Applying Machine Learning in Marketing: An Analysis Using the NMF and k-Means Algorithms

被引:0
|
作者
Gallego, Victor [1 ,2 ]
Lingan, Jessica [1 ]
Freixes, Alfons [1 ]
Juan, Angel A. [2 ]
Osorio, Celia [2 ]
机构
[1] Euncet Business Sch, Business Analyt Res Grp, Terrassa 08225, Spain
[2] Univ Politecn Valencia, Res Ctr Prod Management & Engn, Alcoy 03801, Spain
关键词
machine learning; digital marketing; algorithms; artificial intelligence; BIG DATA; ARTIFICIAL-INTELLIGENCE; IMPACT;
D O I
10.3390/info15070368
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The integration of machine learning (ML) techniques into marketing strategies has become increasingly relevant in modern business. Utilizing scientific manuscripts indexed in the Scopus database, this article explores how this integration is being carried out. Initially, a focused search is undertaken for academic articles containing both the terms "machine learning" and "marketing" in their titles, which yields a pool of papers. These papers have been processed using the Supabase platform. The process has included steps like text refinement and feature extraction. In addition, our study uses two key ML methodologies: topic modeling through NMF and a comparative analysis utilizing the k-means clustering algorithm. Through this analysis, three distinct clusters emerged, thus clarifying how ML techniques are influencing marketing strategies, from enhancing customer segmentation practices to optimizing the effectiveness of advertising campaigns.
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页数:16
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