Foodie 餐廳推薦應用程式

由 Tianyi Qi

客戶: Tianyi Qi

流動類別嘅 A' Design Award 銅獎得獎者

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驗證設計 #136763 嘅獲獎狀態

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設計

關於 Foodie 餐廳推薦應用程式

Foodie係一款手機應用程式,旨在幫助用戶透過朋友嘅推薦搵到心水餐廳。分享美食喜好通常喺線下對話中發生,而Foodie就將呢種交流搬到數碼平台上,方便用戶隨時隨地使用。「朋友」畫面會顯示朋友建立嘅更新同清單。「我的清單」畫面容許用戶管理已儲存嘅餐廳,並按類型進行篩選。「地圖」畫面則支援搜尋附近或指定地點周邊嘅餐廳。Foodie係專為iOS裝置而設計。

榮譽認可

關於A' Design Award 銅獎

Foodie 餐廳推薦應用程式是 A' Design Award 銅獎得主，這是授予以創造力、獨創性和敏銳見長的傑出設計的極具聲望的認可。銅獎得主是技藝嫻熟、創意驚人的作品，印證了其設計師豐富的經驗、想像力與機智。預計Foodie 餐廳推薦應用程式將成為一件備受推崇、令人欽佩且被珍愛的物品，兼具顯著的專業性與創新性。這件贏得 A' Design Award 銅獎的設計融入藝術、科學、設計和技術領域的最佳實踐，並因注重細節而出類拔萃。Foodie 餐廳推薦應用程式出色地滿足需求，觸動渴望，迷住情感，並吸引好奇心。

設計背後

新聞資料包

由設計師提供嘅製作人員名單、團隊成員同技術詳情。

獨特屬性: 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.
尺寸同包裝: The app is designed for iOS systems.
標籤: Social, Restaurant, Food, Application, Recommendation
生產技術: The app requires a strong search engine, map and navigation service, and restaurant database to be functional.
設計挑戰: 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.
研究: 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.
靈感: 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?
項目時長: The project started in August 2019 and finished in January 2020, in New York City.
操作流程: 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.
圖片來源: Image #1-5: Tianyi Qi