Title: The application of AI technology to upgrade retailers' traditional marketing means

Authors: Lu Zhang; Ruixue Dong

Addresses: Department of Economics and Trade, Henan Polytechnic Institute, Nanyang, Hennan, China; Department of Computer Science & Technology, Huazhong University of Science and Technology, Wuhan, Huazhong, China ' Zhengzhou Fengyang Foreign Language School, Zhengzhou, Hennan, China

Abstract: In order to improve the conversion rate of users' purchase and the personalisation of marketing push, the application of AI technology in upgrading traditional marketing methods of retailers was studied. Firstly, it analyses the limitations of traditional retailers' marketing methods. Secondly, aiming at the existing limitations, AI technology is introduced to upgrade marketing means, big data analysis technology is used to mine user behaviour data, collaborative filtering algorithm in machine learning algorithm is used to recommend products individually, and natural language processing technology is used to evaluate user satisfaction. Finally, the application effect of this method is evaluated through a case study. The results showed that the conversion rate of this method is high, with the highest value of 48.3% and the highest score of personalisation degree of 1.0, which showed that it can predict users' purchasing behaviour more accurately and provide more personalised recommendation results.

Keywords: AI technology; retailer; marketing means; user behaviour data; collaborative filtering algorithm; satisfaction evaluation.

DOI: 10.1504/IJPD.2024.143262

International Journal of Product Development, 2024 Vol.28 No.4, pp.288 - 300

Received: 03 Apr 2024
Accepted: 03 Oct 2024
Published online: 11 Dec 2024 *

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