Market Segmentation: Conceptual and Methodological Foundations (International Series in Quantitative Marketing, 8)

Modern marketing techniques in industrialized countries cannot be implemented without segmentation of the potential market. Goods are no longer produced and sold without a significant consideration of customer needs combined with a recognition that these needs are heterogeneous. Since first emerging in the late 1950s, the concept of segmentation has been one of the most researched topics in the marketing literature. Segmentation has become a central topic to both the theory and practice of marketing, particularly in the recent development of finite mixture models to better identify market segments. This second edition of Market Segmentation updates and extends the integrated examination of segmentation theory and methodology begun in the first edition. A chapter on mixture model analysis of paired comparison data has been added, together with a new chapter on the pros and cons of the mixture model. The book starts with a framework for considering the various bases and methods available for conducting segmentation studies. The second section contains a more detailed discussion of the methodology for market segmentation, from traditional clustering algorithms to more recent developments in finite mixtures and latent class models. Three types of finite mixture models are discussed in this second section: simple mixtures, mixtures of regressions and mixtures of unfolding models. The third main section is devoted to special topics in market segmentation such as joint segmentation, segmentation using tailored interviewing and segmentation with structural equation models. The fourth part covers four major approaches to applied market segmentation: geo-demographic, lifestyle, response-based, and conjoint analysis. The final concluding section discusses directions for further research.

Dividing customers into target groups has been a major part of marketing since the late 1950s, and Wedel (U. of Groningen, the Netherlands) and Wagner (U. of Iowa) review the foundations of the concept, then hone in on the finite mixture methodologies that are being found increasingly successful. They do discuss cluster analysis, historically the best known technique for market segmentation, but argue that finite mixture techniques are better because they are model based and allow for segmentation in a framework in which customer behavior is described by an appropriate statistical model that includes a mixture component. They mention no date for the first edition. Annotation c. Book News, Inc., Portland, OR

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Recent computer and statistical developments are helping fulfill marketing's dreams of better measuring and meeting diverse customer needs. Wedel (U. of Groningen) and Kamakura (U. of Pittsburgh) purport to fill a gap in disseminating cutting edge segmentation researchwhich will hopefully provide a competitive edgeby focusing on finite mixture models. Topics include: the historical development of segmentation marketing since the 1950s, methodology, special topics, applied market segmentation, and directions for future research. Graphics and algorithms augment the text. Annotation c. by Book News, Inc., Portland, Or.

PART 1 – Introduction 1 The Historical Development of the Market Segmentation Concept 2 Segmentation Bases 3 Segmentation Methods 4 Tools for Market Segmentation PART 2 – Segmentation Methodology 5 Clustering Methods 6 Mixture Models 7 Mixture Regression Models 8 Mixture Unfolding Models 9 Profiling Segments 10 Dynamic Segmentation PART 3 – Special Topics in Market Segmentation 11 Joint Segmentation 12 Market Segmentation with Tailored Interviewing 13 Model-Based Segmentation Using Structural Equation Models 14 Segmentation Based on Product Dissimilarity Judgments PART 4 – Applied Market Segmentation 15 General Observable Bases: Geo-Demographics 16 General Unobservable Bases: Values and Lifestyles 17 Product-specific Observable Bases: Response-based Segmentation 18 Product-specific Unobservable Bases: Conjoint Analysis PART 5 – Conclusions and Directions for Future Research 19 Conclusions: Representations of Heterogenity 20 Directions for Future Research