This is done by using Machine Learning to train a model off of existing customers across over 3,000 demographic and personal attributed for what the ideal buyer "looks like". Once the model is trained, 96% of adults in the United States are then pre-scored on how closely they fit the model. A custom audience of hashed emails is then created from only the highest scored individuals and this file is delivered to media buying platforms such as Facebook to buy media against.
