In a study examining decision-making patterns among international vacationers,260 respondents provided information on six psychographic orientations; psychological, educational, social, relaxational, physiological, and aesthetic. Cluster analysis was used to group respondents into psychographic segments.The results suggested that there were three meaningful segments based upon these lifestyles. The first segment (53percent) consisted of individuals who were high on nearly all lifestyle scales. This group was called the”demanders.” The second group(20 percent) washi hon the education a scale and was named the”educationalists.”The last group (26 percent) Washington relaxation and low on social scales and was named the “escapists.” Specific marketing strategies were formulated to attract vacation resin each segment. In order to recover from the aftermath of the economic down turn in 2008-2009, Trail and made special fort to reach the “escapists” segmentin2010, because the country would appeal the most to the see vacationers, given its many relaxation opportunities rich in natural beauty.
• Understanding buyer behaviors: Cluster analysis can be used to identify homogeneous groups of buyers. Then the buying behavior of each group may be examined separately, as in the department store project, where respondents were clustered on the basis of self-reported importance attached to each factor of the choice criteria utilized in selecting a department store. Cluster analysis has also been used to identify the kinds of strategies automobile purchasers use to obtain external information
• Identifying new product opportunities: By clustering brands and products, competitive sets within the market can be determined. Brands in the same cluster compete more fiercely with each other than with brands in other clusters. A firm can examine its current offerings compared to those of its competitors to identify potential new product opportunities
• Selecting test markets: By grouping cities into homogeneous clusters, it is possible to select comparable cities to test various marketing strategies.
• Reducing data: Cluster analysis can be used as a general data reduction tool to develop clusters or subgroups of data that are more manageable than individual observations. Subsequent multivariate analysis is conducted on the clusters rather than on the individual observations. For example, to describe differences in consumers’ product usage behavior, the consumers may first be clustered into groups. The differences among the groups may then be examined using multiple discriminant analysis.