Apparatus and methods consistent with the present disclosure route electronic communications to an appropriate resource that can efficiently and effectively provide responses to inquires included in or that are associated with a particular electronic communication. Methods and apparatus consistent with the present disclosure may be optimized for various different types of communication mediums with different sets of capabilities, requirements, or constraints by evaluating data that may be associated with historical information or with a stream of information.

Embodiments of the present disclosure provide methods, apparatus, systems, computing devices, and/or computing entities for processing performance metric recommendations for an agent profile. In accordance with one embodiment, a method is provided that includes: generating an agent feature data object for the agent profile from communication data objects representing communications; processing the agent feature data object using an agent group identifier machine learning model to generate an agent group data object; identifying a top agent performer data object based at least in part on the agent group data object; generating an agent assessment data object representing performance of an agent represented by the agent profile; processing the agent assessment data object and the top agent performer data object using a comparison machine learning model to generate inferred performance gap data objects; and generating the performance metric recommendations based at least in part on the inferred performance gap data objects.

Apparatuses and methods concerning providing a data-communications contact center virtual agent are disclosed. As an example, user-data-communications between client and participant stations are facilitated as follows, which may be implemented using a data communications server and associated communications circuitry. Service request data is received from users at a participant stations, and context information is identified for user-data-communications between a client station and the participant stations based on the service request data at least one communications-specific characteristic associated with the user-data-communications. The identified context information is aggregated for the client station and used for choosing a data routing option routing data with each user at the participant stations, based on the service request data and the aggregated context information.

A dialogue device of a dialogue system relating to provision of a response to an inquiry from a user terminal includes an input unit that acquires the inquiry from the user terminal, a transmission unit that connects the user terminal and an operator terminal responding to the inquiry in accordance with the inquiry, an output unit that outputs questions for ascertaining details of the inquiry to the user terminal before connection made by the transmission unit, and a determination unit that determines a mode of the questions made by the output unit in accordance with an operating status of the operator terminal that can respond to the inquiry.

Methods for optimizing the routing of customer communications include receiving a customer communication; identifying a customer associated with the customer communication; accessing a profile of the identified customer to determine customer data; receiving customer metric scores for a plurality of customer metrics; identifying available agents; accessing a profile of each available agent to determine agent data; predicting interaction outcome metric values for a plurality of customer metrics based on the customer data and the agent data; calculating, in real-time, an aggregate agent-customer pairing score for each available agent; selecting a responding agent from the available agents with the highest aggregate agent-customer pairing score; and providing a routing recommendation to a communication distributor to route the customer communication to the responding agent with the highest aggregate agent-customer pairing score.

A method and system for authenticating customers on call are disclosed. The method includes providing a notification to a customer on an electronic device associated with the customer. The notification is provided in response to the customer placing a call for seeking an interaction with an agent of an enterprise. The notification is configured to trigger authentication of the customer using an application on the electronic device. A status of the authentication of the customer is received from the application on the electronic device and, if the status of the authentication of the customer is a success, the call is connected to the agent to facilitate the interaction between the customer and the agent.

Embodiments of the present disclosure include computer-implemented systems and methods for routing incoming customer requests or inquiries in a customer service center. The system may include at least one processor configured to execute instructions to perform steps. The steps may include receiving a plurality of incoming customer calls and a plurality of incoming customer chat sessions. The steps may include blending the received plurality of customer calls and the received plurality of customer chat sessions into a total queue for presentation to at least one user device. The steps may additionally include determining a respective priority for each of the blended plurality of customer calls and the blended plurality of customer chat sessions and sending, based on the determined priority, to the at least one user device at least one of the blended plurality of customer calls or the blended plurality of customer chat sessions.

A method for resolving customer requests that includes: providing a personal bot assistant and an asynchronous resolution facilitator; receiving a customer request from a first customer and producing a transcript thereof; determining an intent based on the transcript and customer information relating to the determined intent; transmitting an initial set of data to the asynchronous resolution facilitator and assembling therefrom a resolution package that includes an agent interface showing information required to expeditiously resolve the customer request including one or more recommended business processes; displaying the agent interface on a screen of the agent device; receiving input from the agent device that indicates the agent has completed preparing a resolution for the customer request; and providing notification to the first customer of the achieved resolution via the personal device of the first customer.

Techniques for benchmarking performance in a contact center system are disclosed. In one particular embodiment, the techniques may be realized as a method for benchmarking contact center system performance comprising cycling, by at least one computer processor configured to perform contact center operations, between a first contact-agent pairing strategy and a second contact-agent pairing strategy for pairing contacts with agents in the contact center system; determining an agent-utilization bias in the first contact-agent pairing strategy comprising a difference between a first agent utilization of the first contact-agent pairing strategy and a balanced agent utilization; and determining a relative performance of the second contact-agent pairing strategy compared to the first contact-agent pairing strategy based on the agent-utilization bias in the first contact-agent pairing strategy.

The present invention is a system and method of routing incoming communications to a CSR and providing guidance to the CSR based on the incoming communication using feedback information such as sentiment feedback, survey feedback, and feedback from actions taken by CSRs based on skill level. A CEC system receives an incoming communication, analyzes the communication and creates metadata based off of the analysis. The metadata is used by the RAE routing module to route the communication to an appropriate party. The metadata is also used by the GAE guidance module to determine the guidance to provide to the CSR. The CSR then performs an action based on the guidance. The CEC system continues to monitor the interaction until the interaction is completed. The communication metadata, the communication, the guidance, and the CSRs action are all provided to a RAS rules analysis module wherein the RAS analyzes the data and automatedly updates the rules (RAR and GAR) according to the analysis.