In this paper we describe an intelligent and adaptive TV-shopping application that has been designed to recommend mobile phones to perspective buyers. The application is called iTVMobi and its adaptivity is achieved through a user model. The user model monitors users' behaviour and adapts the interaction to them depending on their inferred interests. The underlying reasoning is based on grouping users with similar tastes by the use of k-means clustering. After the clustering, representative vectors of users' preferences are calculated and compared through association rules with the products database in order to achieve product recommendations.