Visual Reality Checks: Visual Discrepancy and the Demand Effects of Buyer-Generated Images

Speaker: Xinyu Cao

Venue: Room 718 School of Economics, Zijingang Campus

Abstract: Many online shopping platforms allow buyers to upload photos with their product reviews, giving prospective consumers access to visual information beyond seller-provided product images. Yet it remains unclear whether such buyer-generated images help or hurt subsequent sales. We examine the demand consequences of buyer review photos and how their effects depend on the visual information they provide relative to seller images. Using item-day data from apparel products on a large e-commerce platform, we exploit the arrival of the first buyer review containing photos and implement a matched event-study design. We find that the arrival of buyer review photos leads to an average 2.8% decline in subsequent sales. Importantly, this negative effect is larger when there is a larger visual gap between buyer- and seller-provided images. We further examine specific visual characteristics underlying this discrepancy. Differences in visual appeal account for part of the negative effect associated with the seller-buyer model-image gap, whereas differences in technical image quality and scene complexity play comparatively limited roles. Together, our findings show that buyer-generated product photos do not necessarily facilitate sales. Instead, their demand consequences depend critically on whether the visual information they reveal confirms or conflicts with the product presentation created by sellers.