现代信息科技2026，Vol.10Issue(5)：90-94,100,6.DOI:10.19850/j.cnki.2096-4706.2026.05.017
机器学习驱动的信用卡客户细分与营销探究
Machine Learning-driven Exploration of Credit Card Customer Segmentation and Marketing
摘要
Abstract
This paper takes the credit card consumption dataset as the analysis object and relies on Machine Learning technology as the core tool to systematically carry out customer segmentation and high-value target customer mining.Firstly,it gains in-depth insight into the intrinsic characteristics of the data through data preprocessing and optimizes the data structure by combining PCA dimensionality reduction and feature standardization methods.Secondly,it compares the clustering effects of the K-means algorithm and the hierarchical clustering algorithm and finally determines that the optimal number of clusters is 4.On this basis,it divides customers into 4 groups with distinct characteristics and further screens out 11 high-value target customers from them.The research results can provide quantitative data support for the formulation of precision marketing plans,the implementation of dynamic risk management and control,and the design of differentiated customer maintenance strategies in the credit card business,and effectively help the business achieve the dual goals of revenue growth and risk controllability.关键词
机器学习/K-means聚类/层次聚类/高价值客户挖掘/营销策略制定Key words
Machine Learning/K-means clustering/hierarchical clustering/high-value customer mining/marketing strategy formulation分类
信息技术与安全科学引用本文复制引用
葛艳娜,陈春娣,理艳荣,曹礼园..机器学习驱动的信用卡客户细分与营销探究[J].现代信息科技,2026,10(5):90-94,100,6.基金项目
广东省高等教育教学改革项目(2023JXGG05) （2023JXGG05）
数智融合优秀课程项目(XJYXKC202539) （XJYXKC202539）
