GustARe is an AR app that helps users to understand text-heavy menu and increase the efficiency of decision making. By importing data from API like Yelp, Google Map and other food-review app, GustARe provides relevant information of menu items such as photos, ingredients and food reviews. It aims to improve the experience of decision making in restaurants. And ‘gustare’ means savour in Italian.
My Role: UI/UX, AR Prototyping Project Duration: 4 weeks Teammate: Lucien Huang
wHAT MAKES FOOD ORDERING DIFFiCULT?
The initiation of this project came from my own experience of ordering food in restaurants while I was studying abroad in Paris. From my observation, more than 90% french restaurants have text-only menus which I always had difficulties to get senses of what those dishes are and how they may taste like. After sharing this issue to my friends, I found that this is a common problem that happens to people who travel a lot or go abroad for studying or working.
In order to better clarify users' pain points, figure out their needs and goals, we conducted user interviews with four people who travel a lot and three people who like to eat out and try foreign food which they are not familiar with. We interviewed them about the overall experience of ordering food in restaurants, what problems they have encountered and what they would do to make decisions as well as what they wish to have. Here are some early insights we took from interviews:
We started with brainstorming by sketching ideas as many as possible. And then we made an affinity map to group them into three main solutions.
1. A diner can scan a QR code to access a h5 or download the app of the restaurant, or restaurant can provide devices like iPads for diners to make order digitally.
2. Create a platform for restaurants to input their menu items.
3. Take advantage of AR as the bridge between physical world and digital experiences.
Interactive Prototype & USER testing
After I finished the first digital prototype, we quickly conduct usability testing with 5 potential users. Because According to Nielsen Norman Group, you can find out 80% of the problems with just five people. All of our Users responded very positively although there are some usability problems which I made iterations to fix them.
Final HI-FI design
A simple and easy way to order food
For further development of this application, we would like to focus on building up the business model and design feature that beyond performance need as a delighter of the product according to Kano model:
1. Integrate AI to provide personalized recommendation by monitoring and analyzing users’ preferences and behaviors
2. Allows users to synchronize theirs choices within the party to increase efficiency