Web-based product recommendation systems are usually based on very simple customer information. Since the adequacy of recommendations depends on the quality of data stored in the customer profile, profiles that store complex information, e.g. about interests, are highly desirable. However, current acquisition methods are not feasible for such kinds of profiles. In this paper we suggest a method for creating complex customer profiles during an adaptive text-based natural language dialog.