Dr. Jay Liebowitz Orkand Endowed Chair in Management and Technology University of Maryland University College Graduate School of Management & Technology 3501 University Boulevard East Adelphi, Maryland 20783-8030 USA jliebowitz@umuc. edu When I first heard the general topic of this book, Marketing Intelligent Systems or what I’ll refer to as Marketing Intelligence, it sounded quite intriguing. Certainly, the marketing field is laden with numeric and symbolic data, ripe for various types of mining―data, text, multimedia, and web mining. It’s an open laboratory for applying numerous forms of intelligentsia―neural networks, data mining, expert systems, intelligent agents, genetic algorithms, support vector machines, hidden Markov models, fuzzy logic, hybrid intelligent systems, and other techniques. I always felt that the marketing and finance domains are wonderful application areas for intelligent systems, and this book demonstrates the synergy between marketing and intelligent systems, especially soft computing. Interactive advertising is a complementary field to marketing where intelligent systems can play a role. I had the pleasure of working on a summer faculty f- lowship with R/GA in New York City―they have been ranked as the top inter- tive advertising agency worldwide. I quickly learned that interactive advertising also takes advantage of data visualization and intelligent systems technologies to help inform the Chief Marketing Officer of various companies. Having improved ways to present information for strategic decision making through use of these technologies is a great benefit.
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The success of companies is partly dependent on the generation of suitable knowledge upon which to base decision-making, and due to the centrality of the marketing function in organizations, marketing-related knowledge is of strategic relevance. In this connection, it is unlikely to reach a full understanding of any set of systems supporting marketing management without paying the necessary attention to the Artificial Intelligence-based methodologies applied to aid marketing-related decisions. However, as yet these methods are both under-developed and under-used. This book represents a notable and creative step forward in this respect. The editorial project has especially focused on the so-called Marketing Intelligent Systems, a cutting-edge category for marketing management support that focuses on a sophisticated treatment of knowledge by Soft Computing and other machine learning techniques. The reader will find smart reflections on this general theme from diverse world-leading marketing academics through short essays, and a collection of chapters devoted to a variety of applications – segmentation, modeling, e-commerce, etc. – using different technologies such as clustering, evolutionary algorithms, multi-agent systems, or fuzzy logic.
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