Aspects of the subject disclosure may include, for example, obtaining data relating to a user, where the data relating to the user includes user profile data regarding user activities in a first domain, mapping the user profile data to a second domain, resulting in mapped user profile data, receiving, from an immersion engine, data regarding an immersion environment, obtaining data relating to advertisement content, where the data relating to advertisement content includes information identifying an advertisement object, deriving immersive advertising data based on the mapped user profile data, the data regarding the immersion environment, and the data relating to the advertisement content, and outputting the immersive advertising data to the immersion engine, where the immersive advertising data enables the immersion engine to embed the advertisement object in the immersion environment. Other embodiments are disclosed.

In one embodiment, a method includes receiving a message comprising status data from a second computing device, determining that a geographic area is a hotspot based at least on the status data, where mobile users in a hotspot have a high probability of accessing an application on their mobile computing devices, and sending an indication that the geographic area is a hotspot to a third-party computing device, where the indication is used by the third-party computing device to determine a value for delivery of content to computing devices associated with the geographic area.

Methods and systems are described for dynamically managing resources when submitting bids for advertising content opportunities. The system may determine whether a bid request is likely to be accepted or rejected, or whether an impression event associated with an impression from a bid associated with the bid request is delayed by a time duration. The system may determine, based on information associated with a bid request, a plurality of features associated with the bid request. Each feature of the plurality of features may be associated with one or more distributions indicating a percentage likelihood that the that the impression from the bid associated with the bid request is delayed by the time duration, or whether a bid is likely to be rejected or accepted. The selected features may be based on the impact the features have on indicating whether a bid is likely to be accepted or rejected or result in a delayed impression.

Enabling advertisers using a computer network such as the Internet and a match engine to submit their offerings to product, service, benefit seeking entities. In some embodiments, a database having accounts for the providers is made available. Accounts contain contact and billing information for an advertiser; and at least one offering having at least a description, a criteria set comprising one or more criterion factors, and a bid amount. An advertiser influences a position of an offering in the advertiser's account by first selecting offering relevant criteria. The advertiser enters the criteria and the description into a listing; influencing at least in part the position for the listing within a results page through an online bidding process. This results page is generated in response to a seeking entity query of the match engine. Pay for performance demographic, geographic, psychographic criteria/characteristics targeted directly advertising (frictionless advertising) is enabled.

The disclosure provides a method for predicting a user object in a real time bidding and an advertisement server. The method includes: obtaining telecommunication data, and building a user behavior model based on the telecommunication data by using at least one of machine learning algorithms; receiving a bid request comprising an advertisement identifier which does not have at least one of an identifier field of a certain user object and an advertisement-related identifier from an advertising trading platform; and predicting a first candidate identifier of a first user object corresponding to the bid request according to the advertisement identifier through the user behavior model.

A computerized method of content verification comprising using a server for receiving a first data from a host monitoring code embedded in a webpage or an application loaded from a content server and executed by a client device, the host monitoring code is executed by the client device during an execution of the webpage or the application which further embeds nesting element(s) for loading nested content from nested content server(s), the first data is indicative of the execution, receiving a second data indicative of the execution from a guest monitoring code embedded in the nested content, combining the first data and second data for compliance verification of the execution with one or more rules associated with the nested content and initiating action(s) according to the verification. Wherein the first data is not available to the guest monitoring code and the second data is not available to the host monitoring code.

Enabling advertisers using a computer network such as the Internet and a match engine to submit their offerings to product, service, benefit seeking entities. In some embodiments, a database having accounts for the providers is made available. Accounts contain contact and billing information for an advertiser; and at least one offering having at least a description, a criteria set comprising one or more criterion factors, and a bid amount. An advertiser influences a position of an offering in the advertiser's account by first selecting offering relevant criteria. The advertiser enters the criteria and the description into a listing; influencing at least in part the position for the listing within a results page through an online bidding process. This results page is generated in response to a seeking entity query of the match engine. Pay for performance demographic, geographic, psychographic criteria/characteristics targeted directly advertising (frictionless advertising) is enabled.

Systems and methods are provided for presenting information about discrete geographical areas and the use of such information by content providers to facilitate delivery of targeted or geographically relevant content to information playback devices located in one or more particular discrete geographical areas. Data (e.g., contextual, behavioral, predictive, trending, geo-consumer patterns) can be collected and associated with relevant virtual cells within a grid. A portal can be provided to enable content provider to search the cells based on customized campaigns to identify trends, interest, patterns and opportunities. Such information can facilitate informed geo-targeting decisions and consumer understandings for business of all sizes and sectors in order to deliver more relevant content to information playback devices within selected cells according to customized settings configured by the content provider.

Methods and apparatus for determining a unique audience exposed to media while reducing memory resources of a computing device are disclosed herein. An example apparatus includes memory; instructions in the apparatus; and processor circuitry to execute the instruction to, based on impression requests from a plurality of client devices via a network, log a plurality of impressions corresponding to media accessed at the client devices; generate a product by multiplying a count of the impressions by a square of a count of registered users of a database proprietor exposed to the media; generate a quotient by dividing the product by a count of demographic impressions logged by the database proprietor; and determine a unique audience size based on a square root of the quotient.

A method and computing device for optimizing placement of digital signage content based on audience segments associated to digital signage display units. A plurality of audience segments are stored in a memory of a computing device. Characteristics of a digital signage content are received by the computing device. The characteristics of the digital signage content and the plurality of audience segments are processed by a processing unit of the computing device, to identify potential placements for the digital signage content based on the characteristics of the digital signage content and the stored audience segments. The potential placements for the digital signage content are provided for bidding. Bids for the potential placements are received for the digital signage content and processed to identify the optimized placement for the digital signage content based on the characteristics of the digital signage content and bids received