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Research on Customer Group Division and Precision Marketing Based on the DWKCN Algorithm.

Authors :
Li, Yanhong
Source :
Journal of Advanced Computational Intelligence & Intelligent Informatics. May2024, Vol. 28 Issue 3, p541-551. 11p.
Publication Year :
2024

Abstract

Classifying customers according to their characteristics can effectively meet the genuine needs of different customer groups. It also helps enterprises formulate reasonable marketing strategies and obtain considerable profits. Currently, there are many ways to classify customers. However, the procedures involved are complicated and cannot comprehensively and objectively reflect customer characteristics. Therefore, a customer group classification model is designed based on the deep cross network (DCN). The DCN algorithm can automatically learn simple data features, achieving data clustering. For the defects in this model, the deep weighted k-means clustering network (DWKCN) customer group classification method is constructed, improving the DCN algorithm. From the results, the algorithm has a high accuracy of 99.5%. Therefore, the proposed DWKCN algorithm can realize the customer group's precise division and the marketing plan design, providing the references for different types of customers to formulate personalized needs. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13430130
Volume :
28
Issue :
3
Database :
Academic Search Index
Journal :
Journal of Advanced Computational Intelligence & Intelligent Informatics
Publication Type :
Academic Journal
Accession number :
177325998
Full Text :
https://doi.org/10.20965/jaciii.2024.p0541