Foodie 레스토랑 추천 애플리케이션 by Tianyi Qi is a highly esteemed winner of the very prestigious 2022 A' Design Award 동상 in 모바일 기술, 애플리케이션 및 소프트웨어 디자인 Competition Category.

동모바일· 2022

Foodie 레스토랑 추천 애플리케이션

by Tianyi Qi

Client: Tianyi Qi

A' Design Award 동상 Winner in 모바일 Category

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The Design

About Foodie 레스토랑 추천 애플리케이션

Foodie는 친구들의 추천을 통해 레스토랑을 찾을 수 있도록 돕는 모바일 애플리케이션입니다. 음식 취향을 공유하는 일은 대개 오프라인 대화에서 이루어지는데, Foodie는 이러한 교류를 디지털 플랫폼으로 옮겨 언제 어디서나 이용할 수 있게 합니다. 친구(Friends) 화면에서는 친구들이 올린 소식과 친구들이 만든 리스트를 확인할 수 있습니다. 내 리스트(My Lists) 화면에서는 저장한 레스토랑을 관리하고 유형별로 필터링할 수 있습니다. 지도(Map) 화면에서는 주변이나 원하는 위치 근처의 레스토랑을 검색할 수 있습니다. Foodie는 iOS 기기용으로 개발되었습니다.

The Recognition

About the A' Design Award 동상

Foodie 레스토랑 추천 애플리케이션, 이 작품은 A' Design Award 동상 수상작으로, 창의성, 독창성, 영민함으로 돋보이는 뛰어난 디자인에 수여되는 높은 권위의 인정입니다. 동상 수상작은 충분히 숙련되고 인상적으로 창의적인 작품으로, 디자이너의 폭넓은 경험, 상상력, 기지를 입증합니다. Foodie 레스토랑 추천 애플리케이션, 이 작품은 높이 평가받고 감탄과 사랑을 받는 사물로서 두드러지게 전문적이고 혁신적일 것으로 기대됩니다. 이 동상 수상 디자인은 예술, 과학, 디자인, 기술의 모범 사례를 담고 있으며 세부에 대한 주의로 훌륭합니다. Foodie 레스토랑 추천 애플리케이션, 이 작품은 필요를 훌륭하게 충족하고 욕망에 닿으며 감정을 매료하고 호기심을 불러일으킵니다.

Behind the Design

Press Kit

Credits, team members and technical details provided by the designer.

Unique Properties: Foodie is a mobile app that aims to leverage the action of sharing personal preference with one's social circle, which happens mostly in offline settings, to a digital platform. This transformation allows this information-sharing process to expand beyond limited scenarios so users can create content and access information whenever and wherever they need it.
Dimensions & Packaging: The app is designed for iOS systems.
Tags: Social, Restaurant, Food, Application, Recommendation
Production Technology: The app requires a strong search engine, map and navigation service, and restaurant database to be functional.
Design Challenge: Why do users use this service when there are already other popular information sources/services existing around? Which was the major challenge I was facing at the beginning stage of the project. The research was designed and planned to answer this question.
Research: I interviewed 10 participants between 20–40, all of them are Yelp or Google users. Participants were asked to arrange the cards with information sources to show how frequently they use and how much they trust each of them. The 3 major research questions are:
1. How and when do people use each information source to find restaurants?
2. What do people trust about each information source?
3. How do people recommend restaurants to their social circle?

The results showed that social circle is the most trusted and the 2nd most used information source when participants are looking for restaurant recommendations. This insight validated the foundation of the project: even though modern technologies have played an important role in helping people find restaurants, people still get recommendations from their friends. From the research, I also learned the requirements participants have on a restaurant's recommendation service and the data gathered from the research was used in persona creation.
Inspiration: As a foodie living in New York City, I have been enjoying using apps like Yelp and Google to find restaurants, especially those that provide ethnic food that I have never tried before. However, I noticed that even though those apps are backed with big data, I trust my friends more in terms of finding restaurants. This experience makes me curious about this totally different mechanism of trust: How might we help people find restaurants from their friends' recommendations?
Project Duration: The project started in August 2019 and finished in January 2020, in New York City.
Operation Flow: On the "Friends" screen, a user will see new updates from their friends, for example, a friend added a new restaurant to their list. They can also explore all the lists created by their friends. To manage restaurants on their own lists, a user can easily navigate to the "My Lists" screen. They can use the filters to easily find the specific types of restaurants on their lists. On the "Map" screen, a user can search for restaurants nearby or around a certain location.
Image Credits: Image #1-5: Tianyi Qi