Network marketing recommendation strategy based on dynamic data mining

Jingjing Zhang; Hong Wang; Yujia Yang

doi:10.1117/12.2639656

27 June 2022 Network marketing recommendation strategy based on dynamic data mining

Jingjing Zhang, Hong Wang, Yujia Yang

Proceedings Volume 12253, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2022); 122531B (2022) https://doi.org/10.1117/12.2639656
Event: Second International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2022), 2022, Qingdao, China

Abstract

The advent of the Internet economy era, while bringing convenience to consumers lives, has brought new opportunities and challenges to the precise positioning of network marketing. Traditional marketing methods often use massive coverage advertising to promote products, reduce prices, discounts, and other promotional preferences to attract customers, which makes it difficult to accurately meet consumer demand, resulting in low advertising conversion rate, huge marketing costs and a serious waste of resources. This paper establishes a precision marketing model for the network community and obtains the characteristics of consumer behavior in the network community, accurate mining and analysis of the network community. Finally, through the experiment to test the effect of the precision marketing model for the network community, some suggestions on the construction and optimization of the precision marketing model and the network community are obtained to get the enlightenment of promoting the steady development of the sales industry and provide a reference for sales enterprises to improve the precision marketing mode and build and maintain their network community.

Citation Download Citation

Jingjing Zhang, Hong Wang, and Yujia Yang "Network marketing recommendation strategy based on dynamic data mining", Proc. SPIE 12253, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2022), 122531B (27 June 2022); https://doi.org/10.1117/12.2639656

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