Brand Perceptual Mapping by Text Mining Online Product Reviews

Abstract

Brand perceptual mapping is a visual technique, which displays how a brand is positioned in the mind of customers as well as in relation to its competitors. Building a perceptual map requires information regarding consumer perceptions towards that brand, which usually comes from a comprehensive market study (e.g. by conducting surveys, interviews or similar techniques). However, with rapid growth of e-commerce and abundance of online consumer-generated content, there is no need for marketers to go through time-consuming and error-prone market research to understand customers opinions. In this study, we propose a method to build a perceptual map automatically by mining customer opinions from online product reviews. We use opinion mining techniques to extract and rank the product aspects that are important to customers while purchasing digital tablets. Then we generate a score for each brand in these aspects and build the perceptual map using clustering the brands by these scores. The proposed method is applied to the online customer reviews for digital tablets extracted from Amazon.com. Our experimental results demonstrate the proposed technique is effective and able to correctly depict the position of a brand in its competitive environment.

Keywords: Brand Position, Perceptual Map, Online Customer Review, Data Mining

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