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.

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.

This application relates to apparatus and methods for training machine learning models, and applying trained machine learning models to generate item ranking values. In some examples, user session data for multiple users is received. Based on the user session data, user engagement data is generated characterizing engagements of corresponding items for a search query. Further, a number of examines is determined for each of the corresponding items. The user engagement data for each item is normalized based on the corresponding number of examines, and ranking data is generated based on the normalized user engagement data. The ranking data characterizes a ranking of at least a subset of the items. Further, a machine learning model is trained based on the ranking data. In some examples, the trained machine learning model is applied to a query to generate a ranking of items, and the ranking data is transmitted to a web server.

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.

Provided herein are methods, apparatus, and computer program products for suppressing content from ranked positioning in electronic correspondence based on rules-based scoring. An example method comprising receiving a set of promotions selected for presentation to the consumer in the electronic correspondence, each promotion respectively associated with a promotion score, determining, using a rules-based filter comprising a set of rules, whether to modify a promotion score, including customer attributes and customer input to a promotion offering system, in an instance in which the promotion score is modified, determining whether to suppress presentation of the associate promotion in the electronic correspondence based at least in part on the modified promotion score, and generating the electronic correspondence to include one or more promotions and one or more ranked positions configured for displaying each of the one or more promotions in the electronic correspondence for presentation on a consumer device associated with the consumer.

Systems and methods relate to display of insights, including a method including: causing a user display to display a graphical user interface (GUI) that enables a user to select a time range and a single digital display as a locale; and causing, based on the user selecting the time range and the single digital display as the locale, the user display to display, on the GUI, a list of a plurality of media content that have been displayed on the single digital display, each of the plurality of media content being ordered according to analysis insight for the single digital display selected and the time range selected. The analysis insight may include at least impression counts that are counts of views by people of the plurality of media content on one or more digital displays associated with the locale.

An online system accesses a model trained based on a topic associated with a set of content items and the content of the set of content items. The online system applies the model to predict a probability that each of multiple content items is associated with the topic based on its content and identifies (a) content item(s) associated with at least a threshold probability. The online system retrieves information describing user engagement with the identified content item(s) and determines a value of a performance metric for the topic based on this information. If the value is at least a threshold value and the online system receives content from an entity describing an item associated with the topic, the online system communicates a recommendation to the entity to create a content item describing the item and to add a tag associated with the item upon determining an opportunity to do so.

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.

Apparatuses, methods, and systems for warming new accounts. One system includes a server electronically networked with a user and a plurality of recipients of an electronic mail campaign of the user, the server operating to obtain an initial contact list, check the initial contact list to determine that the initial contact list satisfies an initial set of engagement rules, generate an active contact list comprising modifying the initial contact list when the initial contact list does not satisfy the initial set of engagement rules, electronically send an electronic message campaign to the active contact list, analyze a success of the electronically sent campaign, and adaptively adjust the active contact list according to active engagement rules based on an evaluated success of the electronically sent campaign.

A method for measuring effectiveness of a media-sharing advertisement includes: obtaining delivery destination ID identified in response to an access to a first address, which is based on a first code that is recorded on a print media and includes the first address to access to a first landing page corresponding to a first business entity of the print media and includes the delivery destination ID of the delivery destination of the print media; obtaining delivery destination ID identified in response to an access to a second address, which is based on a second code that is recorded on the print media and includes the second address to access to a second landing page corresponding to a second business entity that satisfies a media-sharing condition and includes the delivery destination ID, and ID of the second business entity; and providing the first and second business entities with the obtained information.