A software product line allows to derive individual software products based on a configuration. As the number of possible configurations is an indicator for the general complexity of a software product line, automatic #SAT analyses have been proposed to provide this information. However, the number of configurations does not need to match the number of products. Due to this mismatch, using the number of configurations to reason about the technical complexity (i.e., the number of products) of a software product line can lead to wrong assumptions during implementation and testing. How to compute the exact number of products, however, is unknown. In this paper, we mitigate this problem and present a concept to derive a solution-space feature model which allows to reuse existing #SAT analyses to compute the number of products of a software product line. We evaluate our concept by applying it to a total of 119 subsystems of three industrial software product lines. The results not only show that the concept scales for real world software product lines, but also confirm the mismatch between the number of configurations and the number of products.