The number of online shoppers has been increasing in recent years. Online shopping involves the risk that the purchased product may not be what was expected. Recently, the number of product review videos has also been increasing, and more users are using them as a reference because they provide a more accurate understanding of how the product is used than conventional reviews. With this development in mind, we have been developing a review video recommendation system to support online shopping. Our system helps users to know which product review videos they should watch. In this paper, we propose a review video feature analysis method, which is a necessary technology to realize the proposed system, and conduct two evaluation experiments to confirm the effectiveness of the proposed method. The results of the evaluation revealed that the proposed system received good ratings from the users, which confirmed the effectiveness of the proposed method.