Abstract: A computerized system and method may analyze data representing remotely connected computer systems, which may be for example used by agents as part of their activity and/or routine within a given system or organization, to assess and/or quantify critical factors that may impact the output and/or efficiency for a given agent or a plurality of agents within the system or organization. In a computerized-system comprising one or more processors, and a memory including a data store of agents' data and metrics, embodiments of the invention may collect a plurality of data streams, which may include call and/or chat data and/or metadata; store the data streams in an appropriate database; periodically extract parts of the stored data from the database, and calculate effectiveness scores based on the extracted data; and transmit the calculated scores to potential data utilizers and/or target applications, to be presented via a user interface thereof.

Abstract: A computer-implemented method for dynamically prioritizing inbound interactions in a digital multi-channel contact center. The computer-implemented method includes for each inbound interaction via a digital channel: (i) operating an interaction analyzer module to extract one or more metadata parameters from the inbound interaction; (ii) operating a prioritization module to calculate a Digital Interaction Priority Score (DIPS) of the inbound interaction based on the one or more metadata parameters; and (iii) forwarding the DIPS to an interaction distribution module to route the inbound interaction to an agent based on the DIPS. The DIPS is periodically updated until the interaction is assigned to the agent.

Abstract: Agent proficiency scoring systems and methods, and non-transitory computer readable media, include receiving performance details and behavior details for an agent; calculating a performance score and a behavior score for the agent based on the performance details and the behavior details; combining the performance score and the behavior score to yield a current proficiency score of the agent; calculating a proficiency deviation between the current proficiency score of the agent and a previous proficiency score of the agent; determining whether the proficiency deviation of the agent is within an acceptable range; automatically updating the previous proficiency score, or transmitting a proficiency score request to a supervisor of the agent for review; and implementing one or more actions based on the current proficiency score or the previous proficiency score of the agent.

Abstract: A system and a method for managing interactions between agent devices and customer devices, the system comprising: a computing device; a local storage; a memory; and a processor, the processor configured to: identify interaction data in interactions between an agent device and a customer device that show a transition from a first connection type to a second connection type; and when a transition in connection types is identified, initiating one or more remedial measures.

Abstract: A method and system for data synchronization in a multi-tenant data synchronization system is provided. The method and system can allow for prioritizing events from a plurality of tenants for synchronization based at least one, a tenant prioritization score.

Abstract: An event prioritization system and methods are provided that are configured to dynamically prioritize incoming events reported by a plurality of event ticketing systems while the incoming events are live or ongoing. The system includes a processor and a computer readable medium operably coupled thereto, the computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, to perform event prioritization operations which include receiving an event associated with a computing issue affecting a customer entity, extracting a plurality of event prioritization factors from event data of the event, calculating scores for the plurality of event prioritization factors, determining a customer impact score of the event based on the scores, determining a criticality of the event based on the customer impact score and a service level agreement, and prioritizing the event in an event handler queue.

Abstract: A system and method may detect rogue trading by detecting a subset of trades among a plurality of trades, where each trade in the subset does not meet a trade surveillance system threshold, and does meet a trade surveillance system threshold within a tolerance, and each trade falls within the same time period. A ratio of the subset of trades to the plurality of trades may be determined. If the ratio is above a threshold, it may be determined that the subset of trades corresponds to undesirable trading. Undesirable trading may be determined using an additional factor, based on a weighted average of, for each of a trade surveillance system threshold, the number of trades in the subset meeting the trade surveillance system threshold within a tolerance and not meeting a trade surveillance threshold, times a weight based on the position of the threshold in the trade surveillance system.

Abstract: A system automatically prioritizes and resumes disconnected customer interactions. The system includes a processor to perform operations that include: receiving a list of disconnected customer interactions, including their metadata; using a prioritization module and the metadata, assigning a priority score to each disconnected interaction; with a queuing module and the respective priority scores, with an agent assignment module, arranging the disconnected interactions in a priority order; assigning an available agent to each disconnected interaction in the priority order; selecting a channel for each disconnected interaction in the priority order, based on a channel recommendation module and the metadata; and re-connecting a disconnected customer with the respective agent via the respective channel for each respective disconnected customer interaction in the priority order.

Abstract: Translation and customer interaction distribution systems and methods, and non-transitory computer readable media, including receiving an audio interaction from a customer in a source language; identifying the source language from a portion of the audio interaction; dividing the portion of the audio interaction into frames by audio segmentation; converting the frames into text in the source language; translating the text in the source language to text in a target language of an agent; converting the text in the target language to speech in the target language; and providing the speech in the target language to the agent in real-time.

Abstract: A computerized-method for determining an agent-proficiency when addressing concurrent customer sessions via one or more channel types and utilization thereof. The computerized-method includes operating a Concurrent-Sessions-Handling-Agent-Proficiency (CSHAP) module.

Abstract: A computerized-method for calculating a level of friction within a customer and agent interaction, for quality improvement thereof, in a multichannel contact center. The computerized-method includes operating, for each interaction between the customer and the agent, in each channel, an Interaction Friction Score (IFS) calculation module. The IFS calculation module includes retrieving a transcript and interaction metadata of the interaction between the customer and the agent from the friction datastore and the database of interactions transcripts and metadata. The transcript includes ‘N’ sentences and calculating an IFS of the interaction between the customer and the agent then forwarding each interaction between the customer and the agent having a calculated IFS above a calculated Interaction Friction Threshold (IFT) for an intervention.

Abstract: Classification and resolution systems and methods, and non-transitory computer readable media, including receiving a repeat interaction from a customer after a first interaction with a first agent; determining a history of the customer with the contact center, historical statistics of the first agent, skill statistics of the first agent, and contact center information on the first interaction; providing the history of the customer with the contact center, the historical statistics of the first agent, the skill statistics of the first agent, and the contact center information on the first interaction to a source classification model; automatically determining a source of the repeat interaction; automatically ranking based on the determined source of the repeat interaction, one or more reasons for the repeat interaction; and performing an action during the repeat interaction that corresponds to the one or more reasons for the repeat interaction to improve customer satisfaction.

Abstract: A computerized-method for recommending activities for an agent, in a contact center is provided herein. The computerized-method includes operating an activities-recommendation module, for agents in a contact center, during a work-shift of an agent.

Abstract: A computerized-method for identifying high impacted schedules, in a contact center is provided herein. The computerized-method includes retrieving schedules of agents during a preconfigured period from a Workforce Management (WFM) system. For each schedule: (i) operating a schedule quotient module to derive schedule-quotient score; (ii) operating an agent quotient module to derive agent-quotient score; (iii) operating a Schedule Impact Score (SIS) module to derive a schedule-impact score based on the derived schedule-quotient score and the derived agent-quotient score; and (iv) operating a recommendation module for auto-corrective measures in one or more systems based on the derived schedule-impact score.

Abstract: A computerized-method for reducing wait-time in a multichannel-contact-center. For each query that is not resolved by a bot: a. selecting a digital-channel-type from a plurality of digital-channel-types; b. operating an aggregator module on the selected digital-channel-type to aggregate the received query and similar pending queries into a group-of-queries; c. operating a tracker-module on the group-of-queries to identify a query-resolution and to send a notification as to the query-resolution to the customer via the digital-channel-type that the query has been received; and d. repeating operations a.-c. until a query-resolution has been identified or all digital-channel-types in the plurality of digital-channel-types have been selected.

Abstract: A computerized-method for training and applying a Machine Learning (ML) textual behavioral-identification-model to authenticate an agent, in a digital multi-channel environment, is provided herein. The computerized-method may include: (i) training a ML-textual-behavioral-identification-model using retrieved textual responses of each agent in one or more historical-interactions which were conducted in a controlled environment, as a training dataset.

Abstract: A computerized-method for redirecting inbound-voice-interactions to digital channels in a contact center, is provided herein. The computerized-method includes: (i) operating a digital-qualifier module to determine a digital-medium-transition-quotient, of an inbound-voice-interaction of a customer in an inbound-queue. The digital-medium-transition-quotient is an indication of a level of suitability of a digital-communication-channel to resolve a customer issue; (ii) operating an interaction-redirection module to determine a digital-communication-channel for redirection of the inbound-voice-interaction, based on customer-preference and the determined digital-medium-transition-quotient; and (iii) forwarding the inbound-voice-interaction and the determined digital-communication-channel to an Automatic Call Distribution (ACD) system to be carried-out by an agent via the determined digital-communication-channel when the determined digital-medium-transition-quotient is above a preconfigured threshold.

Abstract: A computerized-method for gauging agent's self-assessment effectiveness, is provided herein. The computerized-method includes for each interaction (i) operating a Self-assessment Consolidation module to calculate a confidence-interval for each data-point of one or more preconfigured data-points, and (ii) operating a Self-assessment Divergence Determinant (SDD) module. The operating of the SDD includes: retrieving one or more data-points of the interaction; for each data-point retrieving the confidence interval; setting a divergence-indicator as zero, when the data point is within the confidence-interval; setting the divergence-indicator as a subtraction of the data point from the calculated lower-bound, when the data-point is lower than the lower-bound of the confidence-interval; and setting the divergence-indicator as a subtraction of the calculated upper-bound from the data-point, when the data-point is greater than the upper-bound of the confidence-interval.

Abstract: A computerized-method for authorizing time-off for a skill to increase agents digital availability is provided herein. The computerized-method includes receiving an agent skill-based time-off request having one or more skills and a duration from a User Interface (UI) in a computerized-device of an agent, and for each skill of the one or more skills in the agent skill-based time-off request: (a) operating an agent-skill-based time-off module to calculate au agent time-off eligibility-quotient.

Abstract: A computerized system and method may analyze data representing remotely connected computer systems, which may be for example used by agents as part of their activity and/or routine within a given system or organization, to assess and/or quantify critical factors that may impact the output and/or efficiency for a given agent or a plurality of agents within the system or organization. In a computerized-system comprising one or more processors, and a memory including a data store of agents' data and metrics, embodiments of the invention may collect a plurality of data streams, which may include call and/or chat data and/or metadata; store the data streams in an appropriate database; periodically extract parts of the stored data from the database, and calculate effectiveness scores based on the extracted data; and transmit the calculated scores to potential data utilizers and/or target applications, to be presented via a user interface thereof.