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Applications that are co-scheduled on a multi-core compete for shared resources, such as cache capacity and memory bandwidth. The performance degradation resulting from this contention can be substantial, which makes it important to effectively manage these shared resources. This, however, requires quantitative insight into how applications are impacted by such contention. In this paper we present a quantitative method to measure applications' sensitivities to different degrees of contention for off-chip memory bandwidth on real hardware. We then use the data captured with our profiling method to estimate the throughput of a set of co-running instances of a single threaded application.