The present disclosure provides a campaign configuration method, apparatus, and device, and a storage medium. The method includes: displaying, in response to a select operation on a target campaign template, an element to be configured that corresponds to the target campaign template, where the element to be configured is used to represent campaign information that needs to be configured for a target campaign corresponding to the target campaign template; receiving campaign configuration information entered for the element to be configured; and generating a campaign configuration file corresponding to the target campaign based on the campaign configuration information, where the campaign configuration file is applied to a terminal on which the target campaign is deployed.

Dynamic campaign optimization systems and methods may be used to continuously test many alternative campaign configurations while allowing all configurations, including configurations formerly identified as successful and unsuccessful, to be re-tested in order to identify successful configurations that may previously have been identified as unsuccessful.

A lift reporting system to perform operations that include: accessing user behavior data associated with one or more machine-learned (ML) models, the ML models associated with identifiers; determining causal conversions associated with the ML models based on the user behavior data, the causal conversions comprising values; performing a comparison between the values that represents the causal conversions; determining a ranking of the ML models based on the comparison; and causing display of a graphical user interface (GUI) that includes a display of identifiers associated with ML models.

Selection strategies for a direct marketing campaign that identifies consumers from a credit bureau or other consumer database are refined on a stable subset of the credit database. Once refined, consumer selection criteria may be used to execute the direct marketing campaign on the full consumer/credit database. The data for the test database represents a random sampling of approximately 10% of the full database and the sampling is regenerated approximately weekly in order to provide a stable set of data on which campaign developers test their campaign. For each consumer in the sampling, the environment allows a client to access and use attributes calculated by the credit bureau and proprietary attributes and data owned by the client. The system allows for a plurality of clients to use the system substantially simultaneously while protecting the privacy and integrity of the client's proprietary data and results.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing conversion path performance measures and reports. In one aspect, user interaction data are obtained, were the user interaction data specify user interactions for a plurality of conversions. User interactions that are associated with each conversion are selected from the user interaction data, where the associated user interactions for each conversion are user interactions with a converting user during the conversion cycle for the conversion. Using the user interaction data for the selected user interactions, a quantity of user interactions that are associated with each conversion and occurred during the conversion cycle for the conversion are determined. In turn, conversion path performance measures are computed and reports specifying the conversion path performance measures are generated.

Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium for measuring lift. A method includes: receiving requests for content for which a first content item is an eligible content item; delivering the first content item along with a first pixel that identifies the delivery of the first content item to a first portion of the received requests; delivering a second, different content item along with a second pixel that identifies the non-delivery of the first content item to a second portion of the received plurality of requests rather than the first content item; evaluating searches performed by users that received the first content item as compared to users that received the second content item including using the first pixel and second pixel in evaluating search logs associated with search requests performed by users; and presenting lift data to a sponsor associated with the first content item.

Systems and methods for creating rules for assigning attribution credit across events, includes, identifying, by a processor, conversions at a website. The processor identifies path types associated with the conversions. Each path type identifies events and a index position indicating an event's relative position. The processor identifies a subset of the identified path types to be rewritten according to a path rewriting policy. The processor then rewrites the identified subset of the identified path types as rewritten path types. The processor determines, for each of the rewritten path types and remaining identified path types associated with the identified conversions, attribution credits for each event included in the path type. The processor creates, for each of the rewritten path types and remaining identified path types associated with the identified conversions, a rule for assigning the determined attribution credit to each event of the path type for which the rule is created.

Systems and methods for creating a data-driven attribution model are described. A processor identifies visits to a website. The processor identifies a path for each visitor identifier associated with the visits. The processor determines, for each path type associated with the identified paths, a path-type conversion probability based on a number of visits corresponding to the path type that resulted in a conversion. The processor calculates, for each of a plurality of the path types, a counterfactual gain for each event based on a conversion probability of the given path type and a conversion probability of a path type that does not include the event for which the counterfactual gain is calculated. The processor determines, for each event, an attribution credit based on the calculated counterfactual gain of the event. The processor then stores the attribution credits of each of the events.

Methods and systems for providing for display attribution data associated with one or more events are disclosed. Processor identifies channels from paths including events corresponding to position data identifying a position along the path at which the event was performed. Processor determines attribution credits assigned to each event included in the paths corresponding to the channel. Processor determines a number of attribution credits assigned to the channel. Processor identifies, from the paths, a plurality of event-position pairs. Each event-position pair corresponds to events that correspond to a respective channel and are performed at a respective position of the plurality of paths corresponding to the event-position pair. Processor determines, for each identified event-position pair, a weighting based on an aggregate of the attribution credits assigned to the events to which the event-position pair corresponds. Processor provides, for display, a visual object including an indicator to display the determined weightings.

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.