银行客户精确营销系统设计与实现

发布时间：2018-01-20 18:41

本文关键词： 精确营销聚类分析交叉营销分析经营周期营销分析　出处：《电子科技大学》2015年硕士论文　论文类型：学位论文

【摘要】：从上世纪70年代开始,全球进行信息化建设。各种的应用信息系统遍布各个行业的角落。在长期的使用过程中,生产了大量的数据,形成了数据的初始化积累。在本世纪初期,世界的IT建设发生了重大变化,从含有大量操作界面的人机交互的信息系统,转变为几乎没有界面的自动化数据挖掘和服务发布型系统,典型模式为web2.0、云服务、数据挖掘等。本文论述了对银行数据密集型行业采用了新兴自动化数据挖掘技术,对银行历史数据进行分析,加工出精确营销数据的系统实现方式。银行从传统的借贷业务产生到存款利率差的主要盈利模式进行转变,对中间业务的收入更加重视;客户也将由大型公司客户,逐步转变为更加重要的中小企业客户和零售客户。在这个情况下,传统的粗放式销售方式,在面对庞大的客户群体和复杂的销售产品时就显得有些力不从心了。本文核心工作包含设计和实现两部分。设计部分,首先对国内外的银行业务发展进行讨论和分析,发现其业务模式已经有了很大的转变。通过对业务模式转变的深入分析,发现在当前的业务模式下,需要更加精确的营销方式。再通过对银行销售业务的调研,确定精确营销需求内容,包括:数据清洗、客户整合、客户评级、客户生命周期管理、客户精确营销数据语言等。同时对银行信息建设的现状进行调研和分析,设计出以数据提取、转换和加载(Extraction-Transformation-Loading,ETL)为主要技术架构,以数据挖掘为手段的技术体系。并根据业务需求,设计出聚类分析的方式,对数据进行处理。在确定技术架构后,进入实现部分。首先具体设计出ETL处理的流程和数据模型;制定出ETL分层处理结构,到达系统的松耦合性。采用KETTEL工具实现了ETL处理过程,完成对银行庞大的客户群体的识别、定位、细分;并在此基础上,使用交叉营销分析、经营周期营销分析两种分析方法实现对客户精确营销的预言。在分析出客户精确营销数据后,再次通过ETL方式将该数据推送到web页面进入商机池。在商机池中,客户经理进行商机认领,实现精确营销。完成整个精确营销系统的实现。本文最后会对课题工作进行总结。得出基于数据挖掘的精确营销能够大大的提高银行的营销效率结论。对于银行这类数据富集行业,有效数据挖掘不仅仅只是提高银行营销效率,还能进行广泛的应用,所以应该加大对数据富集行业的数据挖掘,通过数据分析创造价值。
[Abstract]:Since -30s, information construction has been carried out all over the world. A variety of application information systems have spread all over the corners of various industries. In the long-term use process, a large number of data have been produced. In the beginning of this century, the IT construction of the world has changed greatly, from the human-computer interactive information system with a large number of operating interfaces. An automated data mining and service publishing system with almost no interface, typical for web 2.0, cloud services. Data mining. This paper discusses the use of emerging automated data mining technology in data-intensive banking industries to analyze the historical data of banks. The bank changes from the traditional lending business to the main profit mode of deposit interest rate difference, and pays more attention to the income of intermediate business. Customers will also be transformed from large corporate customers to more important SME and retail customers. In this case, the traditional extensive sales mode. In the face of a large number of customers and complex sales of products appears to be a little inadequate. The core work of this paper includes design and implementation of two parts. The design part. First of all, the development of domestic and foreign banking business has been discussed and analyzed, and found that its business model has changed a lot. Through the in-depth analysis of the transformation of the business model, found in the current business model. Need more accurate marketing methods. Then through the bank sales research, determine the content of precise marketing requirements, including: data cleaning, customer integration, customer rating, customer life cycle management. Customer accurate marketing data language and so on. At the same time, the status of bank information construction is investigated and analyzed, and the data extraction is designed. Transformation and loading Extraction-Transformation-Loading ETL is the main technical architecture. Data mining as the means of the technical system. And according to the business requirements, design a cluster analysis method to deal with the data. After determining the technical framework. First, the process and data model of ETL processing are designed. The ETL hierarchical processing structure is worked out to achieve the loose coupling of the system. The ETL processing process is realized by using KETTEL tools, which can identify, locate and subdivide the huge customer group of the bank. And on this basis, the use of cross-marketing analysis, business cycle marketing analysis of the two analysis methods to achieve accurate customer marketing prediction. After analyzing the customer accurate marketing data. Again, the data is pushed to the web page through ETL to enter the pool of business opportunities. In the pool of business opportunities, the account manager claims the business opportunities. In the end, the thesis will sum up the work of the subject, and draw the conclusion that the accurate marketing based on data mining can greatly improve the marketing efficiency of the bank. This type of data enrichment industry. Effective data mining is not only to improve the efficiency of bank marketing, but also can be widely used, so we should increase the data mining of data enrichment industry, through data analysis to create value.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TP311.52

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