Conversational systems use spoken language to interact with their users. Although conversational systems, such as Amazon Alexa, are becoming common and can provide interesting functionalities, there is li le known about the issues users of these systems face.In this paper, we study user reviews of more than 2,800 Alexa skills to understand the characteristics of the reviews and the issues that they raise. Our results suggest that most skills receive fewer than 50 reviews. Our qualitative study of user reviews using open coding resulted in identifying 16 types of issues in the user reviews. Issues related to content, integration with online services and devices, errors, and regression are the top issues raised by the users. Our results also indicate di erences in volume and types of complaints by users when compared with more traditional mobile applications. We discuss the implication of our results for practitioners and researchers.