Academic journal article Journal of Theoretical and Applied Electronic Commerce Research

Busting Myths of Electronic Word of Mouth: The Relationship between Customer Ratings and the Sales of Mobile Applications

Academic journal article Journal of Theoretical and Applied Electronic Commerce Research

Busting Myths of Electronic Word of Mouth: The Relationship between Customer Ratings and the Sales of Mobile Applications

Article excerpt

1 Introduction

Hundreds, if not thousands, of new mobile applications are released every day in mobile application marketplaces, such as the Apple App Store, Google Play, and Windows Phone Marketplace. Together, these three dominant mobile application ecosystems provide over a million applications for customers. For a single developer of an application, differentiating one's offerings from the masses and increasing sales is an arduous task. However, as current research has argued [18], [26]-[28], earlier customers' comments delivered through electronic word-of-mouth, i.e., customer ratings and reviews, can improve sales. Hence, ratings might have a significant effect on the success of a product (see e.g. Site 1). Based on these earlier notions and the increasing relevance of the mobile app business, this paper addresses the relationship between customer ratings and sales in a mobile application marketplace. We use three datasets gathered from Google Play during a time span of 18 months. Together, these sets contain the information of over 800,000 unique applications and over 260 million ratings left by users.

Online recommendations and user reviews have become one of the most important sources of information for modern consumers [42]. Particularly in e-commerce, it is difficult for the customer to evaluate the product or the service and the benefits and value that it generates. Thus, new customers tend to rely on trustworthy independent information sources, such as customers who already have experienced the product. In other words, the customer relies on the judgment of other clients, experts, or actors in the field who share valuable information about the product through divergent ratings and review systems. Their experiences deliver information related to the user or customer perspective and thus reduce the risk and uncertainty perceived by consumers. There are divergent means to deliver consumer reviews and ratings, which are often termed as electronic word-of-mouth (E-WOM). E-WOM is communicated through discussion forums, blogs, online opinion sites, online communities, online product reviews, and comments written by consumers on web pages [11], [15]-[16] and includes divergent verbal and numeric practices of sharing customer experiences and judgments [60]. In this paper, we focus particularly on ratings, i.e., the numerical or star evaluations given by customers.

The rapidly increasing studies on customer reviews and ratings clearly show that the perception of the trustworthiness of a source can lead to the increased persuasiveness of the information, and that user-generated content, such as consumer reviews, are more influential than marketer-generated information on corporate websites (see, e.g., [7], [14], [16], [26], [48]).The extant studies have shown that electronic WOM has an effect on sales [26]-[28], customer value and loyalty [31], and online brand [2], as well as on the success of new product introductions [20]. Due to its rapidly expanding relevance and multiple effects in the context of contemporary business, e-WOM has given rise to much research in multiple disciplines. De Maeyer [26], for example, presents publications from marketing and management to psychology, information system sciences, and computer science. Thus, it can be argued that e-WOM is one of the cornerstones of e-commerce.

It is noteworthy that even though the previous studies have suggested that customer ratings improve sales [13], [18], [28], [60], there are also opposite results indicating that they do not have an impact on sales [38], [41], [44]. The key conceptualizations to measure the ratings' impact on sales have been volume (i.e., the number of ratings), valence (e.g., the average of the ratings), and variance (i.e., the dispersion of the ratings). There are, however, conflicting findings on how these measures indicate further sales: some studies have found a correlation between volume and sales but not between valence and sales [3], [13], whereas other studies have found support for the opposite [19], [29]. …

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