A method for driving trial of a branded product can include defining objectives for a marketing campaign and discovering target brand users. The target brand users comprise loyal branded product users. The method can also include determining life motivators of the target brand users, determining brand motivators of the target brand users, and designing an online engagement activity related to the branded product. The online engagement activity tracks conversion rates related to the branded product. The method can also include engaging the target brand users in use of the online engagement activity.

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 determining the effectiveness of an advertising campaign on an electronic advertising platform includes a computing device configured to obtain exposure data characterizing a user's interaction with the advertising platform during an advertising campaign and to categorize the user into one of a plurality of exposure bins based on the exposure data. The computing device may be further configured to obtain sales feature data characterizing the user's purchase behavior on the advertising platform both before and during the advertising campaign and to categorize the user into one of a plurality of sales clusters based on the sales feature data. The computing device may be further configured to define a control group comprising unexposed users categorized into the same exposure bins and sales clusters as exposed users and to compare purchase data of the exposed users to the purchase data of the control group.

The present disclosure describes systems, methods, and non-transitory computer readable media for generating lookalike segments corresponding to a target segment using decision trees and providing a graphical user interface comprising nodes representing such lookalike segments. Upon receiving an indication of a target segment, for instance, the disclosed systems can generate a lookalike segment from a set of users by partitioning the set of users according to one or more dimensions based on probabilities of subsets of users matching the target segment. By partitioning subsets of users within a node tree, the disclosed systems can identify different subsets of users partitioned according to different dimensions from the set of users. The disclosed systems can further provide a node tree interface comprising a node for the set of users and nodes for subsets of users within one or more lookalike segments.

Embodiments include apparatuses, methods, and systems for segmenting a target region for a target user based on payment transactions within a payment processing system. The embodiments include identifying a target user from users based on payment transaction data, and determining target regions for the target user based on the payment transaction data of the target user and users. The target user may have a propensity for initiating transaction activity in the target regions within a predetermined time period. The embodiments include generating propensity scores for the target regions based on the payment transaction data, identifying a target region for the target user based on the propensity scores, and transmitting merchant offers to the target user based on the identified target region. The propensity scores may be ranked into a list of target region rankings, where the target region is a maximum score in the list of target region rankings.

A method of dynamically binding supplemental content to a content transactional item includes identifying the content transactional item at a device and identifying a description related to the content transactional item. The method also includes obtaining the supplemental content based on the description, where the supplemental content provides additional information about the content transactional item. The method further includes dynamically binding the supplemental content to the content transactional item and positioning the supplemental content in association with the content transactional item using a supplemental interactive display.

A method, system and computer-usable medium for providing cognitive insights comprising receiving streams of data from a plurality of data sources; processing the streams of data from the plurality of data sources, the processing the streams of data from the plurality of data sources performing data enriching to provide enriched data; generating the cognitive session graph, the cognitive session graph being associated with a session, the cognitive session graph comprising at least some enriched data; and, processing the cognitive session graph to provide a cognitive insight, the cognitive insight being related to the session.

Methods and systems are described for providing advertising services to devices with a customized adaptive user experience based on adaptive algorithms. In one embodiment, a system includes a storage medium to store one or more software programs and an adaptive decision unit coupled to the storage medium. The adaptive decision unit includes or is coupled to processing logic that is configured to execute instructions of at least one adaptive decision algorithm to obtain data for different variables including at least two of an advertisement (ad) engagement history for a user, application (app) engagement history for the user, and in-app purchase engagement history for the user when making an ad selection decision. The at least one adaptive decision algorithm determines an ad selection decision for at least one relevant ad or ad content served in an engaging manner to a device of the user.

According to an embodiment, a computing apparatus comprises at least one processor and at least one memory including computer program code. The at least one memory and the computer program code may be configured to, with the at least one processor, cause the computing apparatus to select at least one targeted user from a plurality of users according to a targeting constraint and at least one similarity score. A computing apparatus, a method, and a computer program are described.

According to an embodiment, a computing apparatus comprises at least one processor and at least one memory including computer program code. The at least one memory and the computer program code may be configured to, with the at least one processor, cause the computing apparatus to: calculate a user-specific price of an item. The computing apparatus may calculate the user-specific price based on various factors, such as a score of a user attribute profile vector of the user and an item attribute vector of the item, a price elasticity, and an appeal score. A computing apparatus, a method, and a computer program are described.