Data Mining Cookbook: Modeling Data for Marketing, Risk and Customer Relationship Management
Editorial Reviews
Review
“…the descriptions are clear, concise, unambiguous…she has clearly succeeded…” (The Institute of Direct Marketing -theidm.com
Book Description
Get a data mining recipe for success to increase profits and reduce costs in today s business world with This book shows you how to create and implement models of the most commonly asked data mining questions for marketing, sales, risk analysis, and customer relationship management and support. You ll get proven modeling techniques that address specific questions to help you find new ways to increase profit and cut costs. Starting from the basics, you ll learn how to plan the menu and choose the right ingredients or ask the right questions and get data ready to mine before you get down to the business of creating the meal. You ll find numerous case studies that detail available data sources for developing targeting models, then learn to process, evaluate, and implement them through an extensive case study of a lifetime value model for a life insurance direct-mail campaign. This step-by-step guide will help you to: Mine your company s data or find outside sources for your project Select and transform the variables when preparing data for modeling Test and validate response, activation, and profitability models Perform customer analysis through profiling and segmentation Build models to predict response, risk, churn, and lifetime value Use models for Web-based marketing and customer support Also AvailableData Mining Cookbook CD-ROM see ad in back of bookVisit our Web site at www.wiley.com/compbooks/ Visit the companion Web site atdataminingcookbook.wiley.com
Data Mining Cookbook: Modeling Data for Marketing, Risk and Customer Relationship Management
Data Mining Cookbook: Modeling Data for Marketing, Risk and Customer Relationship Management,Olivia Parr Rud,Wiley,0471385646,Business & Economics,Business/Economics,Computer Bks - Data Base Management,Customer services,Data mining,Data processing,Database Engineering,Database Management - Database Mining,Database Management - General,Information Management,Management - General,Marketing,Marketing - Research,Business information systems,Computers / Data Processing,Databases & data structures
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