Author(s)

Jiaye Huang

Beijing Kaiwen Academy, Beijing, China.

This paper makes multi-dimensional big data analysis on the membership data of a well-known women’s bag fashion brand in China. We use a combination of data cleaning, data visualization, data classification, correlation analysis and data prediction. Based on these analyses, we found eight business insights and made twelve suggestions for business development of the fashion brand. These suggestions include both business development and strategic aspects, as well as suggestions for the upgrading of the member management system. The member management system of the fashion brand has not been very effective maintenance, for example, a lot of data is incomplete, which has a wide range of representation in the member management of Chinese enterprises. Our big data-based analysis method is of great significance for using these incomplete member data to guide the development of the business.

Big Data, Data Mining, Membership Management, Business Insights, Fashion Brand

Huang, J. (2019) Analysis on the Membership Management of a Fashion Brand by Big Data Technology. American Journal of Industrial and Business Management, 9, 1931-1948. doi: 10.4236/ajibm.2019.910126.