The common prior assumption is pervasive in game-theoretic models with incomplete information. This paper investigates experimentally the importance of inducing a common prior in a two-person signaling game. For a specific probability distribution of the sender’s type, the long-run behavior without an induced common prior is shown to be different from the behavior when a common prior is induced, while for other distributions behavior is similar under both regimes. We also present a learning model that allows players to learn about the other players’ strategies and the prior distribution of the sender’s type. We show that this learning model accurately accounts for all main features of the data.