A method for distributing an electronic content item for consumption with advertisements is provided. In one embodiment, a content provider creates a license identifying one or more slots within an electronic content item at which advertisements are to be inserted. The license specifies one or more types of advertisements that are not permitted to be inserted into the slots, and also specifies criteria for dynamically selecting advertisements to insert into the one or more slots. The content provider securely associates the electronic license with the electronic content item and distributes the electronic content item and the electronic license to a third party for consumption or subsequent transfer to an end user.

Disclosed are methods, systems, and non-transitory computer-readable medium for targeting bid and position for a keyword. For instance, the method may include obtaining information about the keyword, the information about the keyword including observations of value with respect to position for the keyword. The method may further include applying a Gaussian Process Model on the observations to obtain a prediction function and associated uncertainties, the prediction function and the associated uncertainties relating positions to expected values; applying a Thompson sampling reinforcement learning model on the expected values and the positions to obtain a target position; and applying a bid model to the target position to obtain bid information for the keyword. The method may also include transmitting a bid message to a search engine, the bid message including the bid information.

One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with a sparse set of field weights associated with feature fields associated with features of the plurality of sets of auction information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. Positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon field weights, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the positive signal probabilities.

An online system determines the score for each additional user based on the measure of similarity between the additional user and a group of seed users. The online system divides the additional users into one or more segments according to their respective scores, and assigns a bid amount for each segment. The online system presents sponsored content to the additional users according to the corresponding bid amounts, and for each of the additional users in each segment that is presented with the sponsored content, the online system identifies a value generated by the additional user due to being presented with the sponsored content. The online system uses the identified values of the additional users for each segment to determine an updated configuration of assigned bid amounts for the segments that is predicted to increase a return on investment and assigns the updated bid amounts for each segment.

A digital advertising system includes at least one processor configured to execute a plurality of functional modules including an analytics module to receive and analyze client attributes associated with a website visitor and a requested website to define an analytics event. The analytics module ingests and enriches data within the analytics event and provides it to a machine learning module that generates prediction models for potential bids. A management platform receives the bidding prediction and generates candidate configs. An optimization module receives the candidate configs and applies weights and additional features to select a config and generate an optimized script for the selected config. A deployment module receives the optimized script and delivers the script to the website visitor.

Embodiments are directed to generating and managing an advertising campaign based on a third-party listing. In particular, an identifier associated with a listing posted over a third-party service from a user of the third-party service is received. Listing data for the listing is retrieved from the third-party service using the identifier associated with the listing. Thereafter, an advertising campaign is automatically generated based at least in part on the retrieved listing data. In one aspect, generation of the advertising campaign includes generating an advertising creative using the retrieved listing data. Subsequently, an advertising opportunity is selected according to the generated advertising campaign. Following the selection, an advertisement based on the advertising creative is provided to a content provider associated with the advertising opportunity.

A method, apparatus, and computer program product are disclosed to improve generation of electronic communications. The method may provide a plurality of content slots each configured to receive content, the content comprising at least one of promotion content or non-promotion content. The method may also include maintaining a database comprising a plurality of promotion content generators and non-promotion content generators, and determining, using a processor, one of the plurality of promotion content generators or non-promotion content generators for respectively supplying corresponding promotion content or non-promotion content to each of the plurality of content slots. The determining the one of the plurality of promotion content generators or non-promotion content generators may include determining selection parameters, and scoring the plurality of promotion content generators and non-promotion content generators based at least in part on the selection parameters.

A system may include an aggregate model comprising a plurality of modules, a monitoring dashboard in communication with the aggregate model, and a search-marketing campaign manager in communication with the aggregate model, the monitoring dashboard, and a search engine entity. Additionally, the system may include a bidding interface in communication with the aggregate model and a search engine entity and/or a monitoring dashboard configured to generate model adjustment data. The search-marketing campaign manager may be configured to determine trend data, measured marketing indicators, or both, from one or more of marketing data or historical data.

A system and method for incorporating branded creative contents into messaging services. In one embodiment, a method comprises receiving profile data associated with a user of a user device; receiving a plurality of bids, the plurality of bids corresponding to bids generated by a plurality of advertisers for providing branded creative contents to user devices; identifying a subset of the plurality of bids based on the profile data associated with the user; generating a set of conditions for identifying a winning bid within the subset of the plurality of bids; and transmitting, to the user device or an intermediate device, data descriptive of the subset of the plurality of bids, identifiers of creative contents associated each bid of the subset, and the set of conditions.

A system and method for dynamically adjusting an online marketing campaign, in various embodiments, is configured to increase and/or decrease one or more keyword bids that make up part of an online mark'seting campaign for a particular product from a particular retailer based on whether: (1) the particular product is or is not competitively priced relative to one or more competing retailers; and/or (2) an advertisement for the particular product from the particular retailer on a search engine results page or in an online marketplace is in a relatively desirable position.