Automotive Market Segmentation by Machine Learning

J. Polpinij (Thailand)


Machine learning, Neural network, Market Segmentation


Due to competitive market, many firms operators are constantly searching for alternative methods to supplement their income. One method of business is market segmentation analysis. Consequently, the classical approaches to segmentation such as demographic and behavioral segmentation schemes are well known. Entrepreneurs may segment their market on the basis of demographic characteristics such as age, income, or gender and geographic concentrations of consumers with the desired attributes. Demographic variables are a critical component to market segmentation because DEMAND for most products is related to factors such as age, income, and race. This research analyzes about automobile data by Back propagation artificial neural networks which one of machine learning technique for determining market plans. It used for classifying the group of geographic concentrations of consumers. When the segment model finished, it shown classifying model for analyzing concentrations of consumers. The third segment of the automobile is favorable, the mostly of group C is the Japanese car. The result from this analysis can be used to help determine marketing plans, particularly promotion, and to help companies retain and regain market share.

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