Patent ID: 8438170
Filing Date: 2013-05-07
Classification: G06F,G06Q

Abstract:
1. A computer-implemented method for utilizing at least a computer processor for determining user behavior from online activity, said method comprising: processing a user data set, comprising past event information from a plurality of events, compiled from past on-line activity between users of said user data set and an entity; analyzing said user data set to ascertain a level of performance of said past event information to predict said user behavior for each of a plurality of targeting objectives comprising at least two of direct response advertising, purchase intention, branding advertising, personalization, and intra company business unit marketing; generating a plurality of models, one for each of said targeting objectives, wherein each model comprises a plurality of weights for determining a user interest score for a corresponding targeting objective; generating said weights for said models by ascribing a prediction value to said past event information in accordance with said level of performance of said past event information for said corresponding targeting objective; storing said models for said targeting objectives; receiving, at said entity, additional event information from at least one event from a user; and generating said user interest score for said user for one of said targeting objectives using a corresponding model for said targeting objective by applying at least one weight from said corresponding model based on said additional event information to predict said user's propensity for success in said targeting objective.