| 基于K-means聚类的快递企业客户细分方法 |
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| 引用本文： | 覃文文,戢晓峰.基于K-means聚类的快递企业客户细分方法[J].世界科技研究与发展,2011(6):955-958,969. |
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| 作者姓名： | 覃文文 戢晓峰 |
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| 作者单位： | [1]昆明理工大学交通工程学院,昆明650500 [2]昆明泛亚交通物流研究院,昆明650500 |
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| 基金项目： | 云南省应用基础研究项目（2010ZC062）,公路工程省部共建教育部重点实验室开放基金（k0100107）资助项目 |
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| 摘 要： | 为了实现对快递企业客户的科学划分，制定差异化的客户营销策略，建立了一种基于K-means聚类的客户细分模型。对快递企业呼叫中心的客户相关数据特征进行了分析与预处理，确定了合理的客户细分变量，并建立了基于呼叫中心数据挖掘的客户细分流程。以某快递企业为例对客户细分方法进行了验证。结果表明该方法能够有效区分快递客户为敏感客户、节俭客户、高端客户、潜在客户与优质客户等五类，为进一步营销方案的设计提供决策支持。
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| 关 键 词： | 客户细分 数据挖掘 快递企业 K-meas 聚类 |
Researches on Customer Segmentation of Express Enterprise Based on K-means Clustering |
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| QIN Wenwen,JI Xiaofeng.Researches on Customer Segmentation of Express Enterprise Based on K-means Clustering[J].World Sci-tech R & D,2011(6):955-958,969. |
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| Authors: | QIN Wenwen JI Xiaofeng |
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| Institution: | 1. Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming 650500 ; 2. Kunming Academy of Pan-Asia Traffic ＆ Logistics, Kunming 650500) |
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| Abstract: | For the scientific division of express enterprise customers to develop differentiated customer marketing strategy, a customer segmen- tation model is established based on K - means clustering. The characteristics of customer data in express enterprise call center were analyzed and pre -treated to determine the reasonable customer segmentation variables,with a customer segulentation process built based＇on the call center data mining. The customer segmentation method has been validated from an example. The results show that the method can effectively distinguish express customer for sensitive customers, thrifty customers, high-end customers, potential customers, and high quality customers. Furthermore, decision support is provided for the design of marketing programs. |
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| Keywords: | customer segmentation data mining express enterprise K-means cluster |
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