratings, etc. to recipes?
Is there a “bot” or AI that helps users learn about more specific things?
Can the app create recipes based on the user’s pantry ingredients, utilizing as many ingredients as possible?
INFORMATION ARCHITECTURE
ORIGINAL WIREFRAMES
Used this time to gain an understanding of the flow of the app, as it is very process-based.
