The Experts below are selected from a list of 210 Experts worldwide ranked by ideXlab platform
Bill Gates - One of the best experts on this subject based on the ideXlab platform.
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‘Up Close and Personal’? Customer relationship marketing @ work
Interactive Marketing, 2000Co-Authors: Bill GatesAbstract:Provides an overview of Customer relationship marketing (CRM) and addresses key issues for companies relating to the management of Customer relationships. Covers who is a Customer and relationships with Customers; issues of corporate planning the formulation of strategies as they relate to Customer relationship marketing; measuring the impact of Customer relationship marketing; the segmentation of Customers into groups and the "top vanilla offer"; how to get started with Customer relationship marketing; Customer loyalty and continuity; transparent marketing, Customer value, and process management; Customer knowledge management; integrating the technology of Customer management systems; managing good and bad Customers; and justifying the CRM investment. Includes a CD-ROM containing a diagnostic tool that will enable one to determine if his or her enterprise is positioned to take forward a new CRM initiative. Coauthors are Merlin Stone, Neil Woodcock, and Bryan Foss. Gamble is Professor of European Management at the University of Surrey. Index.
Li Yong - One of the best experts on this subject based on the ideXlab platform.
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Notice of Retraction: The Research of Personal Customer Relationship Management for Commercial Banks Based on Multidimensional Model of Customer Loyalty
2010 International Conference on E-Business and E-Government, 2010Co-Authors: Li YongAbstract:This article has been retracted by the publisher.
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notice of retraction the research of Personal Customer relationship management for commercial banks based on multidimensional model of Customer loyalty
International Conference on E-Business and E-Government, 2010Co-Authors: Li YongAbstract:Cultivating Customer loyalty is a critical goal of Customer relationship management (CRM). Traditional CRM is lack of a relatively complete model of Customer loyalty and couldn't support Customer loyalty management efficiently in business processes, organization and culture, and information systems. New banking Personal CRM strategy is proposed based on multi-dimensional model of Customer loyalty including Customer perceived value, relationship quality, switching barriers, and Customer complaints. It is focus on cultivating Customer loyalty of valuable and loyal segmentation through multi-driver, multi-channel, secure zone strategy and one to one loyalty program. And Customer loyalty management and analysis sub-system are proposed to enhance banking CRM system. It is helpful for the commercial banks to discover and develop the strategies and systems of Personal CRM further and improve Customer loyalty.
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The Research of Personal Customer Relationship Management for Commercial Banks Based on Multidimensional Model of Customer Loyalty
2010 International Conference on E-Business and E-Government, 2010Co-Authors: Li YongAbstract:Cultivating Customer loyalty is a critical goal of Customer relationship management (CRM). Traditional CRM is lack of a relatively complete model of Customer loyalty and couldn't support Customer loyalty management efficiently in business processes, organization and culture, and information systems. New banking Personal CRM strategy is proposed based on multi-dimensional model of Customer loyalty including Customer perceived value, relationship quality, switching barriers, and Customer complaints. It is focus on cultivating Customer loyalty of valuable and loyal segmentation through multi-driver, multi-channel, secure zone strategy and one to one loyalty program. And Customer loyalty management and analysis sub-system are proposed to enhance banking CRM system. It is helpful for the commercial banks to discover and develop the strategies and systems of Personal CRM further and improve Customer loyalty.
T C E Cheng - One of the best experts on this subject based on the ideXlab platform.
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Customer heterogeneity in operational e‐service design attributes: An empirical investigation of service quality
International Journal of Operations & Production Management, 2008Co-Authors: Rui Sousa, Andy C L Yeung, T C E ChengAbstract:Purpose – This study aims to empirically examine whether heterogeneity in Personal Customer profiles translates to heterogeneity in the valued operational e‐service design attributes. It focuses on a key operational e‐service design attribute – service quality – by investigating whether Customers with different profiles (demographics, pattern of use of the service, and pattern of channel use) attach different levels of importance to different dimensions of web site quality.Design/methodology/approach – The study is based on path analysis of data collected from multiple sources in a commercial e‐service setting (e‐banking): data from an online survey of the Customers of the e‐service; data stored in the transaction and log files generated by the operation of the e‐service over time; and data from the e‐service provider's Customer database and back office IT systems.Findings – The results suggest that: Customer demographics, pattern of service use, and pattern of channel use have no influence on the importa...
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Customer heterogeneity in operational e‐service design attributes
International Journal of Operations & Production Management, 2008Co-Authors: Rui Sousa, Andy C L Yeung, T C E ChengAbstract:Purpose - This study aims to empirically examine whether heterogeneity in Personal Customer profiles translates to heterogeneity in the valued operational e-service design attributes. It focuses on a key operational e-service design attribute - service quality - by investigating whether Customers with different profiles (demographics, pattern of use of the service, and pattern of channel use) attach different levels of importance to different dimensions of web site quality. Design/methodology/approach - The study is based on path analysis of data collected from multiple sources in a commercial e-service setting (e-banking): data from an online survey of the Customers of the e-service; data stored in the transaction and log files generated by the operation of the e-service over time; and data from the e-service provider's Customer database and back office IT systems. Findings - The results suggest that: Customer demographics, pattern of service use, and pattern of channel use have no influence on the importance attached by Customers to web site quality dimensions; and Customer demographics affect the pattern of use of an e-service. Research limitations/implications - Future research should examine this question in other types of e-services and should examine other types of profile variables. Practical implications - Service providers may not need to employ customization at the level of web site quality dimensions. The findings support the existence of the concept of an "optimal" web site design for quality. Originality/value - The paper answers calls for an increased understanding of the design of high quality e-services and for multidisciplinary research in the field of services management, in particular, incorporating operations management perspectives. © Emerald Group Publishing Limited.
Werner Kießling - One of the best experts on this subject based on the ideXlab platform.
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User preference mining techniques for Personalized applications
Wirtschaftsinformatik, 2004Co-Authors: Stefan Holland, Werner KießlingAbstract:Advanced Personalized e-applications require comprehensive knowledge about their users’ likes and dislikes in order to provide individual product recommendations, Personal Customer advice, and custom-tailored product offers. In our approach we model such preferences as strict partial orders with “A is better than B” semantics, which has been proven to be very suitable in various e-applications. In this paper we present preference mining techniques for detecting strict partial order preferences in user log data. Real-life e-applications like online shops or financial services usually have large log data sets containing the transactions of their Customers. Since the preference miner uses sophisticated SQL operations to execute all data intensive operations on database layer, our algorithms scale well even for such large log data sets. With preference mining Personalized e-applications can gain valuable knowledge about their Customers’ preferences, which can be applied for Personalized product recommendations, individual Customer service, or one-to-one marketing.
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PKDD - Preference Mining: A Novel Approach on Mining User Preferences for Personalized Applications
Knowledge Discovery in Databases: PKDD 2003, 2003Co-Authors: Stefan Holland, Martin Ester, Werner KießlingAbstract:Advanced Personalized e-applications require comprehensive knowledge about their user’s likes and dislikes in order to provide individual product recommendations, Personal Customer advice and custom-tailored product offers. In our approach we model such preferences as strict partial orders with “A is better than B” semantics, which has been proven to be very suitable in various e-applications. In this paper we present novel Preference Mining techniques for detecting strict partial order preferences in user log data. The main advantage of our approach is the semantic expressiveness of the Preference Mining results. Experimental evaluations prove the effectiveness and efficiency of our algorithms. Since the Preference Mining implementation uses sophisticated SQL statements to execute all data-intensive operations on database layer, our algorithms scale well even for large log data sets. With our approach Personalized e-applications can gain valuable knowledge about their Customers’ preferences, which is essential for a qualified Customer service.
Rui Sousa - One of the best experts on this subject based on the ideXlab platform.
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Customer heterogeneity in operational e‐service design attributes: An empirical investigation of service quality
International Journal of Operations & Production Management, 2008Co-Authors: Rui Sousa, Andy C L Yeung, T C E ChengAbstract:Purpose – This study aims to empirically examine whether heterogeneity in Personal Customer profiles translates to heterogeneity in the valued operational e‐service design attributes. It focuses on a key operational e‐service design attribute – service quality – by investigating whether Customers with different profiles (demographics, pattern of use of the service, and pattern of channel use) attach different levels of importance to different dimensions of web site quality.Design/methodology/approach – The study is based on path analysis of data collected from multiple sources in a commercial e‐service setting (e‐banking): data from an online survey of the Customers of the e‐service; data stored in the transaction and log files generated by the operation of the e‐service over time; and data from the e‐service provider's Customer database and back office IT systems.Findings – The results suggest that: Customer demographics, pattern of service use, and pattern of channel use have no influence on the importa...
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Customer heterogeneity in operational e‐service design attributes
International Journal of Operations & Production Management, 2008Co-Authors: Rui Sousa, Andy C L Yeung, T C E ChengAbstract:Purpose - This study aims to empirically examine whether heterogeneity in Personal Customer profiles translates to heterogeneity in the valued operational e-service design attributes. It focuses on a key operational e-service design attribute - service quality - by investigating whether Customers with different profiles (demographics, pattern of use of the service, and pattern of channel use) attach different levels of importance to different dimensions of web site quality. Design/methodology/approach - The study is based on path analysis of data collected from multiple sources in a commercial e-service setting (e-banking): data from an online survey of the Customers of the e-service; data stored in the transaction and log files generated by the operation of the e-service over time; and data from the e-service provider's Customer database and back office IT systems. Findings - The results suggest that: Customer demographics, pattern of service use, and pattern of channel use have no influence on the importance attached by Customers to web site quality dimensions; and Customer demographics affect the pattern of use of an e-service. Research limitations/implications - Future research should examine this question in other types of e-services and should examine other types of profile variables. Practical implications - Service providers may not need to employ customization at the level of web site quality dimensions. The findings support the existence of the concept of an "optimal" web site design for quality. Originality/value - The paper answers calls for an increased understanding of the design of high quality e-services and for multidisciplinary research in the field of services management, in particular, incorporating operations management perspectives. © Emerald Group Publishing Limited.