Systems and methods for forecasting campaign parameters using machine learning architectures and techniques

Abstract

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform acts of: providing access to a forecasting system that includes a machine learning model configured to forecast one or more campaign predictions associated with an electronic advertising campaign; extracting historical campaign data from one or more databases using a distributed processing system; generating training features for training the machine learning model; executing a training procedure that is configured to train the machine learning model, at least in part, using the training features; and executing, after completion of the training procedure, the machine learning model to forecast a predicted ROAS value or a predicted budget value. Other embodiments are disclosed herein.