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 normalized 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; normalizing the predicted interaction outcome metric values; 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 computer-implemented method related to routing incoming interactions of contact centers. The method may include: receiving initial data identifying a first incoming interaction that includes information disclosing at least an intent of the first incoming interaction; and performing a first subprocess to generate a personalized routing profile tailored to facilitate routing the first incoming interaction in accordance with preferences of a first customer. The first subprocess may include: accessing data from a database, the database including at least a first customer profile storing data relating to the first customer; based on the accessed data and the intent of the first incoming interaction, determining preferred agent characteristics data of the first customer for the first incoming interaction; and generating the personalized routing profile so to include the preferred agent characteristics data of the first customer.

The present disclosure includes an intelligent customer service system comprising a customer end, a customer service robot, and a human customer-service end. The customer service robot is configured to: receive a session message from the customer end; identify content of the session message; determine whether it is capable of processing the session message based on the identified content; if so, obtain an answer message matching the identified content from pre-stored service resource and transmit the answer message to the customer end; or otherwise, set its state to a session suspended state, obtain a comforting answer message matching the session message from the pre-stored service resource, send the comforting answer message to the customer end, and transmit to the human customer-service end the session message that the customer service robot is not capable of processing or the content of which the customer service robot cannot identify.

Disclosed herein are system, method, and computer program product embodiments for machine learning systems to process incoming call-center calls based on inferred themes. The machine learning system extracts a topic and keywords associated with the topic from a plurality of interactive communications and ranks the keywords based on a frequency of occurrence within the plurality of interactive communications. The machine learning systems select an N highest ranked keywords from the plurality of interactive communications, compares the N highest ranked keywords to previously extracted N highest ranked keywords to identify new keywords, and determines, based on new keywords, that an emerging topic has been articulated in the plurality of interactive communications.

Techniques are described for generating a custom voice for a virtual agent. In one implementations, a method includes receiving information identifying a customer contacting a call center. The method includes selecting a voice for a virtual agent based on information about the customer. The method also includes assigning the voice to the virtual agent during communications with the customer.

Techniques for case allocation are disclosed. In one particular embodiment, the techniques may be realized as a method for case allocation comprising receiving, by at least one computer processor, at least one case allocation allocated using a first pairing strategy, and then reassigning, by the at least one computer processor, the at least one case allocation using behavioral pairing.

Disclosed are systems and methods for routing inbound communications at call centers in order to enhance customer experience and call center agent efficiency. In order to effectively route communications, customer service call types and one or more agent performance rates responding to said customer service calls are analyzed in order to determine which one or more call center agents should be routed which specific customer service call type. Additionally, tools are disclosed for analyzing call center agent performance rates and assigning call center agents to service specific customer service call types.

Certain aspects of the disclosure are directed to template-based configuration and management of telecommunications services. According to a specific example, a VoIP server is provided comprising one or more computer processor circuits configured to interface with a remotely-situated client entity using a first programming language. The VoIP server includes a provisioning circuit and a call control circuit. The provisioning circuit is configured to identify a provisioning template for at least one extension for a client entity, and configure the extension for one or more call processing functions. The call control circuit is configured identify at least one call control template written in a second programming language. The call control circuit is further configured to control call routing for VoIP telephone calls by executing the call control template, and to implement one or more call processing functions specified by the call control template as being conditional upon retrieved data.

Techniques for reprioritizing waitlisted callers using biometric feedback. A biometric aspect of a calling user is monitored in real time via a sensor. A digital output characterizing an emotional state of the user is generated. The digital output is encoded and transmitted to a server via multi-frequency signaling. The server decodes the digital output and reprioritizes the calling user relative to other calling users in the waitlist, in order to expedite the calling user being serviced.

This disclosure provides systems and methods for matching a customer with a service representative. A request for service can be received from a customer. A first service interaction can be initiated between the customer and a first service representative. A customer sentiment metric can be determined during the first service interaction. The customer sentiment metric can indicate a level of customer satisfaction during the first service interaction. A second service representative suitable for fulfilling the customer's request for service can be identified, based at least in part on the customer sentiment metric. A second service interaction can be initiated between the customer and the second service representative, responsive to the identification of the second service representative.