A non-transitory computer readable medium (26s) stores instructions executable by at least one electronic processor (14s) to perform an automated ticketing method (100) including receiving a support request ticket (40) for assistance with a medical device (2), the support request ticket being entered by a requestor via a ticket entry user interface (UI) (42) of an automated ticket management system; analyzing the support request ticket to identify ticket enhancement information not included in the support request ticket; retrieving the ticket enhancement information from one or more databases (46, 48); adding the ticket enhancement information to the support request ticket to generate an enhanced support request ticket (50); and transmitting one of the support request ticket or the enhanced support request ticket to a ticket recipient electronic processing device (12) operable by a ticket recipient.

A non-transitory computer readable medium (26s) stores instructions executable by at least one electronic processor (14s) to perform an automated ticketing method (100) including receiving a support request ticket (40) for assistance with a medical device (2), the support request ticket being entered by a requestor via a ticket entry user interface (UI) (42) of an automated ticket management system; analyzing the support request ticket to identify ticket enhancement information not included in the support request ticket; retrieving the ticket enhancement information from one or more databases (46, 48); adding the ticket enhancement information to the support request ticket to generate an enhanced support request ticket (50); and transmitting one of the support request ticket or the enhanced support request ticket to a ticket recipient electronic processing device (12) operable by a ticket recipient.

An information processing device includes: a distinction unit that distinguishes a captured person on a basis of feature information of the captured person, on a basis of staff registration information containing feature information of staff members, and on a basis of customer registration information containing feature information of customers, the person captured by a camera; a staff-smile determination unit that determines, if one staff member of the staff members is distinguished as corresponding to the captured person, whether the one staff member corresponding to the captured person has smiled on a basis of a smile index of the captured person; a staff-smile counting unit that counts by which the staff members are determined to have smiled in a preset time period; a customer-revisit detection unit that detects that one customer of the customers has revisited; and a customer-revisit counting unit.

The present disclosure is directed to a system and method for a content display located in the chat messaging system. It facilitates communication between at least a first and a second user and further enables content sending in a more efficient and faster way. This disclosure enables users to work with complimentary and different real-time communication systems and enables the display of interactive elements presenting objects in an application. Such display may be personalized and lead to external sources like a web page or other catalog of data with further explanation necessary to purchase or order. Furthermore, the disclosure improves the storage of content that will be displayed upon a frequency of usage and distribute such storage upon two types of memory that communicate over the network.

An adaptive cloud conversation platform capable of making automated decisions regarding when and how to establish ongoing communications with consumers so as to maximize the relationship between the consumer and a given brand. The system has a connection management services layer which determines what communications should be established and how they should be established, an initiation management services layer which determines when communications should be established, and a user management services layer which stores information about consumers and brands for determination of when and how communications should be established. Certain of these services have machine learning algorithms incorporated into them trained to perform analyses of the particular type of operation handled by that service. The outputs of each service can be used as inputs to other services, such that a network of machine learnings algorithms is created which determines when and how to establish ongoing communications with consumers.

Conventional customer relationship management (CRM) systems provide limited data that are not conducive to the calculation of the qualified portion of a sales pipeline. Accordingly, embodiments calculate a metric of qualified pipeline from this limited data, and can do so across one or a plurality of various dimensions. In addition, embodiments can forecast the metric of qualified pipeline at a future time and/or derive a pipeline plan based on a future booking target.

Conventional customer relationship management (CRM) systems provide limited data that are not conducive to the calculation of the qualified portion of a sales pipeline. Accordingly, embodiments calculate a metric of qualified pipeline from this limited data, and can do so across one or a plurality of various dimensions. In addition, embodiments can forecast the metric of qualified pipeline at a future time and/or derive a pipeline plan based on a future booking target.

An information processing device includes: a distinction unit that distinguishes a captured person on a basis of feature information of the captured person, on a basis of staff registration information containing feature information of staff members, and on a basis of customer registration information containing feature information of customers, the person captured by a camera; a staff-smile determination unit that determines, if one staff member of the staff members is distinguished as corresponding to the captured person, whether the one staff member corresponding to the captured person has smiled on a basis of a smile index of the captured person; a staff-smile counting unit that counts by which the staff members are determined to have smiled in a preset time period; a customer-revisit detection unit that detects that one customer of the customers has revisited; and a customer-revisit counting unit.

A checkout system implemented by one or more computers includes: a product detection unit configured to detect a product to be purchased; a detection unit configured to detect whether the product detected by the product detection unit is a restricted product; a camera configured to capture a face image of a customer in a case in which the restricted product is detected; an age estimation unit configured to perform age estimation processing of the customer based on the face image; and a determination unit configured to determine whether the customer is allowed to purchase the restricted product based on an estimated age. The determination unit determines a threshold of the estimated age for determining whether the restricted product is allowed to be purchased based on an environment of a store that sells the restricted product or a situation of the customer.

As described herein, a system, method, and computer program are provided for smart user alert messaging. In use, raw information associated with usage of a communication service by a customer is identified. Additionally, the raw information is processed, using artificial intelligence, to infer one or more aspects of a status of the customer. Further, one or more alerts is generated for the customer, based on the raw information and the one or more aspects of the status of the customer.