System for ranking segmented video files, comprising a server including a computer, said server including one or more segmented video files stored in a video database, each said segmented video file containing video information for visually reproducing at least one video object, where a video object is a visual component of the video file; an object inventory database operating on said server and containing information describing, a location of said at least one video object within each of at least one image frame within at least one of the segmented video files, the server executing software indexing each segmented video file for, the occurrence of at least one video object; the server executing software determining a duration of time that the at least one video object appears in each video file.

The current invention relates to a computer-generated method for optimizing placement of advertising content across multiple different devices. The system permits targeting of advertising content to consumers on TV and mobile devices that can be operated from within a multi-channel video programming distributor's environment. The system is able to use hard and soft constraints to come up with a number of possible targets for an advertising campaign and can then provide tools for optimizing those targets. The system can allocate advertising campaigns and plans to various inventory types based on the probability of accurate consumer matching. Consumer matching can be achieved by generation of look-alike models in a consumer's device graph to predict future consumption behavior. The system includes an interface through which a user can adjust various constraints and optimize a distributor's revenue yield from advertising.

A system and process allowing for online participation in multiple simultaneous live auctions comprising an auction management system providing an advantageous user display enabling concurrent auction participation.

The disclosure herein relates to systems, methods, and devices for decreasing latency and/or preventing data leakage that may arise from advertisement insertion. In some embodiments, the systems, methods, and devices described herein provide for asynchronous advertisement selection and/or insertion separate from user-requested content retrieval and/or delivery, wherein the advertisement selection can be performed in parallel with and/or at a separate location from the user-requested content retrieval and/or delivery, thereby decreasing latency in rendering user-requested content. Further, in certain embodiments, the systems, methods, and devices described herein can prevent data leakage by preventing and/or circumventing the need to use cookie syncing among different DSPs, SSPs, or the like. Moreover, in some embodiments, the systems, methods, and devices described herein are configured to deliver advertisements as a native content, thereby further decreasing latency and/or preventing data leakage.

Systems and methods including one or more processors and one or more non-transitory storage devices storing computing instructions configured to run on the one or more processors and perform determining a respective interaction metric between at least two respective keywords of a plurality of keywords; constructing, using each respective interaction metric, as determined, a graph comprising a plurality of nodes connected by at least one edge; identifying one or more clusters of nodes using the graph; optimizing each cluster of nodes of the one or more clusters of nodes; and facilitating altering a graphical user interface (GUI) of an electronic device based upon a cluster of nodes of the one or more clusters of nodes, as identified and optimized. Other embodiments are disclosed herein.

Systems and methods are disclosed herein for distributing online ads with electronic content according to online ad request targeting parameters. One embodiment of this technique involves placing online test ads across multiple online ad request dimensions and tracking a performance metric for the online test ads. The performance of the online ad request dimensions is estimated based on the tracking of the performance metric for the online test ads and online ad request targeting parameters are established for spending a budget of a campaign to place online ads in response to online ad requests having particular online ad request dimensions. Online ads are then distributed based on using the online ad request targeting parameters to select online ad requests.

A method, system, and computer program product, include tracking eye-reaction of a user each of a plurality of advertisements of an advertisement group on a web page displayed on a display device, calculating an interest of the user for each advertisement of the advertisement group over time based on the tracked eye-reaction, and to assign each advertisement a user engagement value based on the interest, conducting an auction to determine winning advertisements based on advertiser parameters received from a database and the user engagement value of each of the plurality of advertisements, determining at least one time at which to cause the conducting to conduct the auction, and dynamically repopulating the advertisement group with the winning advertisements.

Systems and methods for building a device graph for cooperative device identification are disclosed. Various information is received at a computing system over a communications network, include information defining a relationship between (i) a unique identifier associated with a first device of a user and (ii) a unique identifier associated with the user, and information defining a relationship between (i) a unique identifier associated with a second device of the user and (ii) the unique identifier associated with the user. The unique identifiers associated with the devices are each mapped to the platform-wide identifier based at least in part on the unique user identifier. A device graph comprising a plurality of device nodes is constructed, with related device nodes connected by one or more edges. Nodes representing the devices are linked based on a relationship identified between them using the platform-wide identifier.

A digital ad-buying platform uses counterfactual-based incrementality measurement by implementing randomization and/or a correction for auction win bias to avoid the need to identify counterfactual winner types in the control group. This approach can estimate impact at the individual consumer level. Confidence levels can be determined using Gibbs sampling in the context of causal analysis in the presence of non-compliance.

In general, embodiments of the invention relate to servicing fill request using ad networks and demand-side partners.