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Asian Journal of Research in Social Sciences and Humanities
Year : 2016, Volume : 6, Issue : 11
First page : ( 948) Last page : ( 960)
Online ISSN : 2249-7315.
Article DOI : 10.5958/2249-7315.2016.01242.9

A Cognitive Brand Positioning Exploration with Data Mining

Dr. Maheswaran G.*, Dr. Somasundaram R. S.**

*Associate Professor, Department of Management Studies, SNS College of Engineering, Coimbatore, TamilNadu, India

**Associate Professor, Department of Computer Applications, SNS College of Engineering, Coimbatore, TamilNadu, India

Online published on 9 November, 2016.

Abstract

Globalization takes every consumer in the world to look at branding. Even at rural market Multinational companies do their business. In early days, a product produced locally was distributed to the local market. But the current scenario provides an opportunity to the customer to choose a particular product from a variety of manufacturer and supplier. Here brand positioning plays a vital role. Consumer preferences vary based on the individual tastes, as measured by utility, of various bundles of goods. Coconut oil is preferred by the world for its nourishing nature. It becomes a staple product. It is taken as edible oil for cooking, hair toning oil, massage oil, cosmetic oil, etc. It is also preferred as a raw material for preparing other products such as lotion, cream, medicines. It can be consumed internally and externally. It is marketed by both branded and unbranded companies. Because of its wide importance in the market, it is decided to analyze the coconut oil market consumer brand preferences. For which, a survey was conducted in and around Coimbatore city with about 500 respondents of different category. Now-a-days, Data mining plays an important role in market analysis. Data mining based F-means clustering method is used to analyze the result. It is found that consumer has given importance for the quality and prefers branded coconut oil when compared to others.

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Keywords

Consumer Behaviour, Brand Loyalty, Purchase, Data Mining, Cluster Analysis.

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