DESIGN NAME: See
PRIMARY FUNCTION: E-Commerce App
INSPIRATION: The consumption of young ladies aged 20-30 is rising fast in China developed cities. They began to raise the level of substance, the desire for high-quality fashion brands and willing to be strong consumers, but they seldom see global high-fashion goods in their daily life. And The search engines can not help them find the most accurate product, can only search out images that look like the photo.
Users need professional services to solve their pain points in fashion consumption.
UNIQUE PROPERTIES / PROJECT DESCRIPTION: 1.On-demand and picture-to-pruchasing Service:App users can find all what their want on daily life by See;
2.Fashion Content Community Eco:Users can find their favorite fashion style from the bloggers, and subscribe to them.They can find fashion lovers with the same preferences to form a community.
3.Data Analysis plus Fashion Experts:Through big data analysis of user wishes and global cloud commodity library, See gives the most valuable commodities and push them to the most appropriate fashion.
OPERATION / FLOW / INTERACTION: See obtains images from users and distributes the wish to the respondent who has the capability of corresponding service. It will give the most similarity commodities links to respondents. They can select which is the best selection and answer wish of user. Respondents can use their own fashion taste to provide services. It is rewarded. Though user needs data analysis, See can recommended commodities exact matching their taste, and push the communities to meet users' reading needs daily.
PROJECT DURATION AND LOCATION: The project started in March 2015 in Shenzhen and finished the first version in June 2015 in Shenzhen, and finished the 2.0 version in September 2015, and finished the 2.5 version in January 2016.
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PRODUCTION / REALIZATION TECHNOLOGY: See obtains images and texts feature issues from user own needs. Using data mining, See distributes the wishes to the respondents who have the capability of corresponding service though the cloud data set.
After data analysis of images and texts, See can push commodities exact matching tastes of users to meet reading needs daily. By collecting large amounts of user needs data, See can directly finds the hottest items, as well as fashion trends, and even guides suppliers for production.
SPECIFICATIONS / TECHNICAL PROPERTIES: Number of users: over 600,000
Number of wishes covered effectively: over 900,000
Number of Fashion over Experts: 500
Size: 29.0 MB
Language: Simplified Chinese
Compatibility: Requires iOS 7.0 or later. Compatible with iPhone, iPad, and iPod touch.
TAGS: E-Commerce, App, On-demand, Fashion, Mobile Application, C2B, Dressing
RESEARCH ABSTRACT: At the beginning, our research was about basic information of target users: What problems do ladies meet when shopping on the oversea website? How they feel when using other e-commerce app? We used online questionnaire for hundreds of feedbacks and interviewed dozens of target users.
After demo version finished, we started the usability testing and optimized the app.
Meanwhile, We research algorithm for images identification continuously. Now the algorithm was used for identification of user wishes images.
CHALLENGE: The challenge was how to balance community and e-commerce in See. At the beginning we thought community was more important than shopping area and planned to create SNS. But after demo version, we found that people are not often to communicate fashion and dressing with others online but with friends or experts who they trust in. In China, people need professional service more than communication in dressing. So we invited hundreds of fashion stars to give users professional service.
ADDED DATE: 2016-02-29 11:42:29
TEAM MEMBERS (4) : Strategic Planning: Xucheng Wan, Creative Director: Sheng Yang, Product Manager: Xiao Yang and Designers: Jie Tang, Wanping Liu
IMAGE CREDITS: Image #1:See Design Team
Optional Image #1:See Design Team
Optional Image #2:See Design Team
Optional Image #3:See Design Team
Optional Image #4:See Design Team
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