CookMate

Overview

Team:

Eli Ballesteros

Emily Tuy

Xuefei Cheng

Ritika Vijay Rajpal

Timeline:

Sep 2023 - Dec 2023

THE PROBLEM

Although online recipe apps are helpful in providing support in cooking, many users find it difficult to follow because of the overwhelming filters and insufficient ingredients in real life.

THE SOLUTION

Our solution is an application that incorporates both the filter model and the LLM model to generate recipes according to users’ input. The filter model enables users to input ingredients manually, and the LLM model recognizes the ingredients from the picture taken by the user and generates recipes based on the given ingredients.

DESIGN

Research

Competitive audit on similar AI-powered cooking applications on the App and Google Play store as we wanted to see the functionality, navigability, and usefulness of similar applications.

Below are competitor’s apps:

COMPETITIVE ANALYSIS

Insights about the barrier that users are experiencing:

CONTEXTUAL PARADIGM: USER INTERVIEW

Our goal was to identify user pain points and encapsulate a diverse user pool to include students, professionals, those with dietary restrictions, and unique kitchen setups & cooking skills.

SCENARIO-BASED PARADIGM: TASK ANALYSIS

From the task analysis, we pinpointed the user pain points. We also spoke to potential users to understand why they might utilize the app.

We created two task analyses:

a college student with the CookMate app

a college student without the CookMate app

From our research, we came to the following conclusions:

The main user pain point is insufficiency of ingredients when they find a recipe online that requires it.
Information overload from traditional cooking apps deter users from selecting a recipe and following through with it.
Majority of our users are time constrained. They require an intuitive cooking app that caters to their schedules and offers options that fit within their time frame.
Users value personalization. They want an application that can factor in their dietary restrictions, favorite cuisines, cooking skills, and selective serving sizes.
Users appreciate a streamlined experience where they can control the inputs and easily select the ingredients they have.

RESEARCH INSIGHTS

An ideal app will need to include:

maximizing the ingredients that the user has
meeting the user where they are at (e.g. ingredients, cooking levels, appliances, etc.)
reducing food waste, enhancing their culinary experience
mitigating the hassle and frustrations associated with the decision-making process