When Online Reviews Meet Hyperdifferentiation: A Study of the Craft Beer Industry

Abstract

We analyze how online reviews are used to evaluate the effectiveness of product differentiation strategies based on the theories of hyperdifferentiation and resonance marketing. Hyperdifferentiation says that firms can now produce almost anything that appeals to consumers and they can manage the complexity of the increasingly diverse product portfolios that result. Resonance marketing says that informed consumers will purchase products that they actually truly want. When consumers become more informed, firms that provide highly differentiated products should experience higher growth rates than firms with less differentiated offerings. We construct measures of product positioning based on online ratings and find supportive evidence using sales data from the craft beer industry. In particular, we find that the variance of ratings and the strength of the most positive quartile of reviews play a significant role in determining which new products grow fastest in the market-place. This supports our expectations for resonance marketing.

Evaluating right versus just evaluating online consumer reviews

“…Herr et al (1991), Lee et al (2009), Xue andZhou (2010), Yang and Mai (2010), and Yin et al (2014) empirically show that negative WOM has a stronger impact than positive WOM. A second argument asserts a positivity effect (Clemons et al, 2006;East et al, 2007;Gershoff et al, 2003;Skowronski & Carlston, 1989). Gershoff et al (2003), Clemons et al (2006), and East et al (2007 show that positive reviews have a stronger impact than do negative ones.…”

“…Three competing arguments have been proposed concerning this recommendation valence: the positivity effect (Clemons, Gao, & Hitt, 2006;East, Hammond, & Lomax, 2007;Gershoff, Mukherjee, & Mukhopadhyay, 2003;Skowronski & Carlston, 1989), negativity effect (Chiou & Cheng, 2003;Fiske, 1980;Skowronski & Carlston, 1989;Yin, Bond, & Zhang, 2014), and no effect (Cheung, Lee, & Rabjohn, 2008;Doh & Hwang, 2009). However, the research results have been mixed.…”

Does sampling influence customers in online retailing of digital music?

“…As a result, they negatively influence the number of shoppers interested in a product and the related conversion rate. Previous literature also shows the variance in ratings play a significant role in determining which new products grow fastest in the marketplace (Clemons et al 2006). Therefore we propose:…”

“…Therefore it increases the conversion rate of a product. Previous studies showed that the mean of online product reviews had a significant effect on sales (e.g., Chevalier and Goolsbee 2003;Clemons et al 2006;Dellarocas et al 2007). And we expect that mean of online product reviews will have similar impact on conversion rate.…”

“…While some studies showed that the mean of online product reviews had a significant effect on sales (e.g., Chevalier and Goolsbee 2003;Clemons et al 2006), other studies showed that the average rating of online product reviews might not impact product sales (Chen et al 2004;Duan et al 2008;Liu 2006) because book reviews largely served the purpose of informing consumers about books' contents and characteristics and not its intrinsic quality. For book reviews, any publicity was good publicity because even negative reviews led to increases in sales (Sorensen and Rasmussen 2004).…”