A call handler in a contact center is configured to temporarily derogate the skill level of one or more agents in a group having a common skill. During the time period of derogation, incoming calls will be routed to agents with the highest skill level, such that the normally lower skill level agents will be selected to receive calls. If there are more than one agent meeting this criteria, then the agent that has been waiting the longest to receive a call is selected. This allows the lower skill level agents to gain experience in handling calls and improving their call handling capabilities. After a set threshold, the derogation of the agents is terminated, and their skill level is restored to the pre-derogation level. In this manner the lower skill level agents are given limited opportunities for improvement by handling calls.

Method starts with processing, by a processor, audio signal to generate audio caller utterance. Processor generates an agent action ranking score associated with the audio caller utterance and determines whether the agent action ranking score is below a minimum threshold. In response to determining that the agent action ranking score is below the minimum threshold, processor generates a transcribed caller utterance using a speech-to-text processor and generates an identified task based on the transcribed caller utterance. Using the transcribed caller utterance and a task-specific agent coaching neural network associated with the identified task, processor generates an ideal response. Processor generates a feedback result and causes the feedback result to be displayed on a display device of the agent client device. Other embodiments are disclosed herein.

Systems and methods are provided for attribute-based client callbacks. A client is prompted to leave a voice message. Attributes are extracted from the voice message and, based on the attributes, tokens created for the selection of an appropriate agent is connected to the client, such as having skills or attributes matching one or more tokens. A callback application server transmits prompts and receives requests for client callbacks. an interaction manager determines agent availability and arranges callback handling, and a session management server initiates callbacks to connect the selected agent with the client.

Systems and methods for automatically assessing a quality of service for agents of a customer support system are disclosed. An example method may include retrieving historical conversations between the agents and users of the customer support system, receiving user comments for one or more of the historical conversations, identifying which of the received user comments includes keywords indicative of one or more quality of service attributes, generating transcripts of historical conversations associated with the identified user comments, training a machine learning model based at least in part on the generated transcripts and the user comments of the historical conversations associated with the identified user comments, providing a plurality of current conversations between agents and users of the customer support system to the trained machine learning model, and generating a behavioral score for each of the agents using the trained machine learning model.

A contact center, system, and method of operating a contact center are provided. In one example, the system includes a quantum computing resource and a server. The server is configured to receive a contact from a customer communication device, provide information about the contact to the quantum computing resource, receive a probabilistic output from the quantum computing resource based on the quantum computing resource processing the information about the contact, and make a work assignment decision for the contact based on the probabilistic output.

A device that is configured to assign users to an issue cluster based on issue types for the users. The device is further configured to identify available agents and to assign each available agent to one or more knowledge area clusters based on knowledge scores. A knowledge score indicates an expertise level for an agent in a knowledge area. The device is further configured to identify an issue cluster that is associated with an issue type and to identify a user from the issue cluster. The device is further configured to identify a knowledge area cluster that is associated with the issue type and to identify an agent from the knowledge area cluster. The device is further configured to establish a network connection between a user device associated with the user and a user device associated with the agent.

Predictive mapping technology is used to route a telephone call from a user to a customer service representative. The disclosed technology can use any one or more of the following factors to map a telephone call from a user to a customer service representative: (1) a sentiment score based on a topic of conversation; (2) an experience score of the customer service representative with a topic of conversation; and (3) a performance score of the customer service representative in managing a topic of conversation.

Apparatuses and methods concerning providing a data-communications virtual assistant are disclosed. As an example, one apparatus includes a data-communications server. The data-communications server is configured to process user-data-communications between a client station and another station participating in data-communications via the data-communications services where the client station is associated with one client entity. The server is also configured to identify a context for each respective user-data-communication between the client station and the participating station, where the context data corresponds to at least one communications-specific characteristic associated with the user-data-communications, and to retrieve structured and unstructured data relating to previous data-communications provided by the data-communications server. The server is also configured to provide the integrated contact center to particular end users based on the identified context, and including data generated from the retrieved structured and unstructured data.

Exemplary aspects involve a data-communications apparatus or system communicate over a broadband network with a plurality of remotely-located data-communications circuits respectively associated with a plurality of remotely-situated client entities. The system includes a unified-communications and call center (UC-CC) platform that processes incoming data-communication interactions including different types of digitally-represented communications among which are incoming call, and that is integrated with a memory circuit including a database of information sets. Each of the information sets includes experience data corresponding to past incoming data-communication interactions processed by the platform, and with aggregated and organized data based on data collected in previous incoming interactions. The platform accesses the database and may: use past interactions and other data sources; and facilitate an automated self-service experience for users by resolving inquiries discerned through the incoming interactions; and/or effecting call-decision routing of incoming interactions to call-center agents or specialists.

Method starts with a processor receiving configuration settings including an identified task, a relationship data, and a criticality value. Processor initializes a communication session with an agent client device. The communication session is between a virtual caller associated with the system and the agent client device. Processor then processes an audio signal of the communication session to generate an agent utterance and generates a transcribed agent utterance based on the agent utterance using a speech-to-text processor. Processor generates a virtual caller utterance using a task-specific virtual caller neural network associated with the identified task. The virtual caller utterance can be generated based on the transcribed agent utterance. Processor then causes the virtual caller utterance to be played back in the communication session to the agent client device. Other embodiments are disclosed herein.