One Picture Is Worth a Thousand Words? The Pricing Power of Images in e-Commerce

Abstract

In e-commerce, product presentations, and particularly images, are known to provide important information for user decision-making, and yet the relationship between images and prices has not been studied. To close this research gap, we suggest a tailored web mining framework, since one must quantify the relative contribution of image content in describing prices ceteris paribus. That is, one must account for the fact that such images inherently depict heterogeneous products. In order to isolate the pricing power of image content, we suggest a three-stage framework involving deep learning and statistical inference. Our empirical evaluation draws upon a comprehensive dataset of more than 20,000 online real estate listings. We find that the image content describes a large portion of the variance in prices, even when controlling for location and common characteristics of apartments. A one standard deviation in the image variable is associated with a increase in price. By utilizing a carefully designed instrumental variables estimation, we further set out to obtain causal estimates. Our empirical findings contribute to theory by quantifying the hedonic value of images and thus establishing a causal link between visual appearance and product pricing. Even though a positive relationship seems intuitive, we provide for the first time an empirical confirmation. Based on our large-scale computational study, we further yield evidence of a picture superiority effect: simply put, a beneficial image corresponds to the same price change as 2856.03 additional words in the textual description. In sum, images capture valuable information for users that goes beyond narrative explanations. As a direct implication, we aid online platforms and their users in assessing and improving the multi-modal presentation of product offerings. Finally, we contribute to web mining by highlighting the importance of visual information.