Apple Inc.

Prasenjit Mukherjee

Dan Grigorovici

Eswar Priyadarshan

Omar T Abdala

Ravikiran Chittari

Kenley Sun

Jayasurya S Vadrevu

Eswar Priyadershan

A present technology intelligently retargets invitational content to a user by maintaining a user profile that includes data descriptive of the user's interaction with invitational content previously presented to the user and making decisions regarding retargeting based on an analysis of the user profile. The information in the user profile is not limited to whether or not the user completed a conversion action associated with invitational content presented. Rather, the profile is expanded to include such information as where on the conversion continuum the user abandoned the process and details of how the invitational content was presented to the user, e.g. colors used, situation, and message. When presented with a request for invitational content, the system uses the profile information to influence which content is selected and how it is presented to the user. This enables the system to re-present invitational content in a form and/or situation where the user is more likely to complete the conversion action.

Presenting content packages based on audience retargeting

Systems and methods for planning and booking advertising campaigns are provided. In operation, a booking engine generates a collection of proposed campaigns in response to a campaign request, where the each of the proposed campaigns corresponds to a scenario of atom availability. Such scenarios can account for possible or anticipated changes in the number and cost of atoms or any other changes of interest to the advertiser. The availability for the atoms in the campaign request can be projected using the past history and the known future unavailability of the atoms and is further modified to account for the variation in atom availability associated with each scenario. Thereafter, the booking engine can present the results for each scenario to the advertiser and allow him to select a campaign.

Forecasting and booking of inventory atoms in content delivery systems

Systems and methods are provided for selecting contexts for new invitational content and invitational content for new contexts. In particular, a performance history of delivered invitational content in known contexts is combined with similarity measures for the delivered invitational content, with respect to a new invitational content, to generate a list of potential contexts for the new invitational content. Similarly, a performance history of in known contexts with delivered invitational content can combined with similarity measures for known contexts, with respect to a new context, to generate a list of potential content for the new context. Further, a combination of these methods can be used to pair new invitational content with new contexts.

Predicting content and context performance based on performance history of users

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Bengaluru, India

Prasenjit Mukherjee