I've read the article on presenting sensitivity analysis, which (if I understand correctly) consists of presenting two concepts that are identical, and then changing one feature of a concept while holding all others constant, and running the simulator to observe the resulting impact of that change.
While this makes sense for attributes in which preference is a priori established (such as people preferring a lower than a higher price), I find that some clients have trouble interpreting the results otherwise. I was wondering if it makes more sense to create as many products as there are levels within an attribute, and have each product on a different level, while all other attributes are held to a constant. For instance, if an attribute has 4 levels, I create 4 products and assign a different level to each product for that attribute, apply the same levels across the 4 products for all the other attributes, then observe the share of preference.
Would this make sense, or are there red flags with this method?