Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China

Research Article

Construction and Application of Precision Marketing System of E-commerce Platform under the Background of Big Data

Download268 downloads
  • @INPROCEEDINGS{10.4108/eai.17-6-2022.2322716,
        author={Yuan  Wang},
        title={Construction and Application of Precision Marketing System of E-commerce Platform under the Background of Big Data},
        proceedings={Proceedings of the International Conference on Information Economy, Data Modeling and Cloud Computing, ICIDC 2022, 17-19 June 2022, Qingdao, China},
        publisher={EAI},
        proceedings_a={ICIDC},
        year={2022},
        month={10},
        keywords={big data; e-commerce; precision marketing; hadoop; network platform construction},
        doi={10.4108/eai.17-6-2022.2322716}
    }
    
  • Yuan Wang
    Year: 2022
    Construction and Application of Precision Marketing System of E-commerce Platform under the Background of Big Data
    ICIDC
    EAI
    DOI: 10.4108/eai.17-6-2022.2322716
Yuan Wang1,*
  • 1: Jiangxi Vocational College of mechanical & Electrical Technology
*Contact email: 258812604@qq.com

Abstract

In order to promote the vigorous development of China's Internet industry e-commerce market, help e-commerce enterprises to use big data technology to operate scientifically, so that e-commerce enterprises can achieve sustainable development, gain more profits and more room for growth, and build an accurate marketing system of e-commerce platform. This system uses Python web crawler technology to obtain information data, and carries out data analysis on Hadoop platform. Combined with tableau data visualization technology, it intuitively presents the data required by e-commerce enterprises. Big data precision marketing system can help e-commerce enterprise managers to judge customers' psychology and behavior, understand customers' needs and consumption preferences, and accurately analyze the traffic volume and transaction volume data generated by new and old consumers in different preferential means and different periods to improve user loyalty. So as to increase the user return rate, stabilize the existing user base, improve the marketing plan of enterprises, improve the sales performance of enterprises, and help enterprises obtain more ideal economic benefits.