A key aspect of economic environments is the fact that producers and consumers operate under budget constraints. Consumers’ demand will be inuenced by their preferences for attribute compositions but constrained by the funds they have available to purchase offerings. Conversely, at a given price, the requirement that producers make a prot constrains the costs at which they can produce a product or service. This serves to restrict the feasible attribute compositions they may supply at that price. The prot-maximizing producer faces two separate issues. The rst is to determine the most preferred attribute composition for a product at a given cost (price). The second is to determine the prot-maximizing price (cost). Current approaches to conjoint analysis (CA) and discrete choice experimentation (DCE) design (such as fractional factorial designs) confound these two issues. The mixture/amount approach to experimental design discussed in this chapter provides a means for untangling these issues. We introduced mixture designs in Chapter 2. These designs are widely used in industrial experiments, and their use in CA and DCE is demonstrated in the work of Raghavarao and Wiley (2009). Piepel and Cornell (1985) discuss mixture amount designs in industrial settings.