The Semantic Brand Score
This provides a tool for companies to manage brand equity in big data contexts, though it is incremental as it builds on existing constructs.
The paper introduces the Semantic Brand Score (SBS), a new metric for measuring brand importance using text data through social network and semantic analysis, which can be applied across various contexts and languages to support decision-making like stock price forecasting and competitive assessment.
The Semantic Brand Score (SBS) is a new measure of brand importance calculated on text data, combining methods of social network and semantic analysis. This metric is flexible as it can be used in different contexts and across products, markets and languages. It is applicable not only to brands, but also to multiple sets of words. The SBS, described together with its three dimensions of brand prevalence, diversity and connectivity, represents a contribution to the research on brand equity and on word co-occurrence networks. It can be used to support decision-making processes within companies; for example, it can be applied to forecast a company's stock price or to assess brand importance with respect to competitors. On the one side, the SBS relates to familiar constructs of brand equity, on the other, it offers new perspectives for effective strategic management of brands in the era of big data.