A handful of Apple patents involving population segmentation have appeared at the U.S. Patent & Trademark Office. They relate to electronic content delivery and, more specifically, to intelligent targeting of invitational content to a user based on user characteristics.

Patent number 20120042253 involves population segmentation. Per the invention, segments used to select content to be targeted to a user are recursively refined based on continuously derived user characteristics. Based on information gathered from new requests for targeted content and/or user interaction with previously delivered content the user is assigned to one or additional candidate segments.

The candidate segments can be used to select content to be delivered to the user based on the user's assignment to the targeted segments. Accordingly, each user is grouped into one or more targeted segments and based on the user's inclusion in those segments, requests for targeted content can be served to the user.

Patent number 20120042262 is for population segmentation based on behavioral patterns. Per the invention, the technology analyzes a user's behavior to assign a user to targeted segments. The segments to which the user is assigned can be a reflection of a user's context with respect to potential targeted content. While a user can be assigned to many different segments, the user is likely to be most interested in content that she is presently interested in. Accordingly, the system can also prioritize or rank or order segments based on the user's present context. Content is then provided to the user on the basis of the segments to which the user belongs and the priority of segments.

Patent number 20120041817 involves prioritizing population segment assignments to optimize campaign goals. The technology prioritizes or ranks segments based on the content provider's or content delivery system's goals or priorities. The content delivery system can monitor its performance in meeting any known goals, and should the content delivery system recognize that its progress towards meeting a goal is not satisfactory, the content delivery system can prioritize some segments over others to meet one or more goals. Since prioritizing a selection of segments can impact other system and content provider goals, the system can also be provided with a performance predictor that can run a series of prediction models to predict the optimum prioritization of segments to result in the best performance of the system.

Patent number 20120041792 is for customizable population segment assembly. The described technology provides a mechanism for allowing custom targeted segments to be defined by parties outside of a content delivery system. Segments include collections of users grouped together based on common characteristics wherein targeted content is provided to a user based on her assignment to a segment.

The present technology allows a content provider, as an example, to define a custom segment, thereby creating a grouping of users suited to receive the content provider's content. In some embodiments, a user interface is provided to the content provider, which includes all available characteristics, and value ranges corresponding to the characteristics to create a definition of a custom segment.

Patent number 20120041969 involves deriving user characteristics. The technology derives unknown user characteristics from known user characteristics. Unknown characteristics can be inferred from products purchased by a user; by comparing two similar users and inputing characteristics known about one user to another user with unknown characteristics; by inferring characteristics using classifying algorithms to infer additional user characteristics from a collection of other known data about a user. The inferred characteristics can further be associated with a confidence score which is an indication of the likelihood that the inferred value is the correct value for a user.

The inventors on all the patents are Eswar Priyardarshan, Kenley Sun, Dan Marius Grigorovici, Jayasurya Vadrevu, Irfan Mohammed and Omar Abdala.