Initial Research and Analysis

Interviews | Affinity Diagram | Key Findings | Consolidated Sequence Model

We had 10 participants: 7 female, 3 male, who ranged from 18 to 60. Our questions focused on their experiences finding restaurants in groups of people. Below are a few examples of the type of questions we guided the conversations with.

• What’s important to you when searching for a restaurant?
• What kinds of resources or devices do you use?
• When using digital resources, what features or filter do you take advantage of?
• What kinds of features would you like to see?

We organized the data we gathered from the interviews and created an affinity diagram.

I’ve been to places that don’t take my food allergies seriously which causes concern.

Picking a restaurant with a group is really annoying because no one can agree on anything.

Reviews are the most important when choosing a restaurant for me.

Sometimes searching for a restaurant takes a long time.

Quotes from participants

The key findings from our analysis:

Current methods: Google Maps, paper menus, and word of mouth were the most common ways to find restaurants among our participants.

Most important information: Details about the type of food, location and hours, access to the menu, reviews and ratings, and photos.

We consolidated several models that focused on the culture, artifacts, and different possible user flows into this model:

Our Proposed Solution

Ideation | Use Cases | Predicted Sequence Model

We saw an opportunity for an app, Food Fiends, to be created to make the process of finding a restaurant in a group of people easier because there are struggles that aren’t being addressed by the current methods.

Our idea for an app to help this process would work by creating an ‘eating event’ and inviting the group members to join. They would then be able to input the different dietary restrictions, distance they are willing to travel, amount of money they are willing to spend, etc. Then each group member would individually go through a list of restaurants that fit the requirements and decide whether they would like to eat there. When they are done going through the list, they are presented with a short list that all members are interested in to make the decision easier.

One of the most important aspects we wanted to improve for our users was communication. Specifically, communication between the group of people choosing the restaurant and between the users and the restaurants available. By using Food Fiends, users can have a specific place to choose a restaurant rather than trying to have the conversation over a group text if separate or run into conflicting or distracting conversations in person.

Two of our use cases:

Our predicted sequence model:

Reflections

This project was focused on research, data analysis, and the beginning stages of ideation. Given more time and resources, I would love to take it further and design a prototype and perform usability tests to see the real impact of our proposed solution.