English

Vijayalakshmi S,Magesh S,Mahalakshmi V

doi:10.5897/ajbm2013.7038

Abstract

The global economy is improving every year and during the forthcoming decades, marketers need to enter new national markets towards an understanding of how data mining techniques influences consumer behavior, which will be vital for consumer researches. The comprehension of available data mining methods to the presence of outlying measurements in the observed data is discussed as a major drawback of existing data mining methods. The psychological and social processes involved in consumer behaviour forms the subject matter of this study. The objective in accordance with an optimistic approach in terms of studying cause and effect in consumer behaviour will be combined with interpretative prominence on trying to understand the emotional, non-rational aspects of the process. The scope of this paper is to: (1) provide knowledge discovery in consumer behavior, (2) provide experience in the application of K-means data mining techniques in consumer behavior concepts to marketing management decisions. The methodology involves through systematic sampling method and prepared questionnaire which helps to discover knowledge from consumer behaviour predominantly through data mining for the extraction of hidden predictive information from large databases organizations can recognize valuable customers, predict future behaviors, and enable firms to make practical, knowledge-driven decisions. The study will be based on market segmentation wherein, retailers will realize they could no longer sell whatever they bought but had to begin competing for their businesses. This paper proposes k means clustering methods and dendograms suitable for the analysis of data in management applications. Key words: Data mining, knowledge discovery, segmentation, consumer behaviour, marketing.

Highlights

Chennai is one of the biggest metropolitan cities in South India with huge electronic market which includes the imported electronic goods from Singapore, Malaysia and Japan flourishes the entire city
Data mining is often executed with the aim to extract information relevant for making predictions and/or decision making, which can be described as selecting an activity or series of activities among several alternatives
Data mining methods are routinely used by practitioners in everyday management applications

Summary

Introduction

Chennai is one of the biggest metropolitan cities in South India with huge electronic market which includes the imported electronic goods from Singapore, Malaysia and Japan flourishes the entire city. From the year 2011 the Chennai consumer durables industry has noticed substantial developments due to globalization policies in. The globalization and importing policies have made Chennai a predominant place for the Electronic Market. Several global players like Sony, Whirlpool, Philips, Samsung and LG are well established in the Consumer durables sector in India, with antagonism from strong Indian players like Voltas, Videocon, Bajaj Electricals, Blue Star, Carrier, Godrej, and MIRC Electronics. Data mining is often executed with the aim to extract information relevant for making predictions and/or decision making, which can be described as selecting an activity or series of activities among several alternatives. A statistician commonly deals with observing a smaller number of variables on relatively small samples, which is another difference from the data mining context. The robust version of kmeans cluster analysis tailor-made for high-dimensional applications (Gao and Hitchcock, 2010)

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