The Effect of Online Customer Reviews’ Characteristics on Sales

Abstract

Online customer reviews help consumers make decisions, such as purchasing products, watching movies, or joining a sports club. Online reviews have become a major driving force in marketing (Cui et al., 2012) and are a common feature on many websites. Information from other consumers, such as online reviews, is thought to be more persuasive because it is allegedly written by other consumers rather than brands, and is therefore perceived as being more credible and trustworthy (Willemsen et al., 2012). In addition, online reviews are available wherever and whenever a consumer needs them. Due to their effectiveness and prevalence, online reviews attracted substantial attention from both researchers and practitioners. While previous research has looked into different review features, such as valence, length, and volume, the interaction between different features has been mostly neglected. Also, a large body of research on online reviews is based on experimental or survey based work and assumes that effects of online reviews are linear. We aim to address these shortcomings by relating actual sales in an online shop to various features of online reviews, namely: the number of reviews (review volume), the average number of stars (review valence), and length. The literature shows ambiguous results about the effects of all of the three review features that are covered in this paper. With regard to the valence of online reviews, it is the popular belief that it positively influences attitudes towards the brand and purchase behavior. However, the results of past studies are equivocal (see King et al., 2014 for a review). Some studies have shown that there is a disproportionally high number of positive online reviews, which may cause customers to discount positive reviews as not reliable (Chevalier and Mayzlin, 2006). Furthermore, it has been demonstrated that consumers hold a negativity bias in perception of reviews (Ba and Pavlou, 2002), whereas other studies have demonstrated consumers' positivity (Li and Hitt, 2008) or confirmation biases. Concerning the number of reviews, Bazaar (2015) showed that the count is generally positively correlated with sales volume. However, previous research has shown that for attribute-focused reviews, a large number of reviews creates information overload for consumers (Park and Lee, 2008), which might result in © Springer Fachmedien Wiesbaden 2017 G. Christodoulides et al. (Hrsg.), Advances in Advertising Research (Vol. VII), European Advertising Academy, DOI 10.1007/978-3-658-15220-8_8 88 Maslowska, Malthouse, and Bernritter negative effects on consumers' purchase behavior. Finally, the length of a review may influence consumers' behavior, but existing results are inconsistent. For example, Chevalier and Mayzlin (2006) found contradicting effects of review length between reviews on Amazon.com and barnesandnoble.com and concluded that longer reviews do not necessarily enhance sales. These inconsistencies emphasize that there is still much to be known about the workings and limits of consumers' online reviews (De Bruyn and Lilien, 2008; Kimmel and Kitchen, 2014). We think that the reasons for these inconsistencies rely on several factors. First, the majority of studies has focused on the relative strength of the effect of review valence and tested positivity versus negativity biases. Second, past studies have treated the effect of review valence on dependent variables as linear and have not looked at non-linear effects. Third, length has often been treated as a control variable (e.g., Kim and Gupta, 2012; Xu, 2014) rather than a factor. Fourth, previous studies have mostly dealt with information and entertainment products, such as books, movies, and television shows (Cui et al., 2012), which may be perceived as high-involvement, incidentally purchased products. In order to address these gaps, the aim of this study is to investigate the effects of three online customer reviews' features, that is, valence, volume, and length, on sales of a common use product– a light bulb.