There are disclosed systems and methods for facilitating communications between individuals and enterprises and in particular, to methods and systems for tracking and attributing customer and/or customer prospect online and offline communications in association with a marketing campaign.

The present disclosure relates to systems and methods for identifying products and monitoring planogram compliance using analysis of image data. In one implementation, the method may include accessing at least one planogram describing a desired placement of a plurality of product types on shelves of a plurality of retail stores; receiving image data from the plurality of retail stores; analyzing the image data to determine an actual placement of the plurality of product types on the shelves of the plurality of retail stores; determining at least one characteristic of planogram compliance based on detected differences between the at least one planogram and the actual placement of the plurality of product types on the shelves of the plurality of retail stores; and receiving checkout data from the plurality of retail stores reflecting sales of at least one product type from the plurality of product types.

The Double Blind Machine Learning Insight Interface Apparatuses, Methods and Systems (“DBMLII”) transforms campaign configuration request, campaign optimization input inputs via DBMLII components into top features, machine learning configured user interface, translated commands, campaign configuration response outputs. A decoupled machine learning workflow generation request is obtained. A set of decoupled tasks specified via the decoupled machine learning workflow generation request is determined, wherein each decoupled task in the set of decoupled tasks is associated with a corresponding class. Dependencies among decoupled tasks in the set of decoupled tasks are determined. A decoupled machine learning workflow structure comprising the set of decoupled tasks and the determined dependencies is generated, wherein the decoupled machine learning workflow structure is executable via a decoupled machine learning workflow controller to produce machine learning results.

An area specifying system is a system for specifying an area in which information presented by an information medium is recognizable as the information, and includes a medium position information acquisition unit configured to acquire medium position information indicating a position in which the information medium is provided, an area specifying information acquisition unit configured to acquire area specifying information related to at least one of attributes of the information medium and content of the information presented by the information medium, and a specifying unit configured to specify the area based on the medium position information acquired by the medium position information acquisition unit and the area specifying information acquired by the area specifying information acquisition unit.

Protected audience selection system. Media consumption histories of browsers which have converted are received at a modeling system where targeting of browsers is prohibity. A model is built by determining a frequency of each respective media consumption event among the histories and comparing each determined frequency of a respective media consumption event to a frequency of the respective media consumption event among a population of browsers without the conversion event. The model is sent to a targeting system which excludes conversion events. A description of the conversion event is received at the targeting system. A history of a targetable browser is received at the targeting system. The model is applied to the history of the targetable browser at the targeting system, where conversion events have been excluded from the history. Advertising content is sent to the targetable browser according to a result of applying the model.

The invention relates to a system used to enhance the results of a direct mail marketing campaign. The system processes spanning online and offline efforts with the end result being increased engagement and return on investment through added impressions and real-time Key Performance Indicator (KPI) reporting, in an easy to use and understand dashboard. Additionally, the system has a smart label which communicates with the system of the instant invention to track mail.

At least one aspect is directed to determining an estimate of an intersection of user identifiers in a first set of user identifiers and a second set of user identifiers. The first and second sets of user identifiers can be populated with user identifiers that have interacted with the same content item or content item campaign. Estimates of intersections of the first and the second sets can be determined based on a binomial vector approach, a vector of counts approach, or a hybrid approach. The binomial vector approach generates vectors based on k hashes of each user identifier in the first set and summing the vectors to generate a first vector. The intersection can be determined based on a dot product of the first vector and a second vector similarly generated from the second set of user identifiers.

An advertisement budget optimization device (1) includes an estimation unit (13) that estimates a cost per click of an advertisement for each predetermined unit period (specifically, one day) included in a delivery period of an advertisement campaign as a delivery target, and a determination unit (14) that determines an advertisement budget for each unit period so that a total number of clicks of the advertisement is maximized, based on the cost per click in each unit period estimated by the estimation unit (13) and a total budget for the advertisement campaign in the delivery period.

A system is provided for interpretable viewing interest. A transformer with multi-head self-attention derives different hierarchical orders of input features. Hierarchical attention layers (i) aggregate the different hierarchical orders to obtain aggregated single-order feature representations and (iii) derive aggregation attention weights for the different hierarchical orders based on an applied order of the hierarchical attention layers. An attentional scoring layer evaluates the aggregated representations to output a significance of each order with respect to various CTR predictions. A hierarchical interpretation layer determines a respective importance of each input feature in various combinations from which the various CTR predictions are derived based on the aggregation attention weights and the significance of each order. A display device displays each of the various combinations for the various CTR predictions along with the respective importance of each of the constituent one of the input features in the various input feature combinations.

According to one aspect of the present disclosure, a method is provided for advertising on a content-screened web page. The method includes receiving an impression request for a URL for which an advertising impression is desired; screening HTML content of a web page identified by the URL; generating a rating for the URL based on the HTML content of the web page; assigning the rating to the impression request; and serving an advertising impression on the web page based on the rating.