The present disclosure proposes a device for executing an advertisement service and a method for operating the same, for providing a targeted advertisement according to an advertisement execution condition determined for a terminal on the basis of scanning data obtained by scanning wireless local area networks (WLANs) (for example, Wi-Fi) in an addressable TV advertisement environment. The present disclosure also proposes a device for executing an advertisement service for providing a targeted advertisement for a combination of member terminals and visitor terminals located within a home in an addressable TV advertisement environment.

Apparatuses, methods, and storage media for providing recommendations for an advertisement campaign are described. In one instance, an apparatus for providing recommendations for an advertisement campaign may include a campaign outcome index provision engine communicatively coupled to one or more processors, to generate a campaign outcome index (COI) associated with the advertisement campaign, based at least in part on a ratio between an actual outcome key performance indicator (KPI) associated with the advertisement campaign; and a baseline outcome KPI that reflects an expected average performance of the advertisement campaign; and a recommendation engine, communicatively coupled to the one or more processors, to provide recommendations to adjust a use of advertisements in the advertisement campaign, during the advertisement campaign, based at least in part on the generated COI. Other embodiments may be described and claimed.

Apparatuses, methods, and storage media for providing recommendations for an advertisement campaign are described. In one instance, an apparatus for providing recommendations for an advertisement campaign may include a campaign outcome index provision engine communicatively coupled to one or more processors, to generate a campaign outcome index (COI) associated with the advertisement campaign, based at least in part on a ratio between an actual outcome key performance indicator (KPI) associated with the advertisement campaign; and a baseline outcome KPI that reflects an expected average performance of the advertisement campaign; and a recommendation engine, communicatively coupled to the one or more processors, to provide recommendations to adjust a use of advertisements in the advertisement campaign, during the advertisement campaign, based at least in part on the generated COI. Other embodiments may be described and claimed.

[Problem to be solved] An object of the present invention is to provide a method for improving an advertising effect, particularly in a television commercial. [Solution] According to an embodiment of the present invention, the disclosed method is a method for providing an advertisement for a television program, which determines an advertisement-related product related to a product to be advertised, refers supply prediction information of the advertisement-related product, and determines the time for placing the TV program advertisement based on the supply prediction information.

Methods, systems, and computer-readable media for determining the efficacy of an advertisement are described herein. A computing device may receive an advertisement from an advertisement server. The computing device may determine advertisement information associated with the presentation of the advertisement. The advertisement information may be sent to the advertisement server.

Systems and methods for effectively and efficiently receiving, analyzing, and using subscriber content choice information are described. One embodiment of the present invention includes a subscriber-action database, such as a clickstream database, a media-content database, and a merge processor electronically connected to the two databases for merging data in the subscriber-action database with data in the media-content database to create a subscriber content-choice database. The media-content database may include programming and/or advertising data. The media-content database may also include category and context information to provide the capability to comprehensively analyze data in the subscriber content-choice database.

Systems and methods for effectively and efficiently receiving, analyzing, and using subscriber content choice information are described. One embodiment of the present invention includes a subscriber-action database, such as a clickstream database, a media-content database, and a merge processor electronically connected to the two databases for merging data in the subscriber-action database with data in the media-content database to create a subscriber content-choice database. The media-content database may include programming and/or advertising data. The media-content database may also include category and context information to provide the capability to comprehensively analyze data in the subscriber content-choice database.

Systems and methods are provided for determining a media cost equivalent to attribute to the appearance of a sponsor's logo or other object in a media item, such as an image or video. This determination may be based on factors such as clarity, prominence, visibility, size, or placement of a sponsor logo or other object related to the sponsor within at least one media item. One or more machine learning models may be utilized to automatically identify objects within, and otherwise analyze, image data in order to determine sponsor value.

A scientific system and methods are disclosed for optimizing television (e.g., “CTV” and “OTT”) advertising and related expenditure to maximize efficiency and return on investment (“ROI’) for advertisers. The scientific system comprises an initial-feedback engine that develops and refines creatives or outcomes by creating and using an artificial intelligence (“AI”) engine that creates an initial feedback loop from social media platforms and subsequently uses an intelligent advertisement-selection engine that takes the highest performing advertising on the social media platforms and directs or imports them for connected television or over-the-top advertising. The system includes a performance engine that optimizes performance of the connected television and over-the-top advertising and then moves the winning combination of a creative or outcome resulting from the application inventory, the audience segment, the part of day, the frequency or the like to linear television purchase actions.

A scientific system and methods are disclosed for optimizing television (e.g., “CTV” and “OTT”) advertising and related expenditure to maximize efficiency and return on investment (“ROI’) for advertisers. The scientific system comprises an initial-feedback engine that develops and refines creatives or outcomes by creating and using an artificial intelligence (“AI”) engine that creates an initial feedback loop from social media platforms and subsequently uses an intelligent advertisement-selection engine that takes the highest performing advertising on the social media platforms and directs or imports them for connected television or over-the-top advertising. The system includes a performance engine that optimizes performance of the connected television and over-the-top advertising and then moves the winning combination of a creative or outcome resulting from the application inventory, the audience segment, the part of day, the frequency or the like to linear television purchase actions.