Amobee, Inc.

Scott Andrew Ferber

Kevin Coates Haley

Aleck Howard Schleider

D Bryan Jones

The present teaching relates to method, system, and medium for profiling accounts. A plurality of identifiers are obtained, wherein each of the plurality of identifiers is associated with one of a device operated by a user and a platform on which the user consumes content in one or more media types. An account corresponding to the user is created, wherein the account represents the user across devices, platforms, and/or media types. A persistent identifier is generated for the account, wherein the persistent identifier links the plurality of identifiers. Consumption data related to the account with the persistent identifier is obtained. The consumption data is gathered from sources associated with the plurality of identifiers across different devices, platforms, or media types, and the account is profiled based on the obtained consumption data.

Method and system for persistent account generation and profiling

The present teaching relates to method, system, and medium for determining audience clusters to be assigned to an advertisement exposure opportunity. A plurality of advertisement exposure opportunities are obtained, wherein each of the plurality of advertisement exposure opportunities is to be used for placing an advertisement. For each of the plurality of advertisement exposure opportunities, a plurality of audience clusters are generated based on at least one criterion associated with the advertisement exposure opportunity. The plurality of audience clusters are ranked based on at least one ranking criterion, and ordered audience clusters are generated based on the ranking. The ordered audience clusters associated with the plurality of advertisement exposure opportunities in response to an event are updated, wherein the ordered audience clusters for each of the plurality of advertisement exposure opportunities are generated prior to receiving a request for placing the advertisement.

Method and system for generating audience clusters

Methods, systems, and programming for recommending targeted television programs based on online behavior is provided. In one example, information related to one or more online activities of a user is received. An identifier associated with the user is determined. Information related to television consumption of the user is assessed based on the identifier. An index is generated based on the online activity information and the television consumption information. One or more recommendations are generated based on the index.

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Bethesda, MD, United States of America

Scott Andrew Ferber