Systems, devices, media, instructions, and methods are provided for presentation of media collections with automated interactive advertising. In one embodiment, a client device receives content elements for display as part of a content collection. Advertising data is also received for display between selected content elements. Interaction elements are merged with the create an advertising element. During display of the advertising data, the interaction elements are presented on the client device output, and are controllable via user inputs. In various embodiments, interaction data recorded at the device is used to manage the presentation of future advertising data.

A social media impact analysis (SMIA) computer device and methods for allocating resources in response to social media conversations are provided. The SMIA device stores for a plurality of escalation levels, corresponding trigger criteria and resource allocations, where each trigger criteria includes a sales impact range and a content category. The SMIA device is configured to receive tracking signals relating to social media conversations about a product over a time period, each tracking signal including a topic of social media conversation and correlated to a predicted future sales impact; detect that a tracking signal deviates from a threshold; compare the tracking signal to the trigger criteria for the escalation levels; and allocate resources automatically in response to the social media conversations according to the resource allocation for a first of the escalation levels.

Method and computing device for performing dynamic digital signage campaign optimization. Screen data associated to screens controlled by the computing device and requirements of active campaigns are stored at the computing device. The screen data comprise characteristics of the screens and screen activity data defining the activity the screens for the active campaigns. The computing device receives requirements of a candidate campaign and generates a mathematical model based on the requirements of the candidate campaign, the requirements of the active campaigns, and at least some of the screen data. The mathematical model is transmitted to a mathematical solver and a mathematical solution generated by the mathematical solver is received. The computing devices generates configuration data for the candidate campaign based on the mathematical solution. The configuration data define a configuration for displaying a content of the candidate campaign on selected screens among the screens controlled by the computing device.

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 instructions to: receive, over a network, consumer data from a client device; identify a plurality of client-provided consumers from the consumer data; obtain a plurality of unique consumer identifiers corresponding to the plurality of client-provided consumers; and identify at least one first overlapping unique consumer identifier by matching at least one of the plurality of client-provided consumers with at least one publisher-provided consumer provided by a first publisher device of a plurality of publisher devices, the first publisher device having a highest priority among the plurality of publisher devices.

In some examples, a computing device may receive data from a plurality of groups of data sources. The computing device may access a plurality of data synthetization machine learning models configured for generating synthetic data. Respective ones of the data synthetization machine learning models may correspond to respective ones of the groups of data sources. The computing device generates first synthetic data by inputting, to a first data synthetization machine learning model, first data received from a first data source group, and generates second synthetic data by inputting, to a second data synthetization machine learning model, second data received from a second data source group. The computing device determines an allocation of resources based at least in part on comparing the first data and the first synthetic data with the second data and the second synthetic data.

According to an embodiment, a data processing apparatus generalizes an element described in advertising campaign information and derives a first target model representing a recipient image. The data processing apparatus generates, on the basis of an attribute and an action history of a recipient collected from the recipient, recipient information indicating a characteristic of each attribute of the recipient and derives, for each attribute, a second target model representing a recipient image. Further, the data processing apparatus determines a target model who is a target of the advertising campaign.

A dynamically regulated advertising delivery control system. A campaign is operated by sending bids to an exchange responsive to receiving bid requests from the exchange, each bid request representing an opportunity to expose a browser to content. Won bid notifications are received from the exchange and exposure notifications are received from exposed browsers. Failed exposures are detected by detecting won bid notification identifiers without corresponding exposure notification identifiers. Responsive to the failed exposures exceeding an upper limit, the campaign is operated in a throttled mode. Responsive to detecting successful exposures in the throttled mode, the campaign is operated in a recovered mode.

A targeted advertising scheduling and displaying process in the context of product terminal displays is made possible by systems and methods as disclosed herein. A graphical user interface (GUI) allows a content provider to select digital content and display timing instructions, which the associated server will ultimately send to a server associated with the product terminal displays by first sending data that references the digital content and includes the display timing instructions, and then sending the digital content itself in response to the execution of the data at the server associated with the product terminal displays. Using this claimed technique and system, a content provider can target digital content to particular product terminal displays.

A targeted advertising scheduling and displaying process in the context of product terminal displays is made possible by systems and methods as disclosed herein. A graphical user interface (GUI) allows a content provider to select digital content and display timing instructions, which the associated server will ultimately send to a server associated with the product terminal displays by first sending data that references the digital content and includes the display timing instructions, and then sending the digital content itself in response to the execution of the data at the server associated with the product terminal displays. Using this claimed technique and system, a content provider can target digital content to particular product terminal displays.

A method is disclosed for enabling a network location to provide an ordering process for data relevant to connected network devices' activities. The method includes assembling the data, utilizing the activity data, and associating the data, such that information is derived to enable a desired expansion of at least one designated activity. Another method is disclosed for managing an object assignment broadcast operations for a network location based on a network device's previous activities. This second method includes tracing a network device's conduct to determine that a network device prefers a particular class of content. The method also includes tagging a network device's profile with the respective observation and deciding by a network location as to the classification factor for a network device to be targeted for an object assignment broadcast.