Foodie Restoranų rekomendacijų programa by Tianyi Qi is a highly esteemed winner of the very prestigious 2022 Bronzinis apdovanojimas A' Design Award in Mobiliųjų technologijų, programėlių ir programinės įrangos dizainas Competition Category.
BronzinisMobilusis· 2022
Foodie Restoranų rekomendacijų programa
by Tianyi Qi
Client: Tianyi Qi
Bronzinis apdovanojimas A' Design Award Winner in Mobilusis Category
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The Design
About Foodie Restoranų rekomendacijų programa
„Foodie“ yra mobilioji programa, sukurta padėti žmonėms rasti restoranus pagal draugų rekomendacijas. Maisto pomėgių pasidalijimas dažniausiai vyksta neformaliuose pokalbiuose, o „Foodie“ šį bendravimą perkelia į skaitmeninę platformą, kuria galima naudotis bet kada ir bet kur. Ekrane „Draugai“ rodomi draugų atnaujinimai ir jų sudaryti sąrašai. Ekranas „Mano sąrašai“ leidžia naudotojams valdyti išsaugotus restoranus ir filtruoti juos pagal tipą. Ekranas „Žemėlapis“ suteikia galimybę ieškoti restoranų netoliese arba pasirinktoje vietovėje. „Foodie“ sukurta iOS įrenginiams.
The Recognition
About the Bronzinis apdovanojimas A' Design Award
Foodie Restoranų rekomendacijų programa laimėjo Bronzinį apdovanojimą A' Design Award, labai prestižinį pripažinimą, skiriamą išskirtiniams dizainams, kuriuos žymi kūrybiškumas, išradingumas ir sumanumas. Bronzos laureatai yra pakankamai įgudę ir stulbinamai kūrybingi dirbiniai, patvirtinantys jų kūrėjų didelę patirtį, vaizduotę ir išteklių gausą. Tikimasi, kad Foodie Restoranų rekomendacijų programa bus aukštai vertinamas, žavimas ir brangus daiktas, žymiai profesionalus ir novatoriškas. Šis Bronziniu apdovanojimu įvertintas dizainas įtraukia geriausias praktikas mene, moksle, dizaine ir technologijose ir yra puikus dėl dėmesio detalėms. Foodie Restoranų rekomendacijų programa puikiai tenkina poreikius, paliečia troškimus, žavi jausmus ir traukia smalsumą.
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
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