基于可拓数据挖掘的客户价值分析软件设计与实现
发布时间：2018-07-15 19:34
【摘要】：随着信息技术和“以客户为中心”的经营模式发展,客户价值逐渐成为客户关系管理(CRM)的核心;科学、全面地掌握和评估客户价值大小并采取有效的、正确的策略提升客户价值,成为企业有效管理客户资源和把握市场的关键。因此,有效的客户价值管理和营销策略对企业的发展具有十分重要的意义。利用数据挖掘技术处理海量的客户数据,根据客户价值理论对客户进行细分、客户流失预测等是客户价值领域研究的热点技术。由于现有的数据挖掘技术更多的是从静态数据中获取静态知识,忽略了变换对数据影响作用,故基于数据挖掘的客户价值分析系统不能挖掘变换作用的知识及变换导致客户价值变化的规律。然而,这些变换知识对帮助企业解决客户价值矛盾问题具有指导意义。 本文提出将可拓学和可拓数据挖掘技术应用到客户价值分析中,研究设计与实现一种基于可拓数据挖掘的客户价值分析软件,用于挖掘客户价值变换的知识,为企业掌握各种营销变换下客户价值变化规律和衡量营销策略优劣提供方便、可靠的工具。 本文主要完成了以下研究工作： 1.研究客户价值理论知识,客户价值评价特征选取方法,并设计与实现了具备适用性、灵活性的客户价值评价体系。 2.介绍了可拓学和可拓数据挖掘理论知识,信息元形式化表示客户信息及可拓数据挖掘过程。 3.研究了客户价值各要素的关联函数和综合关联函数模型构造方法,提取发生传导变换的传导特征方法,及获取客户价值可拓知识的技术规则与算法设计。 4.对JFreechart可视化图表技术进行研究,实现了图形化展示客户价值分析结果。 5.详细设计了基于可拓数据挖掘的客户价值分析软件架构、软件功能模块划分,通过采取动态库和数据转换服务以屏蔽底层数据,从信息元特征中提取客户价值评价指标,分析企业客户价值情况,实现了客户价值可拓分类知识、传导知识获取及挖掘结果可视化显示。 最后,以某服装企业的应用为例,研究该企业的客户价值可拓分类知识和传导知识的挖掘,表明获取的知识对企业调整营销策略、采取差异化服务具有很大的参考价值。 本文创新之处在于： 1.将可拓数据挖掘技术应用于客户价值分析中,设计实现基于可拓数据挖掘的客户价值分析软件,帮助企业解决衡量策略作用规律和优劣,动态地掌握客户价值变化情况,弥补了当时基于传统数据挖掘的客户价值系统不能挖掘变换知识的不足,为客户价值系统提供新的解决思路。 2.现有的可拓数据挖掘软件或系统往往采用的是单一固定形式的关联函数模型,而本文实现了三种基本的关联函数模型,并由需求选择具体的模型;通过建立动态表,数据转换和动态建立评价体系,动态识别传导特征能够适用于不同企业进行可拓分类知识和传导知识挖掘,具有更强的通用性和灵活性。 本文是广东省自然科学基金资助项目“基于可拓数据挖掘的客户价值研究”(批准号：10151009001000044)的研究成果。
[Abstract]:With the development of information technology and "customer centered" management model, customer value has gradually become the core of customer relationship management (CRM); scientific, comprehensive grasp and evaluation of the value of customer value, and take effective and correct strategies to improve customer value, become the key to the effective management of customer resources and the market. Effective customer value management and marketing strategy are of great significance to the development of the enterprise. Using data mining technology to deal with mass customer data, subdividing customers according to customer value theory, prediction of customer loss and so on is a hot technology in the field of customer value research. The state data acquires static knowledge and ignores the influence of transformation on data. Therefore, the customer value analysis system based on data mining can not excavate the knowledge of transformation and change the law of customer value change. However, these transformation knowledge is of guiding significance to help enterprises to solve the contradiction of customer value.
This paper puts forward the application of extenics and extension data mining to customer value analysis, and studies the design and implementation of a customer value analysis software based on extension data mining, which is used to excavate the knowledge of customer value transformation, and for the enterprise to master the change rule of customer value and measure the marketing strategy under various marketing changes. It is a reliable tool.
This paper mainly completed the following research work:
1. study customer value theory knowledge, customer value evaluation feature selection method, and design and implement a customer value evaluation system with applicability and flexibility.
2. introduced extenics and extension data mining theory knowledge, information element formalized customer information and extension data mining process.
3. the related function of each factor of customer value and the construction method of the integrated association function model are studied. The method of conducting the conduction characteristic of the conduction transformation is extracted and the technical rules and algorithms for obtaining the extension knowledge of customer value are designed.
4. research on JFreechart visualization chart technology, and achieve graphical display of customer value analysis results.
5. the architecture of customer value analysis software based on extension data mining is designed in detail, and the software function module is divided. By adopting dynamic library and data conversion service to shield the underlying data, extracting customer value evaluation index from information element characteristics, analyzing customer value situation, realizing customer value extension classification knowledge and conducting knowledge. The visual display of the acquisition and mining results.
Finally, taking the application of a garment enterprise as an example, this paper studies the enterprise's customer value extension classification knowledge and the transmission knowledge mining. It shows that the acquired knowledge is of great reference value to the enterprise adjustment marketing strategy and the differential service.
The innovation of this article lies in:
1. apply the extension data mining technology to the customer value analysis, design and implement the customer value analysis software based on the extension data mining, help the enterprise to solve the law and the good and bad of the measurement strategy, and dynamically grasp the change of the customer value, and make up for the knowledge that the customer value system based on the traditional data mining can not be excavated. Lack of knowledge provides a new solution for customer value system.
2. the existing extension data mining software or system often uses a single fixed form of association function model, and this paper implements three basic association function models, and selects specific models from demand. By establishing dynamic tables, data conversion and dynamic establishment of evaluation system, dynamic identification of transmission features can be applied to different enterprises. The extension knowledge and knowledge mining are more versatile and flexible.
This paper is the research achievement of the Guangdong Provincial Natural Science Foundation Project "customer value research based on extension data mining" (approval number: 10151009001000044).
【学位授予单位】：广东工业大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP311.13
本文编号：2125154
[Abstract]:With the development of information technology and "customer centered" management model, customer value has gradually become the core of customer relationship management (CRM); scientific, comprehensive grasp and evaluation of the value of customer value, and take effective and correct strategies to improve customer value, become the key to the effective management of customer resources and the market. Effective customer value management and marketing strategy are of great significance to the development of the enterprise. Using data mining technology to deal with mass customer data, subdividing customers according to customer value theory, prediction of customer loss and so on is a hot technology in the field of customer value research. The state data acquires static knowledge and ignores the influence of transformation on data. Therefore, the customer value analysis system based on data mining can not excavate the knowledge of transformation and change the law of customer value change. However, these transformation knowledge is of guiding significance to help enterprises to solve the contradiction of customer value.
This paper puts forward the application of extenics and extension data mining to customer value analysis, and studies the design and implementation of a customer value analysis software based on extension data mining, which is used to excavate the knowledge of customer value transformation, and for the enterprise to master the change rule of customer value and measure the marketing strategy under various marketing changes. It is a reliable tool.
This paper mainly completed the following research work:
1. study customer value theory knowledge, customer value evaluation feature selection method, and design and implement a customer value evaluation system with applicability and flexibility.
2. introduced extenics and extension data mining theory knowledge, information element formalized customer information and extension data mining process.
3. the related function of each factor of customer value and the construction method of the integrated association function model are studied. The method of conducting the conduction characteristic of the conduction transformation is extracted and the technical rules and algorithms for obtaining the extension knowledge of customer value are designed.
4. research on JFreechart visualization chart technology, and achieve graphical display of customer value analysis results.
5. the architecture of customer value analysis software based on extension data mining is designed in detail, and the software function module is divided. By adopting dynamic library and data conversion service to shield the underlying data, extracting customer value evaluation index from information element characteristics, analyzing customer value situation, realizing customer value extension classification knowledge and conducting knowledge. The visual display of the acquisition and mining results.
Finally, taking the application of a garment enterprise as an example, this paper studies the enterprise's customer value extension classification knowledge and the transmission knowledge mining. It shows that the acquired knowledge is of great reference value to the enterprise adjustment marketing strategy and the differential service.
The innovation of this article lies in:
1. apply the extension data mining technology to the customer value analysis, design and implement the customer value analysis software based on the extension data mining, help the enterprise to solve the law and the good and bad of the measurement strategy, and dynamically grasp the change of the customer value, and make up for the knowledge that the customer value system based on the traditional data mining can not be excavated. Lack of knowledge provides a new solution for customer value system.
2. the existing extension data mining software or system often uses a single fixed form of association function model, and this paper implements three basic association function models, and selects specific models from demand. By establishing dynamic tables, data conversion and dynamic establishment of evaluation system, dynamic identification of transmission features can be applied to different enterprises. The extension knowledge and knowledge mining are more versatile and flexible.
This paper is the research achievement of the Guangdong Provincial Natural Science Foundation Project "customer value research based on extension data mining" (approval number: 10151009001000044).
【学位授予单位】：广东工业大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP311.13
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