The Effect of Electronic Word of Mouth on Sales: A Meta-Analytic Review of Platform, Product, and Metric Factors

Ana Babić Rosario, Francesca Sotgiu, Kristine De Valck, and Tammo H.A. Bijmolt
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Key Takeaways

On average, eWOM is positively correlated with sales (.091), but its effectiveness differs across platform, product, and metric factors.

Negative eWOM does not always jeopardize sales, but high variability (i.e., consumer disagreement on a product's quality) does.

eWOM volume has a stronger impact on sales than eWOM valence (bandwagon effect). 


Article Snapshot​s: Executive Summaries from the Journal of Marketing Research​​

We find that the sales effectiveness of electronic word of mouth (eWOM) differs across online platforms, product characteristics, and eWOM metrics, such that eWOM on e-commerce sites, about newly introduced tangible goods, and measured in terms of volume (e.g., number of reviews) is most effective.
Research

This study was motivated by two inconclusive areas of research. First, because prior studies on eWOM have mostly looked at one platform and/or one product type (e.g., online ratings of books on Amazon.com), little was known about the way platform and product characteristics could change the effectiveness of eWOM. Second, researchers were in disagreement about the importance of specific eWOM metrics (e.g., volume, valence, variance).

  • ​General expectation: The effectiveness of eWOM will depend on the product characteristics and the online context.

Method

We analyzed previous academic literature on eWOM using a meta-analysis. Our sample consisted of 1532 statistical effect sizes from 96 studies, which allowed us to capture 40 online platforms and 26 product categories -- more than a regular research study is typically able to capture. We also collected additional information on online platforms using the Wayback Machine (https://archive.org/web), an Internet archive that provides access to past interfaces. Using this information, we analyzed when eWOM increases sales and when it jeopardizes it.


"The Effect of Electronic Word of Mouth on Sales: A Meta-Analytic Review of Platform, Product, and Metric Factors"


Findings

eWOM volume has a stronger impact on sales than eWOM valence. So, the dominant underlying aspect of eWOM is the bandwagon effect, where consumers tend to follow the crowd. Negative eWOM does not always jeopardize sales, but high variability (i.e., consumer disagreement on a​ product's quality) does. All eWOM is not alike: its sales effectiveness differs significantly across online platforms and product characteristics.

Implications

Our findings should be of interest to product and platform managers, eWOM monitoring agencies (e.g., Keller Fay Group, Nielsen BuzzMetrics), and academic researchers. Based on our study, we advise: (1) primarily monitoring the eWOM volume and variability (consumer disagreement), (2) acknowledging the context (product prices, promotions, and previous sales), and (3) noting that methodological choices, such as the type of endogeneity controls or the number of parameters used, can lead to an overestimation of eWOM effectiveness.

 

 Figure 1 is based on split-sample HiLMA analyses by platform type. We find that platform, product, and metric factors that moderate eWOM effectiveness differ by platform type. For instance, looking at eWOM that was only displayed on e-commerce platforms, we see that it is especially effective on the sales of newly introduced products


 

​Figure 2 is based on split-sample HiLMA analyses by product characteristics. We find that, from the perspective of product managers who want to increase eWOM-driven sales, it is important to assess the most salient characteristics of their products (i.e., tangibility, hedonic score, stage in the product life cycle, and level of financial risk).

 

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Figure 3 illustrates the predicted correlations of eWOM and sales. Negative eWOM is detrimental to mature products and those of low financial risk, but overall it is less concerning than eWOM variability (i.e., consumer disagreement).


Questions for the Classroom


  • Download classroom exercises HERE​
    • ​Which eWOM metric do you think is most related to sales? (Use a screenshot of an Amazon page showing a product and (1) volume of ratings, (2) avg. rating, (3) number of pos./neg. ratings, (4) distribution of ratings, and (5) textual review. Settle the discussion by showing how the context matters.)
    • Which eWOM metric and platform would you advise product managers to focus on? How will this recommendation change across industries and over time (in general and throughout product life cycle stages)?
    • Divide students into teams of 3-4 and assign a position to research and defend in a classroom debate regarding the key eWOM metric to monitor and boost: (1) eWOM volume vs. (2) eWOM valence. Detailed description of the class exercise is available here/ from the authors.



"The Effect of Electronic Word of Mouth on Sales: A Meta-Analytic Review of Platform, Product, and Metric Factors"​


 

​Full Article

Ana Babić Rosario, Francesca Sotgiu, Kristine De Valck, and Tammo H.A. Bijmolt (2016), "TheEffect of Electronic Word of Mouth on Sales: A Meta-Analytic Review ofPlatform, Product, and Metric Factors." Journal of Marketing Research, Vol. 53, No. 3, pp. 297-318.


Ana Babić Rosario was a doctoral candidate in Marketing, HEC Paris at the time of publication. Ana is now Assistant Professor of Marketing at the Daniels College of Business, University of Denver (e-mail: ana.babic-rosario@du.edu).



Francesca Sotgiu is Assistant Professor of Marketing, Vrije Universiteit Amsterdam (e-mail: f.sotgiu@vu.nl).



Kristine de Valck is Associate Professor of Marketing, HEC Paris (e-mail: devalck@hec.fr).



Tammo H.A. Bijmolt is Professor of Marketing Research, Faculty of Economics and Business, University of Groningen (e-mail:t.h.a.bijmolt@rug.nl).


Author Bio:

 
Ana Babić Rosario, Francesca Sotgiu, Kristine De Valck, and Tammo H.A. Bijmolt
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