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

Olivia Parr Rud (Author)

Book Description

Publication Date: November 3, 2000 | ISBN-10: 0471385646 | ISBN-13: 978-0471385646 | Edition: 1

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.

Editorial Reviews

Review

“…the descriptions are clear, concise, unambiguous…she has clearly succeeded…” (The Institute of Direct Marketing -theidm.com

From the Inside Flap

CD-ROM InstructionsInsert the CD-ROM and launch the readme.htm file in a web browser, or navigate using Windows® Explorer to browse the contents of the CD. The model programs and output are in text format that can be opened in any editing software (including SAS) that reads ASCII files. Spreadsheets are in Microsoft® Excel 97/2000 or 5.0/95. Launch the application (SAS 6.12 or higher) and open the file directly from the CD-ROM. If you wish to make changes, you can rename the files and save them to your local hard drive.Customer Note: Please read the following before launching the CD-ROMThis software contains files to help you utilize the models and code described in the accompanying book, sold separately. By opening the package, you are agreeing to be bound by the following agreement:This software product is protected by copyright and all rights are reserved by the author, John Wiley & Sons, Inc., or their licensors. You are licensed to use this software as described in the software and the accompanying book. Copying the software for any other purpose may be a violation of the U.S. Copyright Law.This software product is sold as is without warranty of any kind, either express or implied, including but not limited to the implied warranty of merchantability and fitness for a particular purpose. Neither Wiley nor its dealers or distributors assumes any liability for any alleged or actual damages arising from the use of or the inability to use this software. (Some states do not allow the exclusion of implied warranties, so the exclusion may not apply to you.)©2000 John Wiley & Sons, Inc. --This text refers to the Software edition.

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Product Details

• Paperback: 367 pages
• Publisher: Wiley; 1 edition (November 3, 2000)
• Language: English
• ISBN-10: 0471385646
• ISBN-13: 978-0471385646
• Product Dimensions: 9.3 x 7.4 x 0.9 inches
• Shipping Weight: 1.2 pounds (View shipping rates and policies)
• Average Customer Review: 4.2 out of 5 stars  See all reviews (14 customer reviews)
• Amazon Best Sellers Rank: #139,555 in Books (See Top 100 in Books)
  • #50 in Books > Computers & Technology > Databases > Data Mining

More About the Author

Olivia is an internationally known expert in Business Intelligence and Organizational Alignment. Her passion for finding successful solutions for her clients and partners has inspired her research in systems thinking and integrated business practices. She is considered a thought leader in the integration of analytic tools and holistic organization practices that deliver success through the optimal leverage of quantitative and qualitative practices and methodologies.

Her many years of research and study in the areas of Data Mining and Business Intelligence led to the writing of her first book, Data Mining Cookbook, Modeling for Acquisition, Risk and Customer Relationship Management (Wiley 2001). Seeing a larger need in the blending of analytics with softer skills, she was inspired to conduct research in the areas the integration of more qualitative skills building. This led to her research into the link between Organizational Development and Complexity Science and the writing of her second book, Her book, Business Intelligence Success Factors, Aligning for Success in a Global Economy (Wiley/SAS, 2009).

She has been working with clients for several years in areas of communication, change management, team building and leadership development. Olivia is a certified Holacracy Practitioner. Holacracy is a set of practice designed to tap into the wisdom of the organization.

Her clients include Cisco, Citizen's Bank, Clorox, HP, IBM, Xerox, Providian Insurance, Ameriquest, State Farm, Nationwide, and SAS. Olivia has a BA in Mathematics from Gettysburg College and an MS in Decision and Information Systems, with a concentration in Statistics, from Arizona State University.

Please visit www.oliviagroup.com for more information.

Customer Reviews

Most Helpful Customer Reviews

42 of 45 people found the following review helpful:

1.0 out of 5 stars DM Cookbook CD ROM, April 16, 2002

By A Customer

This review is from: Data Mining Cookbook: Modeling Data for Marketing, Risk and Customer Relationship Management (Software)

Book is OK, but DON'T BUY THE CD-ROM! I dropped [a large amount] for what I thought would be a worth-while "self-learning" course on Data Mining programming in SAS. To my great disappointment, I found that while Olivia had included the code (which you can type in yourself), there was NO DATA PROVIDED, making the code all but useless (can't run the models with no data!). I e-mailed her asking for some kind of a sample data set. She agreed, but after months of begging she provided nothing whatsoever. Don't make the same mistake I did - STAY AWAY FROM THE CD-ROM!!!

18 of 18 people found the following review helpful:

5.0 out of 5 stars Wholesome - no frills - data mining cooking !!, December 19, 2001

By 

Oliver Femminella (London, United Kingdom) - See all my reviews

This review is from: Data Mining Cookbook: Modeling Data for Marketing, Risk and Customer Relationship Management (Paperback)

By reading this book you should learn how to cook data mining applications...but if you have very little or no appreciation of data mining and customer relationship management (CRM), and you have never used SAS software, you'll probably end up burning your first few cakes or even worst your fingers !!
As the author gives a very brief introduction to data mining, make sure before you even start reading this book that you have a grasp of statistical modelling and data mining in a CRM context, otherwise you will find the material presented in this book too much to take in at once, and worst, you may probably end up being put off building your own data mining applications.
The author clearly has a solid statistical (read SAS) background, making this book a strong contender as one of the best books on data mining around, providing the reader with a number of useful recipes, practical examples and pragmatic data mining approaches which should be studied and understood in detail. Being a cookbook, the author's (or should I say the chef's) particular style may not suite your palate. In other words, you may not like the author's bias towards using logistic regression as the main data mining technique. As a result, you will not learn how to cook exotic dishes using ingredients such as neural networks. However, the choice to use logistic regression as the main statistical techniques pays off, as this allows the reader to start learning to cook robust/reliable meals (models), before cooking with the more exotic ingredients (techniques).
The topics and interventions provided by the well-experienced contributors are in context with the author's material, strengthening the practical context in which data mining applications are presented. On a few occasions, I found that the author does not discuss figures and tabulated outputs in a straightforward way, inevitably affecting the readability of the book. Notwithstanding, the methodology and material presented has a considerable amount of depth and rigour, and the general themes are well structured and maintained throughout.
Many figures and tabulated results are presented in the graphical output provided by the SAS system, which may be less appealing to you if you are not going to be using SAS. Also, many data mining software tools now available have significantly better graphical data presentation capabilities than those presented in this book, inevitably giving it a slightly dated look. Unsurprisingly, being the first version of the cookbook, there are a few typos (and one incorrect figure at the beginning of the first chapter).
In summary, this book is not for the novice, but will be a book that you will want read more than once.

13 of 13 people found the following review helpful:

5.0 out of 5 stars A foundation book for middle-advanced analysts, March 26, 2002

By 

Michael Wexler "michaelwexler" (Westfield, NJ, United States) - See all my reviews
(REAL NAME)   

This review is from: Data Mining Cookbook: Modeling Data for Marketing, Risk and Customer Relationship Management (Paperback)

Yes, its not for beginners or executives. That's great, because so many other books are aimed at glossing over the details for novices. This book gets down and dirty with exactly how one goes about analyzing and modeling data in applied marketing. It assumes some knowledge of data and basic analysis, but it also reviews assumptions along the way and points out "gotchas" for the less experienced. Yes, there is an overemphasis on Logistic Regression and a paucity of info on other techniques, but the Logistic Regression work is well done. Yes, it is very SAS based, but the code is not hard to translate to other systems. She doesn't spend as much time as I would prefer on explaining all the output that she presents, though its an excellent start. But she does provide specific details on ALL the steps, from getting and transforming data to how to present your results and use your model, things that are ignored in many other books. Sure, there are easy quibbles and minor errors throughout, but what tech book today is error free? So, if you are looking for the basic guidebook on just how one goes about "modeling", then this is the one. Its got a permanent place on my bookshelf, and is one of the standards I recommend along with Kimball, Pyle, and other "ya gotta have" books.