But in practical terms, the problem with this approach -- if I'm understanding it correctly -- is that it has no way to detect and reject outliers, and therefore the data can't be validated in any way. It only makes sense if all your clients are 100% trustworthy.
Let's say you want to know whether to keep supporting ARMv5, and your data says 10% of users are using it. There's no way to tell whether that's accurate, or if you have 0.01% of die-hard users who modified their telemetry code to report 1000x as frequently as they're supposed to. Even if you suspect this is happening (and you might not), there's no way to identify the culprit and filter out their data without tracking personal identifiers such as IP addresses.
So even if most of the time the telemetry data is valid, over time it will trend toward uselessness, because it can be endlessly second-guessed unless it confirms a decision you wanted to make anyway.