Predicting outcomes via marketing asset analytics

Abstract

Systems and methods for predicting an outcome for a marketing asset. The systems and methods comprise first determining by a computing device, for a marketing asset received by the computing device, at least one asset type of the marketing asset. The marketing asset is parsed, by the computing device, into a plurality of segmented components, based on the determined at least one asset type. For at least one of the plurality of segmented components, at least one discrete marketing message conveyed by the marketing asset is determined, by applying at least one of a predictive model or rules to the at least one segmented component, where the at least one predictive model or rules are stored in a memory associated with the computing device. The method further includes determining, for each of the at least one discrete marketing message, at least one associated score. The method yet further includes inputting the determined at least one associated score to a trained predictive model to obtain a predicted marketing outcome, where the trained predictive model was trained using training scores associated with a multitude of training discrete marketing messages as independent variables and corresponding training marketing outcome data as dependent variables.