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Secure multi-party computation (MPC) allows multiple parties to jointly compute the output of a function while preserving the privacy of any individual party's inputs to that function. As MPC protocols transition from research prototypes to real-world applications, the usability of MPC-enabled applications is increasingly critical to their successful deployment and wide adoption. Our Web-MPC platform, designed with a focus on usability, has been deployed for privacy-preserving data aggregation initiatives with the City of Boston and the Greater Boston Chamber of Commerce. After building and deploying an initial version of this platform, we conducted a heuristic evaluation to identify additional usability improvements and implemented corresponding application enhancements. However, it is difficult to gauge the effectiveness of these changes within the context of real-world deployments using traditional web analytics tools without compromising the security guarantees of the platform. This work consists of two contributions that address this challenge: (1) the Web-MPC platform has been extended with the capability to collect web analytics using existing MPC protocols, and (2) this capability has been leveraged to conduct a usability study comparing the two version of Web-MPC (before and after the heuristic evaluation and associated improvements). While many efforts have focused on ways to enhancemore »the usability of privacy-preserving technologies, this study can serve as a model for using a privacy-preserving data-driven approach in evaluating or enhancing the usability of privacy-preserving websites and applications deployed in real-world scenarios. The data collected in this study yields insights about the interplay between usability and security that can help inform future implementations of applications that employ MPC.« less