数据挖掘在电子商务客户关系管理中的应用

有效及时的处理客户信息,并挖掘出客户的消费倾向,实现精确营销成为电子商务时代企业的关注。本文主要阐述数据挖掘在电子商务环境下客户关系管理中的具体应用及应用步骤,用实例说明了电子商务客户关系管理中数据挖掘的应用价值。     

基于数据挖掘的客户关系管理系统研究

在CRM客户关系管理中,反馈和交流的管理过程是重要的内容,通过与客户的深入交流对客户的需求进行更加详细具体的了解,之后再根据客户的需求对企业的产品和服务进行一系列的改造。为了能够更好地实现这一目的,基于面向对象的编程方法,研究开发了新的客户关系管理系统,利用遗传算法和神经网络算法挖掘数量庞大的客户数据,从而取得客户关系管理的有效信息。利用遗传算法将数据挖掘应用到客户获取中,利用神经网络算法将数据挖掘应用到交叉营销中,并取得良好效果。     

客户关系管理中基于数据挖掘的客户细分研究

客户关系管理(CRM)是适应企业"以产品为中心"到"以客户为中心"的经营模式的战略转移和关系营销的需要而发展起来的新的管理理念,它把在保证企业利益的前提下追求客户满意和客户忠诚作为最终目标。客户细分是客户关系管理系统的核心功能之一,可以对客户获取、客户保持及客户增值等客户关系管理过程提供全面支持,提升客户满意和客户忠诚。本文将从客户关系管理中客户细分问题的特点出发,探索基于数据挖掘的客户细分模型,为客户关系管理提供新的应用方法。     

基于数据挖掘的企业CRM系统分析与设计

主要研究基于数据挖掘技术的客户关系管理的应用,概述了数据挖掘技术的基本理论知识以及客户关系管理的理论和应用,提出了制药企业客户资源管理中存在的问题及解决的方法,实践了数据挖掘在客户等级评价上的主要过程和一般分析方法,这对于数据挖掘实践研究有着重要的现实意义。     

数据挖掘在电信运营中的运用

本文首先分析目前数据挖掘在电信运营中的重要性,然后分别从客户精准营销、客户关系管理、客户流失三个层面来阐明数据挖掘大电信运营中的作用。     

浅谈E-mail营销中的客户关系管理

客户关系管理(CRM)是企业经营管理的重点,互联网时代如何利用网络营销进行客户关系管理是电子商务管理中的实际问题.本文从E-mail营销入手探讨了E-mail营销中的客户关系管理的策略和模式.有侧重地描述了在实际电子商务活动中进行E-mail营销与CRM的关系、常用的E-mail营销策略以及在实际运用中应当注意的问题--如何更好地发现客户、吸引客户、留住客户等.     

数据挖掘在客户关系管理中的应用探讨

随着计算机技术、网络技术、数据库技术的快速发展和进步,客户关系管理系统得到了广泛地普及和应用,尤其是数据挖掘技术诞生之后,客户关系管理系统能够精确提升客户服务质量,以便能够长期保持和维系良好的客户关系,发展企业业务,提升企业的市场竞争力,具有重要的作用和意义。本文就数据挖掘在客户关系管理中的应用展开论述。     

数据挖掘技术在CRM中的应用

随着电子商务经济模式在社会经济发展中应用程度的加深,客户关系管理逐渐受到企业的关注和重视,而在客户关系管理中,客户的分类是其中的一项必备职能。客户作为一个庞大的群体,要想在庞大的不确定客户信息中挖掘出有价值的信息,还需要数据挖掘技术的应用。基于此,文章先对数据挖掘技术和CRM的相关内容进行了介绍,在此技术上分析了数据挖掘技术在CRM中的具体应用情况。     

数据挖掘技术在呼叫中心中的应用

在市场竞争日益激烈的今天,呼叫中心已经被证明在企业客户关系管理中是一种行之有效的模式.它为企业提供了一条快速通道,以便主动接触目标客户并与其保持良好的联系,因而获得大量的客户信息.呼叫中心数据挖掘,就是将从呼叫中心渠道收集的客户信息进行整合后,应用超级计算机、并行处理、神经元网络、模型化算法和其他信息处理技术,从中提炼出有价值的信息运用到企业服务、营销活动中.本文重点论述了常用数据挖掘技术在呼叫中心的应用.     

基于数据挖掘的服装业客户流失分析研究

服装业的发展推动了中国国民经济的发展,在企业间的竞争日趋激烈,实施客户关系管理(CRM)策略将成为企业竞争的核心,维护老客户,减少客户流失则是重中之重.通过数据挖掘对服装企业客户进行流失分析,得到客户流失特征,通过这些特征来对现存客户进行流失预测,以帮助企业管理者对流失客户进行营销策略,减少客户流失或者将要流失的客户.     

基于移动通信客户行为分析的精确营销策略研究

随着全业务和3G运营的发展,粗放式的营销方式已明显滞后于电信市场的发展。将精细化营销、数据挖掘等营销管理理念和智能计算方法运用到电信产品营销中,提出了基于移动通信客户行为分析的精确营销策略模型。本模型依据客户行为分别建立客户价值模型、客户粘性模型、客户异动模型和客户需求鉴别模型,利用4个模型构建营销矩阵,实现客户群细分,针对不同客户实施不同保有和营销策略并对模型实施应用评估。精确营销策略能够为营销队伍提供常规化营销支持服务,提升企业市场竞争力。     

Study of customer acquisition support system for mobile operators

The mobile operators are struggling for improving the market share and the revenues.One important method is to acquire the potential customers from the competitors.This article presents a whole acquisition process and an integrated framework for customer acquisition support system (CASS).The core of the system is the customer acquisition identification models which are built based on data mining technologies.The CASS can automate the acquisition process and decrease the cost and implement precise marketing strategy for mobile operators.     

A Million Segments of One — How Personal Should Customer Relationship Management Get?

The foundation upon which customer relationship management (CRM) stands is a single, definitive view of customers which spans functions, channels, products and customer types and drives every customer interaction. CRM purports to recreate the ‘traditional corner shop’ experience to millions of clients. However, as techniques for data mining and pattern matching allow companies to build a relationship with customers, customers are questioning whether they actually want to have a relationship with companies. As CRM becomes more personalised, is it providing the experience that customers want? Are companies spending on personalised CRM only to reap limited benefits? This paper considers the different ways that companies such as Capital One, First Direct, Amazon and Tesco are personalising a CRM experience and examines the resulting relationship that they develop with their customers. Ultimately, the future of personalised CRM is dependent on non-intrusive, mutually beneficial and cost-effective strategies delivered through the appropriate medium for the customer. This requires recognition that CRM is more than just deployment of technology. It is a fusion of strategy, process and technology. Companies need to consider what customers want from them and whether the personalised solution that is being proposed reaps financial benefits. Building a million segments of one may work for some companies but others need to consider what kind of relationship their customers want from them and what they (and their customers) can gain from the data that they gather.     

数据挖掘技术在客户关系管理中的应用研究

在电子商务环境下,客户对企业起着至关重要的影响。新客户的获取无疑对企业的生存和发展起到很重要的作用。客户关系管理系统中,通过分析海量数据之间的联系,建立规范全面的信息模型。为了解决新客户的获取问题,采用数据挖掘技术对客户类别进行预测。通过对数据挖掘各种算法的比较,做了决策树算法编程实验,获得客户类别的预测结果。结果表明,数据挖掘技术能有效提高客户预测的准确率,提高了数据利用率。     

CRM在中国电信业中的应用

客户关系管理(CRM)是基于数据仓库的信息分析系统。它利用数据仓库和数据挖掘技术分析客户的需求,从而为企业确定市场方向,巩固和发展新老客户提供依据。中国加入WTO后,面对即将来临的电信市场大战,国内电信运营商必须调整经营观念,加快CRM的建设。     

Mining Demand Chain Knowledge for New Product Development and Marketing

Many enterprises devote a significant portion of their budget to new product development (NPD) and marketing to make their products distinctive from those of competitors, and better fit the needs and wants of consumers. Hence, knowledge and feedback on customer demand and consumption experience has become an important information and asset for enterprises. This paper investigates the following research issues in a world leading bicycle brand/manufacture company, GIANT of Taiwan: what exactly are the customers’ “functional needs” and “wants” for bicycles? Does knowledge of the customers and the product itself reflect the needs of the market? Can product design and planning for production lines be integrated with the knowledge of customers and market channels? Can the knowledge of customers and market channels be transformed into knowledge assets of the enterprises during the stage of NPD? The a priori algorithm is a methodology of association rule for data mining, which is implemented for mining demand chain knowledge from channels (sales and maintenance) and customers. Knowledge extraction from data mining results is illustrated as knowledge patterns and rules in order to propose suggestions and solutions to the case firm for NPD and marketing.      

电信客户社交网络分析方法与营销应用探讨

社交网络成为推动移动互联网迅猛发展的生力军,人与人的交往数据越来越集中,随着数据条件的成熟,社交网络分析迅速成为一个新兴的跨学科的专业研究方向。电信网络原本就是一个巨大的社交网络,电信企业如何才能让社交网络分析成为企业认识刻画客户的利器,并用之于客户关系管理和市场营销决策管理支撑呢?本文首先在对社交网络分析的概念界定、方法及发展趋势作简单介绍的基础上,探讨研究电信客户社交网络分析模型的意义;然后在界定社交网络分析的目标和对象,区别社交网络分析与传统分析方法之不同的基础上,探讨基于通话详单记录,电信企业建立社交网络分析的模型方法;最后,对电信企业如何应用电信客户社交网络分析结果提出了两方面建议。     

Management of Address Information to Improve Quality of Customer Contact

Customer relationship management systems are gaining importance in today's business environment since customer satisfaction is crucial to the success of an enterprise, and especially so in e-business environment where customers can find substitute suppliers quite easily. In CRM, the quality of customer information is very important, and the address information even more so. It is because the address information plays a major role for customer contact channel and for timely and effective marketing service. Furthermore, it gives the basic source of geographic information for the offline delivery, the terminal activity of the e-commerce. In this study, we analyze various standards and proposals for the address information, and propose data models for the management of the information focusing on address components, and proto-type systems for management and service.     

数据挖掘技术及其在经营分析系统中的应用

为了在市场竞争中保持及发展客户、提升客户价值,运营商迫切需要了解客户的行为特征以及业务发展、收益、营销、服务等方面的运营情况,以便及时制定更加合理和高效的经营策略,更好地在竞争中掌握主动.于是,电信企业纷纷着手建立数据仓库和在线分析处理(OLAP)系统,通过对运营支撑系统多年积累的业务数据进行整合和分析,以获得有价值的分析结果.但是,OLAP侧重的是对历史数据的分析,回答的是"过去发生了什么和为什么会发生"的问题,而运营商在对过去和现在的经营状况进行分析掌握的同时,更加渴望对整个企业未来的发展状况做出比较完整、合理、准确的分析和预测,于是,数据挖掘技术由于能够发现潜在的知识以及能够回答"将要发生什么"的问题而被电信企业加以"重用".本文简要阐述了数据挖掘技术、主要模型及方法、数据挖掘的实施步骤,并结合具体的案例说明数据挖掘在电信行业经营分析系统中的应用.     

Research of CRM Based on Customer Intelligence Engine

The discipline of business intelligence addresses a broad range of functional activities from data mining and statistical analysis to predictive modeling and reporting, and customer intelligence is the actionable output from an intelligence eco-system. In order to focus enterprise's attention on their customers satisfaction in the customer relationship management and make CRM system run more efficiently, a new concept of customer intelligence engine(CIE) is proposed at first time in the paper, the architecture of CIE is structured, the trigger of CIE is defined and described, the CIE-based CRM eco-system is also discussed.