This is an applied handbook for the application of data mining techniques in the CRM framework. It combines a technical and a business perspective to cover the needs of business users who are looking for a practical guide on data mining. It focuses on Customer Segmentation and presents guidelines for the development of actionable segmentation schemes. By using non-technical language it guides readers through all the phases of the data mining process.

Many companies have invested in building large databases and data warehouses capable of storing vast amounts of information. This book offers business, sales and marketing managers a practical guide to accessing such information.

Special Features: · Best-in-class data mining techniques for solving critical problems in all areas of business· Explains how to pick the right data mining techniques for specific problems· Shows how to perform analysis and evaluate results· Features real-world examples from across various industry sectors· Companion Web site with updates on data mining products and service providers About The Book: Companies have invested in building data warehouses to capture vast amounts of customer information. The payoff comes with mining or getting access to the data within this information gold mine to make better business decisions. Readers and reviewers loved Berry and Linoff's first book, Data Mining Techniques, because the authors so clearly illustrate practical techniques with real benefits for improved marketing and sales. Mastering Data Mining takes off from there-assuming readers know the basic techniques covered in the first book, the authors focus on how to best apply these techniques to real business cases. They start with simple applications and work up to the most powerful and sophisticated examples over the course of about 20 cases. (Ralph Kimball used this same approach in his highly successful Data Warehouse Toolkit). As with their first book, Mastering Data Mining is sufficiently technical for database analysts, but is accessible to technically savvy business and marketing managers. It should also appeal to a new breed of database marketing managers.

Learn how to use customer relationship management (CRM) techniques to give your company an edge in the competitive marketplace. --

A step-by-step guide to data mining applications in CRM. Following a handbook approach, this book bridges the gap between analytics and their use in everyday marketing, providing guidance on solving real business problems using data mining techniques. The book is organized into three parts. Part one provides a methodological roadmap, covering both the business and the technical aspects. The data mining process is presented in detail along with specific guidelines for the development of optimized acquisition, cross/ deep/ up selling and retention campaigns, as well as effective customer segmentation schemes. In part two, some of the most useful data mining algorithms are explained in a simple and comprehensive way for business users with no technical expertise. Part three is packed with real world case studies which employ the use of three leading data mining tools: IBM SPSS Modeler, RapidMiner and Data Mining for Excel. Case studies from industries including banking, retail and telecommunications are presented in detail so as to serve as templates for developing similar applications. Key Features: Includes numerous real-world case studies which are presented step by step, demystifying the usage of data mining models and clarifying all the methodological issues. Topics are presented with the use of three leading data mining tools: IBM SPSS Modeler, RapidMiner and Data Mining for Excel. Accompanied by a website featuring material from each case study, including datasets and relevant code. Combining data mining and business knowledge, this practical book provides all the necessary information for designing, setting up, executing and deploying data mining techniques in CRM. Effective CRM using Predictive Analytics will benefit data mining practitioners and consultants, data analysts, statisticians, and CRM officers. The book will also be useful to academics and students interested in applied data mining.

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.

This book covers the fundamental concepts of data mining, to demonstrate the potential of gathering large sets of data, and analyzing these data sets to gain useful business understanding. The book is organized in three parts. Part I introduces concepts. Part II describes and demonstrates basic data mining algorithms. It also contains chapters on a number of different techniques often used in data mining. Part III focuses on business applications of data mining.

The explosion of Web-based data has created a demand among executives and technologists for methods to identify, gather, analyze, and utilize data that may be of value to corporations and organizations. The emergence of data mining, and the larger field of Web mining, has businesses lost within a confusing maze of mechanisms and strategies for obta

Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. - Includes input by practitioners for practitioners - Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models - Contains practical advice from successful real-world implementations - Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions - Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications

Preface Corporations that achieve high customer retention and high customer profitability aim for: The right product (or service), to the right customer, at the right price, at the right time, through the right channel, to satisfy the customer's need or desire. Information Technology—in the form of sophisticated databases fed by electronic commerce, point-of-sale devices, ATMs, and other customer touch points—is changing the roles of marketing and managing customers. Information and knowledge bases abound and are being leveraged to drive new profitability and manage changing relationships with customers. The creation of knowledge bases, sometimes called data warehouses or Info-Structures, provides profitable opportunities for business managers to define and analyze their customers' behavior to develop and better manage short- and long-term relationships. Relationship Technology will become the new norm for the use of information and customer knowledge bases to forge more meaningful relationships. This will be accomplished through advanced technology, processes centered on the customers and channels, as well as methodologies and software combined to affect the behaviors of organizations (internally) and their customers/channels (externally). We are quickly moving from Information Technology to Relationship Technology. The positive effect will be astounding and highly profitable for those that also foster CRM. At the turn of the century, merchants and bankers knew their customers; they lived in the same neighborhoods and understood the individual shopping and banking needs of each of their customers. They practiced the purest form of Customer Relationship Management (CRM). With mass merchandising and franchising, customer relationships became distant. As the new millennium begins, companies are beginning to leverage IT to return to the CRM principles of the neighborhood store and bank. The customer should be the primary focus for most organizations. Yet customer information in a form suitable for marketing or management purposes either is not available, or becomes available long after a market opportunity passes, therefore CRM opportunities are lost. Understanding customers today is accomplished by maintaining and acting on historical and very detailed data, obtained from numerous computing and point-of-contact devices. The data is merged, enriched, and transformed into meaningful information in a specialized database. In a world of powerful computers, personal software applications, and easy-to-use analytical end-user software tools, managers have the power to segment and directly address marketing opportunities through well managed processes and marketing strategies. This book is written for business executives and managers interested in gaining advantage by using advanced customer information and marketing process techniques. Managers charged with managing and enhancing relationships with their customers will find this book a profitable guide for many years. Many of today's managers are also charged with cutting the cost of sales to increase profitability. All managers need to identify and focus on those customers who are the most profitable, while, possibly, withdrawing from supporting customers who are unprofitable. The goal of this book is to help you: identify actions to categorize and address your customers much more effectively through the use of information and technology, define the benefits of knowing customers more intimately, and show how you can use information to increase turnover/revenues, satisfaction, and profitability. The level of detailed information that companies can build about a single customer now enables them to market through knowledge-based relationships. By defining processes and providing activities, this book will accelerate your CRM "learning curve," and provide an effective framework that will enable your organization to tap into the best practices and experiences of CRM-driven companies (in Chapter 14). In Chapter 6, you will have the opportunity to learn how to (in less than 100 days) start or advance, your customer database or data warehouse environment. This book also provides a wider managerial perspective on the implications of obtaining better information about the whole business. The customer-centric knowledge-based info-structure changes the way that companies do business, and it is likely to alter the structure of the organization, the way it is staffed, and, even, how its management and employees behave. Organizational changes affect the way the marketing department works and the way that it is perceived within the organization. Effective communications with prospects, customers, alliance partners, competitors, the media, and through individualized feedback mechanisms creates a whole new image for marketing and new opportunities for marketing successes. Chapter 14 provides examples of companies that have transformed their marketing principles into CRM practices and are engaging more and more customers in long-term satisfaction and higher per-customer profitability. In the title of this book and throughout its pages I have used the phrase "Relationship Technologies" to describe the increasingly sophisticated data warehousing and business intelligence technologies that are helping companies create lasting customer relationships, therefore improving business performance. I want to acknowledge that this phrase was created and protected by NCR Corporation and I use this trademark throughout this book with the company's permission. Special thanks and credit for developing the Relationship Technologies concept goes to Dr. Stephen Emmott of NCR's acclaimed Knowledge Lab in London. As time marches on, there is an ever-increasing velocity with which we communicate, interact, position, and involve our selves and our customers in relationships. To increase your Return on Investment (ROI), the right information and relationship technologies are critical for effective Customer Relationship Management. It is now possible to: know who your customers are and who your best customers are stimulate what they buy or know what they won't buy time when and how they buy learn customers' preferences and make them loyal customers define characteristics that make up a great/profitable customer model channels are best to address a customer's needs predict what they may or will buy in the future keep your best customers for many years This book features many companies using CRM, decision-support, marketing databases, and data-warehousing techniques to achieve a positive ROI, using customer-centric knowledge-bases. Success begins with understanding the scope and processes involved in true CRM and then initiating appropriate actions to create and move forward into the future. Walking the talk differentiates the perennial ongoing winners. Reinvestment in success generates growth and opportunity. Success is in our ability to learn from the past, adopt new ideas and actions in the present, and to challenge the future. Respectfully, Ronald S. Swift Dallas, Texas June 2000