Disclosed herein are embodiments of systems, methods, and products comprises an analytic server for electronic requests routing and distribution. The server receives a plurality of requests from a plurality of electronic user devices. Aiming to routing the plurality of requests to appropriate agents, the server trains an artificial intelligence model for each agent based on historical data. For each request, the server executes the artificial intelligence model to determine a score indicating the probability of the agent converting the request to a successful sale. The server determines an entropy value for each request based on the scores and order the requests into a queue based on the entropy values. The server also calculates a capacity for each agent based on historical agent data. For each request in the queue, the server routes the request to an agent based on at least one of the score and capacity of the agent.

The distribution of incoming queries to a customer interaction center agent group is parallel processed amongst agents of that group to improve queue wait times. A threshold number of queries that may be processed by agent devices associated with the agent group at a given time are defined based on a number of agents of the agent group that are available at the given time. In response to determining that the number of queries is satisfies the threshold number of queries based on the number of agents that are available at a current time, a number of queries awaiting processing are distributed to one or more agent devices of the agent group. The threshold number of queries may be based on half of the number of agents that are available at the given time.

A method, system and program product, the method comprising: obtaining for each call in one set of calls a respective pattern representing multiple different respective data fields; obtaining performance data for the respective patterns of the calls; obtaining performance data for the respective agents; determining agent performance sensitivity to call pattern performance for agents in a set of agents comprising the agent performance data correlated to call performance data for the calls the agent handles; and matching a respective one of the agents from the set of agents to one of the calls based at least in part on the performance data for the respective pattern of the one call and on the agent sensitivity to call performance for the respective one agent of the set of agents.

A computerized-method for measuring an Agent-Engagement-Index (AEI) and associating actions to improve thereof, is provided herein. The computerized-method may operate an AEI module for an assessment of agents. The AEI module includes: (i) retrieving data from applications to derive agent's related-data and exporting the agent's related-data into data-files; (ii) operating a data-ingest module to store the agent's related-data from the data-files; (iii) operating a transform module to transform the agent's related-data by creating relational-entities and calculating metrics; (iv) operating an analytic-engine to process the relational-entities and the calculated metrics for calculating indicators and an AEI based thereon; (v) determining actions to improve the AEI based on the calculated AEI and the indicators; (vi) storing the determined actions in the data-store of agents to improve the AEI and the indicators; and (vii) upon user's request displaying the indicators and the AEI for each agent and the determined actions for each agent.

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 system for performing contact center agent scheduling according to an embodiment includes at least one processor and at least one memory comprising a plurality of instructions stored thereon that, in response to execution by the at least one processor, causes the system to generate a workload forecast indicative of a demand that will be introduced into the contact center in a future planning period based on a workload forecast model and time series data, generate a staffing requirement forecast indicative of a number of agents required to handle the workload forecast based on the workload forecast, one or more service goals, and a staffing requirement model, and perform schedule optimization using column generation to generate an optimized contact center agent shift schedule for a plurality of agents based on the staffing requirement forecast and one or more constraints.

A process is described for a call management system to provide a call transcription supervisory monitoring interactive dashboard of incoming calls at a command center. A plurality of incoming calls are received including a first call reflecting a first incident and a second call reflecting a second incident. Audio from the first and second calls are transcribed. First and second incoming call objects are displayed in a call-by-call portion of the interactive dashboard. The transcripts are cross-referenced with a call-by-call keyword database to identify call-by-call keywords of interest, and the incoming call objects are populated with the call-by-call keywords of interest. An all-call object is displayed in an all-call portion of the interactive dashboard. The transcripts are cross-referenced with an all-call keyword database to identify all-call keywords of interest, and the all-call object is populated with the all-call keywords of interest.

Techniques for workforce management in a contact center system are disclosed. In one particular embodiment, the techniques may be realized as a method for workforce management in a contact center system comprising generating historical workforce data regarding an agent workforce capacity of the contact center system, and initiating an increase or decrease to an agent workforce of the contact center system based at least in part on the historical workforce data to increase an amount of choice among available agents or waiting contacts.

A method and system matching experts or potential experts with an agent request for an expert are disclosed. Exemplary systems include an expert term extraction engine, an agent term extraction engine, and a matching engine to compare agent request terms to the expert terms from the expert term extraction engine and to determine whether there is a match or a potential match between the agent request terms and the extracted expert terms.

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.