The traditional innovation process is staggered, comprising an initial product optimisation followed by messaging evaluation. Typically, product offers may be screened as they are moved from one stage to the other. This not only means more time to go-to-market but also risks some relatively less optimal products being rejected when they may actually succeed in the next phase of evaluation by responding better to messaging. There is a need for a singl- stage optimisation process. However, one of the best optimisation tools, conjoint, is limited in its ability to optimise messaging, i.e. preference share impact of response to brand communication. We demonstrate how messaging impact can be modelled into a conjoint model as covariates allowing for a single-step optimisation process.