Data Mining Techniques in Crm
Inside Customer Segmentation
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The book aims to be a complete and comprehensive handbook for the use of Data Mining Techniques in the CRM framework. It combines a technical and a business perspective, bridging the gap between data mining & business professionals. By using non-technical language it focuses on Customer Segmentation and presents guidelines for the development of actionable segmentation schemes.It guides readers through all phases of the data mining process, from the understanding of the business objective and the setting of the data mining goal to the model development, evaluation and deployment.Methodological...
The book aims to be a complete and comprehensive handbook for the use of Data Mining Techniques in the CRM framework. It combines a technical and a business perspective, bridging the gap between data mining & business professionals. By using non-technical language it focuses on Customer Segmentation and presents guidelines for the development of actionable segmentation schemes.
It guides readers through all phases of the data mining process, from the understanding of the business objective and the setting of the data mining goal to the model development, evaluation and deployment.
Methodological and technical guidelines are supplemented by real-world application examples from all major industries, including Telecommunications, Banking and Retailing and recommendations for the use of the data mining results for effective marketing.
Data mining algorithms are presented in a simple and comprehensive way for the business users with no technical expertise.
Mining data marts for Telecommunications, Banking and Retailing and full lists of recommended input fields are proposed that can serve as the base for the implementation of data mining applications.
The book is mainly addressed to business users who are looking for a practical guide on data mining. It presents the authors' knowledge and experience from the 'data mining trenches', demystifying the secrets for data mining success.
It guides readers through all phases of the data mining process, from the understanding of the business objective and the setting of the data mining goal to the model development, evaluation and deployment.
Methodological and technical guidelines are supplemented by real-world application examples from all major industries, including Telecommunications, Banking and Retailing and recommendations for the use of the data mining results for effective marketing.
Data mining algorithms are presented in a simple and comprehensive way for the business users with no technical expertise.
Mining data marts for Telecommunications, Banking and Retailing and full lists of recommended input fields are proposed that can serve as the base for the implementation of data mining applications.
The book is mainly addressed to business users who are looking for a practical guide on data mining. It presents the authors' knowledge and experience from the 'data mining trenches', demystifying the secrets for data mining success.
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