A method includes receiving, by a computing device of a media service provider, a search request associated with a first product. The search request is received from a media device associated with a subscriber of a service provided by the media service provider. The method includes, in response to the search request, determining, by the computing device, a responsible party associated with the first product based on a purchase date of the first product and a return period for the first product. The method also includes sending, from the computing device to the media device, contact information of the responsible party. The contact information is to be displayed by the media device to a display device with an option to contact the responsible party.

A method includes receiving, by a computing device of a media service provider, a search request associated with a first product. The search request is received from a media device associated with a subscriber of a service provided by the media service provider. The method includes, in response to the search request, determining, by the computing device, a responsible party associated with the first product based on a purchase date of the first product and a return period for the first product. The method also includes sending, from the computing device to the media device, contact information of the responsible party. The contact information is to be displayed by the media device to a display device with an option to contact the responsible party.

A method for implementing chats that includes: providing a chat feature and chat interface on a webpage; providing two types of the chat resources for generating the text inputs of the chats, an automated chat resource type and a human chat resource type; providing a routing function that selectively routes incoming chats between the two types of the chat resources; providing a first selectable portion on the chat interface that, when selected by a customer, indicates a customer chat preference as to whether the customer prefers to chat with chat resources of the automated chat resource type or human chat resource type; receiving input from the customer device indicating that the customer selected the first selectable portion; determining from the received input the customer chat preference; and routing in accordance with the determined preference.

A data processing server may receive a set of data objects for frequent pattern (FP) analysis. The set of data objects may be analyzed using an attribute diversity technique. For the set of data attributes of the set of data objects, the server may arrange the attributes in one or more dimensions. The server may initialize a set of centroids on data points and identify mean values of nearby data points. Based on an iteration of the mean value calculation, the server may identify a set of attributes corresponding to final mean values as being groups of similarly frequent attributes. These groups of similarly frequent attributes may be analyzed using an FP analysis procedure to identify frequent patterns of data attributes.

A computer-implemented method for automating service provider status and reporting during a service visit includes the initial steps of creating a service provider transaction, initiating the transaction, and calculating an estimated completion time of the transaction. The estimated completion time is based on at least one service condition, which may include the availability of servicing tools and components, the availability of service provider employees, the priority status, if any, of the service provider transaction, and the level of difficulty of service provider transaction, among others. Preferably, the service conditions include constant or variable associated values. The completion time is calculated based upon a sum of these values. If an unexpected service need or service delay arises, the service provider transaction status is updated, which includes recalculating the estimated time of completion based on a new service condition that arose from the unexpected need or delay. When the service provider transaction is complete, the customer reviews the transaction, confirms that the service provider transaction is complete, and schedules a service completion event.

A data server may support segment identification based on a selected user profile. For example, a user may select a user profile as the basis for identifying a segment of additional user profiles. The server may identify attributes associated with the selected user identifier and generate an expression based on the identified subset. The expression may include a normalization function corresponding to at least one attribute. The normalization function may identify correlated attribute values for an attribute associated with the selected user profile. The data server may query a data storage system to identify the additional user profiles based on the expression. The data server may also support user defined Boolean expressions such that the expression is used to identify user identifiers associated with a first attribute and a second attribute.

A computing system facilities live and robo-advising sessions, and transitions therebetween based on detection of triggers. The computing system may extract voice inputs of a user from ambient sounds captured using a sound sensor. Based on an analysis of the voice inputs and detection of corresponding triggers, the computing system may initiate a robo-advising session, or a live communication session between a user computing device and an advisor computing device. Detection of another trigger during the robo-advising session or the live communication session may lead to a transition to a live communication session or a robo-advising session, respectively.

A customer who is contacting customer care via a support session regarding a problem is classified into a customer category of multiple customer categories based at least on customer account information of the customer. A customer care topic in a predetermined set of multiple customer care topics that correspond to the problem is then identified via machine learning. A topic script that corresponds to the customer category of the customer for the customer care topic in the predetermined set of customer care topics is further retrieved or generated, in which the topic script includes one or more topic issues related to the customer care topics. The topic script is provided for presentation to a customer service representative (CSR) to prompt the CSR to discuss the one or more topic issues related to the customer care topic with the customer.

A communication session may be established between a customer device and a customer service representative device. An artificial intelligence assistant may access the communication session and receive an input. The artificial intelligence assistant may process in the input. The artificial intelligence assistant may determine one or more characteristics of the input. The artificial intelligence assistant may determine an output based on the characteristics of the input. The artificial intelligence assistant may communicate the determined output to the customer service representative.

A communication session may be established between a customer device and a customer service representative device. An artificial intelligence assistant may access the communication session and receive an input. The artificial intelligence assistant may process in the input. The artificial intelligence assistant may determine one or more characteristics of the input. The artificial intelligence assistant may determine an output based on the characteristics of the input. The artificial intelligence assistant may communicate the determined output to the customer service representative.