The concept of communities and the interaction between people are not new concepts. People have always gathered around common conditions shared by those in the group such as shared emotions, interests, beliefs and needs. It is however the way we interact, with whom we interact, and when and where these meetings take place which has changed. This has been a direct result of the development of the internet and exacerbated with the move to the second phase of internet development. This second phase of internet development provides users with real-time functionality enabling interaction with global users in a virtual environment. This interaction is termed online social networking and takes place in online communities. Online communities present opportunities for marketers as they give rise to a virtually unlimited number of different consumers, structured around finer consumption and marketing interests. Research indicates that online community users are market-oriented and therefore online communities provide a meaningful medium of exchange for these users. The challenge for companies today has been trying to develop ways to capitalise on this trend and raise their competitive advantage. However, in order to effectively understand these users, an understanding of their characteristics is fundamental to the development of any tailored marketing campaign. This thesis therefore aims to shed an insight into a segmentation model designed for online communities - firstly by empirically testing it and secondly, by enriching the data with a typology of online buying behaviour characterised by psychographic and behaviour variables. Therefore the research question posed is “Can online community users be classified by their online buying behaviours so that they are useful to marketers?”. The empirical data was gathered quantitatively through an online questionnaire designed to classify the respondents into meaningful segments and clusters. The report reflects a social constructionist methodology where the results have been interpreted and given meaning. The report is based on the segmentation models presented by Kozinets’ ‘virtual communities of consumption’ and Barnes et al. typology on online buying behaviour. This report combines the two models in order to enrich the segmentation model presented by Kozinets’ with attributes of online buying behaviour in order to provide a more comprehensive understanding of online community users. The results indicated that the four online user profiles defined in Kozinets’ model did not show differences in their online purchasing behaviour. Rather all online community users could be categorised by Barnes et al’s three clusters of online buying behaviour.