基于客户感知价值的客户细分研究

摘要/Abstract

摘要： 基于客户感知价值进行了客户细分的理论和实证研究，以物流公共信息平台为例提出依据客户感知价值进行客户细分的一般流程：首先利用文献查阅与问卷调查方法确定客户感知价值的驱动因素，接着利用因子分析法对驱动因素变量降维处理，然后利用聚类方法识别客户，再利用决策树方法寻找客户分类规则并分析各类客户特征。最后依据客户特征将物流公共信息平台的客户分为4类：高价值需求客户、中等价值需求客户、低价值需求客户与高性能需求客户，研究结果可以为不同企业实施客户细分提供借鉴和参考。

关键词: 客户细分, 客户感知价值(CPV), 聚类, 决策树

Abstract: Based on customer perceived value (CPV) and using the customer segmentation theory, an empirical study is been conducted. Taking for example the logistics public information platform (LPIP), a general process of performing customer segmentation based on CPV is proposed：Firstly, the driving factors of customer perceived value are determined by a literature review and a questionnaire survey. Secondly, driving factor variables are reduced by a factor analysis. Then, the customer categories are identified by using clustering method. Finally, customer classification rules are found using decision tree method. In the end, according to customer characteristics, customers of LPIP fall into 4 categories: customers expecting high value, customers expecting medium value, customers expecting low value, customers expecting high performance. Research results can provide reference for different enterprises to fractionalize customers.

Key words: customer segmentation, customer perceived value(CPV), cluster, decision tree

宋华，云俊. 基于客户感知价值的客户细分研究[J]. 工业工程, 2015, 18(4): 36-42.

Song Hua, Yun Jun. A Research of Customer Segmentation Based on Customer Perceived Value[J]. Industrial Engineering Journal , 2015, 18(4): 36-42.

参考文献

［1］齐佳音,万岩, 尹涛. 客户关系管理［M］. 北京：北京邮电大学出版社，2009. ［2］吴丽华,张瑜,曹均阔.基于客户感知价值的云计算服务动态定价策略优化方法［J］.计算机与数字工程,2013, 41(2):244-247. Wu Li-hua, Zhang Yu, Cao Jun-kuo. Optimization method of dynamic pricing strategies of cloud computing services based on customeroriented perceived value［J］. Computer & Digital Engineering, 2013，41(2):244-247. ［3］何健,王永贵,石贵成. 关系强度的前置因素及其绩效影响［J］. 管理世界,2009(5):180-181. He Jian, Wang Yong-gui, Shi Gui-cheng. Presage factor relationship strength and its performance influence ［J］. Management World, 2009(5):180-181. ［4］苗瑞,林建良,曹金涛,等.面向产品服务系统的顾客感知价值测量研究［J］.工业工程与管理, 2013,18(2):1-5. Miao Rui, Lin Jian-liang, Cao Jin-tao, et al. Research on the customer perceived value measurement of product service system［J］. Industrial Engineering and Management, 2013,18(2):1-5. ［5］刘英姿,吴昊.客户细分方法研究综述［J］.管理工程学报,2006,20(1):53-57. Liu Ying-zi,Wu Hao. A summarization of customer segmentation methods［J］. Journal of Industrial Engineering/Engineering Management, 2006,20(1):53-57. ［6］林勤,薛云.双聚类算法在电信高价值客户细分的应用［J］.计算机应用,2014,34(6):1807-1811. Lin Qin, Xue Yun. Application of biclustering algorithm in highvalue telecommunication customer segmentation［J］. Journal of Computer Applications, 2014,34(6):1807-1811. ［7］Marcus C. A practical yet meaningful approach to customer segmentation ［J］. The Journal of Consumer Marketing, 1998,15(5):494. ［8］Anton, J. The past, present and future of customer access centers ［J］. International Journal of Service Industry Management, 2000, 11 (2): 120-130. ［9］于红霞,汪波,钱荣.基于三维客户分类价值体系的客户关系管理研究［J］.商业经济与管理,2006(11):43-47. Yu Hong-xia, Wang Bo, Qian Rong. Researches on CRM based on a 3dimension value system of customer classification［J］. Business Economics and Administration, 2006(11):43-47. ［10］褚格林.基于聚类模型的电信客户细分研究［J］.统计与决策,2014(8):176-179. Chu Ge-lin. Telecom customer segmentation study based on clustering model［J］. Statistics and Decision, 2014(8):176-179. ［11］路晓伟,蒋馥,张欣欣.CRM中客户识别的多维框架［J］.软科学,2004,18(1):40-43. Lu Xiao-wei, Jiang Fu, Zhang Xin-xin.The multidimensional framework of customer identification in CRM［J］. Soft Science, 2004,18(1):40-43. ［12］孙树垒,路晓伟,张庆民,等.基于客户识别的客户保持决策模型与定价策略［J］.管理学报,2011(10):1504-1508. Sun Shu-lei, Lu Xiao-wei, Zhang Qing-ming, et al. Decision model and pricing strategies for customer retention based on customer identification［J］. Chinese Journal of Management, 2011(10):1504-1508. ［13］Bourdeau L, Chebat J C, Couturuerr C. Internet consumer value of university students: Email vs Web users［J］. Journal of Retailing and Consumer Services,2002(9):121-141. ［14］孟庆良,韩玉启,吴正刚.电子商务模式下顾客价值度量模型的构建与应用［J］.科技进步与对策, 2006,23(6):148-150. Meng Qin-liang, Han Yu-qi, Wu Zheng-gang. Research on application and measurement model of customer value under e-commerce pattern［J］. Science & Technology Progress and Policy, 2006,23(6):148-150. ［15］雷星辉,张伟.电子商务平台顾客感知价值对购买行为及企业未来销售的影响［J］.上海管理科学,2012,34(08):27-33. Lei Xing-hui, Zhang Wei. Influence of customer perceived value on purchase behavior and enterprise future sales on electronic commerce platform［J］. Shanghai Management Science, 2012,34(08):27-33.

[1]	张和平, 李俊武. 基于模糊c均值聚类算法的控制图模式识别[J]. 工业工程, 2021, 24(5): 108-116.
[2]	吴斌, 宋琰, 程晶, 董敏. 基于密度峰值聚类的VRPTW问题研究[J]. 工业工程, 2020, 23(5): 58-66,74.
[3]	王海燕, 侯琳娜. 基于随机森林的统计控制图模式识别研究[J]. 工业工程, 2019, 22(5): 118-125.
[4]	肖玉徽, 楼振凯. 考虑客户满意度的物流末端节点选址模型及算法[J]. 工业工程, 2019, 22(3): 126-131.
[5]	贾甜, 梁一鸣, 黄威. 基于Kano模型的原型模式系统需求排序方法研究[J]. 工业工程, 2018, 21(2): 87-93,102.
[6]	牛占文, 杨福东, 荆树伟. 基于模糊聚类分析的制造企业精益管理工具分类研究[J]. 工业工程, 2017, 20(4): 1-10.
[7]	李康, 徐海燕, 陈浩. 基于灰色聚类方法的关键链项目工期风险评估[J]. 工业工程, 2017, 20(4): 57-64.
[8]	武小军, 孟苏芳. 基于客户细分和AdaBoost的电子商务客户流失预测研究[J]. 工业工程, 2017, 20(2): 99-107.
[9]	孙一品1，齐剑川1，秦华2，钮伟芳3，苏宁4，钮建伟1. 基于J48决策树算法的大学生社交网络游戏参与原因分析[J]. 工业工程, 2016, 19(6): 116-122.
[10]	李志1，江舟2，周愉峰1. 基于灰色聚类评估的配送中心选址模糊多目标优化模型[J]. 工业工程, 2016, 19(5): 24-32.
[11]	罗文德，陈庆新，毛宁，俞爱林，刘建军. 基于聚类和统计分析的模具工序标准工时制定方法[J]. 工业工程, 2013, 16(4): 126-132.
[12]	郝景新1，2，刘文金1，2，吴新凤1. 基于模糊聚类分析的家具零件成组研究[J]. 工业工程, 2012, 15(5): 51-54.
[13]	王宁，徐济超. 服务产品设计质量保证的质量功能展开集成方法[J]. 工业工程, 2012, 15(5): 66-72.
[14]	涂袁志，孙树栋，李庆贺，王萌. 基于粗糙聚类的航空制造企业零件生产周期分析[J]. 工业工程, 2012, 15(4): 119-124.
[15]	张旭梅，石瀚凌. 基于分类挖掘方法的商业银行个人理财业务客户流失分析[J]. 工业工程, 2011, 14(6): 126-132.