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Simulation Tools and Techniques. 13th EAI International Conference, SIMUtools 2021, Virtual Event, November 5-6, 2021, Proceedings

Research Article

Cosmetics Sales Data Classification Method of Japanese Cross-Border E-Commerce Platform Based on Big Data

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  • @INPROCEEDINGS{10.1007/978-3-030-97124-3_13,
        author={Jingxian Huang},
        title={Cosmetics Sales Data Classification Method of Japanese Cross-Border E-Commerce Platform Based on Big Data},
        proceedings={Simulation Tools and Techniques. 13th EAI International Conference, SIMUtools 2021, Virtual Event, November 5-6, 2021, Proceedings},
        proceedings_a={SIMUTOOLS},
        year={2022},
        month={3},
        keywords={Big data Japanese cross-border e-commerce platform Cosmetics sales Data classification Consumer Sales potential},
        doi={10.1007/978-3-030-97124-3_13}
    }
    
  • Jingxian Huang
    Year: 2022
    Cosmetics Sales Data Classification Method of Japanese Cross-Border E-Commerce Platform Based on Big Data
    SIMUTOOLS
    Springer
    DOI: 10.1007/978-3-030-97124-3_13
Jingxian Huang1
  • 1: Guizhou Minzu University, Guiyang

Abstract

Data analysis is playing an increasingly important role in the cross-border e-commerce platform in the cosmetics industry. Therefore, this paper proposes a cosmetics sales data classification method for the Japanese cross-border e-commerce platform based on big data. Taking the cosmetics sales data on the Japanese cross-border e-commerce platform as the research object, the development model of Japanese cross-border e-commerce and the connotation of cosmetics are expounded. Take targeted methods and measures; extract consumer purchase behavior characteristics on Japanese cross-border e-commerce platform, conduct in-depth analysis of customer relationship from three aspects: customer analysis, sales analysis and e-commerce platform analysis, and guide the behavior of maintaining customer relationship; Big data technology is used to predict the sales potential of cosmetics, determine the output according to the actual sales volume, and design the sales data classification model according to the characteristics of the data samples. Experimental results have classify the sales data, it is of great significance to the cosmetics sales of the e-commerce platform.

Keywords
Big data Japanese cross-border e-commerce platform Cosmetics sales Data classification Consumer Sales potential
Published
2022-03-31
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-97124-3_13
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