Electronic correspondence that includes one or more promotions may be generated for presenting to a consumer. In order to determine whether to present the electronic correspondence to the consumer, the promotions included in the electronic correspondences may be analyzed in terms of a probability the consumer will accept the promotions, a relevance level between the promotions and attributes of the consumer, a relevance level between the promotions and the consumer, a relevance level between the promotions and a set of goals or rules, among other similar terms. After the analysis, a determination may be made whether to send the electronic correspondence to the consumer. Similarly, the analysis may compare multiple electronic correspondences, and determine, based on the comparison, which of the multiple electronic correspondences to send to the consumer.

Among other things, videos and commercials are downloaded to a mobile device for storage on the mobile device and later playout on the mobile device. The downloading includes downloading of metadata associated with the commercials and based on which the mobile device can select commercials for insertion into videos being played back to the user of the mobile device. The commercials to be downloaded are selected based on one or a combination of any two or more of the location of the user, the type of mobile device, and personally-identifiable information about a user of the mobile device.

A method and digital signage server for managing display of a distributed digital signage content. The digital signage server stores a first placement target for the distributed digital signage content, and a second placement target for the distributed digital signage content. The distributed digital signage content is displayed on a first digital signage player according to the first placement target and displayed on a second digital signage player according to the second placement target. The digital signage server exchanges messages with the first and second digital signage players for negotiating a modification of the first and second placement targets. The digital signage server ultimately modifies the first and second placement targets based on the messages exchanged with the first and second digital signage players.

Systems, apparatus, methods, and non-transitory media for providing user interfaces are discussed herein. Some examples may include an apparatus configured to determine one or more additional items based on relevance data related to a primary purchase item that is associated with a user profile, generate a user interface, determine at least one selected item from the one or more additional items, receive an expiration signal indicating expiration of an automatic completion time period, and execute an automatic purchase completion transition routine associated with the at least one selected item in response to receiving the expiration signal.

Methods and apparatus to deliver targeted advertising are disclosed. An example apparatus includes a media object assembler to, in response to receiving a request to provide a media object, generate a custom media object using a first media object element and a second media object element based on at least one of a user profile or a group profile corresponding to a user, the user corresponding to the request; an interface to transmit the custom media object to the user; and a performance analyzer to analyze a performance of the custom media object; and update at least one of the user profile or the group profile based on the performance.

According to an embodiment, an image display device includes: a display; a memory storing one or more instructions; and a processor executing the one or more instructions stored in the memory, wherein the processor executes the one or more instructions: to determine whether it is a recommended time for outputting advertisement content, from a user's log data, based on a first trained model using one or more neural networks; to determine a recommended attribute of an advertisement display region from the user's log data, based on a second trained model using the one or more neural networks, when it is determined that it is the recommended time for outputting the advertisement content; and to adjust an attribute of the advertisement display region based on the determined recommended attribute and control the display to output the advertisement content in the attribute-adjusted advertisement display region.

In one embodiment, a promotional subsystem generates promotional plans that include promotionals, where each promotional targets one or more pieces of scheduled content. First, the promotional subsystem generates a statistical model based on historical respondent viewership data. The statistical model model maps a respondent viewing of a promotional that targets a piece of scheduled content to a probability of the respondent viewing the piece of scheduled content. Subsequently, the promotional subsystem generates a proposed promotional plan based on the statistical model, a schedule that includes the piece of scheduled content, and a risk tolerance. Advantageously, the promotional subsystem may be configured to generate different proposed promotional plans based on different risk tolerances associated with different viewership growth strategies. Automatically generating proposed promotional plans based on probabilities reduces the time required to identify an acceptable promotional plan compared to current techniques that generate a single promotional plan based on deterministic strategies.

Examples of techniques for predictive media content delivery are disclosed. In one example implementation according to aspects of the present disclosure, a computer-implemented method for predictive media content delivery includes identifying, by the processing device, a customer approaching a kiosk. The method further includes determining, by the processing device, an estimated duration that the customer is expected to be in proximity to the kiosk. The method further includes presenting, by the processing device, media content to the customer that has a playback duration commensurate with the estimated duration that the customer is expected to be in proximity to the kiosk.

To place an efficient advertisement to a particular target. A spot planning evaluation system according to one aspect of the present disclosure includes: an acquisition unit configured to acquire information for identifying effective areas configured with advertisement slots with particular-target content rates equal to or larger than a given threshold; and a control unit configured to perform, in order that a sum total of total audience ratings (acquired gross rating point (GRP) rates) expected to be acquired by the advertisement slots of the effective areas with respect to all advertisement slots during a given period becomes a given value, adjustment of acquired GRP rates of all the advertisement slots during the given period.

Systems and methods for recommending purchase of a new smart appliance are described. The method includes receiving operational information relating to a first smart appliance. The method includes predicting, based on the operational information, a future date by which the first smart appliance will be required to be replaced by a second smart appliance. The method includes estimating, based on financial history of a user, a budget capacity for the user to purchase the second smart appliance. The method includes determining, based on the user's budget capacity and a predicted operating cost of the first smart appliance, a recommended date to purchase the second smart appliance. The recommended date is no later than the future date. The method includes providing the estimated budget capacity and the recommended date to the user.