Various proxy metrics for test quality have been defined in order to guide developers when writing tests. Code coverage is particularly well established in practice, even though the question of how coverage relates to test quality is a matter of ongoing debate. Mutation testing offers a promising alternative: Artificial defects can identify holes in a test suite, and thus provide concrete suggestions for additional tests. Despite the obvious advantages of mutation testing, it is not yet well established in practice. Until recently, mutation testing tools and techniques simply did not scale to complex systems. Although they now do scale, a remaining obstacle is lack of evidence that writing tests for mutants actually improves test quality. In this paper, we fill this gap. We analyze a large dataset of 15 million mutants and investigate how the mutants influenced developers over time, and how the mutants relate to real faults. Our analyses suggest that developers using mutation testing write more tests, and actively improve their test suites with high quality tests such that fewer mutants remain. By analyzing a dataset of historic fixes of real faults we further provide evidence that mutants are indeed coupled with real faults. In other words, had mutation testing been used for the changes introducing the faults, it would have reported a live mutant that could have prevented the bug.