1. A method of behavioral targeting comprising: identifying, via a computing device, a user data set associated with a plurality of users, the user data set comprising past event information from a plurality of events, the past event information being generated based on past on-line activity between each user of the plurality of users and an entity, the user data set comprising categories of activities, wherein each activity of a particular user associated with the past event information is categorized within the user data set, the entity being an online entity; analyzing, via the computing device, the user data set to determine a performance metric based upon the past event information, the determination comprising predicting user behavior responsive a targeting objective associated with the past on-line activity, the targeting objective comprising branding advertising associated with the entity; generating, via the computing device, a model for the targeting objective, the model being based upon the performance metric and the past event information between each user and the entity; storing, via the computing device, the model, the computing device being different from the entity; receiving, at the computing device, an event associated with a first user, the first user being not within the plurality of users, the event comprising activity between the first user and the entity; and generating, via the computing device, an interest score between the first user and the entity, the interest score being based upon the stored model.