The BRILLO (Bartending Robot for Interactive Long-Lasting Operations) project aims to create an autonomous robotic bartender that can interact with customers while accomplishing its bartending tasks. In such a scenario, people's novelty effect connected to the use of an attractive technology is destined to wear off and, consequently, negatively affects the success of the service robotics application. For this reason, providing personalised natural interaction while people access its services is fundamental for increasing users' engagement and, consequently, their loyalty. In this paper, we present the developed three-layer ROS architecture integrating a perception layer managing the processing of different social signals, a decision-making layer for handling multi-party interactions, and an execution layer controlling the behaviour of a complex robot composed of arms and a face. Finally, user modelling through a beliefs layer allows for personalized interaction. We also present the results of both people's interaction, experience and performances in a real user case. The user study involved 116 participants and showed that BRILLO is considered an easy-to-use and attractive system by the users.