Author : Bruce Ratner
Publisher : CRC Press
Page : 383 pages
File Size : 46,46 MB
Release : 2003-05-28
Category : Business & Economics
ISBN : 0203496906
Traditional statistical methods are limited in their ability to meet the modern challenge of mining large amounts of data. Data miners, analysts, and statisticians are searching for innovative new data mining techniques with greater predictive power, an attribute critical for reliable models and analyses. Statistical Modeling and Analysis fo
Author : Bruce Ratner
Publisher : CRC Press
Page : 544 pages
File Size : 42,75 MB
Release : 2012-02-28
Category : Business & Economics
ISBN : 1466551216
The second edition of a bestseller, Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data is still the only book, to date, to distinguish between statistical data mining and machine-learning data mining. The first edition, titled Statistical Modeling and Analysis for Database Marketing: Effective Techniques for Mining Big Data, contained 17 chapters of innovative and practical statistical data mining techniques. In this second edition, renamed to reflect the increased coverage of machine-learning data mining techniques, the author has completely revised, reorganized, and repositioned the original chapters and produced 14 new chapters of creative and useful machine-learning data mining techniques. In sum, the 31 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature. The statistical data mining methods effectively consider big data for identifying structures (variables) with the appropriate predictive power in order to yield reliable and robust large-scale statistical models and analyses. In contrast, the author's own GenIQ Model provides machine-learning solutions to common and virtually unapproachable statistical problems. GenIQ makes this possible — its utilitarian data mining features start where statistical data mining stops. This book contains essays offering detailed background, discussion, and illustration of specific methods for solving the most commonly experienced problems in predictive modeling and analysis of big data. They address each methodology and assign its application to a specific type of problem. To better ground readers, the book provides an in-depth discussion of the basic methodologies of predictive modeling and analysis. While this type of overview has been attempted before, this approach offers a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with.
Author : Bruce Ratner
Publisher : CRC Press
Page : 690 pages
File Size : 38,8 MB
Release : 2017-07-12
Category : Computers
ISBN : 149879761X
Interest in predictive analytics of big data has grown exponentially in the four years since the publication of Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition. In the third edition of this bestseller, the author has completely revised, reorganized, and repositioned the original chapters and produced 13 new chapters of creative and useful machine-learning data mining techniques. In sum, the 43 chapters of simple yet insightful quantitative techniques make this book unique in the field of data mining literature. What is new in the Third Edition: The current chapters have been completely rewritten. The core content has been extended with strategies and methods for problems drawn from the top predictive analytics conference and statistical modeling workshops. Adds thirteen new chapters including coverage of data science and its rise, market share estimation, share of wallet modeling without survey data, latent market segmentation, statistical regression modeling that deals with incomplete data, decile analysis assessment in terms of the predictive power of the data, and a user-friendly version of text mining, not requiring an advanced background in natural language processing (NLP). Includes SAS subroutines which can be easily converted to other languages. As in the previous edition, this book offers detailed background, discussion, and illustration of specific methods for solving the most commonly experienced problems in predictive modeling and analysis of big data. The author addresses each methodology and assigns its application to a specific type of problem. To better ground readers, the book provides an in-depth discussion of the basic methodologies of predictive modeling and analysis. While this type of overview has been attempted before, this approach offers a truly nitty-gritty, step-by-step method that both tyros and experts in the field can enjoy playing with.
Author : Ronald G Drozdenko
Publisher : SAGE Publications
Page : 425 pages
File Size : 29,31 MB
Release : 2002-03-26
Category : Business & Economics
ISBN : 145226404X
"Destined to be the definitive guide to database marketing applications, analytical strategies and test design." - Brian Kurtz, Executive Vice President, Boardroom Inc., 2000 DMA List Leader of the Year and DMA Circulation Hall of Fame Inductee "This book is well written with interesting examples and case studies that both illustrate complex techniques and tie the chapters together. The level of detail and treatment of statistical tools and methods provides both understanding and enough detail to begin to use them immediately to target marketing efforts efficiently and effectively. It is perfect for a course in database marketing or as a handy reference for those in the industry. " - C. Samuel Craig, New York University, Stern School of Business "This book should be studied by all who aspire to have a career in direct marketing. It provides a thorough overview of all essential aspects of using customer databases to improve direct marketing results. The material is presented in a style that renders even the technical subjects understandable to the novice direct marketer" Kari Regan, Vice President, Database Marketing Services, The Reader′s Digest Association "Finally, practical information on database marketing that tackles this complex subject but makes it clear enough for the novice to understand. This book serves as more than a primer for any senior manager who needs to know the whole story. As one who has spent over 20 years of his career involved in publishing and database marketing, I have a real appreciation for how difficult it is to explain the finer points of this discipline, while keeping it understandable. This book does that admirably. Well done!" - Patrick E. Kenny, Executive Vice President, Qiosk.com "This book is especially effective in describing the breadth and impact of the database marketing field. I highly recommend this book to anyone who has anything to do with database marketing! -- works in or with this dynamic area." - Naomi Bernstein, Vice President, BMG Direct "Ron Drozdenko and Perry Drake have written a guide to database marketing that is thorough and that covers the subject in considerable depth. It presents both the concepts underlying database marketing efforts and the all-important quantitative reasoning behind it. The material is accessible to students and practitioners alike and will be an important contribution to improved understanding of this important marketing discipline. " Mary Lou Roberts, Boston University and author of Direct Marketing Management "I think it is a terrific database marketing book, it′s got it all in clear and logical steps. The benefit to the marketing student and professional is that complex database concepts are carefully developed and thoroughly explained. This book is a must for all marketing managers in understanding database issues to successfully manage and structure marketing programs and achieve maximum results. " - Dante Cirille, DMEF Board Member and Retired President, Grolier Direct Marketing "An excellent book on the principles of Direct Marketing and utilization of the customer database to maximize profits. It is one of the best direct marketing books I have seen in years in that it is broad with specific examples. I am going to require new hires to read this (book) to get a better understanding of the techniques used in Database Marketing." - Peter Mueller, Assistant Vice President of Analysis, Scholastic, Grolier Division "This is an amazingly useful book for direct marketers on how to organize and analyze database information. It′s full of practical examples that make the technical material easy to understand and apply by yourself. I strongly recommend this book to direct and interactive marketers who want to be able to perform professional database analyses themselves, or be better equipped to review the work of analysts. " - Pierre A. Passavant, Professor of Direct Marketing, Mercy College and Past Director, Center for Direct Marketing, New York University "The most useful database marketing reference guide published today. The authors do an excellent job of laying out all the steps required to plan and implement an effective database marketing strategy in a clear and concise manner. A must have for academics, marketing managers and business executives." - Dave Heneberry, Director, Direct Marketing Certificate programs, Western Connecticut State University and Past Chair, Direct Marketing Association "This book is essential for all direct marketers. It serves as a great introduction to the technical and statistical side of database marketing. It provides the reader with enough information on database marketing and statistics to effectively apply the techniques discussed or manage others in the environment " - Richard Hochhauser, President, Harte-Hanks Direct Marketing Ronald G. Drozdenko, Ph.D., is Professor and Chair of the Marketing Department, Ancell School of Business, Western Connecticut State University. He is also the founding Director of the Center for Business Research at the Ancell School. He has more than 25 years of teaching experience. The courses he teaches include Strategic Marketing Databases, Interactive/Direct Marketing Management, Product Management, Marketing Research, and Consumer Behavior. He is collaborating with the Direct Marketing Education foundation to develop a model curriculum for universities pursing the area of interactive or direct marketing. Working with an advisory board of industry experts, he co-developed the Marketing Database course in model curriculum. Dr. Drozdenko has co-directed more than 100 proprietary research projects since 1978 for the marketing and research and development of several corporations, including major multinationals. These projects were in the areas of strategic planning, marketing research, product development, direct marketing, and marketing database analysis. He also has published several articles and book chapters. He holds a Ph.D. in Experimental Psychology from the University of Missouri and is a member of the American Marketing Association, the Society for Consumer Psychology, and the Academy of Marketing Sciences. He is also the co-inventor on three U.S. patents. Perry D. Drake has been involved in the direct marketing industry for nearly 15 years. He is currently the Vice President of Drake Direct, a database marketing consulting firm specializing in response modeling, customer file segmentation, lifetime value analysis, customer profiling, database consulting, and market research. Prior to this, Perry worked for approximately 11 years in a variety of quantitative roles at The Reader′s Digest Association, most recently as the Director of Marketing Services. In addition to consulting, Perry has taught at New York University in the Direct Marketing Master′s Degree program since Fall, 1998, currently teaching "Statistics for Direct Marketers" and "Database Modeling." Perry was the recipient of the NYU Center for Direct and Interactive Marketing′s "1998-1999" Outstanding Master′s Faculty Award. Perry also lectures on testing and marketing financials for Western Connecticut State University′s Interactive Direct Marketing Certificate Program. Along with Ron, he is collaborating with the Direct Marketing Education Foundation to develop a model curriculum for universities pursuing the area of interactive or direct marketing. Perry earned a Masters of Science in Applied Statistics from the University of Iowa and a Bachelor of Science in Economics from the University of Missouri. The book evolved from an outlined developed by an advisory board of industry experts that was established by the Direct Marketing Educational Foundation. Contemporary direct marketing and e-commerce could not exist without marketing databases. Databases allow marketers to reach customers and cultivate relationships more effectively and efficiently. While databases provide a means to establish and enhance relationships, they can also be used incorrectly, inefficiently, and unethically. This book looks beyond the temptation of the quick sale to consider the long-term impact of database marketing techniques on the organization, customers, prospective customers, and society in general. Ron Drozdenko and Perry Drake help the reader gain a thorough understanding of how to properly establish and use databases in order to build strong relationships with customers. There is not another book on the market today that reveals the level of detail regarding database marketing applications - the how′s, why′s and when′s. Features/Benefits: Draws on numerous examples from real businesses Includes applications to all direct marketing media including the Internet Describes in step-by-step detail how databases are developed, maintained, and mined Considers both business and social issues of marketing databases Contains a sample database allowing the reader to apply the mining techniques Offers access to comprehensive package of academic support materials
Author : Robert C. Blattberg
Publisher : Springer Science & Business Media
Page : 875 pages
File Size : 38,70 MB
Release : 2010-02-26
Category : Business & Economics
ISBN : 0387725792
Database marketing is at the crossroads of technology, business strategy, and customer relationship management. Enabled by sophisticated information and communication systems, today’s organizations have the capacity to analyze customer data to inform and enhance every facet of the enterprise—from branding and promotion campaigns to supply chain management to employee training to new product development. Based on decades of collective research, teaching, and application in the field, the authors present the most comprehensive treatment to date of database marketing, integrating theory and practice. Presenting rigorous models, methodologies, and techniques (including data collection, field testing, and predictive modeling), and illustrating them through dozens of examples, the authors cover the full spectrum of principles and topics related to database marketing. "This is an excellent in-depth overview of both well-known and very recent topics in customer management models. It is an absolute must for marketers who want to enrich their knowledge on customer analytics." (Peter C. Verhoef, Professor of Marketing, Faculty of Economics and Business, University of Groningen) "A marvelous combination of relevance and sophisticated yet understandable analytical material. It should be a standard reference in the area for many years." (Don Lehmann, George E. Warren Professor of Business, Columbia Business School) "The title tells a lot about the book's approach—though the cover reads, "database," the content is mostly about customers and that's where the real-world action is. Most enjoyable is the comprehensive story – in case after case – which clearly explains what the analysis and concepts really mean. This is an essential read for those interested in database marketing, customer relationship management and customer optimization." (Richard Hochhauser, President and CEO, Harte-Hanks, Inc.) "In this tour de force of careful scholarship, the authors canvass the ever expanding literature on database marketing. This book will become an invaluable reference or text for anyone practicing, researching, teaching or studying the subject." (Edward C. Malthouse, Theodore R. and Annie Laurie Sills Associate Professor of Integrated Marketing Communications, Northwestern University)
Author : Ken Yale
Publisher : Elsevier
Page : 824 pages
File Size : 10,13 MB
Release : 2017-11-09
Category : Mathematics
ISBN : 0124166458
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
Author : Bettina Hüttenrauch
Publisher : Springer
Page : 361 pages
File Size : 34,88 MB
Release : 2016-06-10
Category : Business & Economics
ISBN : 3658145773
This study delivers insights on which external sources – e.g. website click behavior, surveys, or social media data – can and cannot be used for data augmentation. A case study is performed to test the suitability of different sources in order to create a generalized practical guide for data augmentation in marketing. Data augmentation is a beneficial tool for companies to use external data, if the internal data basis for targeting is not sufficient to reach the customers with the highest propensity. This study shows that augmenting data from feasible sources leads to significant conversion lifts.
Author : Chris Chapman
Publisher : Springer
Page : 0 pages
File Size : 38,49 MB
Release : 2015-03-25
Category : Business & Economics
ISBN : 9783319144351
This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis. Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis. With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications.
Author : National Research Council
Publisher : National Academies Press
Page : 191 pages
File Size : 44,97 MB
Release : 2013-09-03
Category : Mathematics
ISBN : 0309287812
Data mining of massive data sets is transforming the way we think about crisis response, marketing, entertainment, cybersecurity and national intelligence. Collections of documents, images, videos, and networks are being thought of not merely as bit strings to be stored, indexed, and retrieved, but as potential sources of discovery and knowledge, requiring sophisticated analysis techniques that go far beyond classical indexing and keyword counting, aiming to find relational and semantic interpretations of the phenomena underlying the data. Frontiers in Massive Data Analysis examines the frontier of analyzing massive amounts of data, whether in a static database or streaming through a system. Data at that scale-terabytes and petabytes-is increasingly common in science (e.g., particle physics, remote sensing, genomics), Internet commerce, business analytics, national security, communications, and elsewhere. The tools that work to infer knowledge from data at smaller scales do not necessarily work, or work well, at such massive scale. New tools, skills, and approaches are necessary, and this report identifies many of them, plus promising research directions to explore. Frontiers in Massive Data Analysis discusses pitfalls in trying to infer knowledge from massive data, and it characterizes seven major classes of computation that are common in the analysis of massive data. Overall, this report illustrates the cross-disciplinary knowledge-from computer science, statistics, machine learning, and application disciplines-that must be brought to bear to make useful inferences from massive data.
Author : Management Association, Information Resources
Publisher : IGI Global
Page : 2335 pages
File Size : 40,34 MB
Release : 2012-11-30
Category : Computers
ISBN : 1466624566
Data mining continues to be an emerging interdisciplinary field that offers the ability to extract information from an existing data set and translate that knowledge for end-users into an understandable way. Data Mining: Concepts, Methodologies, Tools, and Applications is a comprehensive collection of research on the latest advancements and developments of data mining and how it fits into the current technological world.
