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Research on Customer Group Division and Precision Marketing Based on the DWKCN Algorithm
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Research on Customer Group Division and Precision Marketing Based on the DWKCN Algorithm
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Journal Article
Research on Customer Group Division and Precision Marketing Based on the DWKCN Algorithm
2024
Overview
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.
Publisher
Fuji Technology Press Co. Ltd
