A method of assisting an agent in real-time includes receiving a call interaction between a customer and an agent; identifying words spoken in the call interaction; providing the words to a behavioral models module; computing a score for a plurality of behavioral metrics; providing a phrase formed by the words to a knowledge article selection module; providing each score for the plurality of behavioral metrics to the knowledge article selection module; providing a plurality of knowledge selection rules to the knowledge article selection module; evaluating a combination of the phrase and the scores of the plurality of behavioral metrics against each of the plurality of knowledge selection rules; matching a knowledge selection rule to the combination; selecting a knowledge article associated with the matched knowledge selection rule; generating a visual representation of the selected knowledge article; and presenting in real-time the visual representation on a graphical user interface.

A method for providing anonymized contact information to a workforce management system includes receiving contact information from a plurality of customer business units; assigning each of the plurality of customer business units one or more industry classification codes or product classification codes; anonymizing, by a processor, the contact information to the one or more industry classification codes or product classification codes; receiving, by a processor, a query from a workforce management system for anonymized contact information in one or more industry classification codes or product classification codes; and providing the anonymized contact information to the workforce management system for use in a workforce management predictive model.

A pairing module comprising a memory storing contact center information that i) identifies a first set of available agents that are available to be paired with a contact and ii) identifies a first set of available contacts that are waiting to be paired with an available agent. The pairing module further comprises a contact/agent (C/A) pair selector that functions occasionally read the memory to obtain contact center information and then use the obtained contact center information to pair available agents with available contacts.

Computer-implemented methods disclosed herein can intelligently determining a stress level of an agent at a contact center. Such computer-implemented methods can include identifying one or more escalation factors that are indicative of an escalation of stress. The computer-implemented method can include aggregating the one or more escalation factors that have been identified into a total stress level. The computer-implemented method can include presenting one or more stress reduction suggestions for reducing the total stress level.

Disclosed are systems and methods for forecasting inbound telecommunications, and more particularly, for analyzing real-time and historical call center data, and applying a forecasting model to said data in order to predict inbound call volume. Additionally, tools are disclosed for manipulating call center data and generating visual representations of metrics pertaining to forecasting call center data via a dashboard.

A computerized-method for operating an Omni Session Handling (OSH) engine for proactive OSH to determine that an outreach is required, according to one or more predefined requirements, to maximize capacity of an agent in a contact center by omni session handling, is provided herein. The computerized-method may retrieve one or more interactions from a Customer-Relations-Management database based on a requirement for an outreach to be stored in a queue of proactive contacts. The computer-implemented method may further allocate a queue of one or more interactions to an agent or to a team of agents and then present the agent with a digital preview of an interaction from the queue of one or more interactions for consideration via a display unit, while the agent is handling one or more interactions. The computer-implemented method may further receive from the agent a decision upon review of the presented digital preview of the interaction.

Techniques for behavioral pairing in a contact center system are disclosed. In one particular embodiment, the techniques may be realized as a method for behavioral pairing in a contact center system comprising: determining, by at least one computer processor communicatively coupled to and configured to operate in the contact center system, a plurality of contacts available for connection to an agent; determining, by the at least one computer processor, a plurality of preferred contact-agent pairings among possible pairings between the agent and the plurality of contacts; selecting, by the at least one computer processor, one of the plurality of preferred contact-agent pairings according to a probabilistic network flow model; and outputting, by the at least one computer processor, the selected one of the plurality of preferred contact-agent pairings for connection in the contact center system.

Technologies for scaling call center support staff include one or more local agent computing devices of a call center that includes an interaction management computing device communicatively coupled to one or more customer computing devices and one or more remote agent computing devices. The interaction management computing device is configured to receive inbound service calls and insert them into a respective service queue. The interaction management computing device is additionally configured to determine whether a service queue response threshold associated with the service queue has been violated as a function of each service call having been inserted into the service queue, identify, in response to a determination that the service queue response threshold associated with the service queue has been violated, one or more remote agents from a queue of available remote agents, and add the identified one or more remote agents to an agent pool associated with the service queue. Additional embodiments are described herein.

A method for leveraging automated process discovery in a contact center system according to an embodiment includes determining, by a computing system and for each of a plurality of agent-client interactions, an context of an interaction between a corresponding contact center agent and a corresponding contact center client, capturing, by the computing system and for each of the plurality of agent-client interactions, actions taken by the corresponding contact center agent during the corresponding interaction, determining, by the computing system and for each of the plurality of agent-client interactions, a corresponding sequence of actions taken by the corresponding contact center agent based on the captured actions, and applying, by the computing system, sequence matching to generate a common sequence of actions based on the determined corresponding sequence of actions taken for the plurality of agent-client interactions.

A redundant Session Initiation Protocol (SIP) call center system has two data centers each having a first and a second SIP server cooperating as a first SIP-server high availability (HA) pair, a set of SW applications executable at each data center, and a plurality of agent stations each comprising a SIP telephone and a computerized appliance executing a desktop application at each agent station. The HA pairs operate as SIP server peers, the agent SIP phones are configured to maintain simultaneous registration with both SIP server peers, and Agent Desktop applications log in to only one SIP server peer, wherein the SIP Server peers collaborate to deliver calls to individual agent SIP phones via the SIP server peer where the agent is logged in, and wherein, upon failure of either data center agent's desktop applications log in to the other data center, allowing the associated agent to continue working.