Foodie Aplikasyon Rekòmandasyon Restoran by Tianyi Qi

Foodie Aplikasyon Rekòmandasyon Restoran by Tianyi Qi is a highly esteemed winner of the very prestigious 2022 A' Design Award Bwonz in Mobil Competition Category.

BwonzMobil· 2022

Foodie Aplikasyon Rekòmandasyon Restoran

by Tianyi Qi

Client: Tianyi Qi

A' Design Award Bwonz Winner in Mobil Category

15,082

Verified Award Winner

Verify Award Status for #136763

Visit Site View at A' Design Award Press Release Award Badge

Colors

The Design

About Foodie Aplikasyon Rekòmandasyon Restoran

Foodie se yon aplikasyon mobil ki fèt pou ede moun jwenn restoran gras ak rekòmandasyon zanmi yo. Pataje preferans manje anjeneral fèt nan konvèsasyon face-a-face, e Foodie deplase echanj sa a sou yon platfòm dijital pou itilizasyon nenpòt kilè ak nenpòt kote. Ekran Zanmi an montre mizajou ak lis zanmi yo kreye. Ekran Lis Mwen yo pèmèt itilizatè jere restoran yo anrejistre ak filtre yo dapre kategori. Ekran Kat la sipòte rechèch pou restoran ki tou pre oswa nan yon zòn itilizatè a chwazi. Foodie fèt pou aparèy iOS.

The Recognition

About the A' Design Award Bwonz

Foodie Aplikasyon Rekòmandasyon Restoran se yon ganyan A' Design Award Bwonz, yon rekonesans ki gen anpil prestij yo bay design ekselan ki make pa kreyativite, enjenyozite ak finès. Ganyan Bwonz yo se objè ki abil anpil e ki kreyatif nan fason ki frape, ki otantifye gwo eksperyans, imajinasyon ak debouyaj designer yo. Yo atann Foodie Aplikasyon Rekòmandasyon Restoran pou se yon objè anpil moun estime, admire e renmen, ki pwofesyonèl e inovatè nan fason remakab. Design sa a ki ganyen A' Design Award Bwonz enkòpore pi bon pratik nan atizay, syans, design ak teknoloji, e li ekselan pou atansyon li bay detay. Foodie Aplikasyon Rekòmandasyon Restoran satisfè bezwen yon fason espledid, li touche dezi, li chame santiman e li atire kiryozite.

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