It’s handy as we talk about code review to use some benchmarks that anchor our expectations for review performance in data. The best that I know of are in a 2018 paper from Google: “Modern Code Review: A Case Study at Google”. I find these helpful when breaking down qualitative feedback about reviews as if you can get the data, you can start to get a feel for where improvements in your review process can come from. The blog post uses this paper to set out benchmarks for review request rate, completion rate, speed, size, comment rate, number of reviewers, review comments vs tenure and review rate vs tenure.