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AUTOMOTIVE MARKET SEGMENTATION BY MACHINE LEARNING

机译:通过机器学习进行汽车市场细分

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摘要

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.
机译:由于市场竞争激烈,许多公司运营商一直在寻找替代方法来增加收入。一种业务方法是市场细分分析。因此,众所周知的经典分割方法如人口统计和行为分割方案。企业家可以根据人口特征,例如年龄,收入或性别以及具有期望属性的消费者的地理集中度来细分市场。人口统计学变量是市场细分的关键组成部分,因为大多数产品的需求与年龄,收入和种族等因素有关。本研究通过反向传播人工神经网络对汽车数据进行分析,这是确定市场计划的机器学习技术之一。它用于对消费者的地理集中度组进行分类。当细分模型完成时,它显示了用于分析消费者集中度的分类模型。汽车的第三部分是有利的,C组中的大多数是日本汽车。分析的结果可用于帮助确定营销计划,尤其是促销计划,并帮助公司保留和重新获得市场份额。

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