CRM SEGMENTATION AND CLUSTERING USING SASR ENTERPRISE MINERTM PDF

Randall S. Collica is a senior business and data mining analyst at Hewlett-Packard, where he uses data mining techniques for targeted marketing and customer analytics in the Customer Data and Knowledge Services department. Randy has developed customer scoring models, as well as models to estimate corporate IT spending for use in tactical and strategic customer and prospect business intelligence. He earned a B. Understanding the customer is critical to your company's success. You will learn how to segment customers more intelligently and to achieve, or at least get closer to, the one-to-one customer relationship that today's businesses want.

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Skip to main content. Start your free trial. You will learn how to segment customers more intelligently and to achieve, or at least get closer to, the one-to-one customer relationship that today's businesses want. Step-by-step examples and exercises clearly illustrate the concepts of segmentation and clustering in the context of CRM. The book is divided into four parts.

Part 1 reviews the basics of segmentation and clustering at an introductory level, providing examples from a variety of industries. Part 2 offers an in-depth treatment of segmentation with practical topics such as when and how to update your models and clustering with many attributes. Part 3 goes beyond traditional segmentation practices to introduce recommended strategies for clustering product affinities, handling missing data, and incorporating textual records into your predictive model with SAS Text Miner software.

Part 4 takes segmentation to a new level with advanced techniques such as clustering of product associations, developing segmentation scoring models from customer survey data, combining segmentations using ensemble segmentation, and segmentation of customer transactions. Updates to the second edition include four new chapters in Part 4, Chapters , that introduce new and advanced analytic techniques that can be valuable in many customer segmentation applications.

Also included are business insights and motivations for selection settings and analytical decisions on many of the examples included in this second edition. This straightforward guide will appeal to anyone who seeks to better understand customers or prospective customers. Additionally, professors and students will find the book well suited for a business data mining analytics course in an MBA program or related course of study. You should understand basic statistics, but no prior knowledge of data mining or SAS Enterprise Miner is required.

This book is part of the SAS Press program. Show and hide more. Table of Contents Product Information. The k-Means Algorithm and Variations.

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CRM Segmentation and Clustering Using SAS Enterprise Miner

Skip to main content. Start your free trial. You will learn how to segment customers more intelligently and to achieve, or at least get closer to, the one-to-one customer relationship that today's businesses want. Step-by-step examples and exercises clearly illustrate the concepts of segmentation and clustering in the context of CRM. The book is divided into four parts. Part 1 reviews the basics of segmentation and clustering at an introductory level, providing examples from a variety of industries.

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Customer Segmentation and Clustering Using SAS Enterprise Miner, Second Edition, 2nd Edition

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