Data Mining Cookbook: Modeling Data for Marketing, Risk and Customer Relationship Management

by Olivia Parr Rud

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.

367 pages, Paperback

First published November 3, 2000

Reviews

[Xianshun Chen · Rating 2 out of 5]

Although from my personal opinion, the book is not very well written, it provides quite a bit of insights on how mining method such as logistic regression can be used to customer segmentation, profiling, and create various targeting, propensity models for marketing and risk as well as customer relationship management. the illustrated programming language is in SAS, but the code is not completely listed in the book. It is not a beginning book for SAS but a seasoned programmer who previously does not programme in SAS should not have difficulty picking up the code and implementation in the book. btw the book is outdated,