Items related to CRM Segmentation and Clustering Using SAS Enterprise...
Synopsis
In this instructive guide, Collica employs SAS Enterprise Miner and the most commonly available techniques for CRM (customer relationship management). Readers learn how to segment customers more intelligently to achieve the relationship that today's businesses want. The CD-ROM features example SAS code, data sets, macros, and Enterprise Miner templates.
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Review
Using nontechnical terms, this book skillfully guides the user through the powerful SAS Enterprise Miner software to answer critical questions such as: What are the characteristics of my best customers?, How can I optimize their value?, and How can I use this knowledge to grow my business?. The ease and precision with which these techniques are explained will be appreciated by marketers, managers, analysts, and anyone else whose role it is to turn customer data into actionable knowledge. For those who seek practical techniques and rich examples for applying statistical concepts to common marketing and CRM challenges, this book is destined to become an essential reference. --C. Olivia Parr Rud, M.S., Data Mining, Strategist/Author/Facilitator, OLIVIAGroup
This book addresses an important and still often-misunderstood topic of utilizing advanced analytics to better understand consumer behavior. It has an application, how-to focus rather than a detailed description of algorithmsand the inclusion of data at the end of the book is a tremendous value-add to professors. --Stephan Kudyba, Ph.D., Founder of Null Sigma, Inc.
The application of SAS Enterprise Miner and data mining analytics continues to broaden to new domains, from medical epidemiology to advanced business practices. Randy Collica provides us with an intuitive, hands-on guide to implementing the science behind comprehensively and accurately understanding one's customers. The efficiency of these CRM techniques has been maximized through the described segmentation and clustering methods and through the mining of underutilized data types, such as free text. These techniques are presented in a detailed, yet appealing and sensible manner; one that is a welcomed contribution to the state of the art in data mining analytics. --Daniel C. Payne, Ph.D., M.S.P.H, Epidemiologist
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CRM Segmentation and Clustering Using SAS Enterprise Miner (Sas Press Series)
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Condition: good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail. Seller Inventory # OTV.1590475089.G