The Dynamics of Online Customer Review Engagement
Patrick A. Barbro
Temple University
Department of Marketing and Supply Chain Management
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ABSTRACT
Consumers and retailers increasingly benefit from online customer reviews, especially in online environments with high consumer engagement. This study examines the dynamics of customer review engagement, as indicated by changes in review votes or comments. This study presents a theory-based explanation of how social dynamics, review position on the page, and the static and variable characteristics of the review, combine to affect the level of customer engagement with online reviews. The research builds on the work of Moe and Trusov (2011) and Sridhar and Srinivasan (2012) who established that social dynamics impact the review environment and the volume and characteristics of future reviews. The model is tested using a unique data set of reviews from Amazon.com that includes data on how reviewing behavior for newly launched products changed over time. The findings provide insights on the theoretical underpinnings of consumer engagement with online reviews, and implications for managers.
Information from other consumers has been shown to impact consumer action in the online review environment (Moe and Trusov 2011). In addition, the norms of the online review community need to be considered in the context of social dynamics and engagement. Online communities have norms of reviewing behavior, with consequences when not followed (Kozinets et al 2010). Reviews with comments on retailer service or on off-topic subjects, violate established practice and social norms, and lead to negative engagement.
In addition, many retail websites like Amazon.com give a visible and favorable position on the page to reviews that are considered to be helpful or recent. This is an important determinant of review engagement, as any factor that increases the accessibility of an input increases the chance that it will be used (Janiszewski 1998). Review position on the page changes daily due to other factors present in the environment, thereby constituting a variable characteristic. In addition, static features of reviews, including star rating and word count, have previously been shown to influence customer evaluations of reviews (Mudambi and Schuff 2010). The quantifiable static features, and the qualitative aspects of text content, especially regarding review alignment with community norms, are important drivers of review engagement.
To evaluate these expected drivers of review engagement, product review data were collected for the first 30 days after launch on Amazon.com. In recognition that books are an important subject of online reviews (Chevalier and Mayzlin 2006), the reviews were of newly released books. Detailed information on the review social dynamics, the static review characteristics, the variable position on page, and the nature of consumer engagement responses were captured every 24 hours after the book’s release. This unique data set enabled the capture and tracking of all variable review characteristics and social dynamics from the start and as it happens. Results suggest that factors concerning a review and its environment can impact the amount of engagement a review receives. Higher levels of engagement were found for negative reviews, reviews with content that violates community norms, and reviews placed in positions with increased visual accessibility. Additionally, a relationship was found between reviewer identity disclosure and review helpfulness that could impact engagement levels. Overall, the findings highlight the role of social dynamics and community norms in determining engagement with user generated review content.
References
Chevalier, J.A. Mayzlin, D. (2006). The Effect of Word of Mouth on Sales: Online Book Reviews. Journal of Marketing Research, 43(3), 345-354.
Kozinets, R., de Valck, K., Wojnicki, A. C. & Wilner, S. J. S. (2010). Networked Narratives: Understanding Work-of Mouth Marketing in Online Communities. Journal of Marketing, 74(2), 71-89.
Janiszewski, C. (1998). The Influence of Display Characteristics on Visual Exploratory Search Behavior. Journal of Consumer Research, 25(3), 290-301.
Moe, W. W. & Trusov, M. (2011). The Value of Social Dynamics in Online Product Ratings Forums. Journal of Marketing Research, 48(3), 444-456.
Mudambi, S. M. & Schuff, D. (2010). What Makes a Helpful Online Review? A Study of Customer Reviews on Amazon.com. MIS Quarterly, 34(1), 185-200.
Sridhar, S. & Srinivasan, R. (2012). Social Influence Effects in Online Product Ratings. Journal of Marketing, 76(3), 70-88.