Techniques are disclosed for determining application experience of a user. One embodiment presented herein includes a computer-implemented method, which includes receiving, at a computing device, eye tracking data of a user interacting with at least a first page of an application. The computer-implemented method further includes determining, based at least on the eye tracking data, at least a current user experience regarding the first page. The computer-implemented method further includes predicting, based on evaluating the current user experience, that the user is likely to discontinue use of the application. The computer-implemented method further includes determining, based at least on the prediction, an intervention that reduces a likelihood of the user discontinuing use of the application, and interacting with the user according to the intervention.

Methods, apparatus, systems, and articles of manufacture to perform computer-based monitoring of audiences of network-based media using information theory to estimate intermediate level unions are disclosed. An example apparatus to determine a deduplicated, census-based audience metric of media includes panel union calculator circuitry to calculate a threshold statistic corresponding to an intermediate union of a panel hierarchy, and census union calculator circuitry to calculate a deduplicated audience value corresponding to the intermediate union of the census hierarchy based on the threshold statistic.

Techniques are disclosed for determining application experience of a user. One embodiment presented herein includes a computer-implemented method, which includes receiving, at a computing device, eye tracking data of a user interacting with at least a first page of an application. The computer-implemented method further includes determining, based at least on the eye tracking data, at least a current user experience regarding the first page. The computer-implemented method further includes predicting, based on evaluating the current user experience, that the user is likely to discontinue use of the application. The computer-implemented method further includes determining, based at least on the prediction, an intervention that reduces a likelihood of the user discontinuing use of the application, and interacting with the user according to the intervention.

Embodiments disclosed herein address these and other concerns by providing for means by which a customer's level of engagement with media can be determined. In particular, media and questions regarding the content of the media may be sent to a ticketing device and provided to the customer. The ticketing device can further obtain the customer's answers to the questions, and send the answers to a server, which can determine a level of engagement can be assessed from the answers and issue a discounted ticket. The amount of the discount may be proportional to the level of engagement.

Distributed muster includes distributing to different mobile devices an identity of an assigned muster location of an ocean-going vessel, and associating each mobile device both with a corresponding passenger of the ocean-going vessel, and also with the assigned muster location. Thereafter, a timer initiates that defines a period during which a muster drill must be completed by all of the passengers and, in response, a message is transmitted to each mobile device that the muster drill has commenced. During the period, as each mobile device is sensed within a geographically defined area of a correspondingly assigned muster location, a record of the completion of the muster drill by the passenger associated with the sensed mobile device is recorded in the memory. As well, subsequent to a lapsing of the timer, a listing is displayed of any passenger not recorded as having completed the muster drill.

A loyalty gamification server platform with a plurality of micro-services are provided. Custom-defined rules permit gamification elements to be integrated as enhancements into loyalty applications though interaction with the micro-services using a platform Application Programming Interface (API). Artifacts associated with rewards and status level of rewards are earned based on activities associated with transactions of a user in accordance with the rules. Social standing artifacts are also earned based on the same or different activities. In an embodiment, users form a community and a dashboard microservice permits each user's ranking relative to games, competitions, status, and social standing to be viewed relative to other users of the community as a dashboard presentation on a display of a transaction terminal or a user device.

Embodiments of the present disclosure provide mechanisms for selection of a user survey data object from a set of user data objects, and processing of survey engagement data associated with a selected user survey data object. The user survey data object selected is appropriate for providing associated with a particular user data object, and the survey engagement data received associated therewith enables programmatic selection and use of particular ranking model(s) for use in generating and providing an output ranked item data object set. Example embodiments utilize selected ranking model(s) of a set of ranking models to programmatically generate and output an output ranked item data object set for a particular user profile.

A system to provide an interactive advertisement to a user includes an advertisement server, a user device, and an advertisement application software installed on the user device. The advertisement server includes a database which stores a plurality of questions concerning an advertiser or the advertiser's goods, each question having an answer hint. The advertisement server includes a question selection module, an advertisement assessment module, and a user selection module. The advertisement application software is configured to: receive a commercial of the advertiser; receive a combination of questions from the advertisement server, and display the combination of questions; and receive answers from the user, and send the answers to the advertisement server. The user is allowed to change the answers, and a reward is given to the user if the number of correct answers exceeds a predetermined number.

The present disclosure provides an intelligent pairing system for online review tasks which includes a server. The server includes at least a task pairing module and an AI-driven review evaluation module. The task pairing module includes a plurality of task sub-modules, and each task sub-module stores a plurality of online review task items. Each online review task items includes standards and a bonus value. The AI-driven review evaluation module is configured to evaluate whether a submitted review for webpage content meets the standards. If the submitted review meets the standards, the bonus value is awarded to an online bonus account of a task executor.

Methods, apparatus, systems, and articles of manufacture to perform computer-based monitoring of audiences of network-based media using information theory to estimate intermediate level unions are disclosed. An example apparatus to determine a deduplicated, census-based audience metric of media includes panel union calculator circuitry to calculate a threshold statistic corresponding to an intermediate union of a panel hierarchy, and census union calculator circuitry to calculate a deduplicated audience value corresponding to the intermediate union of the census hierarchy based on the threshold statistic.