The present disclosure describes techniques of implementing a collaborative advertising mechanism. The techniques comprise receiving a plurality of pieces of content associated with a mission event from a first plurality of client computing devices associated with a first plurality of users, evaluating the plurality of pieces of content based on one or more predetermined rules of the mission event and information indicative of viewer reactions to the plurality of pieces of content, determining at least one subset of the plurality of pieces of content based on a plurality of evaluation results corresponding to the plurality of pieces of content and user input from a client computing device associated with one of a second plurality of users, and distributing the at least one subset of the plurality of pieces of content.

A method and system provide the ability to deliver media content. Input data is ingested and includes raw data for household locations and marketing data. The input data further consists of physical out-of-home activity data from advertisement exposure and business points of interest visitation, and digital internet based online activity data. The ingestion is performed through a pre-setup process that identifies a data delivery format, a data schema, and a linking key used in a Graph within a database. The input data is processed by determining when new data is ready for ingestion, identifying a file source, extracting the input data from the file source, and importing and storing the extracted input data into the Graph using the key. The input data is linked in the Graph. Measurements and analytics are generated and provide a measurement of exposure to and effectiveness of delivered media content.

The subject technology provides a targeted content curation and placement optimization system comprising a processor connected to a publication network, the publication network navigated by an online consumer seeking actionable content. An online demand side portal is accessible, via the publication network, to a content provider. An online supply side portal is accessible, via the network, to a publisher of content on the publication network. An integrated bidding exchange is communicatively coupled to the demand side portal and the supply side portal and presents user interfaces enabling receipt of bids from the content provider for placement of content by the publisher at a specified location or domain on the publication network. A geographic insights generator may generate geo-specific intender attributes that may be used to curate the targeted content and optimize one or more bidding parameters of the content provider.

A device and method, as disclosed herein, are operable to receive reference data during an in-process period that occurs while an advertising campaign is implemented based on purchase data. The reference data includes first reference data arranged in accordance with a first data organization. The reference data also includes second reference data arranged in accordance with a second data organization that differs from the first data organization. The purchase data includes an actual rate related to one or more ad placements. During the in-process period, with respect to the at least one ad placements, the device and method are operable to determine a plurality of metrics related to the one or more ad placement. The metrics depend at least partially on the reference data. Also, during the in-process period, the device and method are operable to determine a target rate related to the one or more ad placements. The target rate depends at least partially on a plurality of the metrics. The device and method are operable to cause an output device to indicate information based on a difference between the target rate and the actual rate related to the one or more ad placements.

The present disclosure relates to improving recommendations for small shops on an ecommerce platform while maintaining accuracy for larger shops. The improvement is achieved by retraining a machine-learning recommendation model to reduce sample selection bias using a meta-learning process. The retraining process comprises identifying a sample subset of shops on the ecommerce platform, and then creating shop-specific versions of the recommendation model for each of the shops in the subset. A global parameter adjustment is calculated for the global model based on minimizing losses associated with the shop-specific models and increasing the probability of items being recommended from small shops. The latter is achieved by introducing regularizer terms for small shops during the meta-learning process. The regularizer terms serve to increase the probability that an item from a small shop will be recommended, thereby countering the sample selection bias faced by small-shop items.

A service receives a persuasion-based input comprising a text and one or more marketing objectives to persuade a desired response. The service evaluates persuasion values of text segments of the text and persuasion transition values consecutively between respective persuasion values of the persuasion values across the text segments. The service generates a desired curve of persuasion factors across the text segments according to the one or more marketing objectives. The service recommends one or more replacement words to replace one or more selected words in text to move a deviation between the persuasion values and transition values in comparison to the desired curve of persuasion factors.

Systems and methods are disclosed for determining an estimate of available user impressions on a network, comprising receiving a request for an estimate of available user impressions for viewing one or more media elements on a network, the request comprising one or more viewer demographic group limitations. A request may be received to include deterministic users and probabilistic users in the estimate of available user impressions. A number of deterministic users may be determined based on query results from a deterministic user data set. A number of probabilistic users may be determined based on query results from a probabilistic user data set, and the estimate of available user impressions may be determined based on the number of deterministic users and the number of probabilistic users.

A display system may include a display, a first server transmitting first content to the display device, a second server receiving the first content from the first server, and a camera transmitting second content obtained by capturing images on the display, to the second server. The second server may be configured to determine whether a rate at which the first content coincides with the second content is greater than or equal to a specified value, by comparing the first content with the second content. The second server measures a first time period during which a region of the captured images corresponding to the first content coincides with the second content at a rate which is greater than or equal to the specified value. Advertising costs are calculated based on the measured first time period.

A system and method for providing and synthesizing data for publishers operating in the connected television ecosystem. Data from third party reporting platforms may be combined to present a unified view. Audience engagement may be measured, observed, and combined in a novel manner, providing unique insights to users.

Members of an audience of a visually dynamic event are clustered using a plurality of sources. A current point of interest (POI) of the visually dynamic event and a future POI of the visually dynamic event are identified across the member clusters. An effectiveness score for given content and a given member cluster is computed for the current point of interest and an effectiveness score for a given content and a given member cluster is computed for the future POI by tracking a position, a speed, and a direction of movement of the current POI. A location of a background area is determined and ranked for each member cluster based on the current point of interest. Electronic displays that correspond to the ranked background areas are identified and ranked. Content is distributed across the electronic displays for each current time period based on the ranked display areas.