The Impact of Online Product Reviews on Product Returns

Abstract

Although many researchers in information systems and marketing have studied the effect of product reviews on sales, few have looked at their effect on product returns. We hypothesize that, by reducing product uncertainty, product reviews affect the probability of product returns. We elaborate this hypothesis starting with an analytical model that examines how changes in valence and precision of information from product reviews influence the purchase and return probabilities of risk-averse, but rational, consumers. We then empirically test our hypotheses using a transaction-level data set from a multichannel, multibrand North American specialty retailer. Harnessing different consumers’ purchases and returns of the same products, but with varying sets of product reviews over two years, we show that the availability of more reviews and the presence of more “helpful” reviews, as voted by consumers, lead to fewer product returns—after controlling for customer, product, and other context-related factors. Analyzing the purchase behavior of the consumers, we find that when fewer product reviews are available, consumers buy more substitutes in conjunction with a product, potentially to mitigate their uncertainty. Purchase of substitutes, in turn, leads to more product returns. Finally, leveraging a discontinuity in the displayed average ratings, we find that when products are shown with an average rating that is higher than the true rating, they are returned more often. These results support the predictions of our theoretical model—unbiased online reviews indeed help consumers make better purchase decisions, leading to lower product returns; biasing reviews upward results in more returns. The presence of online reviews has important cost implications for the firm beyond the cost of reprocessing the returns; we observe that when consumers return products, they are more likely to write online reviews and that these reviews are more negative than reviews that follow a nonreturned purchase. The online appendix is available at https://doi.org/10.1287/isre.2017.0736 .

(Poor) seeing is believing: When direct experience impairs product promotion

“…Indeed, positive reviews were found to facilitate product choice and increase sales (Chevalier & Mayzlin, 2006;Senecal & Nantel, 2004), although their effect might vary across markets, products, and consumers (Babic, Sotgiu, de Valck, & Bijmolt, 2015). A recent interesting study suggests that the variance in ratings also positively correlates with product returns (Sahoo, Srinivasan, & Dellarocas, 2013), a finding that seems consistent with our assertion that the effect of experiential information is very limited when it does not fully resolve uncertainty. Technological advances now enable consumers to have at least some direct experience online, and it is not clear how the two sources of information (self experience vs. online reviews) are combined to form overall product impression.…”

How online word‐of‐mouth impacts receivers

“…A more specific reputation marker that appears on Amazon (and some other platforms) ranks each sender and designates some with “top reviewer” badges (e.g., top 1,000, top 50) based on their average helpfulness ratings for each review and on the total number of reviews they have written (Amazon.com, n.d.). However, sender badges and rankings have shown inconsistent effects on receivers in terms of review helpfulness, sales, and product returns (Baek, Ahn, & Choi, ; Chen et al, ; Huang et al, ; Otterbacher, ; Pu et al, ; Sahoo, Dellarocas, & Srinivasan, ; Yazdani et al, ).…”

“…Consumer ratings of WOM are widely available, though the rating system varies by platform (e.g., likes, hearts, useful votes, helpful votes). Regardless, the sum or proportion of positive ratings indicates the quality of the information provided (e.g., Chen et al, ; Ghose & Ipeirotis, ; Khern‐am‐nuai et al, ; Sahoo et al, ), and can increase trust (Packard et al, ; Resnick et al, ). Consistent with this, others’ evaluations of a source's past behavior provide a player signal of trustworthiness (Petty, Cacioppo, & Goldman, ; Shapiro, ; Weiss et al, ).…”

The Optimal Carbon Reduction and Return Strategies under Carbon Tax Policy

“…Altug and Aydinliyim [26] studied how consumers' discount-seeking purchase deferrals affect the return policy of online retailers and found that retailers in some conditions can gain a competitive advantage when selling to strategic consumers. Sahoo et al [27] explored the impact of online product reviews on the optimal online return strategy and showed that unbiased online reviews benefit consumers and that biasing reviews upwards results in more returns.…”