Foodie 餐厅推荐应用程序 by Tianyi Qi is a highly esteemed winner of the very prestigious 2022 A' Design Award 铜奖 in 移动技术、应用与软件设计 Competition Category.

铜移动· 2022

Foodie 餐厅推荐应用程序

by Tianyi Qi

Client: Tianyi Qi

A' Design Award 铜奖 Winner in 移动 Category

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Verified Award Winner

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The Design

About Foodie 餐厅推荐应用程序

Foodie是一款移动应用程序,旨在帮助人们通过好友推荐来发现餐厅。以往分享美食喜好大多发生在面对面的交谈中,而Foodie将这种交流迁移到数字平台上,让用户随时随地都能进行分享。"好友"界面展示好友发布的动态与创建的清单;"我的清单"界面便于用户管理已收藏的餐厅,并可按类型进行筛选;"地图"界面则支持搜索附近或指定位置周边的餐厅。Foodie专为iOS设备打造。

The Recognition

About the A' Design Award 铜奖

Foodie 餐厅推荐应用程序是 A' Design Award 铜奖得主，这是授予以创造力、独创性和敏锐见长的杰出设计的极具声望的认可。铜奖得主是技艺娴熟、创意惊人的作品，印证了其设计师丰富的经验、想象力与机智。预计Foodie 餐厅推荐应用程序将成为一件备受推崇、令人钦佩且被珍爱的物品，兼具显著的专业性与创新性。这件赢得 A' Design Award 铜奖的设计融入艺术、科学、设计和技术领域的最佳实践，并因注重细节而出类拔萃。Foodie 餐厅推荐应用程序出色地满足需求，触动渴望，迷住情感，并吸引好奇心。

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