p99 for the same reason has been used widely in monitoring systems and benchmarks.

For instance, all commercial A/B testing services (as far as I can tell) compute the 99%-Winsorized stats for their reports. This is partially due to several common cases that can mess up an average computation, especially between two halves: How many times has the developer testing account clicked on “Buy”? Obviously, those should not been the dataset in the first place, but when dealing with corporate clients, the commercial thing to do is to fix the problem and not confuse the client with the details, unless they dig in the documentation.

I've seen published estimates of statistical efficiency for a few test distributions for the trimmed mean, but not the Winsorized mean. Can anyone suggest references on this?