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A brand share prediction model based on several disparate sources of data: an empirical model of detergent choice in Mumbai, India

Arindam Banerjee (Associate Professor, Marketing Area, Indian Institute of Management Ahmedabad, Vastrapur, Ahmedabad, Gujarat, Pin 380015, India)

Asia Pacific Journal of Marketing and Logistics

ISSN: 1355-5855

Article publication date: 1 September 2004

Abstract

We describe the application of a nested logit function for modelling consumer brand choice using household transaction data from the Indian market. This is unique since it is one of the first attempts to integrate disparate consumer information sources available at various levels of aggregation towards developing a prediction model for brand market share in India. We test the usefulness of the model for forecasting brand market share in the premium detergents market in Mumbai, India. The results of the model building exercise reveal the importance of advertising, specifically the role of ad message in influencing brand choice. It is concluded that such modelling initiatives show significant returns for market planning exercises in developing markets. However, the need for streamlining the collection of market data and its subsequent organization in a form that can help develop more portent prediction models is apparent.

Keywords

Citation

Banerjee, A. (2004), "A brand share prediction model based on several disparate sources of data: an empirical model of detergent choice in Mumbai, India", Asia Pacific Journal of Marketing and Logistics, Vol. 16 No. 3, pp. 3-22. https://doi.org/10.1108/13555850410765203

Publisher

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Emerald Group Publishing Limited

Copyright © 2004, Emerald Group Publishing Limited