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Foreword
Various business problems such as market segmentation, targeted marketing, personalization, cross selling and modeling customer lifetime value are of interest to both the data mining and marketing academic communities. However, these two disciplines have different approaches to analyzing these problems. Data mining research incorporates methodologies from various disciplines such as statistics, machine learning, databases, optimization and pattern recognition, and is primarily data-driven. It focuses more on the effectiveness of problem solving, and pays greater attention to actual performance on data. In contrast, marketing research advocates more theory-based analysis and its theories are often built upon statistics, psychology, economics and other social sciences. The broader research goal that motivates the ideas described here is to integrate and compare methods from marketing research and data mining research to solve marketing problems.
This book consists of two essays that contribute to this goal. In each essay, data mining and marketing approaches are used to address specific marketing problems. The first essay develops a new data mining