机器学习驱动的信用卡客户细分与营销探究

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关键词：机器学习； K- means聚类；层次聚类；高价值客户挖掘；营销策略制定中图分类号：TP181 文献标识码：A 文章编号：2096-4706（2026）05-0090-06

Machine Learning-driven Exploration of Credit Card Customer Segmentation and Marketing

GE Yanna’， CHEN Chundi1， LI Yanrong'， CAO Liyuan² （1.Guangzhou CollegeofCommere，Guangzhou 511400，China; 2.Dongguan City UnversityDongguan523419，China）

Abstract：This paper takes the credit card consumption datasetas the analysis object and relies on Machine Learning technologyasthecoretltosystematicallycarryutcustomersegmentatioandhigh-valuetargetcustomermiing.Firstlyit gainsin-depthinsightintotheintrinsiccharacteristicsofthedatathroughdatapreprocessingandoptimizesthedatastructure by combining PCAdimensioalityductioandfeaturestandardizatiomethods.Scondly，itcompares theclusteringectsofthe K-means algorithmandthe hierarchicalclusteringalgorithmandfinalldeterminesthattheoptimal numberofclusters is 4.On thisbasis，itdividescustomersinto4groupswithdistinctcharacteristicsandfurtherscreensout11igh-valuetargetcustomers fromthem.Theresearch resultscanprovide quantitative data support fortheformulationof precision marketing plans，the implementationofdynamicrisk managementandcontrol，andthedesignofdiffrentiatedcustomermaintenancestrategies inthe creditcard businessand effectively helpthe businessachieve thedual goals ofrevenue growthandrisk controllability.

Keywords：Machine Learning; K-means clustering; hierarchical clustering; high-value customer mining;marketing strategy formulation

0 引言

当前金融市场竞争激烈，银行信用卡业务面临风险治理弱与客户需求多样化的双重难题。（剩余4585字）