The disclosure includes a system and method for generating virtual reality content. For example, the disclosure includes a method for generating virtual reality content that includes a stream of three-dimensional video data and a stream of three-dimensional audio data with a processor-based computing device programmed to perform the generating, providing the virtual reality content to a user, detecting a location of the user's gaze at the virtual reality content, and suggesting an advertisement based on the location of the user's gaze. Another example includes receiving virtual reality content that includes a stream of three-dimensional video data and a stream of three-dimensional audio data to a first user with a processor-based computing device programmed to perform the receiving, generating a social network for the first user, and generating a social graph that includes user interactions with the virtual reality content.

An improved architecture including system and methods for online advertising placement that provide possibly defaulting advertisement tags the opportunity to serve an advertisement ahead of a lower value tag that is guaranteed to fill, resulting in higher CPMs (i.e., Cost Per Mille) for web publishers. The system and methods are configured to deterministically render an advertisement impression from a list of possibly defaulting advertisements in a JavaScript-enabled web browser. The knowledge of the complete outcome of such an “ad chain” at render-time significantly reduces complexity and latency in the supporting ad server. The system and method centers around a novel JavaScript approach to detect when an advertisement has been loaded but not defaulted. Additionally, the system and methods integrate the network and RTB demand channels by looking at all demand sources simultaneously and selecting the buyer from within the user's browser, and address predictive pricing to further enhance the online advertising placement process.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for providing data and analysis for advertising on networked devices. One of the methods includes creating a vector of identifiers representing an ad opportunity. The method includes linking data attributes that describe the ad opportunity to the identifiers. The method includes expressing the data attributes following predefined scheme of hierarchy. The method includes linking a taxonomy describing data attributes. The method includes obtaining outcome measurements of ad events associated with the ad opportunity. The method also includes associating user interaction events with the ad with at least one of the identifiers or data attributes associated with the identifier.

Methods and apparatus to monitor media presentations are disclosed. Disclosed example apparatus include memory, instructions, and at least one processor to execute the instructions to at least receive demographic information from a user, transmit the demographic information to a central facility, cause storage of a consent identifier in a pasteboard of the media device, the consent identifier accessible to a first instrumented application and a second instrumented application executed in a sandbox environment, the consent identifier to indicate to the first instrumented application and the second instrumented application that monitoring is allowed, access the consent identifier from the pasteboard, present media, generate monitoring information if the consent identifier permits collection of monitoring information, not generate monitoring information if the consent identifier does not permit the collection of the monitoring information, and transmit the monitoring information to the central facility.

Disclosed examples determine a duplicated audience size representative of panelists exposed to television media and digital media; determine a panel duplication reach based on the duplicated audience size and a panelist population; determine a did-not-view reach based on a television audience size, a digital audience size, the duplicated audience size, and the panelist population; obtain an overlap multiplier as a ratio of (1) a product of the panel duplication reach and the did-not-view reach and (2) a product of a television panel reach and a digital panel reach; determine a duplication factor for a media item based on a television audience reach, a digital audience reach, and the overlap multiplier; and determine a total audience for the media item based on the television audience reach, the digital audience reach, and the duplication factor.

Systems and methods including one or more processing modules and one or more non-transitory storage modules storing computing instructions configured to run on the one or more processing modules and perform acts of collecting training attribute values for a set of attributes; generating a probability model using the training attribute values, the probability model providing predicted outcomes for at least one attribute in the set of attributes; identifying, using the probability model, a first predicted outcome corresponding to a subsequent combination of attribute values collected by a collection module, wherein the predicted outcomes can comprise the first predicted outcome; coordinating a first display of an ad content version of a subsequent webpage when the first predicted outcome satisfies an objective of the subsequent webpage, wherein the first display can comprise: (a) an ad at a first location on the subsequent webpage and a webpage content in a first format at a second location on the subsequent webpage; or (b) the ad at a third location on the subsequent webpage and the webpage content in a second format at a fourth location on the subsequent webpage; and coordinating a second display of an ad-free version of the subsequent webpage when the first predicted outcome does not satisfy the objective of the subsequent webpage. Other embodiments are disclosed herein.

Systems and methods are described herein for determining user exposures to content, such as content presented by physical objects (e.g., advertisements on billboards). The systems and methods may determine a probability (an “exposure probability”) that a user has viewed or consumed content, information, or other visual media presented by a physical object, such as a billboard, vehicle, sign, or other structure, and provide the determined probability to various attribution systems, such as systems that attribute user engagements (e.g., store visits, app downloads, website visits, product purchases, and so on) to earlier content exposures.

A social networking system receives information describing locations associated with a plurality of its users. Based on information identifying each user and a location associated with each user, the social networking system generates and stores hash values. For example, the social networking system maintains various geo-tiles that each identify geographic areas and generates a hash value based on a user identifier and an identifier of a geo-tile including the location associated with the user. Based on the hash values and locations associated with one or more users, the online system determines a number of unique users associated with locations included in a geographic region. When determining the number of unique users, the online system accounts for a rate at which the online system updates location information associated with various users.

Systems and methods are disclosed for conducting media lift studies for online advertising concurrently with operating an advertising campaign. While operating an advertising campaign for a first advertiser/client focused primarily on a set of intended ads and a specific targeted viewer audience, a non-intended ad is occasionally substituted to run in an ad slot, and is tracked as belonging to the first advertiser/client. The non-intended ad can be for example one of: an ad for a second advertiser/client; an alternate ad for the first advertiser/client; or a blank/unrelated ad. After the campaign, attribution results for the intended ads are adjusted according to those for non-intended ads to provide an indication of net media lift resulting from the intended ads—typically at no additional cost to the first advertiser/client. Analysis results may also be compared between different attribution data providers to determine which provide the more accurate attribution data.

A system to control programmatic advertising traffic that provides to a demand-side platform (DSP) server a desired amount and type of digital advertisement inventory data traffic from at least one real-time-bidding (RTB) advertising exchange. The system includes a network traffic management computing platform that receives the digital advertisement inventory data traffic over at least one network. The system also includes a toggle component of the network traffic management computing platform that restricts delivery of a portion and routes delivery of an unrestricted portion of the digital advertisement inventory data traffic to the DSP server based on pre-selected parameters. The toggle component also routes data representing a bid to the at least one RTB advertising exchange associated with the unrestricted portion of the digital advertisement inventory data traffic delivered to the at least one DSP server.