For consumers, online product reviews have become an important source for product-related information. Furthermore, they represent a beneficial addition to online retailers’ websites. Due to the increasing amount of available product reviews, identifying the most helpful product reviews represents an important task in order to reduce information overload. Therefore, the factors influencing review helpfulness have to be identified. Thus, in order to explain Review helpfulness, we build upon and extend review diagnosticity theory with concepts from marketing research and propose a research model that includes product quality, review sentiment and review uncertainty. Based on a sample of amazon.com product reviews, we evaluate our research model and find that statements about product quality positively influence review helpfulness. Furthermore, we identify that sentiment as well as uncertainty expressed in product reviews have an impact on review helpfulness. Finally, we confirm that the product category has a moderating effect on these relationships.