ABSTRACT
Classifying objects into similar groups is a task most of us have encountered in our daily lives. A child classifies his toys according to his favorite colors; a real estate agent classifies his homes according to the location and price; and a direct marketer classifies his target according to a variety of geographic, demographic, psychographic, and behavioral attributes. As the field of classification science has become more sophisticated, we have grown to rely more on objective techniques of numerical taxonomy. The advent of high-speed desktop computers having enormous storage capacities has greatly facilitated the applications of advanced statistical tools in business situations. The common term for the class of procedures that are used to isolate component data into groups is “cluster analysis.” The application of cluster analysis is prevalent in such diverse areas as (1) psychology for classifying individuals into personality types; (2) chemistry for classifying compounds as per their properties; (3) regional analysis for classifying cities as per their demographic and other variables; and (4) marketing analysis for classifying customers into segments on the basis of their buying behavior and product use.
