In large ubiquitous computing environments it is hard for users to identify and activate the electronic services that match their needs. This user study compares the newly developed service matcher system with a conventional system for identifying and selecting appropriate services. The study addresses human factors issues such as usability, trust and service awareness. With the conventional system users have to browse a hierarchical list of currently available services and activate the service that they think satisfies their current needs. With the service matcher users just enter their current need using natural language, after which a wizard, emulating an existing service matcher algorithm, searches for and activates a matching service based on the given need and the users location and gaze direction. This study shows that with the hierarchical list, only 66% of the tasks are solved correctly, and females score significantly worse than males. With the service matcher, the performance increases significantly to 84% correctly performed tasks and the gender difference disappears.