基于商业智能的铁路货运客户精准识别方案  

Study on Accurate Identification of Railway Freight Customers Based on Business Intelligence

作　　者：陈宁[1] 孙晓阳[1] 龚德鹏 CHEN Ning;SUN Xiaoyang;GONG Depeng(School of Transportation and Logistics,Southwest Jiaotong University,Chengdu 610031,China;China Railway Design Corporation,Tianjin 300251,China)

机构地区：[1]西南交通大学交通运输与物流学院,四川成都611756 [2]中国铁路设计集团有限公司,天津300251

出　　处：《综合运输》2018年第7期103-109,共7页China Transportation Review

基　　金：中国铁路总公司科技研究开发计划(2014S14046);中国铁路总公司科技研究开发计划(2015S14002)

摘　　要：铁路货运运能的释放以及市场份额不断下降使得铁路货运急需改善现有的营销模式,完善客户关系管理机制并有效精准识别客户。依托铁路货运既有的大量历史数据,应用商业智能相关技术,提出了铁路货运既有客户细分定位和待开发客户有效识别的方案。首先提出两种类型客户定位识别的总体方案流程,然后构建数据仓库整合内外部数据资源;进一步基于客户特征进行既有客户细分,并对既有客户细分类型运用数据挖掘算法提取属性特征,最后通过信息匹配实现对待开发客户的识别,并针对每一类待开发客户的具体特征提出简要营销服务策略。The need of customer identification is urgent for railway freight as it is at disadvantage in contemporary freight market competition. Here, an integrative method is proposed to acquire and identify characteristics of existing and potential customers by virtual of BI and historical freight data. Firstly, the overall flow of identification models are put forward. Then, a data warehouse is established to integrate internal and external data resources. Further, based on customer characteristics, existing customer segmentation is performed, and data mining algorithms are used to extract attribute features from existing customer segmentation types. Finally, the identification of potential customers is achieved through information matching, and a correspondent service pattern is proposed for identification of potential customers on their own characteristics.

关 键 词：铁路货运 客户识别 商业智能 数据整合 数据挖掘 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论] F532.6[自动化与计算机技术—计算机科学与技术]