At least one embodiment of the disclosed system is directed to computer-implemented method for using machine vision to categorize a locality to conduct lead mining analyses. Embodiments of the method may include: generating locality profile scores and economic categorization for each locality of a plurality of localities, the locality profile score for each locality being derived through neural network analyses of map images of the locality, the economic categorization being derived through neural network analyses of images of entities within the locality; and generating a lead score for each entity in the locality group as a function of the locality profile score for the locality in which the entity is located, the economic categorization of the locality in which the entity is located, and campaign vehicles used in the locality in which the entity is located.

A sales enhancement system and method is disclosed. The sales enhancement system is configured to use one or more deal program collections, which are groupings or compilations of deal programs. The sales enhancement system manages deal programs in the deal program collections at various stages of use including: associating a deal program with multiple deal program collections; determining the number of deals to assign to the different deal programs; using triggers to select which deal program collections to access; transmitting an offer for a deal; and processing acceptances of the offers.

In one embodiment, a method includes obtaining, from a demand-side platform (DSP), impression data specifying service providers and consumer tokens representing consumers who have received digital impressions of a set of advertising campaigns. A set of tokenized claims data records related to a prescription of a product is then received from a database server. A result set of integrated measurement records specifying measured campaigns linking the tokenized claims data records with impression data associated with consumer tokens and/or service provider identifiers is further received from the database server. Aggregated analytics reports based on the integrated measurement records are generated and presented. A machine learning model may be trained using a training dataset comprising features selected from the impression data and tokenized claims data records, to predict bid values or other parameters for use in updating, optimizing or modifying operation of the DSP for the original campaign or for other campaigns.

Certain aspects of the disclosure are directed to contact center management, using a data communications server. According to a specific example, the data communications server includes one or more computer processor circuits coupled to memory circuits and configured to interface with a plurality of remotely-situated client entities. The data communications server may be configured and arranged to monitor a plurality of communications placed to target recipients in a first communications-based campaign of a first client entity among the plurality of remotely-situated client entities, and to determine a disposition of each of the plurality of communications based at least on data received and relating to the plurality of communications. Based at least in part on the disposition of the plurality of communications from the first communications-based campaign, data communications server may generate a contact list of target recipients for a second communications-based campaign associated with a second remotely-situated client entity.

A system and method for optimizing marketing campaigns is presented. Two marketing campaigns are received. Each is presented to a subset of users. The conversion rates of both marketing campaign are used to determine weighting of the two marketing campaigns. The weighting is determined using a range of conversion rates and maximizing the minimum expected value through the range of conversion rates. The process can be iteratively performed to converge upon an optimum weighting of the first and second conversion rates. More than two marketing campaigns can be used. The marketing campaign can be an email marketing campaign, a web marketing campaign, or an advertising keyword campaign. Other embodiments also are disclosed.

A multivariate testing platform is disclosed. The platform includes a test definition environment including a test deployment and data collection interface configured to (1) manage test deployments within a retail environment to a controlled subset of users across a plurality of content delivery channels, and (2) receive test data from an analytics server regarding user interaction regarding the test deployment. The test definition environment includes a self-service test definition and analysis tool configured to generate a user interface accessible by enterprise users, the user interface including a test definition interface useable to define a test selectable from among a plurality of test types and an analysis interface graphically displaying test results based on the test data from the analytics server.

Methods and systems for dynamically incorporating advertising content into multimedia environments, such as games, are provided. Example embodiments include a dynamic inserter, which selects content, based upon a set of criteria, to deliver to a receiving client system, such as a game client. The game client typically dynamically determines locations with the game where advertisements may be inserted. Associated with these locations are ad tags that specify criteria for the ads. For example, the criteria may include ad type, ad genre, and scheduling information. The game client then sends indications of these ad tags to the dynamic inserter to be used to select appropriate ads. The dynamic inserter selects ads based upon the criteria and sends them to the game client, which selects them for ad tags with conforming criteria. The game client then renders the selected ad in the appropriate location. In one embodiment, the dynamic inserter comprises a game client, game server, ad server, a communications channel, and, optionally, an ad client.

A computer-implemented method for dynamic link redirection includes determining current retailer product links in online content, for each current retailer product link among the plurality of current retailer product links, generating a current retailer monetization assessment for the current retailer product link based on current retailer monetization parameters, obtaining a plurality of alternative retailer product links based on the current retailer product link, generating a plurality of alternative retailer monetization assessments for each alternative retailer product link, determining, or receiving from a user, a selected retailer product link among the plurality of alternative retailer product links based on the current retailer monetization assessment and the plurality of alternative retailer monetization assessments, and replacing the current retailer product link in the online content with the selected retailer product link.

Off-policy evaluation of a new target policy is performed using historical data gathered based on a previous logging policy to estimate the performance of the target policy. An estimator may be used, wherein either a quality-based estimator or a quality-agnostic estimator is used to weight the difference between an observed reward in the historical data and an estimated reward generated by the target policy. A quality-agnostic estimator may be used to evaluate an importance weight according to a threshold. In such examples, when the importance weight exceeds the threshold, the quality-agnostic estimator clips the importance weight at the threshold, thereby providing an fixed upper bound irrespective of the quality of the reward predictor. In other examples, a quality-based estimator is used, in which an upper bound incorporates the quality of the reward predictor in order to modify an importance weight used by the estimator.

A system of assessing deployments in a network-based media system is provided herein. The system includes a data storage system storing observation vectors, each observation vector being associated with an outcome indicator, and a processing device in communication with the data storage system to receive and store observation vectors and associated outcome indicators. The processing device performs operations including communicating with an endpoint device of a user to obtain information associated with the endpoint device; and transmitting an instance of a variable user interface to the endpoint device for presentation to the user via the endpoint device based on the stored observation vectors, the stored associated outcome indicators, and the obtained information associated with the endpoint device. Related systems and methods are also disclosed.