A Unique Method of Constructing Brand Perceptual Maps by the Text Mining of Multimedia Consumer Reviews

A Unique Method of Constructing Brand Perceptual Maps by the Text Mining of Multimedia Consumer Reviews

Amir Ekhlassi, Amirhosein Zahedi
DOI: 10.4018/IJMCMC.2018070101
(Individual Articles)
No Current Special Offers


Brand perceptual mapping is a visual technique, it displays how a brand is positioned in the mind of customers, as well as in relation to the competitors. With the rapid growth of e-commerce and the abundance of online consumer-generated content, there is no need for marketers to go through market research in order to understand consumers' opinions. Therefore, in this study, the authors propose a unique method which allows the building of a perceptual map automatically by mining consumer opinions from in particular online product reviews. The authors employ opinion mining techniques to extract and rank the product aspects that are important to customers, during purchasing digital tablets. Subsequently, they generate a score for each brand in these aspects and build the perceptual map using clustering of the brands by these scores. This proposed method is applied to the online customer reviews for digital tablets obtained from Amazon.com. The experimental results highlight the proposed technique is effective and able to correctly depict the position of a brand in its particular competitive environment.
Article Preview

1. Introduction

To succeed in our over communicated society, companies must manage their brands through creating a distinct position in the minds of prospective customers. (Ries & Trout, 2010). For performing positioning analysis, marketers widely use perceptual mapping tool (Aggarwal, Vaidyanathan, & Venkatesh, 2009). Traditionally, the information needed for the design of a perceptual map would be obtained from comprehensive market research studies. In these methods, you want the customer to score on different aspects of several brands simultaneously (by surveys, interviews or similar techniques). While the existing approaches for perceptual mapping contribute to our understanding of the consumers’ behavior, they are also associated with various drawbacks, such as the limited sample sizes and the complications involved in developing a survey that is able to fully capture the consumers’ perceptions (Crotts, Mason & Davis, 2009). However, over recent years with the changes in consumer behavior, online shopping is increasingly becoming people's first choice when shopping (Singh, Irani, Rana, Dwivedi, Saumya, & Kumar Roy, 2017). Along with that, an exponential growth has occurred in the individual's activities in online channels of communication. Nowadays random conversations about brands are now more credible than targeted advertising campaigns and social circles have become the main source of influence overtaking external marketing communications and even personal preference (Kotler, Kartajaya & Setiawan, 2017). For instance, a recent study on the www.brightlocal.com suggested that 87% of buyers read 10 or less than 10 reviews before trusting a business (Singh et al., 2017).

Online channels of communication contain brand-related information and descriptors that define brand positions in the offline world (Aggarwal et al., 2009). Therefore, analyzing the vast amounts of available web-based information could replace polls, focus groups and other similar techniques used for market research (Marrese-Taylor, Velásquez, Bravo-Marquez, & Matsuo, 2013). However, due to the sheer quantity of this type of data (weblogs, online reviews, discussion boards and other unsolicited forms of consumer opinions), manual tracking of all the available data and processing of the competitors’ activities might be tedious, inaccurate, and rapidly outdated for marketers (Leong, Ewing, & Pitt, 2004). Therefore, a different approach than conventional marketing methods is required for the analysis of large datasets for research purposes (Krawczyk & Xiang, 2015). With this background in mind, an area of increasing attention among retailing researchers and strategists is the positioning of brands based on opinion of the online users (Ailawadi & Keller, 2004). This made academics and practitioners to try to construct algorithms for the effective analyzing of the valuable data of consumer forums, blogs, and product reviews. However, due to the lack of effective methods to extract the key features of these online texts, businesses might be unable to obtain useful information to develop a market structure map.

Complete Article List

Search this Journal:
Volume 14: 1 Issue (2023)
Volume 13: 4 Issues (2022): 2 Released, 2 Forthcoming
Volume 12: 4 Issues (2021)
Volume 11: 4 Issues (2020)
Volume 10: 4 Issues (2019)
Volume 9: 4 Issues (2018)
Volume 8: 4 Issues (2017)
Volume 7: 4 Issues (2016)
Volume 6: 4 Issues (2014)
Volume 5: 4 Issues (2013)
Volume 4: 4 Issues (2012)
Volume 3: 4 Issues (2011)
Volume 2: 4 Issues (2010)
Volume 1: 4 Issues (2009)
View Complete Journal Contents Listing