Analyzing competitive market structures based on online consumer-generated content and sales data

Purpose This study aims to provide a way to derive inter-brand similarities from user-generated content on online brand forums, which enables the authors to analyze the market structures based on consumers' actual information searching and sharing behavior online. This study further presents a method for deriving inter-brand similarities from data on how the sales of competing brands covary over time. The results obtained by the above two methods are compared to each other. Design/methodology/approach In drawing similarities between brands, the authors utilized a newly proposed measure that modified the lift measure. The derived similarity information was applied to multidimensional scaling (MDS) to analyze the perceived market structure. The authors applied the proposed methodology to the imported car market in South Korea. Findings In light of some clear information such as the country of origin, the market structure derived from the presented methodology was seen to accurately reflect the consumer's perception of the market. A significant relevance has been found between the results derived from user-generated online content and sales data. Originality/value The presented method allows marketers to track changes in competitive market structures and identify their major competitors quickly and cost-effectively. This study can contribute to improving the utilization of the overflowing information in the big data era by proposing methods of linking new types of online data with existing market research methods.

Automated summary

This study presents a method for deriving inter-brand similarities and analyzing market structures based on user-generated content and sales data. The results show a significant correlation between user-generated online content and sales data.