The signaling effect of sampling size in physical goods sampling via online channels

Prior literature has focused primarily on offline sampling of physical goods and online sampling of information goods, whereas a new form of sampling campaign—physical goods sampling via online channels—receives little attention. Leveraging a rich data set from Taobao, a large e-commerce platform in China, this study strives to understand the mechanisms of physical goods sampling via online channels. Specifically, we investigate (1) how the sampling size (number of free samples provided) acts as a signal of product quality and (2) how the signaling effect of sampling size varies across product types (i.e., search, experience, and credence products). We use a structural model to characterize the e-tailers’ decision process as a trade-off between the incurred cost of free sampling at present and the economic returns in future. We find that a 1% increase in sampling size leads to a total sales increase of 5.34% daily sales over a month. Of all product types, experience products benefit the most from the signaling effect of sampling size, whereas search products benefit the least. We further perform a policy simulation on the sampling threshold, that is, the minimum total value of the sampling product required to join the sampling campaign. Our results show that increasing the threshold leads to decreases in average sales and the number of e-tailers involved, and vice versa. As one of the first studies focusing on the mechanisms of physical goods sampling in the online context, our study provides empirical evidence of the signaling effect of sampling size. Full paper available at https://doi.org/10.1111/poms.13557