Point Of Sale Machines: Customer Relationship Management: Concepts and Cases

Customer Relationship Management: Concepts and Cases

Customer Relationship Management: Concepts and Cases - Innovative strategies are taken up by the companies today to seek, attract, and win new clients, nurture and retain the existing ones, entice former clients back into the fold, and reduce the costs of marketing and client service. Customer relationship management denotes a company-wide business strategy embracing all client-facing departments. This book gives an analytical insight on the CRM practices adopted by various organizations, and the advancements made in the field. The book elaborates the role of IT in CRM technology (e-CRM) like data mining, warehousing and so on.
Intended as a text for the students of management, the book can prove equally beneficial for the retailers, bankers, insurers, and telecom professionals.

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Microsoft Points On Sale: Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner

Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner

Data Mining for Business Intelligence: Concepts, Techniques, and Applications in Microsoft Office Excel with XLMiner - Praise for the First Edition" full of vivid and thought-provoking anecdotes needs to be read by anyone with a serious interest in research and marketing."
—Research magazine"Shmueli et al. have done a wonderful job in presenting the field of data mining a welcome addition to the literature."
—computingreviews.comIncorporating a new focus on data visualization and time series forecasting, Data Mining for Business Intelligence, Second Edition continues to supply insightful, detailed guidance on fundamental data mining techniques. This new edition guides readers through the use of the Microsoft Office Excel add-in XLMiner for developing predictive models and techniques for describing and finding patterns in data.From clustering customers into market segments and finding the characteristics of frequent flyers to learning what items are purchased with other items, the authors use interesting, real-world examples to build a theoretical and practical understanding of key data m

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