Title: Research on the application of K-means clustering algorithm in college students' network marketing precision promotion

Authors: Yangyang Li

Addresses: School of Economics and Management, Xi'an Mingde Institute of Technology, Xi'an, Shaanxi Province, China

Abstract: With the development of information technology, precision marketing is gradually applied in various fields. Taking the telecommunications industry as an example, this study optimises the K-means clustering algorithm, analyses the precision promotion of college students' network marketing combined with data mining technology, and puts forward the precision marketing strategy based on data mining. The results show that the optimised K-means clustering algorithm has better operation efficiency and convergence speed than the traditional algorithm, shorter response time and significantly improved analysis performance. In the actual case, this study puts forward the precision marketing strategy through cluster analysis and uses this strategy for customer maintenance and marketing in daily work to verify the accuracy of this method. It is hoped that the proposal of this strategy can provide some reference for the research on precision marketing.

Keywords: K-means clustering; colleges and universities; college student; marketing; forecast.

DOI: 10.1504/IJWMC.2023.132425

International Journal of Wireless and Mobile Computing, 2023 Vol.25 No.1, pp.84 - 93

Received: 17 Apr 2022
Received in revised form: 30 Nov 2022
Accepted: 28 Mar 2023
Published online: 19 Jul 2023 *

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