1. A method for mixing models to optimize media placement, the method comprising: receiving a user input of a plurality of combinations of decision variables, wherein each of the plurality of combinations is associated with a potential media placement slot; identifying, for each of the plurality of combinations of decision variables, a plurality of natural language identifiers; determining, for each of the plurality of combinations of decision variables, a first plurality of standardized identifiers corresponding to the plurality of natural language identifiers; replacing, for each of the plurality of combinations of decision variables, the plurality of natural language identifiers with the first plurality of standardized identifiers; retrieving a second plurality of the first plurality of standardized identifiers for a first subset of the plurality of combinations of decision variables; applying the retrieved second plurality of the first plurality of standardized identifiers for the first subset to a first linear model that represents a first relationship between the plurality of combinations and associated reach metrics to generate a first reach metric associated with the first subset; retrieving a third plurality of the first plurality of standardized identifiers for a second subset of the plurality of combinations of decision variables; applying the retrieved third plurality of the first plurality of standardized identifiers for the second subset to a second non-linear model that represents a second relationship between the plurality of combinations and associated reach metrics to generate a second reach metric associated with the second subset; comparing the first reach metric and the second reach metric; determining, based on the comparison, that the first reach metric is greater than the second reach metric; and storing, in a media placement database, an identifier of a media asset in a media placement slot associated with the plurality of combinations of decision variables in the first subset.