Show distribution of users affected by outlier response times
One option would be look at conditional probability based on percentiles.
First, find percentiles based on all the data. For example, 99th percentile is 1432 milliseconds.
Then, find percent of a specific user request above that threshold. For example U1 has 50% of requests above 99th percentile.
This could be made into a cross-tabs table for easier exploration. The rows would be each user and the columns would be binned response time percentiles.