Optimizing primary content selection for insertion of supplemental content based on predictive analytics

Abstract

Supplemental content associated with an advertising campaign may be evaluated by an object recognition service to classify the content using ad classification key words. The classification of the supplemental content may be used, along with publisher content descriptions associated with primary content, to identify targeting criteria for the supplemental content that may have a success metric above a threshold. Past campaigns deployed against primary content having similar publisher content descriptions may be evaluated to determine how certain key words or targeting criteria perform. If historical results are positive, the targeting criteria may be added to existing campaigns or approved for existing campaigns. Predicted success of the targeting criteria may be used to provide recommendations to users who control which primary content the supplemental content should be included.