Expert Systems for Scanner Data Environments: The Marketing Workbench Laboratory Experience

ISBN-13: 9789401057462 / Angielski / Miękka / 2012 / 224 str.

John M. McCann; John P. Gallagher

Opis

This book is about the role of expert systems in marketing, particularly in the consumer goods industry. Section I describes the changing nature of consumer marketing and presents the rationale and need for expert systems. The remainder of the book combines a tutorial on expert systems with a series of expert system prototypes. The tutorial material is presented in three places. First, section II is devoted to introducing expert systems in general. Chapter 3 provides a general introduction to the topic, which is continued in chapter 4 where a small expert system (the Promotion Advisor) is used to illustrate the important features of a backward-chaining, rule-based system. The promotion theme is extended in chapter 5 where a larger system is presented. The material in all three of these chapters was designed as an introduction and tutorial on the most common technology for building applied expert systems: the backward-chaining, rule-based inference engine. Tutorial material is also contained in the body of the chapters that describe the prototypes. This material is usually in the form of sample rules and a description of the process for applying the rules. The third location of the expert system material is in chapters that follow discussions of the prototypes. Chapter 7 is a technical chapter on the coupling of expert systems to traditional systems.

Spis treści

List of Figures.- Preface.- Acknowledgments.- SECTION I: The Changing Marketing World.- 1 The Marketing Data Explosion: The Promise and the Reality.- 2 A Necessary Transition.- SECTION II: Knowledge-Based Systems.- 3 An Introduction to Knowledge Systems.- 4 Expert Systems in Marketing. An Introduction.- 5 Textbook Promotion Advisor.- SECTION III: Applications.- 6 A Marketmetrics Knowledge System.- 7 The Coupled System.- 8 Model Animation.- 9 The Promotion Detective.- 10 Dealmaker.- 11 Dealmaker: A Model-Based Reasoning System.- 12 Related Research.- 13 Implementation Issues.- Author Index.