Increase profits and reduce costs by utilizing this collection of models of the most commonly asked data mining questions In order to find new ways to improve customer sales and support, and as well as manage risk, business managers must be able to mine company databases. This book provides a step-by-step guide to creating and implementing models of the most commonly asked data mining questions. Readers will learn how to prepare data to mine, and develop accurate data mining questions. The author, who has over ten years of data mining experience, also provides actual tested models of specific data mining questions for marketing, sales, customer service and retention, and risk management. A CD-ROM, sold separately, provides these models for reader use.
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OLIVIA PARR RUD (Olivia@datasquare.com) is Executive Vice President of Data Square, LLC, a leading database marketing consulting firm. She has over 22 years' experience in data mining, predictive modeling, and segmentation for a variety of industries, including credit card, insurance, high tech, telecommunications, and catalog industries. She provides analysis and solutions for her clients in the areas of acquisition, retention, risk, and overall profitability for direct mail, telemarketing, broadcast marketing, and the Internet.
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
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