通信企业CRM中数据挖掘的应用研究

通信企业CRM的构建目标是为了使服务内容、服务方式、服务质量、经营管理以及服务意识不断提升与完善,赢得更多的客户并且提高客户的忠诚度和满意度,挖掘客户潜在价值以及降低销售和管理成本。本文通过通信CRM系统的框架结构、CRM中数据仓库的作用、通信CRM中数据挖掘的具体应用三个方面论述了详细论述了通信企业CRM中数据挖掘的应用。     

通信企业CRM中数据挖掘的应用研究

通信企业CRM的构建目标是为了使服务内容、服务方式、服务质量、经营管理以及服务意识不断提升与完善．赢得更多的客户并且提高客户的忠诚度和满意度，挖掘客户潜在价值以及降低销售和管理成本。本文通过通信CRM系统的框架结构、CRM中数据仓库的作用、通信CRM中数据挖掘的具体应用三个方面论述了详细论述了通信企业CRM中数据挖掘的应用。     

数据挖掘技术在中国移动CRM中的应用

CRM是一种帮助企业向客户提供优质服务的工具,在CRM中利用数据挖掘技术不断的收集、分析客户资料,从而达到保有优质老客户、获取新顾客的目的,帮助企业制定有效的营销策略,提高企业的收益率。     

基于电商平台国际贸易中CRM的研究

伴随着国家两化融合的推进,信息化已经成为各行业发展的助推剂。传统的国际贸易业务模式已经无法适应当前高速发展的信息化时代,随着当前电子商务平台的广泛发展,传统的客户关系管理方式已经无法适用电商平台下的国际贸易模式,新的客户关系管理(CRM)融合了大数据、数据挖掘等技术颠覆了传统的CRM模式,实现了企业、客户的实时连接,使得企业能够实时了解客户需求,从而为客户提供更好的、更合适的产品。主要介绍了电商平台下的CRM模式以及其在国际贸易中的应用研究。     

数据挖掘在汽车销售企业CRM中的应用

数据挖掘技术在汽车销售企业客户关系管理中的有效应用,有助于跟踪发现业务发展的趋势,预测未知的结果,并帮助企业分析出完成任务所需的关键因素,以达到增加收入、降低成本的目的。文章通过具体的实验:利用聚类分析的K-Means算法对汽车销售企业客户资料进行挖掘,为企业预售车型找出其目标客户,为汽车的销售提供指导性的服务,帮助企业提高销售的成功机率。     

神经网络算法在CRM中的应用

神经网络算法能通过对网络的训练,使客户关系管理系统中客户行为做出预测,便于企业更好为客户服务,改善客户关系,挽留客户.本文就神经网络算法的CRM应用做了相关的探讨.     

A conceptual model for acceptance of social CRM systems based on a scoping study

Recent developments in information technology and Web services have increased the potential for creating more rapid and extensive social networks and business relationships. Web 2.0 technologies, commonly referred to as online social media, have become important tools within the growth of information and communication technology (ICT) in the last few years. Web 2.0 tools such as blogs, Wiki and other services, which are widely used by individuals, also have an effect on customer relationship management (CRM) systems. Consequently, social CRM (SCRM) is emerging as a new paradigm for integrating social networking in more traditional CRM systems. However, social CRM is yet to be fully utilised as a value-adding tool in improving customer relationships. This paper reports on a scoping study that explored the current situation of CRM adoption in banking industry in Saudi Arabia. The aim of this paper is to identify the factors that may influence businesses and customers’ adoption of social CRM. Various models have been proposed to study ICT and information systems acceptance and usage. This paper proposes an enhancement to one of these models, specifically the Technology Acceptance Model (TAM), by incorporating a range of factors identified in the social networking and business relationships literature believed to influence social CRM adoption. In particular, the model proposes that familiarity, caring behaviour, sharing information and perceived trustworthiness can generate cognitive view about the relationships between employees and customers. This view besides Web 2.0 features may offer a way of analysing the potential adoption of social CRM.     

IT alignment strategies for customer relationship management

Customer relationship management (CRM) is the overall process of building and maintaining profitable customer relationships by delivering superior customer value and satisfaction. A CRM strategy involves the entire enterprise and is employed on an ongoing basis. Despite the fact that CRM projects incur huge expenditures, a large percentage fails to achieve the stated objectives. Failure in CRM initiatives could be avoided if a firm's CRM strategies are intelligently linked with its employees, customers, channels, and IT infrastructure. In this paper, we focus on those linkages, particularly on the linkages between an organization's CRM strategies and its IT infrastructure. Even though the relationships between IT and business strategies have been extensively explored in the IT alignment literature, prior research has not addressed how a firm's CRM strategies are aligned with its IT infrastructure. In this paper, we investigate the issues relating to CRM-IT alignment based on an in-depth case study of a large, well-known Internet travel agency.     

基于WebService的CRM接口设计与实现

随着网络业务的迅速普及,各种宽带接入用户的数量日益增长,使得电信运营商迫切需要开发相关的预处理系统,有效提高前台业务系统的响应速度、处理能力与服务质量,以提高客户满意度。由于预处理系统需要整合多个前后台业务系统的功能,从而需要在各种异构系统中实现跨平台通信。WebService是一种通用模型,可以在任何支持网络通信的平台上运行。本文分析基于WebService的CRM接口,介绍其具体设计与实现方案。     

银行客户关系管理与数据挖掘的应用

客户关系管理是一种全新的商业理念，为处理公司与客户之间的关系提供了新的管理模式。数据挖掘是一门新兴的信息处理技术，在商业信息的提取和利用中发挥着日益重要的作用。从数据挖掘的定义和本质出发，阐述了客户关系管理的概念、构成和发展趋势，分析了数据挖掘技术在银行客户关系管理中的应用。     

以客户为中心的CRM体系结构

客户关系管理系统（CRM）是提高企业核心竞争力的有力保障。但现有CRM产品存在某些缺陷，如不以客户为核心进行客户服务、客户服务过程自动化缺乏柔性，以及系统各功能模块协同能力较差等。针对上述问题，提高了以业务过程分类为基础的，基于事件驱动、工作流技术和ECA规则实现CRM系统体系结构的方法。该体系结构能够有效地解决目前CRM产品中的上述问题，为改善现有CRM产品的性能和开发性能更优的产品提供了一种新的手段。     

Web数据挖掘在企业CRM中的应用

CRM的本质在于通过WWW的渠道,在营销、销售、服务和支持四个方面与客户建立良好的关系,从而提高企业收益。在电子商务中,提高客户忠诚度保持住客户,实现交叉销售等成为电子商务成败的一个关键问题。而Web数据挖掘能在电子商务中更好地运作CRM,建立良好客户关系的一种解决方法。该文研究了Web数据挖掘技术在CRM中的应用。     

Moving beyond the direct impact of using CRM systems on frontline employees' service performance: The mediating role of adaptive behaviour

Despite substantial investments in customer‐relationship‐management (CRM) systems, companies continue to experience pain rather than profit. Meanwhile, the concept of “adaptive behaviour” of frontline employees has received little attention in the literature related to CRM systems in which the frontline employees are the primary users. In this study, we propose that with the aid of CRM systems, individual employees are able to immediately access information about customers and service offerings, thus enabling their adaptive behaviours to provide personalized service to individual customers. Based on coping theory, we develop a CRM system‐driven adaptive behaviour model that explains how CRM systems facilitate individual employees' service performance by enabling adaptive behaviour during their service encounters. Multisourced data from a financial company in China largely support our proposed model, showing that employees' postadoption of CRM systems (routinization and infusion of use) enables interpersonal and offering adaptive behaviours, which in turn enhance employees' service performance. In addition, forming a postadoption behaviour of CRM systems relies on the frequent use. We discuss the theoretical and practical implications of adaptive behaviour in service encounters with the aid of CRM systems.     

知识发现在CRM中的应用

企业在广泛应用CRM（Customer Relationship Management)对客户信息进行管理的同时，如何进一步提高CRM系统数据资源利用率是本文的重要论题。本文利用知识发现的相关技术以及数据库查询语言对隐藏在大量客户信息中的知识发现算法进行描述，并在此基础上结合CRM系统给出了知识发现的求解过程和结果。     

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.     

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.     

支持CRM分析的数据仓库多维启动模型

CRM是一种整合了知识管理、数据挖掘及数据仓库技术的商业策略,旨在支持制定决策来保留长期有利的客户关系。分析了CRM中数据仓库的设计问题,提出一种支持CRM分析的强劲的多维启动模型。为验证此模型,用一些CRM的查询进行测试,并定义两个量:成功率和适配率来评估。实验结果表明,此启动模型具有很高的成功率和适配率,可用于客户收益分析、市场收益分析、产品收益分析、渠道收益分析等多种收益分析。     

客户价值评价体系在高尔夫CRM 中的研究

客户价值评价体系是CRM（CustomerRelationshipManagement,即客户关系管理）系统的核心,通过对高尔夫行业客户价值评价体系的分析,建立了高尔夫球场预定服务业客户价值评价体系模型,介绍了应用层次分析法计算该模型的客户价值．根据不同的客户价值把客户分为四种类型,建议针对不同类型的客户采用不同的营销、销售以及服务策略．最后介绍了该模型在CRM系统中的应用．     

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.     

The priority factor model for customer relationship management system success

As the market competition becomes keen, constructing a customer relationship management system is coming to the front for winning over new customers, developing service and products for customer satisfaction and retaining existing customers. However, decisions for CRM implementation have been hampered by inconsistency between information technology and marketing strategies, and the lack of conceptual bases necessary to develop the success measures. Using a structural equation analysis, this study explores the CRM system success model that consists of CRM initiatives: process fit, customer information quality, and system support; intrinsic success: efficiency and customer satisfaction; and extrinsic success: profitability. These constructs underlie much of the existing literature on information system success and customer satisfaction perspectives. We found the empirical support for CRM implementation decision-making from 253 respondents of 14 companies which have implemented the CRM system. These findings should be of great interest to both researchers and practitioners.