A system for processing information requests associated with mobile devices comprises an evaluation module configured to determine at least one performance measure for each of a plurality of information documents using at least data in one or both of a requests database and events database. The at least one performance measure includes at least one of an impression-based performance measure, a click/call-based performance measure, and an off-line site-visit-based performance measure. The system further comprises an information server configured to select a first information document for transmitting to a first mobile device to fulfill a first request. The information server includes a volume control unit configured to derive an off-line site visit projection in response to the first document being selected based at least in part on an off-line site-visit-based performance measure and having been impressed on the first mobile device, and to adjust a budget associated with the first document using the off-line site visit projection.

Adaptive control of exposure. A proportional exposure cap is a maximum fraction applicable to a recipient's total viewable attention in a time window. The total viewable attention represents all viewable advertising content which will be provided to the recipient. A notification of availability of an opportunity to expose a specified recipient to advertising content is received during the time window. The specified recipient's consumed viewable attention is detected. The specified recipient's total viewable attention for the time window is predicted. Responsive to the maximum fraction of the specified recipient's predicted total viewable attention for the time window being greater than the consumed viewable attention of the specified recipient, content is sent to the specified recipient and the consumed viewable attention is updated.

Disclosed herein are a method and system that utilize a programmed content predictor to dynamically select electronic publishing content. In particular, the content predictor applies a selection model to select content for one or more selected webpages presented during an electronic transaction. The selection model utilizes a set of one or more machine learning models to select content based on calculated quality scores. The nature of the quality scores determined by the quality score model depend on the particular application. The predictor generates and populates a permutation quality table based on a set of selected content items and page variant, wherein the page variant defines locations of content positions within a webpage. The predictor then consumes the selection model to select a best permutation of content item-content position combinations to be returned for display on a webpage.

A method, apparatus and computer program product are provided for integrated sales management. A sales resource may use the system to track and modify promotion proposals for providers. Data defining the proposed promotion may include information relating to the provider, capacity, the promotion structure, return on investment, and/or an auto-approval status. Some data defining the proposed promotion may be automatically generated by the promotional system and/or modified by the provider. The proposal may be auto-approved or approved manually by a sales resource. Upon approval, the promotion may be made available for sale.

The invention generally relates to systems and methods for an interactive platform which facilitates the management of social media accounts and content across multiple social media networks, and which facilitates collaboration between influencers and brand owners with respect to social media marketing, advertising, and content publishing.

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.

A quantification system is configured for debiasing media creative efficiency. In some embodiments, the quantification system leverages a weighted generalized linear model (GLM) to determine the individual impacts of media creatives beyond network effects. To prepare input data for fitting the weighted GLM, the quantification system analyzes spot airing data, creates a specific data structure for storing observations (e.g., network-media creative combinations) that can be provided to the weight GLM as input, and computes additional input data points needed by the weighted GLM (e.g., network spend, media creative efficiency per network-media creative combination, etc.). The weighted GLM is then fitted to obtain coefficients representing the individual impacts of the media creatives. The quantification system utilizes the computed impacts to adjust the previously computed media creative efficiency for each media creative. In this way, relative performance of media creatives can be objectively quantified across networks without needing digital evidence.

Method and server for managing placement of a digital signage content based on metric thresholds. The server stores parameters associated to a plurality of locations. The parameters for each location comprise at least one metric and a corresponding threshold for each metric. The server determines a plurality of candidate locations among the plurality of locations for displaying the content. For each candidate location, the server processes the at least one metric and corresponding threshold of the candidate location to determine if each metric among the at least one metric is within the corresponding threshold. The server identifies one or more target location among the plurality of candidate locations for displaying the content. Each metric among the at least one metric of the one or more target location is within the corresponding threshold. The locations may include digital signage players, geographical areas, displays controlled by a player.

A computer-implemented system and a method for automatic electronic order creation are disclosed. The system and method may be configured to: receive a digitized document comprising embedded metadata related to contents of the digitized document; analyze the embedded metadata to extract a boundary parameter; generate a unique reference identifier associated with the digitized document and the boundary parameter; receive a first input data setting one or more target measurements for one or more predefined periods of time, wherein a sum of the one or more target measurements is less than or equal to the boundary parameter; receive a second input data setting configuration data for achieving the one or more target measurements; and generate an electronic order based on the configuration data.

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