Customer relationship management

About: Customer relationship management is a research topic. Over the lifetime, 12852 publications have been published within this topic receiving 264200 citations. The topic is also known as: CRM & Customer Relationship Management System.

Understanding customer relationship management (CRM): People, process and technology

Abstract: Customer relationship management (CRM) is a combination of people, processes and technology that seeks to understand a company's customers. It is an integrated approach to managing relationships by focusing on customer retention and relationship development. CRM has evolved from advances in information technology and organizational changes in customer‐centric processes. Companies that successfully implement CRM will reap the rewards in customer loyalty and long run profitability. However, successful implementation is elusive to many companies, mostly because they do not understand that CRM requires company‐wide, cross‐functional, customer‐focused business process re‐engineering. Although a large portion of CRM is technology, viewing CRM as a technology‐only solution is likely to fail. Managing a successful CRM implementation requires an integrated and balanced approach to technology, process, and people.

An empirical analysis of the antecedents of electronic commerce service continuance

Abstract: This paper examines key drivers of consumers' intention to continue using business-to-consumer e-commerce services. Multiple theoretical perspectives are synthesized to hypothesize a model of continuance behavior, which is then empirically tested using a field survey of online brokerage (OLB) users. Salient results include: (1) consumers' continuance intention is determined by their satisfaction with initial service use, their perceived usefulness of service use, and the interaction between perceived usefulness and loyalty incentives for service use, and (2) satisfaction and perceived usefulness are both predicted by consumers' confirmation of expectations from initial service use. Implications of these findings for e-commerce firms contemplating customer relationship management (CRM) initiatives are discussed.

Engine to present a user interface based on a logical structure, such as one for a customer relationship management system, across a web site

Abstract: A flowchart-based tool can be used to build a logical structure. In the context of a customer relationship management (CRM) system, the logical structure can comprise an ordered set of questions and branching logic that are presented to a customer of the business when the customer contacts the business with an inquiry, such as for a sale or service inquiry or other interaction. An engine can run a session associated with the logical structure, with the session presenting questions, text, graphics, and the like dynamically to customer across a network, such as the Internet and a web site. Branching logic determines the appropriate information to present to the user based on answers to previous questions. The engine allows presentation of the information to the user/customer, by generating hypertext markup language (HTML) files to display the questions or other elements of the logical structure as part of a user interface on a client terminal of the customer.

The Impact of Customer Relationship Characteristics on Profitable Lifetime Duration

Abstract: The authors develop a framework that incorporates projected profitability of customers in the computation of lifetime duration. Furthermore, the authors identify factors under a manager’s control that explain the variation in the profitable lifetime duration. They also compare other frameworks with the traditional methods such as the recency, frequency, and monetary value framework and past customer value and illustrate the superiority of the proposed framework. Finally, the authors develop several key implications that can be of value to decision makers in managing customer relationships.

Review: Application of data mining techniques in customer relationship management: A literature review and classification

Abstract: Despite the importance of data mining techniques to customer relationship management (CRM), there is a lack of a comprehensive literature review and a classification scheme for it. This is the first identifiable academic literature review of the application of data mining techniques to CRM. It provides an academic database of literature between the period of 2000-2006 covering 24 journals and proposes a classification scheme to classify the articles. Nine hundred articles were identified and reviewed for their direct relevance to applying data mining techniques to CRM. Eighty-seven articles were subsequently selected, reviewed and classified. Each of the 87 selected papers was categorized on four CRM dimensions (Customer Identification, Customer Attraction, Customer Retention and Customer Development) and seven data mining functions (Association, Classification, Clustering, Forecasting, Regression, Sequence Discovery and Visualization). Papers were further classified into nine sub-categories of CRM elements under different data mining techniques based on the major focus of each paper. The review and classification process was independently verified. Findings of this paper indicate that the research area of customer retention received most research attention. Of these, most are related to one-to-one marketing and loyalty programs respectively. On the other hand, classification and association models are the two commonly used models for data mining in CRM. Our analysis provides a roadmap to guide future research and facilitate knowledge accumulation and creation concerning the application of data mining techniques in CRM.