Social business intelligence (SBI) is a rather novel discipline, emerged in the academic and business literature as a result of the convergence of two distinct research domains: business intelligence (BI) and social media. Traditional BI scientists and practitioners, after an inevitable initial shock, are currently discovering and acknowledge the potential of user generated content (UGD) published in social media as an invaluable and inexhaustible source of information capable of supporting a wide range of business activities. The confluence of these two emerging domains is already producing new added value organizational processes and enhanced business capabilities utilized by companies all over the world to effectively harness social media data and analyze them in order to produce added value information such as customer profiles and demographics, search habits, and social behaviors. Currently the SBI domain is largely uncharted, characterized by controversial definitions of terms and concepts, fragmented and isolated research efforts, obstacles created by proprietary data, systems and technologies that are not mature yet. This paper aspires to be one of the few - to our knowledge-contemporary efforts to explore the SBI scientific field, clarify definitions and concepts, structure the documented research efforts in the area and finally formulate an agenda of future research based on the identification of current research shortcomings and limitations.