Viral marketing campaigns target primarily those individuals who are central in social networks and hence have social influence. Marketing events, however, may attract diverse audience. Despite the importance of event marketing, the influence of heterogeneous target groups is not well understood yet. In this paper, we define the Spreading Potential (SP) problem of target group selection given the mixture of influential and ordinary agents in groups. The SP problem is different from the well-known Influence Maximization (IM) problem that aims to find the most influential individual agents but does not consider mixture of influential and ordinary agents in target groups. We provide a systemic test for ranking influence measures in the SP problem based on node sampling and on a novel statistical method, the Sum of Ranking Differences. Using a Linear Threshold diffusion model on an online social network, we evaluate seven network measures of social influence. We demonstrate that the statistical assessment of these influence measures is remarkably different in the SP problem, when low-ranked individuals are present, from the IM problem, when we focus on the algorithm's top choices exclusively.