Usually the company is quite aware the feature is half finished, but the data shows that hardly anyone uses it, and hardly anyone is asking for it to be improved. So that time would be better spent improving things that there is lots of usage on.
There are multiple ways to interpret the same data. Your interpretation is a valid one. There are other valid ones all from the same data.
If your company sees the simple lack of feedback as a valid signal, then a feature with lots of usage but no feedback means you should not improve it but simply leave it be. It's used, so it seems popular and nobody complained about it, so it must be good enough. Build something else.
Of course your company may also view a simple lack of feedback as not enough signal. If a new feature that is half finished sees hardly any usage this can be taken as a signal that the feature needs to be improved. It's not useful enough in its half finished state to attract usage. Or your users may simply not be able to find the feature because in its half finished state it's too hidden and thus you have neither lots of usage nor feedback on it.
