A system and method is disclosed for predicting user behavior in response to various tasks and or/applications. This system can be a neural network-based joint model. The neural network can include a base neural network portion and one or more task-specific neural network portions. The artificial neural network can be initialized and trained using data from multiple users for multiple tasks and/or applications. This user data can be related to characteristics and behavior, including age, gender, geographic location, purchases, past search history, and customer reviews. Additional task-specific neural network portions can be added to the neural network and may be trained using a task-specific subset of the training data. The joint model can be used to predict user behavior in response to an identified task and/or application. The tasks and/or applications can relate to use of a website by users.

The present invention relates to a method, system and related devices for predicting the engagement level of a user of a user device, said user device receiving content for presentation at said user device, wherein said method comprises the steps of capturing at least one context of said user of said user device and capturing at least one context of the environment of said user of said user device, predicting a level of user engagement by processing at least one of said context of said user of said user device captured and said context of the environment of said user of said user device and scheduling the processing of said content received based on said level of user engagement.

The disclosed tools include enhanced and flexible tools to enable users who may be business competitors to share non-generic data in a substantially generic and in a substantially equitable manner. The resulting incentive to more freely share data between competitors will benefit users such as brand owners and enhance content delivered to their end users based on shared data.

A system, computer program product, and method for activation-based marketing are presented. In one embodiment, the system includes one or more data storage devices configured to store demographic data, healthcare utilization data, and response data associated with a target individual. The system may include a server coupled to the one or more data storage devices. The server may be suitably programmed to determine a life stage associated with a target individual, determine an attitudinal segment associated with the target individual, and determine a response model associated with the target individual. The server may assign the target individual to at least one of a predetermined set of segmentation groups in response to the life stage, the attitudinal segment, and the response model associated with the individual. The system may generate a personalized communication modality tailored to the target individual in response to the segmentation group assigned to the target individual.

A method for identifying web documents for presenting an advertisement. The method comprises receiving an advertisement for members of one or more demographic segment, identifying at least one web document with an editing style of an author from the demographic segment and allowing a presentation of the advertisement to at least one visitor of the at least one identified web document.

An approach is defined to establish consumption analytics of network nodes of a social network. Content is tagged and the content consumption analytics are derived from the content consumption. The content analytics and related heuristic is applied to new content shared in the social network. The content is compared to policies for content push operations and cellular network constraints to determine whether the content is proactively pushed to a mobile device.

A method for a content marketing includes identifying a plurality of topics found in content data based on a campaign, selecting relevant topics from the plurality of topics, which are relevant to the campaign, contextually matching contents of a plurality of publishers to the relevant topics, collecting customer data from the plurality of publishers, after a job is placed in the contextually-matched content of the plurality of publishers, and generating a predictive model for a conversion journey based on the customer data and the content data.

Disclosed is a method that includes: profiling a set of mobile applications according to revenue-related parameters; tracking a user's interaction with a mobile application; scoring the user's interaction levels, and based on the score, grouping users into mobile analytics groups associated with the targeting profiles; facilitating the transmission of user information, user interaction data, and specific mobile analytics groups to advertising campaigns. The method may be executed on a digital device. A related system is disclosed.

The disclosure is related to an advertisement service using mobile vehicles. Particularly, the disclosure relates to providing advertisement content selected based on statistical information on an advertisement target at an advertisement display location. Furthermore, the selected advertisement content may be provided to a corresponding mobile vehicle before the corresponding mobile vehicle arrives at the advertisement display location.

A method and system optimizes investments for each marketing channel of a multichannel marketing campaign. Past optimal investments are compared to current sales or profits for each marketing channel, and a new optimal investment is estimated for each marketing channel, which may be used as a marketing budget. A marketing dashboard is used to determine the new optimal investments for the marketing channels, and the new optimal investments are stored in a marketing database.