Research on the enterprise online marketing mode based on data mining

Article type: Research Article

Authors: Zheng, Yulan

Affiliations: School of Economics and Management, Fuzhou University, Fuzhou, Fujian, China | E-mail: [email protected]

Correspondence: [*] Corresponding author: School of Economics and Management, Fuzhou University, Fuzhou, Fujian, China. E-mail: [email protected].

Abstract: With the development and popularity of mobile networks, online shopping has gradually become a trend. For enterprises, the traditional marketing mode has been difficult to play an effective role when facing the emerging online shopping mode. This study aims to improve the revenue benefits of online shopping. This paper first introduces the traditional marketing mode and then selects the data mining model used for consumption preference segmentation to build an online marketing mode. An example analysis was conducted on a book sales company and a real estate company. The results showed that more users in this community preferred five types of books, and the percentages from high to low were teaching and learning materials, modern novels, popular science books, historical literature, and classical novels; more customers preferred online platforms among the channels for collecting information on home purchase. No matter it was the book sales company or the real estate company, compared with no fluctuation in the company’s turnover under the traditional marketing mode, the turnover of the company increased month by month after adopting the online marketing mode.

Keywords: Internet, marketing, community network, data mining

DOI: 10.3233/JCM-215794

Journal: Journal of Computational Methods in Sciences and Engineering, vol. 22, no. 2, pp. 553-562, 2022