数据挖掘技术在客户关系管理系统的应用

为了提高客户关系管理系统的系统效率,在客户关系管理系统中引入了数据挖掘技术,改善后的系统整合管理资源、业务流程和专业技术,能够构建服务消费者的集合,满足客户需求。笔者通过研究潍坊市的电信业务,在客户关系管理系统中加入了数据挖掘技术,从而提高客户关系管理系统的效率和客户满意度。     

基于数据挖掘技术的银行CRM系统的研究

数据挖掘技术的主要作用是进行客户的信息整合,揭示出潜在的关联性和规律,进行客户细分和沟通,为决策者制定决策提供参考,为客户提供个性化服务,从而提升银行的盈利与竞争力。客户关系管理一种新型的以客户中心的管理机制,银行客户关系管理系统利用数据挖掘技术实现有效的客户关系管理,能够提高市场竞争能力。本文在对客户关系管理和数据挖掘简要介绍的基础上,主要阐述了数据挖掘技术在银行客户关系管理系统的应用。     

基于数据挖掘的客户细分框架模型

数据挖掘技术在客户关系管理领域的应用较广泛,能提高客户细分能力。针对目前客户细分研究缺乏统一研究框架的问题,分析现有的客户关系管理系统构架及其与客户细分的集成关系,对客户细分问题进行构架性研究,提出一种基于数据挖掘的客广细分框架模型,包括空间逻辑模型和数据-功能-方法模型。     

零售流通业的客户“关怀”管理

零售流通业的客户关系管理是企业管理中很重要的一部分,零售商们也对CRM（客户关系管理）曾经足够重视,并进行了大量投资,为什么客户满意度却没有得到预期的提高呢？如何降低理论的高度,将客户关系管理理解为客户关怀管理？在具有快速建立客户和快速流失客户这个鲜明特征的零售流通业,     

基于数据挖掘技术的客户关系管理——以微信平台为例

笔者先介绍了数据挖掘和客户关系管理的基本概念,然后在数据总结、分类发现以及研究关联信息的基础上,详细分析了数据挖掘技术在客户关系管理中的作用。进而以微信平台和公众号为例,从获取潜在新客户、提升客户价值以及预防客户流失相关方面入手,详细阐述了数据挖掘技术在客户关系管理中的具体应用方式。     

银行业客户关系管理系统的体系架构研究与实践

我国银行业已经进入以客户为中心的客户关系管理阶段,现有信息系统在客户关系管理方面的问题日益突出,为了落实"以产品为中心"转变到"以客户为中心"的理念,提高客户的满意度和忠诚度,通过设计基于NHibemate的客户关系管理系统的四层体系结构建立客户关系管理系统来健全客户的维系与培育体制,实现合理的客户信息审核机制,将客户关系管理融入银行的金融资源体系,优化银行市场价值链条,最终实现银行核心竞争力的提升.     

基于数据仓库的客户关系管理

数据仓库是数据管理信息领域近年来出现并发展迅速的一种新技术,它可以将各个渠道得来的数据,整理成全面、完善的客户信息库,通过数据挖掘和数据分析,来了解客户的需求,以保持良好的客户关系,维系客户忠诚,从而提高企业核心竞争力。论文介绍了数据仓库的基本概念及其技术特征,详细分析了数据仓库在客户关系管理中的作用。在此基础上,提出了客户关系管理数据仓库系统的具体设计方案。     

基于数据挖掘的银行客户关系管理系统的研究

数据挖掘是一种新兴的信息处理技术,客户关系管理是以客户为中心的管理机制和发展策略,银行客户关系管理系统将二者结合起来,能够提高市场竞争能力。本文对银行客户关系管理系统的系统架构进行了介绍,阐述了数据挖掘技术在银行客户关系管理系统的应用。     

聚类分析在电信行业客户关系管理中的应用

客户关系管理在电信行业被广泛应用,它已经成为电信运营商增加收入和利润,提高客户满意度、忠诚度的有效工具。聚类分析是数据挖掘的一种重要方法,将它应用在客户关系管理中,可以改善客户关系,并对将来的趋势和行为进行预测。本文采用k-means聚类算法对电信客户数据进行聚类分析,得到具有不同特征的客户群组,对不同群组采取不同的经营策略,帮助管理者提供了合理的决策支持。     

基于数据挖掘的客户细分模型研究及应用

为企业更深入了解消费者的行为和偏好,帮助企业制定决策和发展客户关系,结合现有的客户细分方法,提出一种多指标客户细分模型。从宏观和微观角度,对传统指标进行优化,构建RFMPA多指标客户体系;采用熵值法客观赋权;采用因子分析降维;采用改进的K-means算法完成客户细分。利用大型连锁超市客户消费数据进行实证研究,对比数据实验结果表明,该模型能够更好解决客户细分问题,提高企业客户关系管理和决策质量。     

Evolving the online customer experience … is there a role for online customer support?

This paper advances our theoretical understanding with regard to the online customer experience in a utilitarian context. The aim of this research is to understand if there is a need for online customer support during search for information and services on business support websites. In contrast to previous studies highlighting time distortion as part of the optimal customer experience, the findings of this research illustrate that customers are time conscious during a utilitarian search with the perceived length of time spent on the website influencing the customer experience. Additionally, the perceived length of time spent on the website influences the need to seek online customer support. The outcomes of customers requiring online customer support in relation to the customer experience have been established. The findings provide key managerial implications for economic development agencies and online business support providers on the requirement of online customer support and insight into the time conscious nature of customers in relation to the online customer experience.     

Intelligent value-based customer segmentation method for campaign management: A case study of automobile retailer

Most marketers have difficulty in identifying the right customers to engage in successful campaigns. So far, customer segmentation is a popular method that is used for selecting appropriate customers for a launch campaign. Unfortunately, the link between customer segmentation and marketing campaign is missing. Another problem is that database marketers generally use different models to conduct customer segmentation and customer targeting. This study presents a novel approach that combines customer targeting and customer segmentation for campaign strategies. This investigation identifies customer behavior using a recency, frequency and monetary (RFM) model and then uses a customer life time value (LTV) model to evaluate proposed segmented customers. Additionally, this work proposes using generic algorithm (GA) to select more appropriate customers for each campaign strategy. To demonstrate the efficiency of the proposed method, this work performs an empirical study of a Nissan automobile retailer to segment over 4000 customers. The experimental results demonstrate that the proposed method can more effectively target valuable customers than random selection.     

Comprehensive understanding of smart product service system from multi-dimension and multi-perspective: An innovative service model for Customer-product Interaction Life Cycle (CILC)

With the improvement of living standards and the rapid development of the Internet, customers gradually pursue personalized smart products and services. Traditional smart product service system is mainly aimed at the service of customers and products in one or several interactive links. Furthermore, in the mass personalization model, in order to give full play to the customer experience and participation satisfaction, it is necessary to study the smart product service system based on the interaction between customers and products. However, there is a gap in the research on integrating the whole life cycle of customer-product interaction. In order to meet this industrial need, the innovation of this paper is to construct an innovative service model for Customer-product Interaction Life Cycle (CILC) and analyse the service impact factors and countermeasures using fuzzy DEMATEL method. The study can provide enterprises with the top-level framework and decision-making of smart product service system based on CILC, and realize the effective integration, expansion and value-added of service resources. At the same time, the application of this research methods can shorten the distance between customers and products, improve customer satisfaction.     

Development of a strategic research plan for an academic department through the use of quality function deployment

Quality Function Deployment (QFD) is a popular approach for formalizing the process of listening to “the voice of the customer,” and assigning responsibilities to members of an organization in an effort to respond effectively to customer needs, QFD is being used by the Department of Industrial Engineering at Mississippi State University to help identify key customers for departmental research efforts, to identify and track the research needs of those customers, to fashion a comprehensive strategic plan for departmental research activities based on customer needs, to deploy various research functions and responsibilities to specific faculty members or groups, and to track research performance relative to goals. This approach appears to be an excellent means of formalizing the process of strategic research planning.     

Exploring the influence of personal schema on trust transfer and switching costs in brick-and-click bookstores

Due to competition, most firms try to retain and lock in customers; this is likely to ensure a greater market profit than that gained by acquiring new customers. While many studies have investigated customer satisfaction and retention in online and offline firms, scant research exists on customer satisfaction and customer retention in the context of brick-and-click firms: i.e., those that conduct business both online and in stores. Such firms encourage trust transfer among their customers. However, most studies have failed to consider the role of personal schema in trust transfer. Based on social exchange, investment, and information integration theories, we analyzed the impact of trust transfer, switching costs, and personal schema on customer satisfaction and repurchase intentions in the context of an offline bookstore that has now launched an online business. Our results indicated that trust transfer and switching costs had a small effect on customer satisfaction and repurchase intentions. Personal schema, however, affected both customer satisfaction and repurchase intention.     

再多一次接触:顾客反馈机制对服务失败后顾客评价的影响

It is difficult to control service quality for any service firm and service failure is inevitable due to human or non-human factors. As a result, service recovery stirred the interest of researchers and practitioners. However, service failure may not be identified by firms because a majority of dissatisfied customers will not complain to the service provider. Thus, this research proposes a proactive customer feedback mechanism comprised of proactive solicitation of customer feedback, customers providing feedback and follow-up communication and examine their impact of customer evaluations in the context of service failure. This research tries to establish that through adding a continuous series of satisfied service encounters or "moment of truth" to service failure encounters, the customer evaluations (e.g. satisfaction, trust, purchase intent and positive WOM) toward the service will be significantly improved. Our research employed a 2×2×2 between subjects experimental design. Three independent variables were manipulated as presence and absence level, that is, firms either proactively solicitted customer feedback or employed no solicitation of feedback, Customers either provided feedback to the service firm or refused to provide feedback, and service firm either conducted follow-up communication or no follow-up communication. Our research adoptted a scenario in the context of patronizing a three-star hotel on a business trip. In total, 221 business administration graduates from a famous university in Shanghai participated in the experiment. MANOVA was used to test the hypotheses. The results indicated that proactive solicitation significantly influenced trust (p<0.01). Besides satisfaction, the other dependent variables such as trust, purchase intent and positive WOM significantly differred between with and without follow-up communication groups (p<0.05). Third, a significant difference was detected regarding satisfaction, trust, purchase intent and positive WOM between customer providing feedback groups and no customer feedback groups (p<0.05). Moreover, significant interactive effects were found of customers provided feedback and follow-up communication on trust and purchase intent. Trust and purchase intent reached highest when a follow-up communication occurred after customers provided feedback. However, no interactive effects were found of proactive solicitation of customer feedback and customer providing feedback. This research suggests that service providers should create new encounters with customers when they are confronted with service failure, and in this study, through proactive customer feedback mechanism. That is, first, the service provider should encourage customers to provide feedback, which can improve customer evaluations after service failure and after customers providing feedback. At the same time, the firm should employ follow-up communication with the customer and inform them about how the firm responded to their complaints, suggestions and comments. It is worth to note that companies just need to have follow-up communication with those customers who have provided feedback. More important, as information technology and internet prevails, it is very likely sending email and short messages after a service failure to maintain customer relationships could significantly enhance customer evaluations of the service provider. Of course, how consumers respond to such measures online is an promising research area and needs further investigation.     

利用数据挖掘方法分析客户生涯价值

针对客户生涯价值分析这一客户关系管理系统的重要问题,在分析已有工作的基础上,经过多级数据归约,提出了多商品配送企业适合工程计算的客户生涯价值公式。进而对客户进行了高速聚类挖掘,找出了客户群的特点,对公司有针对性地制定客户策略起到了一定的指导作用。     

“What can I(S) do for you?”: How technology enables service providers to elicit customers’ preferences and deliver personalized service

This research studies the effective use of an IT-enabled Customer Service System (CSS) in the hospitality sector. Drawing on Effective Use Theory, we study how digital representations of customers’ preferences support service providers in the service personalization process. Our model posits customers’ preferences elicitation as the antecedent of CSS’ effective use, which yields superior customer value. This representational perspective matches recent efforts to study customer value as cocreated by customers and service providers. Based on a longitudinal dataset of 118,647 hotel reservations, we explain how digital representations of customers’ preferences enable service providers to personalize service and increase customer value.     

A PSO-based intelligent service dispatching mechanism for customer expectation management

In the era of experience economy, service providers have to provide customers with high quality service experience in order to attract more customers and achieve higher customer satisfaction. Managing customer expectation is a critical approach for service providers to consider. Although customer expectation has been discussed across different research disciplines, to our knowledge, there is still no systematical and feasible way to apply customer expectation management into real environments. This study attempts to establish an intelligent service dispatching mechanism by using particle swarm optimization for customer expectation management. This mechanism can help service providers design and deliver satisfactory service experience to customers. In order to evaluate the effectiveness and robustness of this mechanism, this study employs micro- and macro-simulation experiments to confer and analyze its performance. The simulation results show service providers can gain benefit and raise customer satisfaction by managing customer expectation during service experience delivery. Meanwhile, customers can also receive memorable experiences and have positive responses to service providers and other customers. Consequently, a high performance ecosystem within service providers and customers can be formed.     

基于客户喜好的双向个性化推荐算法

为了解决现有推荐算法仅考虑同类产品间单向推荐所缺乏的灵活性,提升产品的销量及用户的购物体验,提出一种基于客户喜好的双向个性化推荐算法,不仅可以为客户精准推荐产品,还可以为商家推荐潜在客户.首先,基于产品购买网络中客户及其邻居的购买信息,扩展客户购买信息;其次设计客户产品喜好权重计算办法,分析客户的购买喜好,并在客户喜好的指导下为客户提供个性化的产品推荐;最后,基于商家提供的样本客户,挖掘与样本客户相似的客户构成社区,为商家提供潜在客户推荐以及精准客户维护.在真实数据集上的实验验证了算法的有效性.该算法从客户和商家两个维度出发实现了产品与客户的双向推荐,为个性化推荐领域的研究提供有益的帮助.