1. A computer-implemented method for automatically processing marketing and sales information, the method comprising: selecting a response curve from among multiple response curves associated with an optimized marketing model, wherein the multiple response curves each identify a historical sales performance outcome for a product relative to a single, respective marketing input driver, and wherein the optimized marketing model is optimized based on iteratively generating multiple candidate models, and evaluating the candidate models using one or more fitness functions; obtaining survey questions for the respective marketing input driver associated with the selected response curve, the survey questions soliciting responses that, when combined, quantify, in terms of percentage contributions, an extent to which changes to past conditions of the marketing input driver will affect an overall impact of the marketing input driver on the selected response curve at a future time, wherein the responses are quantified numerically and are combined by selecting an average or median value; obtaining the responses to the survey questions from multiple analysts; combining the responses to the survey questions from the multiple analysts; determining a scaling factor for the selected response curve based on the combined responses; generating, by one or more processors, an adapted optimized model based on applying, using one or more processors, the scaling factor to the selected response curve; determining an allocation of marketing resources using the adapted optimized model; and presenting information that identifies the allocation of marketing resources.