Embodiments of the present invention provide systems and methods for determining an engagement level for a customer-agent interaction (e.g., a phone call, text chat, etc.), and the engagement level can be used to evaluate the performance of the agent. For example, the engagement level can be used to determine or adjust a skill level of the agent, a performance of the communication channel that facilitates the interaction, and/or an optimal workload of the agent. According to some embodiments, the engagement level is used to determine that the agent may be experiencing difficulty satisfying a customer inquiry such that the agent should be assigned resources or assistance.

A method for using piecewise forecasts involves obtaining, by a model discovery service, a plurality of models and generating, by a demand prediction service, a plurality of values for a time series variable. The plurality of values corresponding to a plurality of days to be predicted. The method further involves inputting the plurality of values for the time series variable as part of a piecewise forecast to a headcount estimation service and generating, by the headcount estimation service with the piecewise forecast, an estimated headcount from the time series variable.

A method and system matching contact center agents and back office staff with a customer inquiry. Exemplary systems include an expert term extraction engine, a customer term extraction engine, and a matching engine to compare customer request terms to the expert terms from the customer term extraction engine. The comparison determines whether there is a match or potential match between the customer request terms and the stored expert terms. An exemplary system may also include a timer that communicates with one or more communication servers. Back office staff may assist contact center agents when one or more conditions are met, such as when a customer wait time exceeds a predetermined period or when there is no match or potential match between the customer request terms and the stored expert terms for contact center agents.

Call preparation engine for customer relationship management (“CRM”) is presented. Example embodiments of the present invention include invoking an intelligence assistant to retrieve lead details, customer information, and insights for use during a call between a tele-agent and a customer; administering tele-agent call preparation notes for use during the call between the tele-agent and the customer; and displaying, through a call preparation cockpit, the lead details, customer information, insights and tele-agent call preparation notes.

Systems and methods simulate call centers networks and call loads to test load balancing and routing. The simulation can be used for generating, using a load balancer, a call score for the one or more calls based on the call information and selecting, using the load balancer, one of the simulated call centers as a selected call center based on the call score and the respective response entity profile.

A data processing system for artificial intelligence-based setting of controls in an evaluation interface comprising a data store storing: a plurality of transactions; a plurality of completed evaluations, each completed evaluation including an indication of a transcript portion associated with an evaluation answer. The system determines a word or phrase common to a first set of transcript portions associated with the evaluation answer; creates a first set of auto answer parameters that includes the word or phrase; auto answers the question for a set of test transactions to generate an auto answer for each test transaction; and based on a determination that the first set of auto answer parameters auto answered the question with a threshold level of accuracy, configures an evaluation system to use the first set of auto answer parameters to preset an answer control in an evaluation operator interface.

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.

Systems and methods forecast inbound telecommunications, and more particularly, analyze real-time and historical call center data, and apply a forecasting model to the data in order to predict inbound call volume. These systems and methods employ tools that manipulate call center data and generate visual representations of metrics pertaining to forecasting call center data via a dashboard.

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.

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.