In talking about Powerset and natural language search, I am frequently asked "When is Natural Language search useful?". The idea here is that maybe there are some specific situations where you really want natural language search. My general response is that this is like asking "When is Natural Language useful?" to talk to other people? The very question assumes that there are some particular situations where you want to use natural language, and others where you would prefer to just grunt out a few words.
The answer is obviously: when the interlocutor understands what you are saying. Using complex speech with dogs may satisfy our anthropomorphic urges, but as the famous Far Side cartoon reminds us, it might not achieve all that we hope for.
The question about natural language in search is not whether it would be useful, but whether it would be usefully understood by the search engine. If the search engine is like Ginger, it might be more effective to make that clear to users. There is a steep tradeoff between depth of understanding and robustness in all current computational linguistics methods. In seeking deeper understanding, we may get deeper confusion instead, from a system that is unable to recognize its own confusion. Whether there is a useful point in that tradeoff is an empirical question, not one that can be answered by in-principle arguments.