WiFi networks are becoming increasingly ubiquitous. In addition to providing network connectivity, WiFi finds applications in areas such as indoor and outdoor localisation, home automation, and physical analytics. In this paper, we explore the semantics of one key attribute of a WiFi network, SSID name. Using a dataset of approximately 120,000 WiFi access points and their corresponding geo-locations, we use a set of similarity metrics to relate SSID names to known business venues such as cafes, theatres, and shopping centres. Such correlations can be exploited by an adversary who has access to smartphone users preferred networks lists to build an accurate profile of the user and thus can be a potential privacy risk to the users.