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MANAGERIAL DECISIONS ON OPTIMAL NUMBER OF DEMAND SEGMENTS
Abstract
Demand segmentation is an important tool for enterprises to improve planning and apply various marketing policies. The purpose of this study is to present a new approach to determining the optimal number of market segments taking into consideration the measure of homogeneity of certain segments, their size, and economic attractiveness. In this study the mathematical background is described based on a Fuzzy C-Means clustering algorithm. The method is then demonstrated using concrete data with the age and the average spending of the respondents of a questionnaire enquiry as two input variables for the clustering method. A method of quota selection was used for the data structure to match the reality. Demand segmentation is used for targeting a smaller, relatively homogenous market and is helpful for managers to reach the chosen segment of customers effectively with one marketing mix. Using the suggested method, the managers can determine which segment is still of interest to an enterprise in terms of financial income and which no longer is. In this way, it is possible to define the optimal number of segments to be focused on by the enterprise. Future research will be concerned with an analysis of the potential use of the method in a space of dimension greater than two and the graphical output options. Further research will also be concerned with the mathematical model and graphical output of the measure of competition in selected segments.
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