A system and method for identifying prospects with a buying intent and connecting them with relevant businesses. An example method may comprise obtaining a training dataset; applying a first scoring algorithm to obtain a first score for each entry in the training dataset; receiving one or more scores from a user for one or more entries in the training dataset; rescoring the training dataset based on the one or more scores received from the user; creating a deep learning model based on the rescored dataset; obtaining digital media posts comprising data from one or more digital media platforms; scoring each received digital media post by using the deep learning model; providing certain scored digital media posts to the user; receiving a second score from the user; and updating the deep learning model based on the second score.

An apparatus for providing customized advertisements includes a database that stores a plurality of electronic advertisements, receives biometric information of a client from at least one biometric device of the client, and receives receptivity information of the client responding to the plurality of electronic advertisements, as well as a processor that accesses the database, and maps the biometric information and the receptivity information and analyzes the mapped information to generate customized marketing data. The processor also calculates a receptivity probability for each of the plurality of electronic advertisements based on the customized marketing data by using current biometric state of the client, selects an electronic advertisement from the plurality of electronic advertisements based on the calculated receptivity probabilities, and outputs to the client the selected electronic advertisement.

Systems and methods are disclosed for online distribution of content based on a user sentiment index. The method may include receiving, over a network and from a user device, one or more user generated inputs and calculating the user sentiment index based on the one or more user generated inputs. The method may also include receiving, over the network, from a content or advertising provider, instructions on publishing content or advertising to a webpage based on the calculated user sentiment index, and publishing content for display on user devices over the network based on a comparison of the calculated user sentiment index and the received instructions.

A system that analyzes a user's communications to select a promotion that is presented to the user. The analysis may occur in two stages: a first stage analyzes a single communication from a user to determine whether the user is a potential target for a promotion; for potential targets, a second stage analyzes a history of communications from the user to generate a user profile. The system may then select a promotion based on the profile. The profile may include a set of profile tags that are considerably more detailed and granular than traditional demographic data; tags may for example indicate user affiliations with groups or ideas (such as religions or political parties), or user life cycle stages. Using these rich, detailed user profile tags, the system may achieve promotion response rates far above those from traditional advertising, which relies on cookies or simple demographic categories.

Described are systems and methods for determining a diversity function in connection with potential advertisements in determining one or more advertisements to present to a user. This can facilitate presenting diverse advertisements to users. The diversity function can yield a diversity penalty for each potential advertisement to be able to determine a rank order of the potential advertisements. The diversity function can include a repetition score and a multiplier for each potential advertisement.

A marketing analytics pipeline includes an opportunity detection analytics hub and a marketing platform, wherein the opportunity detection analytics hub is configured to use trend data reports from a consumption database to fit statistical models based on streaming consumption and interaction patterns of social media UGC (user generated content) and to send growth and re-engagement opportunities to a marketing action analytics hub, and wherein the marketing platform is configured to interact with the marketing action analytics hub to create targeted marketing campaigns based around high growth potential audiences. In a further aspect, the opportunity detection analytics hub includes an offline prediction model generation component and an online opportunity detection component that receives both current streaming consumption and social media UGC interaction data for a plurality of media IP assets and identifies opportunities from the combination of these two data sources that could not be detected if analyzed separately, inclusive of a case where significant changes are detected in social media UGC interaction patterns, but are not yet detected in streaming consumption.

A system and associated methods for managing digital advertising promotions on behalf of merchants, in response to changes in the availability of promoted items, are provided. In some embodiments, the method includes receiving purchase data from an electronic shopping cart associated with a merchant, based on which a rate of sale of a purchased item is generated. The method includes accessing a database storing a plurality of node data set, each node data set being associated with a warehouse node. Based on the node data sets and the rate of sale, the method additionally includes determining a projected availability of the purchased item in a delivery region. The method also includes adjusting, based on the projected availability, a digital promotion advertising at least the purchased item.

An online system accesses a model trained based on a topic associated with a set of content items and the content of the set of content items. The online system applies the model to predict a probability that each of multiple content items is associated with the topic based on its content and identifies (a) content item(s) associated with at least a threshold probability. The online system retrieves information describing user engagement with the identified content item(s) and determines a value of a performance metric for the topic based on this information. If the value is at least a threshold value and the online system receives content from an entity describing an item associated with the topic, the online system communicates a recommendation to the entity to create a content item describing the item and to add a tag associated with the item upon determining an opportunity to do so.

A system and method for identifying prospects with a buying intent and connecting them with relevant businesses. An example method may comprise obtaining a training dataset; applying a first scoring algorithm to obtain a first score for each entry in the training dataset; receiving one or more scores from a user for one or more entries in the training dataset; rescoring the training dataset based on the one or more scores received from the user; creating a deep learning model based on the rescored dataset; obtaining digital media posts comprising data from one or more digital media platforms; scoring each received digital media post by using the deep learning model; providing certain scored digital media posts to the user; receiving a second score from the user; and updating the deep learning model based on the second score.

A multidimensional marketing system and method is provided that allows a real estate agent to communicate with a group of homeowners, buyers and sellers via a customized document that is mailed to these subjects. The marketing system is a computer-network-based application or an application operated on a smartphone, a tablet, a computer or other computer network-communicated device. The marketing system helps an agent create a customized document using a variety of templates and tools, create personalized messages for the homeowners, buyers and sellers, and create mailing lists where a particular document would be sent to a particular group of homeowners, buyers or sellers. The marketing system helps an agent to schedule when a mailing should occur and allows the agent to customize their mailing lists. The marketing systems helps identify potential sellers and direct mailing/marketing messages to these potential sellers in order for the real estate agent to obtain their listings.