In this chapter, we discuss personalisation of advertisements in the digital TV environment and propose an effective personalisation approach, taking into account unique domain requirements. The proposed approach combines the widely used Pearson-based collaborative filtering technique, applied on numerical ratings with the user’s lifestyle, a stable characteristic drawn from consumer behaviour theory. We claim that users with similar lifestyles are reliable neighbours and can be utilised for the recommendation of advertisements for any member of their lifestyle neighbourhood. We focus on an inherent limitation of collaborative filtering methods that occurs when few ratings are available for each user and demonstrate that the proposed approach effectively manages this problem. Indeed, the hybrid approach combines the ability of the Pearson-based approach to accommodate rapid changes in user needs and make predictions upon one-click interactions and the advantage of the lifestyle-based approach to handle sparse data, which significantly affects the performance of collaborative filtering prediction methods.