Abstract: Agents are grouped into skill groups based on the skills of each agent. Simulation are performed for a contact center with multiple queues, where agents from the skill groups are assigned to the queues based on the skills of the skill groups and the skills of the queues. After running the simulations, for each skill group and for each interval, the time each agent spent working using each associated skill is determined, and an average time for each skill is calculated for each interval. The average times are used to create a skill group weight for the skill group for each interval. Later, when the schedule engine is determining an agent placement for one or more intervals, the skill group weights for the intervals are used to calculate a score for the queues based on different agent placements. The placement with the best score (e.g., lowest) is implemented.

Abstract: Agents are grouped into skill groups based on the skills of each agent. Simulation are performed for a contact center with multiple queues, where agents from the skill groups are assigned to the queues based on the skills of the skill groups and the skills of the queues. After running the simulations, for each skill group and for each interval, the time each agent spent working using each associated skill is determined, and an average time for each skill is calculated for each interval. The average times are used to create a skill group weight for the skill group for each interval. Later, when the schedule engine is determining an agent placement for one or more intervals, the skill group weights for the intervals are used to calculate a score for the queues based on different agent placements. The placement with the best score (e.g., lowest) is implemented.

Abstract: Agents are grouped into skill groups based on the skills of each agent. Simulation are performed for a contact center with multiple queues, where agents from the skill groups are assigned to the queues based on the skills of the skill groups and the skills of the queues. After running the simulations, for each skill group and for each interval, the time each agent spent working using each associated skill is determined, and an average time for each skill is calculated for each interval. The average times are used to create a skill group weight for the skill group for each interval. Later, when the schedule engine is determining an agent placement for one or more intervals, the skill group weights for the intervals are used to calculate a score for the queues based on different agent placements. The placement with the best score (e.g., lowest) is implemented.

Abstract: Agents are grouped into skill groups based on the skills of each agent. Simulation are performed for a contact center with multiple queues, where agents from the skill groups are assigned to the queues based on the skills of the skill groups and the skills of the queues. After running the simulations, for each skill group and for each interval, the time each agent spent working using each associated skill is determined, and an average time for each skill is calculated for each interval. The average times are used to create a skill group weight for the skill group for each interval. Later, when the schedule engine is determining an agent placement for one or more intervals, the skill group weights for the intervals are used to calculate a score for the queues based on different agent placements. The placement with the best score (e.g., lowest) is implemented.

Abstract: An evaluation criterion for a call performed between an operator and a customer is set without taking time and effort. A voice recognition system includes a call recording unit that records a call performed between a customer and an operator, a voice recognition unit that recognizes the call recorded by the call recording unit and a value of non-verbal information indicating a feature of a calling party in the call and accumulates a recognized result in a storage unit, and a voice recognition result managing unit that sets a reference value for evaluating the calling party on the basis of the value of the non-verbal information included in the recognized result.

Abstract: Techniques for decisioning behavioral pairing in a task assignment system are disclosed. In one particular embodiment, the techniques may be realized as a method for decisioning behavioral pairing in a task assignment system comprising: determining, by at least one computer processor communicatively coupled to and configured to operate in the task assignment system, a plurality of possible task-agent pairings among at least one task waiting for assignment and at least one agent available for assignment; and selecting, by the least one computer processor for assignment in the task assignment system, a first task-agent pairing of the plurality of possible task-agent pairings based at least in part on a first offer set to be offered by the agent or a first compensation to be received by the agent.

Abstract: A call management system of a call center retrieves from a customer database enterprise customer data associated with an identified customer in a customer call, which may include customer event data, attributions data, and activity event data. The customer database tracks prospects, leads, new business, and purchasers of an enterprise. The system retrieves customer demographic data associated with the identified customer. A predictive model is selected from a plurality of predictive models based on retrieved enterprise customer data. The selected predictive model, including a logistic regression model and tree based model, determines a value prediction signal for the identified customer, then classifies the identified customer into a first value group or a second value group. The system routes a customer call classified in the first value group to a first call queue assignment, and routes a customer call classified in the second value group to a second call queue assignment.

Abstract: A computer-implemented method for proactive fraudster exposure in a customer service center according to content analysis and voice biometrics analysis, is provided herein. The computer-implemented method includes: (i) collecting call interaction; (ii) storing the collected call interactions; (iii) performing a first type analysis to cluster the call interactions into ranked clusters and storing the ranked clusters in a clusters database; (iv) performing a second type analysis on a predefined amount of the highest ranked clusters, into ranked clusters and storing the ranked clusters; the first type analysis is a content analysis and the second type analysis is a voice biometrics analysis, or vice versa, (v) enabling a user to repeat steps (iii) and (iv); (vi) retrieving from the ranked clusters, a list of fraudsters; and transmitting the list of potential fraudsters to an application to display to a user said list of potential fraudsters via a display unit.

Abstract: Systems and methods for a work distribution service. At a multi-tenant platform that provides a work distribution service for a plurality of external systems, a priority is assigned to a first work item of a first external system. The work item is received via a RESTful work item API call request. The priority is assigned based on work item attributes of the work item and a workflow instruction corresponding to workflow information specified by the work item. The workflow instruction is provided by the external system via a RESTful Workflow API. A worker is assigned to the work item based on: the priority of the work item, the workflow information, and worker state managed by the first external system via a RESTful Worker API. The worker state includes worker attributes. The work item is generated by the external system, and the workflow instruction is managed by the external system.

Abstract: A device receives, from a user device, a communication associated with a support issue encountered by a user of the user device and assigns the communication to a position in a support queue based on when the communication is received, wherein the support queue includes data identifying positions of other communications received from other users, and data identifying when the other communications were received. The device processes data identifying the communication and historical communication data describing prior communications associated with the user, with a model, to determine an average time spent on hold by the user for the prior communications. The device modifies the position of the communication in the support queue based on the average time and performs one or more actions based on modifying the position of the communication in the support queue.

Abstract: Disclosed embodiments may relate to systems and methods for monitoring and/or mapping noise data from a plurality of noise monitoring devices. In some embodiments, the plurality of noise monitoring devices may include hearing protection devices configured to detect noise, and typically may communicate such noise data (which may also include location) so that the noise data can be pooled. The pooled noise data from the plurality of noise monitoring devices may then be used to the benefit of one or more of such noise monitoring devices.

Abstract: A redirection and messaging system receives telephony information identifying a caller and call context from a telephony system. The system selects one of a plurality of messaging operators based on the call context, optionally sends an introductory message to the caller via a messaging service, and generates a message interface for the selected message operator. The message interface includes the caller and call context and any messages sent between the caller and the selected message operator, with an input interface allowing the selected message operator to input and send messages to the caller.

Abstract: A system is provided that employs a multi-dimensional presence model to manage routing of interaction requests from customers to available agents over available omni-channels in contact center(s). The multi-dimensional presence model employs multiple model states that define availability and capacity for a given agent or class of agents, including, but not limited to, an availability state of the agent, as well as occupancy, activity, device, and channel states to which a routing engine in the contact center can effectively route requested interactions of a customer with an agent. A capacity manager is also disclosed that can be used to facilitate the configuring of the multi-dimensional presence model for a given agent or class of agents.

Abstract: A system for scheduling and initiating a conference call including an application server including: an interface and a parser operably coupled to the interface to extract information from received information. The system may further include a communication server that includes an event database operable to generate an event ID responsive to the received event information and store an event record, and a contact database comprising a plurality of contact records that determines if the plurality of contact records comprises either of the event host or the event participant. The system further includes an interface operable to establish a conference call responsive to the event date and the event time and call each of the event host and the event participant.

Abstract: Communication events often produce a significant volume and variety of data. While such data is often useful as a teaching or configuration tool or as a source of troubleshooting information, such information often results in “information overload.” By providing a “highlight reel,” communication data comprising only relevant information, which may be further limited to a specific number of duration of events, allows for key data to be identified for presentation and avoid the need to further process, store, or otherwise maintain irrelevant or less relevant data.

Abstract: A telecommunications service provider's real time analysis system analyzes communications data to detect potentially fraudulent communications data, where the analysis is performed in real time in the routing path of the communications data. The communications data may include calls (e.g., SS7, VoIP, etc. based calls) and messages (e.g., SMS, MMS, etc.). The real time analysis system rejects potentially fraudulent communications data and non-fraudulent communications data in order to be used in real time in the routing path of the communications data. A rejection by the real time analysis system may cause non-fraudulent communications data to still be sent to the intended destination of the communications data. The real time analysis system can be in the routing path of the communications data without further routing non-fraudulent communications data traffic to the next appropriate hop in the routing path.

Abstract: 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.

Abstract: A call management system of a call center retrieves customer demographic data associated with a customer identifier for an inbound caller, i.e., customer. A predictive model including a logistic regression model and tree based model determines a value prediction signal for the identified customer. Based on the value prediction signal determined, the predictive model classifies the identified customer into a first value group or a second value group. The call management system routes a customer classified in the first value group to a first call queue for connection to one of a first pool of call center agents who are authorized to present an offer to purchase a product, and routes a customer classified in the second value group to a second call queue for connection to one of a second pool of call center agents who are not authorized to present the offer to purchase the product.

Abstract: A method of providing blockchain wireless services in a controlled environment is provided. The method comprises a wireless communication device associated with an inmate of a controlled environment receiving one of a voice and video call from a device external to the controlled environment. The method further comprises the device placing the received call into a hold state and sending a request for validation of the call via a blockchain, the request identifying at least parties to the call. The method further comprises the device, upon receipt of validation, removing the call from the hold state; and enabling at least one of voice and video functionality for the parties. The method further comprises the wireless communication device sending the request for validation to a telecommunications server and the server conducting real time monitoring of the call. The method further comprises the device continuously recording the call.

Abstract: Methods and systems for intelligently joining a conference are provided. The method includes matching a user with contact details comprising at least one of name, email address, phone number, user ID, and/or enterprise of the user. The method also includes verifying an identity of the user when a confidence score exceeds a predetermined threshold. The method also includes searching calendar data for a meeting involving the user based on the contact details of the user, the meeting scheduled proximate to a local time of the user. The method also includes joining the user to the meeting via an audio conferencing service based on the calendar data.