Data Mining in Customer Relationship Management - Nekvapil, Viktor
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The book addresses possibilities of deploying the freeware data mining system LISp-Miner in customer relationship management (CRM), specifically in the area of lead management. The data used in the project were obtained from a major logistic company operating worldwide (the company wished to remain anonymous). The principle aim of the project is to provide information contributing to the possible change of internal processes of the company. Further aims are to propose directions of the use of the LISp-Miner when solving a similar data mining task, and propose a simple and understandable way of…mehr

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Produktbeschreibung
The book addresses possibilities of deploying the freeware data mining system LISp-Miner in customer relationship management (CRM), specifically in the area of lead management. The data used in the project were obtained from a major logistic company operating worldwide (the company wished to remain anonymous). The principle aim of the project is to provide information contributing to the possible change of internal processes of the company. Further aims are to propose directions of the use of the LISp-Miner when solving a similar data mining task, and propose a simple and understandable way of presenting the results. The aims have been achieved through analysis in compliance with the CRISP-DM Methodology. The asset of the book is the description of the whole project, which includes the analysis of real data using the LISp-Miner. The book also offers instructions and recommendations for similar future projects. Section I outlines the LISp-Miner and its procedures. Section II A case study describes the process of analysing the data. Section III summarises the observations gained during the entire project and gives recommendations and instructions for similar projects.
Autorenporträt
Viktor Nekvapil is a PhD. student of Applied Informatics at the University of Economics, Prague, and data analyst in financial advisory. His research interests lie in commercial applications of data mining. He is the author of Data Mining in the Medical Domain, Lambert Academic Publishing, 2010.