Methods, systems, and computer programs are presented for the determination of optimal communication scheduling. Send Time Optimization (STO) uses machine learning (ML) to recommend a personalized send time based on a recipient's past engagement patterns. The purpose of the ML model is to learn patterns in the data automatically and use the patterns to make personalized predictions for each recipient. The send time recommended by the model is the time at which the model believes the recipient will be most likely to engage with the message, such as clicking or opening, and use of the send time mode is expected to increase engagement from recipients. Additional customizations include communication-frequency optimization, communication-channel selection, and engagement-scoring model.

Methods and systems are provided herein for recommending a media asset based on a geographic location at which that media asset was frequently consumed. For example, the system may monitor a location, such as New York City or Times Square, to determine popular media assets watched there, such as “The Avengers,” and when another user visits New York City, the system may then notify the user that the movie, such as “The Avengers,” is associated with New York City. The system stores the geographic locations associated with the media asset in the database based on the consumption of the media asset so that other users may be notified which media assets are associated with each geographic location.

An advertising method, device and system, and a computer-readable storage medium are provided. The method includes: acquiring user information; sending the user information to a server that stores an advertising requirement, wherein the advertising requirement includes an advertisement content and an advertising condition of the advertisement content; receiving an advertising instruction of the advertisement content from the server, wherein the advertising instruction of the advertisement content is generated by the server when the user information meets the advertising condition of the advertisement content; and playing the advertisement content in response to the advertising instruction.

Aspects of the subject disclosure may include, for example, embodiments for detecting a navigation application operating on a first communication device, and identifying a location of the first communication device. Further embodiments can include obtaining a first advertisement and a second advertisement according to the location of the first communication device as well as determining a first priority associated with the first advertisement and a second priority associated with the second advertisement. Additional embodiments can include determining the first priority is higher than the second priority resulting in a determination to present the first advertisement prior to the second advertisement, and providing the first advertisement, the second advertisement, and the determination to the first communication device. The first communication device presents the first advertisement within navigation content utilizing the navigation application prior to presenting the second advertisement within the navigation content based on the determination. Other embodiments are disclosed.

System and method for promoting mobility and logistics of goods services based on advertisements. The system allows the user to be given the freedom to choose and hire the service and the price of the service they want, based on a series of advertisements that promote the services of the drivers before an audience of potential customers generated by an operating system to show the offer of the drivers, of their services of transport of people and/or logistics and delivery of goods. The customers create their own community of favorite and trusted drivers to more easily hire that community of drivers when a service is required. The driver and the customer can agree on special and fixed prices between both parties so that the customer can hire their favorite and trusted drivers on a regular basis with the certainty that the prices are those agreed between both parties.

Technology is described for providing targeted electronic advertisements on an aircraft. A server onboard the aircraft may establish a connection with a client device onboard the aircraft. The server may identify a user profile associated with a user of the client device. The user profile may include itinerary information for the user of the client device. The server may select a targeted electronic advertisement based in part on the itinerary information. The targeted electronic advertisement may be selected from a data store of electronic advertisements. The targeted electronic advertisement may be sent to the client device to be displayed using a graphical user interface on the client device.

Systems and methods of distributing campaign media are disclosed. In some embodiments, a campaign data structure is obtained related to campaign media. Additionally, audience data structures are obtained, wherein each of the audience data structures describes a corresponding audience of a plurality of audiences. Using a computer device, at least one target audience is selected for the campaign media from the plurality of audiences based on the campaign data structure and the audience data structures. Also using the computer device, one or more electronic transmissions of the campaign media are scheduled to at least one user device associated with the at least one target audience based on the campaign data structure and the audience data structures.

A media distribution system includes an enterprise hub, which in turn includes a processor and memory, multiple media outlets, and multiple integrated services layers (ISLs) acting as intermediaries between the enterprise hub to the media outlets. A first media outlet is served by a single ISL, while a second media outlet is served redundantly by at least two ISLs.

Systems, apparatus, methods, and non-transitory media for providing multiple items for purchase to consumers are discussed herein. Some embodiments may include a system including circuitry configured to initiate an add-to-order session timer subsequent to the primary purchase of a first item using transaction data of the consumer. The add-to-order session timer may indicate a period of time in which one or more additional items may selected for purchase using the same transaction data as the primary purchase. In some embodiments, the system may be further configured to provide incentives to the consumer for selecting an additional item prior to expiration of the add-to-order session timer.

Methods, systems, and computer programs are presented for the determination of optimal communication scheduling. One method includes an operation for training a machine-learning program to generate a frequency model that determines a frequency for sending communications to users. The training utilizes training data defined by features related to user information and responses of users to previous communications to the users. The method further includes determining, by the frequency model and based on information about a first user, a first frequency for the first user. The first frequency identifies the number of communications to transmit to the first user per period of time. Further, the method includes operations for receiving a communication request to send one or more communications to the first user and determining send times for the one or more communications to the first user based on the first frequency. The communications are sent at the determined send times.