Visualization of brand positioning based on consumer web search information: Using social network analysis. Issue 2 (3rd April 2017)

• Record Type: Journal Article
• Authors: Jun, Seung-Pyo; Park, Do-Hyung
• Is Part Of: Internet research. Volume 27:Issue 2(2017)
• Page Start: 381
• Page End: 407
• Publication Date: 2017-04-03
• Subjects: Google Trends -- Social network analysis -- Brand positioning -- Search behaviour -- Web search traffic; Internet -- Periodicals; Computer networks -- Periodicals; 004.678
• DOI: 10.1108/IntR-02-2016-0037
• Languages: English
• ISSNs: 1066-2243

Abstract

Abstract : Purpose: Online web searches have played crucial roles in influencing consumers' purchasing decisions. Web search traffic information enables researchers and practitioners to better understand consumers in terms of their preferences and interests, among other things. The purpose of this paper is to use web search traffic information provided by Google Trends to derive relationships among product brands as well as those between product brands and product attributes to propose a method to enhance the visibility of consumer brand positioning. Design/methodology/approach: This study builds upon the interesting observation that consumers' behavior in performing simultaneous searches, or searches including two or more keywords, can be converted into data indicating relationships among brands as well as those between brands and their attributes. The study focuses on the cases of hybrid cars and tablet PCs, and applies a social network analysis method to identify these relationships. Time series information on web search traffic is used because it can track these two product groups from the early stages to the present. This step is completed to verify the changes in the status of each brand and in their relationships that occurred in consumers' minds over time. Findings: Results show that consumers' web search behaviors reveal the brand positioning and brand-attribute associations in their minds. Specifically, using consumers' simultaneous search data, the authors derived relationships among brands (brand-brand network) from consumers' behaviors of searching simultaneously for two brands and the relationships between brands and attributes (brand-product attributes network) from consumers' behavior of searching simultaneously for a specific brand and certain product attributes. Originality/value: Theoretically, this study verifies that consumers' web search traffic information can be used to microscopically identify the positions of individual brands and their relationships in the minds of consumers. Regarding practical applications, this study proposes a method that can be used by companies to track how consumers perceive their brands by performing a simple and cost-effective analysis using the free search traffic information provided by Google.