A system receives a marketing campaign from an advertiser. The marketing campaign identifies tasks to be performed by users on social networks. The system provides a cellular message to each of the plurality of cellular devices. The system retrieves a plurality of activities performed by each of the users of the plurality of cellular devices at each of the one or more social networks. The system identifies, for a user of the users, that the user performed activities responsive to receiving the cellular message identifying the advertiser. The system determines that the activities match the tasks included in the marketing campaign. The system then provides, to the cellular device of the user via at least one of the one or more social networks, a notification identifying the advertiser in response to determining that the one or more activities match the one or more tasks included in the marketing campaign.

A content scheduling method is provided. The content scheduling method, which is performed by a content scheduling apparatus, comprises acquiring a total play count of target content, determining a plurality of weight values of the target content with respect to a plurality of time slots, each weight value of the plurality of weight values indicating a first preference for the target content with respect to each time slot of the plurality of time slots, generating a linear programming model using the acquired total play count and the plurality of weight values and determining, via a processor, a play count of the target content in the each time slot of the plurality of time slots based on the linear programming model.

Methods and systems are disclosed to monitor a media device via a universal serial bus (USB) port. An example method includes obtaining a voltage output by a UBS port of the media device and determining if the voltage exceeds a threshold. If the voltage exceeds the threshold, the example method includes determining the media device is in an on state. If the voltage does not exceed the threshold, the example method includes determining the media device is in an off state.

Systems and methods for targeted advertising to specific consumers are disclosed. A system may include a memory storing instructions and at least one processor configured to execute the instruction to: receive, over a network, client-provided data from a client device; identify at least one consumer by comparing the client-provided data against consumer data recorded in an electronic consumer database; obtain at least one unique consumer identifier for the identified at least one consumer, the at least one unique consumer identifier not including personal identifiable information; generate a target audience pool based on the at least one unique consumer identifier; and deliver, over a network, the target audience pool to the client device to facilitate targeted advertising to specific consumers.

Provided is a content scheduling method performed by a content scheduling apparatus for a plurality of content reproducing apparatuses located at different geographical locations. The method comprises obtaining a total play count of target content, determining a plurality of weight values of the target content, each weight value of the plurality of weight values indicating a preference for the target content with respect to each content reproduction apparatus of the plurality of content reproduction apparatuses, wherein the plurality of weight values are different for at least some of the plurality of content reproduction apparatuses, generating a linear programming model based on the total play count and the plurality of weight values and determining, via a processor, a play count of the target content in each time slot of a plurality of time slots for the each content reproduction apparatus based on the linear programming model.

An embodiment may involve receiving, from one or more server devices, representations of past amounts spent on paid search engine listings for a web site and representations of paid search conversions involving the web site that are attributable to the paid search engine listings. The embodiment may also involve receiving representations of past amounts spent on the display promotions for the web site and representations of display conversions involving the web site. The embodiment may also involve receiving a request for a graphical representation of the cross-channel performance of the web site with respect to conversions. In response to receiving the request for the graphical representation of the cross-channel performance of the web site, the computing system may transmit the graphical representation of the cross-channel performance of the web site.

Disclosed is an online system providing a fair measurement platform for people-based measurement of performance of an online campaign across different third-party systems that eliminates bias for certain third-party systems. The online system determines the measurable portion of the online campaign, where this is a portion of the campaign for which the online system knows the identities of the users and the online system knows that the impressions were viewable. The online system extrapolates with a model out from the measurable portion of the campaign to provide a broader measurement for the campaign including impressions for which identify coverage is incomplete and for which viewability is not available to provide a full, unbiased measurement for the online campaign across various third-party systems, regardless of whether they account for viewability, have identity coverage, or detect fraud.

A system for providing an advertisement in an interactive environment is provided. The system comprises a database for identifying and storing datasets representing advertisements, quantitative metrics, and a virtual game environment. Representations of the datasets are rendered on a user interface of a communication device by a processor based on user interaction data. An access to the virtual game environment having an indicia indicative of a real-world prize is provided by the processor based on a value associated with one of the datasets representing the quantitative metrics indicative of a measure of one of the user interaction data. The indicia can be attributed to a user account stored in the database based on another user interaction data that the processor receives from the communication device through the user interface on which the virtual game environment is rendered.

A cost-focused determination of whether to deliver an electronic advertisement or notice to a particular user can be made through a cumulative consideration of the predicted return on investment over each of a plurality of electronic channels. A plurality of channel-specific budget values are calculated for the user, one for each channel, each setting an upper spending limit for advertisement to the user over that channel based on the user's information and their activity on the channel. A global budget is calculated for the user using a weighted aggregation of the channel-specific values, information about the user and their activity with the advertiser, and consideration of overlap effects of advertising to the same user on several channels. When managing whether to deliver an advertisement over a channel, if the channel-specific value is lower than the global budget, the advertisement is delivered, and the global budget is decreased by a complementary amount.

Systems and methods for content selection and presentation are disclosed. Training data including indicating one or more interactions with one or more content elements and associated with one of a plurality of individual contexts is received. A selection model is trained by applying a reinforcement learning mechanism and an individual explore-exploit mechanism. A context for a user is selected by applying the selection model, which is configured to determine an expected future reward value of at least one of the plurality of individual contexts, determine an expected future reward value of a global context based on a past click-through rate, a reward value, and a future click-through rate, and, select the global context or one of the one or more individual contexts based on a comparison of the expected future reward values.