数据挖掘技术在房地产客户关系管理中的应用研究

发布时间：2018-03-14 17:24

本文选题：客户关系　切入点：房地产　出处：《天津大学》2016年硕士论文　论文类型：学位论文

【摘要】：在竞争激烈的房地产市场中,客户是企业生存的基础,维系客户关系和拓展客户资源对于房地产企业生存和发展具有重要意义。本文在深入研究客户细分相关参考文献的基础上,构建了客户细分的指标体系,并将数据挖掘算法应用于客户细分中。根据实际的房地产客户关系管理的业务功能需求,设计实现了以B/S为架构的客户关系管理系统,对房地产客户关系的数据进行有效管理和维护。本文的主要研究内容如下:(1)通过房地产企业销售部门的实际调研获取客户关系管理的重点内容及需要切实解决的实际问题,归结了系统所需实现的功能需求,实现了对系统的总体架构及功能模块的设计。(2)根据房地产企业客户的特征,设计客户细分指标体系及客户细分模型。在深入研究客户细分的相关参考文献的基础上,从客户价值及客户忠诚度两个方面构建了客户细分的指标体系。(3)利用K-means算法实现对客户信息数据的处理,设计了客户细分模型框架。同时,为提升算法执行的效率,研究并采用了主成分分析法对采集的数据降维。(4)根据客户细分指标体系的需求,从企业中抽取的40个客户样本数据,并利用SPSS软件对样本数据进行预处理及主成分分析研究,获取客户细分结果,并针对不同类型的客户提出了不同的客户关系管理建议。(5)根据系统用户需求分析及设计实现了系统各个模块的开发。
[Abstract]:In the competitive real estate market, customers are the basis for the survival of enterprises. It is of great significance to maintain customer relationship and expand customer resources for the survival and development of real estate enterprises. Based on the in-depth study of relevant references on customer segmentation, this paper constructs an index system of customer segmentation. And the data mining algorithm is applied to customer segmentation. According to the business function requirements of real estate customer relationship management, a customer relationship management system based on B / S architecture is designed and implemented. The main research contents of this paper are as follows: 1) get the key contents of customer relationship management and the practical problems that need to be solved through the actual investigation of the sales department of real estate enterprises. The functional requirements of the system are summed up, and the overall structure of the system and the design of the function module are realized. (2) according to the characteristics of the real estate enterprise customers, Design customer segmentation index system and customer segmentation model. On the basis of in-depth study of customer segmentation related references, This paper constructs the index system of customer segmentation from two aspects of customer value and customer loyalty. It uses K-means algorithm to deal with customer information data, designs the framework of customer segmentation model, at the same time, in order to improve the efficiency of algorithm execution, According to the requirement of customer subdivision index system, 40 customer sample data are extracted from enterprises, and the sample data are preprocessed and analyzed by SPSS software. The customer segmentation results are obtained, and different customer relationship management suggestions are put forward for different types of customers. (5) based on the analysis and design of the system user demand, the development of each module of the system is realized.
【学位授予单位】：天津大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：F274;F299.233.4;TP311.13

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