Since the arrival of Web 2.0, there is an increasing amount of on-line Reviews and Ratings about diverse products or services. These reviews contain general comments as well as highly personal elements or opinions about their customers' experience with the product. Other customers or companies are facing the problem of extracting the relevant information from this mass of reviews. In this paper, we present a comparative study of three different summarisation techniques for reviews analysis. From this study, we propose a general architecture which relies on a customisable abstractive summarisation approach making use of domain knowledge and temporal analysis. The paper ends by identifying research directions for improving the efficiency of review summarisation methods.