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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.
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.
Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. - Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects - Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields - Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data
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.
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.
This book presents an extensive discussion of the strategic and tactical aspects of customer relationship management as we know it today. It helps readers obtain a comprehensive grasp of CRM strategy, concepts and tools and provides all the necessary steps in managing profitable customer relationships. Throughout, the book stresses a clear understanding of economic customer value as the guiding concept for marketing decisions. Exhaustive case studies, mini cases and real-world illustrations under the title “CRM at Work” all ensure that the material is both highly accessible and applicable, and help to address key managerial issues, stimulate thinking, and encourage problem solving. The book is a comprehensive and up-to-date learning companion for advanced undergraduate students, master's degree students, and executives who want a detailed and conceptually sound insight into the field of CRM. The new edition provides an updated perspective on the latest research results and incorporates the impact of the digital transformation on the CRM domain.
About the Book: Customer Relationship Management CRM was born in the 1990s in the West. In the initial phases, the over enthusiastic businesses invested almost US$ 400 billion. But, the very same businesses were disheartened very soon primarily because there were no * visible. And, there were no quick results mainly because 80 per cent of the investments were made in technology. 'CRM' meant 'technology' to them then; 'CRM' means 'technology' to them even today. However, no business need bother so long as it is ready to go by the 'human' aspect of CRM, and take technology only as a facilitator. This book is an attempt to present this 'human' side of CRM. The authors' belief is that, in the long-term, CRM can be successful only due to its 'human' face. The book is arranged in three Parts. Part I, Customer Relationship Management, contains the academic inputs titled as Customer is King, Customer Managed Relationships MINI-Marketing, Types of CRM, Building Blocks of CRM & CRM Strategies, Customer Relationship Management by Indian Firms, Customer Retention Strategies, HRM in CRM, and Implementing a Technology-based CRM Solution. Part II, Call Centre Management, covers the areas concerning the working of a call centre titled as The Call Centre, Call Centre Functionality, Team Building, Customer Relationship Management, Web-based Customer Support, and Contact Centre Glossary. Part III, Cases, gives a first-hand idea of the working of CRM in the more peculiar contexts, like public sector undertakings through five well documented cases. Contents Part I: Customer Relationship Management, Customer is King, Customer Managed Relationships-Mini-Marketing, Types of CRM, Building Blocks of CRM & CRM Strategy, Customer Relationship Management by Indian Firms, Customer Retention Strategies, HRM in CRM, Implementing a Technology-based CRM Solution, Future Trends in CRM Part II: Call Centre Management, The Call Centre, Call Centre Functionality, Team Building, Customer Relatio
This volume presents a selection of new methods and approaches in the field of Exploratory Data Analysis. The reader will find numerous ideas and examples for cross disciplinary applications of classification and data analysis methods in fields such as data and web mining, medicine and biological sciences as well as marketing, finance and management sciences.