The Dynamics of Online Customer Review Engagement
Patrick A. Barbro
Temple University
Department of Marketing and Supply Chain Management
Email: pbarbro@temple.edu
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.