Chapter 2 Segmentation Basics Section 2 1 Segmentation

Chapter 2 Segmentation Basics

Section 2. 1 Segmentation Bases, Descriptors, and Methods

Objectives n n 3 State the difference between segmentation bases and segmentation descriptors. List the differences between segmentation studies for developing advertising versus segmentation studies for developing new products/services. State different types of segmentation variables. List different types of segmentation methods.

Primary Characteristics of Segments n n 4 Bases – characteristics that are used in deriving segments (such as customers’ needs, wants, preferences, and so on). Descriptors – characteristics that help us find and reach segments. – Examples in consumer markets include age, income, education, lifestyles, media habits, and so on. – Examples in business markets include SIC codes, employee size, yearly revenue, location, and so on.

Segmentation Variables and Methods: Some Caveats n n 5 Segments may not be physical entities that occur naturally. Rather, these are used by managers so that they can better serve the customers in these market segments. Identification of market segments is highly dependent on the variables and methods used to define them. The choice of a set of segmentation variables depends on the purpose of a study. The choice of a segmentation method depends on both the purpose of a study, as well as the segmentation variables.

Different Segmentations for Different Purposes Source: “Rediscovering Market Segmentation” by Yankelovich and Meer, Harvard Business Review, 2006. 6

Classification of Segmentation Variables General Product-Specific Observable Cultural, Demographic, User status, usage Geographic, Sociofrequency, RFM, loyalty, economic. situations. Unobservable Psychographics, values, life styles, personality. Benefits, perceptions, preferences, intentions Source: Market Segmentation by Wedel and Kamakura, International Series in Quantitative Marketing, 2000. 7

Classification of Segmentation Methods A Priori Post Hoc Descriptive Contingency tables, Log-linear models Clustering methods: Hierarchical, k-means, Kohonen (SOM) Predictive Cross-tabs, Regression, Logistic, Neural Networks, Discriminant Analysis, Decision Trees, CART, Mixture models Source: Market Segmentation by Wedel and Kamakura, International Series in Quantitative Marketing, 2000. 8

Normative Methods of Segmentation These use standard segmentation methods, but they use demand elasticities as segmentation variables. n Elasticities are useful concepts because they best capture the “responsiveness” dimension. n But, the elasticities are often hard to estimate reliably at the individual customer level. 9