让客户知识智能化

目前大多CRM应用的重点放在了客户交互，客户数据的收集与分析上，其结果是缺乏对面向客户的决策提供有效客户知识的能力。反过来讲，仅有客户知识是不够的，还必须有效地管理，使用客户知识，才能为企业带来价值。以一个客户的超市消费为例，某客户常年在一个超市消费，却发现该超市对他的消费偏好几乎是一无所知。这主要因为超市管理者仅注意收集了该客户的消费额，而不会利用该客户多次消费的信息挖掘其消费偏好方面的知识。例子中的消费偏好就是客户知识。     

客户关系管理系统的设计

客户关系管理系统(CRM--Customer Relationship Managerment)对市场、客户信息资源进行整合，在企业内部达到资源共享，从而提高了服务质量和服务水平，提高了客户的忠诚度，也使得企业能够更容易地开发新的客户资源，增强了企业的市场竞争能力。本文对CRM系统的设计提出了一些看法，阐述了数据挖掘在CRM系统当中的应用。     

不同业态的CRM实际应用

如同BI,CRM只是一种IT应用系统,CRM如何应用、应用到何种程度,要由使用者使用状况而定。CRM系统在零售企业内不会单独存在,它需要POS系统支持,也需要财务方面配合,还需要ERP系统支持。零售企业想要对客户消费信息进行锁定跟踪分析并维护使之成为忠实客户,需要由CRM进行建模分析,根据客户消费行为习惯进行产品优化组合调整。     

分析型CRM系统--KDACRM的软件体系结构

分析型CRM使用数据挖掘技术对客户数据进行分析，并预测客户未来的行为。分析型CRM的主要功能有客户保持，交叉营销，市场划分和风险评估。本文介绍了一个分析型CRM系统——KDACRM的软件体系结构，并阐述了各个功能模块的作用和实现的方法。     

CRM环境下面向知识发现的数据分类技术的应用研究

为提高CRM对市场活动和销售活动的分析能力，本文提出将数据挖掘技术应用于CRM系统中，采用数据分类方法从CRM数据库的大量信息中发现企业产品的销售规律和客户群的特征。讨论了数据分类的定义和方法，介绍了决策树分类和朴素贝叶斯分类的算法，并给出了具体的数据分类实例，以期为企业更好地掌握市场动态以及潜在客户的挖掘提供有力的技术支持。     

面向CRM系统的数据仓库的设计与实现

介绍了CRM系统的相关知识,阐述了数据仓库技术在CRM系统中应用的必然性,给出了一个基于数据仓库技术的分析型CRM系统的体系结构图,并且针对某网上书店,以客户购买主题为例,提出了该分析型CRM系统中客户信息数据仓库模型的设计方案,具体阐述了概念模型设计、逻辑模型设计和物理模型设计,并以MS SQL Server 2000平台为基础,给出了具体的实现,在企业引入分析型CRM系统时为构建数据仓库提供了参考依据.     

数据仓库技术在CRM中的应用

介绍了客户信息管理(CRM)系统以及数据仓库技术,着重分析了数据仓库技术在CRM中的作用,并给出基于数据仓库技术的CRM模型框架和客户信息数据模型。     

广东电信公话业务中CRM系统的研究与探索

客户关系管理系统(CRM)的计算机应用是指利用计算机信息技术，针对营销、销售、客户服务、客户交互和客户分析等面向客户的业务领域而设计出的各种软件功能模块的组合，来最大限度地支持CRM的经营理念在企业范围内的具体实践。首先对CRM进行了简单的介绍，然后结合公话业务的特点，对公话业务CRM的设计进行了一定的探索，界定了公话业务CRM应用所涉及的领域，设计了基于分析型公话CRM应用系统的系统模型、基本功能模块及其设计平台。     

数据挖掘技术--模糊聚类分析在客户关系管理中的应用研究

企业的竞争重点正在经历着从以产品为中心向以客户为中心的转移，客户关系管理作为一种全新的管理、经营理念，越来越引起商家的重视。在数据仓库中进行数据挖掘正逐渐成为CRM中最核心的部分。本文从CRM中数据分析的不确定性，提出采用模糊聚类的分析方法来分析、预测客户行为。     

知识管理在CRM中的应用

随着信息技术的发展，客户关系管理和知识管理成为当前的热点研究领域，客户关系管理离不开知识管理的支持。本文通过对知识管理概念的分析，提出了具有知识管理支撑系统的CRM系统，以支持客户关系在企业中的实际应用。     

Customer relationship management mechanisms: A systematic review of the state of the art literature and recommendations for future research

In the information systems, customer relationship management (CRM) is the overall process of building and maintaining profitable customer relationships by delivering superior customer value and satisfaction with the goal of improving the business relationships with customers. Also, it is the strongest and the most efficient approach to maintaining and creating the relationships with customers. However, to the best of our knowledge and despite its importance, there is not any comprehensive and systematic study about reviewing and analyzing its important techniques. Therefore, in this paper, a comprehensive study and survey on the state of the art mechanisms in the scope of the CRM are done. It follows this goal by looking at five categories in which CRM plays a significant role: E-CRM, knowledge management, data mining, data quality and, social CRM. In each category, a couple of studies are presented and determinants of CRM are described and discussed. The major development in these five categories is reviewed and the new challenges are outlined. Also, a systematic literature review (SLR) in each of these five categories is provided. Furthermore, insights into the identification of open issues and guidelines for future research are provided.     

Exploring the role of customer relationship management (CRM) systems in customer knowledge creation

This study explores how customer relationship management (CRM) systems support customer knowledge creation processes [48], including socialization, externalization, combination and internalization. CRM systems are categorized as collaborative, operational and analytical. An analysis of CRM applications in three organizations reveals that analytical systems strongly support the combination process. Collaborative systems provide the greatest support for externalization. Operational systems facilitate socialization with customers, while collaborative systems are used for socialization within an organization. Collaborative and analytical systems both support the internalization process by providing learning opportunities. Three-way interactions among CRM systems, types of customer knowledge, and knowledge creation processes are explored.     

Customer''s time-variant purchase behavior and corresponding marketing strategies: an online retailer''s case

The traditional customer relationship management (CRM) studies are mainly focused on CRM in a specific point of time. The static CRM and derived knowledge of customer behavior could help marketers to redirect marketing resources for profit gain at the given point in time. However, as time goes on, the static knowledge becomes obsolete. Therefore, application of CRM to an online retailer should be done dynamically in time. Though the concept of buying-behavior-based CRM was advanced several decades ago, virtually little application of the dynamic CRM has been reported to date.

In this paper, we propose a dynamic CRM model utilizing data mining and a monitoring agent system to extract longitudinal knowledge from the customer data and to analyze customer behavior patterns over time for the retailer. Furthermore, we show that longitudinal CRM could be usefully applied to solve several managerial problems, which any retailer may face.     

Forecasting social CRM adoption in SMEs: A combined SEM-neural network method

The growth of social media usage questions the old-style idea of customer relationship management (CRM). Social CRM strategy is a novel version of CRM empowered by social media technology that offers a new way of managing relationships with customers effectively. This study aims to forecast the predictors of social CRM strategy adoption by small and medium enterprises (SMEs). The proposed model used in this study derived its theoretical support from IT/IS, marketing, and CRM literature. In the proposed Technology-Organization-Environment-Process (TOEP) adoption model, several hypotheses are developed which examine the role of Technological factors, such as Cost of Adoption, Relative Advantages, Complexity, and Compatibility; Organizational factors, such as IT/IS knowledge of employee, and Top management support; Environmental factors such as Competitive Pressure, and Customer Pressure; and Process factors such as Information Capture, Information Use, and Information Sharing; all having a positive relationship with social CRM adoption. This research applied a following two staged SEM-neural network method combining both structural equation modelling (SEM) and neural network analyses. The proposed hypothetical model is examined by using SEM on the collected data of SMEs in Kuala Lumpur, the central city of Malaysia. The SEM approach with a neural network method can be used to investigate the complicated relations involved in the adoption of social CRM. The study finds that compatibility, information capture, IT/IS knowledge of employee, top management support, information sharing, competitive pressure, cost, relative advantage, and customer pressure are the most important factors influencing social CRM adoption. Remarkably, the results of neural network analysis show that compatibility and information capture of social CRM are the most significant factors which affect SMEs' adoption of this form of customer relationship management. The outcomes of this research benefit executives' decision-making by identifying and ranking factors that enable them to discover how they can advance the usage of social CRM in their firms. Furthermore, the findings of this study can help the managers/owners of SMEs assign their resources, according to the ranking of social CRM adoption factors, when they are making plans to adopt social CRM. This study differs from previous studies as it proposes an innovative new approach to determine what influences the adoption of social CRM. By proposing the TOEP adoption model, additional information process factors advance the traditional TOE adoption model.     

Study of the wireless/wire integration CRM Gateway for the effective application of Event CRM for small and medium sized enterprises

The CRM System, which maximizes business profits by pursuing a continuous relationship with customers, is based on an analytical CRM that sets up a marketing strategy by analyzing customer information. However, thanks to the technological development of the Internet and mobile phones, customer contact is being carried out through a variety of channels. Yet currently, the needs of customers are not being addressed in a timely manner due to a weak system that cannot immediately deal with customer requests and because of which customer information is not administered in a systematic manner.Therefore, rather than focusing on off-line-focused analytical CRM, it is necessary to concentrate on real time CRM that reflects the aspects of the operative or collaborative CRM. This study also develops an Event CRM solution that can bring satisfaction to customers when they want it by systematizing the contact points of customers, which constitute various institutions and channels.The CRM model that this study presents is the support of Event CRM services for all business types against the backdrop of a wireless/wire environment, and the support of small and medium sized companies, which are burdened by information management costs, to meet the demand for CRM.In order to present the wireless/wire integration CRM Gateway Model, the study focuses on insurance CRM services.When a customer event arises through various channels such as the Internet, SFA or CTI, the event data are transferred through a standardized form. Based on these data, the campaign and service is then extracted and analyzed with the Event CRM Gateway Engine. A match is immediately made between the saved rules and the campaign and services that best fit the customer. Finally, the information is provided to the customer via a mobile phone or website.     

基于商务网站CRM的Web挖掘工具架构技术探讨

CRM是一种关系营销,注重保留客户,建立长期稳定的关系。通过本文所架构的基于CRM的Web挖掘工具可挖掘出商务网站客户关系管理方面的许多有用信息,如潜在客户群体信息、重要页面信息、用户的兴趣爱好信息等,从而为电子商务网站在客户获取、客户保持等方面策略的制定提供了一定的依据,促进商务网站健康、有序的发展。     

数据挖掘技术在民航CRM中的应用

进行客户关系管理系统建设,是当今各大航空公司争取竞争优势的重要手段。数据挖掘技术在CRM的实施中起着关键的作用。文章分别介绍了数据挖掘技术和CRM技术,具体介绍了在民航CRM建设中用到的决策树方法和模糊聚类方法这两种数据挖掘方法,并作了实验分析。最后对数据挖掘技术在民航中的应用作了展望。     

基于数据挖掘的CRM分析

进行客户关系管理系统建设,是企业争取竞争优势的重要手段,数据挖掘技术在CRM的实施中起着关键的作用。文章介绍了数据挖掘技术和CRM技术,具体介绍了在酒店CRM建设中用到的决策树和模糊聚类这两种数据挖掘的实现方法,并做出了实验分析。