An on-line marketplace provides systems and methods for a mutually beneficial messaging campaign with one or more merchants, in order to promote the merchants' products. One aspect of the messaging campaign includes augmenting the merchants' budgets across multiple commercial channels. The channels may include merchant-operated channels, marketplace-operated channels, and/or third party channels. The marketplace selects when and how to augment the merchants' budgets. The augmented budget comprises an overall content budget for the messaging campaign, including a first budget portion provided by the merchant(s) and a second budget portion provided by the on-line marketplace. The augmented budget may be determined based on a weighted combination of goals of the marketplace and one or more merchants. The augmented budget may be segmented into static and dynamic portions, in which the dynamic portion is varied between channels to determine variables to optimize budget allocation and message performance.

Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium, including a system that controls content distribution using a feedback loop. Content is distributed over multiple different online channels using a same initial selection value for distribution over each different online channel. An observed user actions required for distribution of the content over the multiple different online channels is received through a feedback loop and for multiple different distributions of the content. Based on the observed user actions received through the feedback loop, a predicted user action rate is determined for the multiple different distributions across the multiple different online channels. The selection value is adjusted based on a difference between the predicted user action rate and a reference distribution amount specified by a provider of the content. The content is distributed over the multiple different online channels using the adjusted selection value.

This document describes the collection, generation, distribution, and management of online web content. The devices, systems, and methods described herein can be used to collect and generate online web content and communications. Specifically, the disclosed devices and systems may be employed to produce one or more marketing and/or advertising campaigns, as well as for monitoring, managing, defining the efficiency, effectiveness, and workability of the campaign with respect to generating user engagement, thereby accurately determining the cost benefits of the campaign. The analytic results provided may then be used to guide the generation of original web content, such as for the purposes of enhancing customer or follower experience, driving business, and for driving advertising campaigns. Alternatively, web content that is in the public domain, and determined to perform well, can be reproduced, referenced, or otherwise referred to, in the context of promoting or presenting the user's web content.

A method for managing advertisement that is to be performed by a server includes a step of receiving a piece of advertisement type information from an enterprise device, a step of selecting pieces of candidate user information from among pieces of user information stored in the server based on the piece of advertisement type information, a step of receiving an advertisement material from the enterprise device, a step of selecting pieces of target user information that corresponds respectively to target users from among the pieces of candidate user information, and a step of performing an advertisement-pushing procedure with respect to the target users.

A method is proposed for providing a content page in an application. In the method, a media item is generated, and the media item is associated with respective resources in a resource list that is received from a resource provider. The media item is presented in the application. A content page is caused to be displayed in response to detecting an interaction event of a user of the application with the media item, the content page including respective content items for the respective resources. Therefore, the media item and the content page are generated and displayed in an automatic way for the one or more resource providers without any label work from the resource providers.

This document describes the autonomous collection, generation, distribution, and management of online web content. The devices, systems, and methods described herein can be used to collect and generate online web content and communications in an automatic and autonomous manner. Specifically, the disclosed methods, devices, and systems may be employed to produce one or more communications and/or advertising campaigns, as well as for monitoring, managing, defining the efficiency, effectiveness, and workability of the campaign with respect to generating predicted user engagements, thereby accurately determining the cost benefits of the communication campaign. The system may track, evaluate, and provide analytic results that may then be used to better guide the system parameters for customizing autonomous communications directed one or more characteristics of a defined target audience.

A system for self-service public radio sponsorship ordering and copywriting of advertisement is disclosed. The system comprises a server and a network interface. The server includes a threshold analyzer configured to receive a budget request from a user and determine if the budget request is within a pre-determined budget range, a payment system for receiving payment information from the user, a scheduler for scheduling an airtime for an advertisement from the user, and an advertisement copywriting generator for generating a preapproved draft message for the user, wherein the draft message is for the advertisement from the user The network interface in signal communication with the server, wherein the network interface is configured to communicate with a remote computing device over a telecommunication network.

A non-transitory computer-readable recording medium stores therein an allocation program that causes a computer to execute a process including: performing, by using a part of data including an objective variable and one or more explanatory variables corresponding to the objective variable as training data, training of a model that predicts the objective variable from the explanatory variables of the data; classifying test data obtained by excluding the training data from the data into a group according to a classification condition regarding at least a part of the explanatory variables of the data; predicting the objective variable from the explanatory variables of the test data using the trained model for each of groups by which classification has been performed at the classifying; and calculating a predetermined resource amount to be allocated to each of the groups based on the objective variable for each of the groups predicted at the predicting.

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.

Methods, systems, and non-transitory computer readable storage media are disclosed for determining parameters for digital campaign content in connection with executing digital campaigns using a rank-one assumption and a best-arm identification algorithm. For example, the disclosed system alternately explores response data in the first dimension and response data in the second dimension using the rank-one assumption and the best-arm identification algorithm to estimate highest sampling values from each dimension. In one or more embodiments, the disclosed system uses the estimated highest sampling values from the first and second dimension to determine a combination with a highest sampling value in a parameter matrix constructed based on the first dimension and the second dimension, and then executes the digital campaign using the determined combination.