Prior research shows that the GenderMag method can help identify and address usability barriers that are more likely to affect software users who are women than those who are men. However, the evidence for the effectiveness of GenderMag is limited to small lab studies. In this case study, by combining self-reported gender data from tens of thousands of users with software logs data gathered over a five-year period, we quantitatively show that GenderMag helped a team at CompanyName (a) correctly identify discoverability as a usability barrier more likely to affect women than men, and (b) reduce the discoverability barrier by 2.4x and achieving gender parity. Thus, this paper contributes the first large-scale evidence of the effectiveness of GenderMag in the field.