Tell me what I want to hear: The effects of matching reviews on consumers’ decision making

Knowing online reviews are helpful for consumers’ decision-making, online shopping platforms often utilize review ranking algorithms to put “featured reviews” on top. This practice is supposed to help consumers navigate the vast quantity and varying quality of online reviews. However, it runs the risk of displaying reviews that do not match consumers’ shopping orientations – the preferences for certain product attributes. We investigate the consequences of this mismatch on consumers’ evaluation of review helpfulness and their downstream purchase decision quality. The research reveals the heterogeneous nature of online reviews by conducting topic modeling with an archival dataset. Next, we conduct experiments to examine the (mis)matching effects. We found that consumers see reviews matching their needs to be more helpful. They also make better shopping decisions. The benefit of matched reviews also holds across both positive and negative reviews. The paper offers theoretical contributions by highlighting the importance of matching reviews with consumers’ orientations and calling attention to the unintended consequences of review ranking practices on shopping platforms.