A method, an electronic device and computer readable medium for A/B testing are provided. The method includes obtaining user interface (UI) variants and parameters for A/B testing. In response to obtaining the UI variants and the parameters, the method includes generating a score relating the UI variants and the parameters to extracted A/B testing data from previously performed A/B tests. The method also includes identifying a previous A/B test from the previously performed A/B tests that is similar to the UI variants and the parameters based on the score. The method further includes generating a result indicating whether one of the UI variants would win an A/B test without performing the A/B testing based on a comparison of one or more thresholds to similarities between the extracted A/B testing data of the previous A/B test and the UI variants and the parameters.

A system and method for multi-channel dynamic advertisement testing. The system comprises a multi-platform adaptive ad campaign manager, a dynamic advertisement engine, a campaign database, and an omnichannel text-based communicator. The system receives customer interactions with two advertisement test variants, establishes a real-time media stream between a customer device and a second user device, and monitors the media stream to collect data related to effectiveness of the advertisement variants. The system may analyze media stream data together with a plurality of other data types to statistically determine which of the two advertisement variants resulted in better performance based on a variety of advertisement metrics. The system may use the plurality of data and the statistical analysis to suggest an advertisement element to be altered in the next round of advertisement variant testing. This system can combine data collection and analytics for an ad campaign together into one system.

The present disclosure describes techniques of implementing a collaborative advertising mechanism. The techniques comprise receiving a plurality of pieces of content associated with a mission event from a first plurality of client computing devices associated with a first plurality of users, evaluating the plurality of pieces of content based on one or more predetermined rules of the mission event and information indicative of viewer reactions to the plurality of pieces of content, determining at least one subset of the plurality of pieces of content based on a plurality of evaluation results corresponding to the plurality of pieces of content and user input from a client computing device associated with one of a second plurality of users, and distributing the at least one subset of the plurality of pieces of content.

Embodiments of the present disclosure provide methods, systems, apparatuses, and computer program products that provide for an improved and more efficient system for transmitting content to client devices. The embodiments disclose an apparatus that clusters user behavior based on platform session records. The platform session records comprise stored data associated with a plurality of user inputs received by the system for the duration of a platform session. The apparatus and methods transform the platform session records into data comprising a form that is usable for identifying clusters of platform sessions. As a result of the clustering methodologies, the apparatus is configured to deliver content specifically optimized for users of client devices. The present disclosure thus provides for an improved networked system that reduces the amount of data transferred via the network and allows for a more efficient system that has reduced infrastructure requirements and improved performance.

The present invention relates to a platform (100) and method for advertisement campaigns. The platform (100) includes computing devices (102) and a processing engine (106). The processing engine (106) includes a memory (108), a processor (110), a database (112), an input module (114), an authentication module (116), a presentation module (118), a service module (120), a logic creation module (122), and a data access module (124). The database (112) stores information related to pre-defined logic rules for services, pre-determined procedures, and pre-determined parameters of services. The input module (114) receives inputs from a computing device (102). The authentication module (116) registers the user, and authenticate the user using an authentication mechanism. The presentation module (118) receives a request from the computing device (102). The service module (120) extracts services from data sources, and selects a service from the extracted services. A logic creation module (122) creates a logic. A data access module (124) provides an access of the service having the generated logic, and transmits the accessed service to the computing device (102).

This paper presents a practical method for measuring the impact of multiple marketing events on sales, including marketing events that are not traditionally trackable. The technique infers which of several competing media events are likely to have caused a given conversion. The method is tested using hold-out sets, and also a live media experiment for determining whether the method can accurately predict television-generated web conversions.

For each service scenario out of a plurality of service scenarios, matching features of a to-be-matched product corresponding to the service scenario are acquired based on user features of users accessing the service scenario. A respective user feature mapping value of the service scenario is calculated based on the matching features of the to-be-matched product corresponding to the service scenario. Out of the plurality of service scenarios, a target service scenario of the to-be-matched product is selected based on the respective user feature mapping value of the service scenario.

An information processing apparatus includes: an output section that outputs display information for displaying discrimination information in association with a broadcast spot in a program guide, the discrimination information discriminating the broadcast spot for broadcasting a commercial associated with an advertisement campaign of a client among a plurality of program spots included in the program guide; and a comparison section that compares a first predicted rating point and a second predicted rating point, the first predicted rating point being predicted by a first prediction algorithm for each program spot of the plurality of program spots included in the program guide, and the second predicted rating point being predicted by a second prediction algorithm whose prediction accuracy is higher than prediction accuracy of the first prediction algorithm, and the output section outputs the display information to display a first program spot in a display format different from display formats of other program spots.

Generating a transformed dataset for use by a machine learning model in an artificial intelligence infrastructure that includes one or more storage systems and one or more graphical processing unit (‘GPU’) servers, including: storing, within one or more storage systems, a transformed dataset generated by applying one or more transformations to a dataset that are identified based on one or more expected input formats of data received as input data by one or more machine learning models to be executed on one or more servers; and transmitting, from the one or more storage systems to the one or more servers without reapplying the one or more transformations on the dataset, the transformed dataset including data in the one or more expected formats of data to be received as input data by the one or more machine learning models.

A method, product and system are provided for determining estimated quality scores in digital content distribution systems. The method comprises, based on monitoring of engagements and conversions, determining a segment-specific estimated quality score of a given traffic; determining an observation-based pair-specific quality score for the given traffic and for a specific campaign; and determining, based on the segment-specific estimated quality score and based on the observation-based pair-specific quality score, a pair-specific estimated quality score of the specific campaign for the given traffic segment indicating an estimated quality score of the specific campaign when presented in the given traffic segment.