In the field of self-organizing networks (SONs), the use case of concurrent capacity and coverage optimization (CCO) is challenging since the objectives are typically conflicting and adequate solutions often require interaction between a multitude of network sites. As a consequence, solving the use case of CCO is particularly difficult. This letter proposes an efficacious modification of the antenna tilt-based SON algorithm by Berger et al. We propose using a probability distribution function (PDF) of throughput measurements and an estimate of the number of covered and uncovered users of each cell considered for optimization in order to construct an objective function that is better suited to jointly maximize throughput and coverage. Due to the limited amount of data required for computing the algorithm's objective function, the SON solution proposed can be implemented not only following a centralized but also following a distributed architecture. Simulations show that the SON algorithm can exploit this additional information to increase its performance in terms of throughput gains.