Even in that simple of an example, we lack the data we need for that number to matter much, and the fact that it's a concrete statistic can easily lead to prioritizing one feature or another using that imperfect data as a cudgel.
In particular, you'd probably want to know how a feature would impact future sales, survivorship curves for current customers, and survivorship curves for whichever kind of customer would sign on with the new feature (treating a single feature in isolation for simplicity). This is especially important when comparing multiple features to put on the roadmap because it's easy for one idea to be simple to imagine and better than the status quo (hence asked for by many customers) but be nowhere near an optimal solution to whichever problem is being solved.
Having that kind of customer insight is better than not having it, as long as such data is used appropriately -- without additional data it can't do much more that guide or refine gut feelings and insights, and attempting to do otherwise is a recipe for an inferior product.