Performance Optimization System and Method for a Client Advertising Campaign

A method for optimizing performance, comprising:

• receiving, by a performance optimization system (POS) comprising a POS data platform configured to store data usable to determine a POS score, the POS data platform comprising a profile store comprising a plurality of profiles of end users, the POS data platform further comprising a model store configured to store a predictive model usable to determine the POS score that the model builder builds, the performance optimization system further comprising a machine learning platform configured to use machine learning to determine the POS score, the machine learning platform operably connected to the POS data platform, the machine learning platform comprising a model builder configured to build the predictive model and a model scorer operably connected to the model builder, the model scorer configured to receive the predictive model from the model builder, the model scorer further configured to use the predictive model to determine the POS score, the performance optimization system further comprising a prediction server operably connected to the machine learning platform, the prediction server comprising a server configured to receive an advertisement request from a client demand-side platform (DSP), the prediction server further configured to create a prediction request from the advertisement request, the prediction server further configured to score the prediction request to determine a likelihood to influence an end user by exposing the end user to the brand advertisement, the prediction server configured to receive the prediction request from the client DSP, and a prediction request log operably connected to the prediction server, the prediction request log configured to log the scored prediction request, an advertisement request;
• selecting, by the performance optimization system, relevant prediction request data from the advertisement request;
• building, by the performance optimization system, using the model builder, the predictive model;
• determining, by the performance optimization system, using the model scorer, the model scorer using the predictive model, the POS score;
• creating, by the performance optimization system, the prediction request by copying the relevant prediction request data from the advertisement request to the prediction request;
• adding, by the performance optimization system, the POS score to the prediction request, creating a scored prediction request;
• and
• sending, by the performance optimization system, the POS score to the client DSP.