Segmenting online communities
Online-communitiesSegmentationBehaviourCommitment communication.Management of enterprisesFöretagsledningManagementBusiness and Economics
Thesis purpose: The main purpose of this study is to empirically verify the applicability of Kozinets´ model on an interest, activity or lifestyle based online community, in order to develop an adaptive segmentation approach for segmenting online communities. Methodology: This research is deductive by nature, cross-sectional by design and undertakes a quantitative approach using self-completion questionnaire as a part of a web survey to collect the empirical data needed. Theoretical perspective: The main theories guiding our work and supporting the findings of this study include: market segmentation (descriptive and behavioural) and communities (consumer communities and online communities). Empirical data: A web survey with self-completion questionnaire used to gather empirical data from members of interest, activity or lifestyle based online communities. Conclusions: This study took the specific characteristics of online communities into more consideration than previous research and literature has done and also recognized that an adaptive segmentation approach is needed, depending on the communities of study. Factors such as motivation, attitude, communication forms and internal community influence, were identified as highly important factors when considering an adaptive approach towards segmentation of online communities.