Recently we worked on our first volumetric conjoint. The project isn't completed yet, but it is going well so far. It was a simple conjoint with just the product items as one attribute and price as the other.
During the set-up for that project, we had some conversations about how price wasn't really likely to change and whether we could simplify the model by leaving it out. Of course, that wasn't possible since we can't have just one attribute in a conjoint. But it seemed to me that there must be a way to gather and use data in this manner.
I have looked around and tried to find an existing methodology that does this, but have been surprised that I can't find something. I feel I've probably missed something obvious, but I'm hoping someone could point me in the right direction.
To summarize the research problem, imagine wanting to do a volumetric choice-based exercise when you have a "product" attribute that has maybe 45 levels. Ultimately you want to be able to run a conjoint-style stimulator to predict market share given a particular sub-set of the 45 products actually on the shelf.