A method and system for entertainment and information services delivered via mobile telecommunication devices include a communication network, and a station communicatively linked to the communication network. The station includes an output and an interface. Also included is a head-end having at least one database configured to store programs including an audio content. The head-end receives a request from the station for a desired one of the programs, verifies the request, transmits a first portion of the desired program to the station, and records an association between the identification and the desired program. The head-end further suspends transmission of a second portion of the program based upon detection of an indication to suspend transmission. The head-end further transmits the second portion of the program based upon detection of an indication to resume transmission and stored bookmark data indicating the starting location in the program of the second portion.

A system and method for managing media advertising enterprise data including a process for learning enterprise data matching. An EDM (Enterprise Data Management) application module can be configured to include a set of rules at an enterprise level to manage disparate and disconnected records associated with an entity. A number of unmatched and enterprise entities that matches with respect to an active entity can be returned based on a fuzzy logic associated with various matching options stored in an EDM database. A matching process can then be performed to accurately match similar records regardless of manual input, location, and format of the records in a distributed system. Each unmatched record can then be assigned with a parent enterprise entity. Such an optimization mechanism can interactively manage and report records at the enterprise level in a simple and efficient manner.

The present disclosure includes a system, method, and article of manufacture for spend based targeting and measurement. The method may comprise transmitting to a third party system a model and/or a measurement file associating a first party cookie ID with a model, and receiving, from the third party system, an updated model (and/or measurement) file associating a third party cookie ID with web-browsing data. The third party cookie ID may anonymously and uniquely correspond to the first party cookie ID, and the first party cookie ID may be stripped from the updated model (and/or measurement) file to de-identify a customer associated with the first party cookie ID. Moreover, the web-browsing data may be received by the third party system from a second party system.

Methods and apparatus to determine efficiencies of media delivery across platforms are disclosed. An example method includes measuring, with a sensor, first neuro-response data from a person when exposed to media output via a first media delivery platform type. Measuring second neuro-response data from the person when exposed to media output via a second media delivery platform type, different than the first media delivery platform type. Accessing a first and second performance metric for the respective media delivery platform type, the performance metrics based on a first and second reach of the respective media delivery platform types with respect to a target group of audience members. Accessing a first and second effectiveness metric for the respective media delivery platform types, the effectiveness metric based on the respective neuro-response data. Rating at least one of the first or second media delivery platform types based on the first and the second platform metrics.

Methods and systems are provided herein for the analysis of information about online actions of a plurality of users. The analysis methods and systems allow for the creation of new online and offline business methods based on online consumer behavior. The methods and systems may obtain an input data set comprising information about online actions of a plurality of users, convert the input data set into data files having a common file format with each data file corresponding to a user of the plurality of users and comprising an identifier for the user and a plurality of Uniform Resource Locations (URLs) associated with online actions of the user, access online information relating to search terms and webpages, and determine one or more metrics of user behavior, including a verticals metric and a search terms metric.

An online system receives user data for users of the online system and assigns the users to one or more user cohorts based on the user data. The online system generates a prompt for content to be included in a landing page presented to each user cohort, in which the prompt includes a template for the landing page and information describing the user cohorts. The online system then provides the prompt to a generative artificial intelligence model to obtain an output and extracts, from the output, a set of content to be included in the landing page for each user cohort. The online system generates variants of the landing page for each user cohort based on the extracted set of content.

Methods, systems, and computer programs are presented for eliminating bias while training an ML model using training data that includes past experimental data. One method includes accessing experiment results, for A/B testing of a first model, that comprise information regarding engagement with a first set of items presented to users, each item being presented within an ordered list of results. A position bias is calculated for positions within the ordered list of results where the items were presented. A machine-learning program is trained to obtain a second model using a training set comprising values for features that include the calculated position bias. The method includes detecting a second set of items to be ranked for presentation to a first user, and calculates, using the second model, a relevance score for the second set of items, which are ranked based on the respective relevance score and presented on a display.

A method of delivering advertising in an online environment includes determining a context of a user operating a client computer to interact with an e-commerce website, where the determined context representing an intent of the user to locate a product for purchase, defining a relation between one or more of a plurality of advertisements and the product based on at least one of a plurality of relevance types, and displaying, to the user, at least one of the advertisements having the relation to the product.

A computing services environment may include a database system, a generative language model interface, a communication interface, and a messaging interface. The database system may store database records reflecting interactions between tenants of the computer services environment and individuals interacting with the tenants, and may determine an input description of a communication campaign between a tenant of the plurality of tenants and a corresponding segment of the individuals. The generative language model interface may determine a textual description of one or more elements of the communication campaign by completing a campaign brief generation prompt via a generative language model. The communication interface may transmit to a client machine authenticated to a database system account linked to the tenant an instruction to generate a graphical user interface at the client machine. The messaging interface may transmit messages based on the input description and the refinement.

Systems and methods for conducting a test on a third-party testing platform are provided. A networked system causes presentation of a setup user interface to a third-party user, whereby the setup user interface includes a field for indicating an attribute of a publication to be tested. The networked system receives, via the setup user interface, an indication of the attribute, a subject to be tested, and one or more test parameters. The networked system applies the attribute change to a first version of the publication to generate a second version of the publication. The first version is presented to a first subset of potential users and the second version is presented to a second subset of potential users. Interactions with both the first version and the second version are monitored and analyzed to determine results of the test. The results are then presented to the third-party user.