基于K-means聚类算法的物流客户分类及R语言实现  

Logistics Customer Classification and R Language Implementation Based on K-means Clustering Algorithms

作　　者：姜晓红[1] 王野 郑琰[1] 余伟[1] JIANG Xiao-hong;WANG Ye;ZHENG Yan;YU Wei(Automotive and Transportation College of Nanjing Forest University,Nanjing 210037,China)

机构地区：[1]南京林业大学汽车与交通工程学院,江苏南京210037

出　　处：《物流工程与管理》2018年第12期66-68,65,共4页Logistics Engineering and Management

基　　金：2017年中国物流学会中国物流与采购联合会研究课题(2017CSLKT3-035)

摘　　要：对物流企业客户的聚类能找出具有相同特征的客户群并予以区分,进而采取差异化营销策略及方案能够更加精准地服务物流企业客户,提升客户关系与企业运营效益。文中采用R语言做K-means聚类分析,将实例物流企业客户群体分为基础客户、重要客户、贵宾客户,通过概率密度函数图、研究样本散点分布图分析不同群体的分布特征,有针对性地提出物流企业客户差异化的营销方案,以确保提出科学合理的营销手段和方案设计。The clustering of logistics enterprise customers could identify and distinguish customer groups with the same characteristics.The differentiated marketing strategies and solutions could be adopted to serve logistics enterprise customers more accurately,and improve customer relationship and business operation efficiency.R language was used to do K-means cluster analysis,and the example logistics enterprise customers were divided into basic customers,important customers and VIP customers.Through the probability density function graph and the research sample scatter distribution map,the distribution characteristics of different groups were analyzed.The differentiated marketing plan was sexually proposed for logistics enterprise customers to ensure the development of scientific and rational marketing tools and program design.

关 键 词：K-MEANS聚类算法 物流客户 分类 营销方案 R语言 

分 类 号：F251[经济管理—国民经济]