Online privacy policies are the primary mechanism for in- forming users about data practices of online services. In practice, users ignore privacy policies as policies are long and complex to read. Since users do not read privacy policies, their expectations regarding data practices of online services may not match a service's actual data practices. Mismatches may result in users exposing themselves to unanticipated privacy risks such as unknowingly sharing personal information with online services. One approach for mitigating privacy risks is to provide simplified privacy notices, in addition to privacy policies, that highlight unexpected data practices. However, identifying mismatches between user expectations and services' practices is challenging. We propose and validate a practical approach for studying Web users' privacy expectations and identifying mismatches with practices stated in privacy policies. We conducted a user study with 240 participants and 16 websites, and identified mismatches in collection, sharing and deletion data practices. We discuss the implications of our results for the design of usable privacy notices, service providers, as well as public policy.