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Customer Segmentation and Clustering Using SAS® Enterprise Miner™, Third Edition
A working guide that uses real-world data, this new edition will show you how to segment customers more intelligently and achieve the one-to-one customer relationship that your business needs. Step-by-step examples and exercises, using a number of machine learning and data mining techniques, clearly illustrate the concepts of segmentation and clustering in the context of customer relationship management.
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Author Spotlight
Randy Collica
Randy Collica is a Principal Pre-Sales Solutions Architect at SAS supporting the retail, communications, consumer, and media industries. His research interests include segmentation, clustering, ensemble models, missing data and imputation, Bayesian techniques, and text mining for use in business and customer intelligence.
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