Mining brand value propositions on Twitter: exploring the link between marketer-generated content and eWOM outcomes

Abstract

Content marketing has become a mainstream channel for brands to engage the market with value propositions. Through content, brands control, instigate and co-create value with its target audience. However, the nature of value propositions embedded within the cycle of content co-creation and their impact on eWOM outcomes has received scant attention from an empirical perspective. In this paper, we propose a value proposition-based framework around content marketing using established business perspectives. We employ bidirectional Twitter data from brands and customers to unearth descriptive, diagnostic and predictive insights into value propositions. Using a sample of marketer- and user-generated data from 10 Coffee (n(MGC) = 290, n(UGC) = 8811) and Car brands (n(MGC) = 635, n(UGC) = 7035) in 2018, a taxonomy of value propositions based on the literature was proposed and validated. The results of our study identify (a) descriptive insights explaining differentiation of brand value propositions, (b) diagnostic insights relating to consumer sentiments in response to the value proposition mix and (c) predictive insights of models predicting brand-specific values’ influencing Like, Share, Comment and Positive/Negative valence. Our results show that an effective social media marketing strategy selectively uses elements of the marketing mix (i.e. 4 P’s) within value propositions to attract favourable eWOM outcomes.

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