A system and method for generating a list of tasks from an interaction recording may include a computing device; a memory; and a processor, the processor configured to: identify, for each sentence of one or more sentences of an interaction recording, whether the sentence comprises at least two nouns and at least one verb; generate a set of actionable items using a long short-term memory (LSTM) model by: when the sentence does not comprise at least two nouns and at least one verb, deleting the sentence; and when the sentence comprises at least two nouns and at least one verb, generating an actionable item; input the actionable items to a language model to generate a list of tasks. Computer systems may use a generated list of tasks to automatically allocate work to agents of a contact center or to automatically update a status of a completed task.
A data query system and methods are provided that are configured to intelligently generate structured data queries from natural language questions using large language models (LLMs). 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 operations which include receiving a natural language question for structured data, converting the natural language question to embeddings, matching the embeddings to pre-generated questions from a user questions repository (UQR), determining an accuracy of the matching meets or exceeds a threshold similarity, determining, using an LLM and metadata corresponding to the pre-generated questions from the UQR, a structured data query for querying for the structured data, and querying the structured database system using the structured data query.
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Cloud-based computer software, namely, temporary use of online, non-downloadable computer software and non-downloadable computer applications for data management, analysis, interpretation, identification, and reporting for use in the fields of employee and customer computer software incorporating omnichannel routing, analytics, artificial intelligence, and automation to perform functions for workforce optimization, customer journey optimization, performance management; providing temporary use of online, non-downloadable software in the nature of application program interfaces for integrated voice infrastructure and turnkey telephony equipment; application service provider featuring software for queuing, handling, logging, recording, monitoring, tracking, supervising, managing, routing, disposition and distribution of telephone calls, facsimile transmissions, emails, social media, and web based messages to or from in office or at home employees, contractors, subcontractors, parties, callers or customers for use in the field of customer service, customer support, inside sales, collections, outside sales, and marketing; application service provider featuring software for scheduling, surveying, monitoring, supervising, rating, reviewing managing, performance forecasting, call, video recording, analyzing and training employees for use in the field of customer service, customer support, inside sales, collections, outside sales, and marketing; application service provider featuring an application software development tool for use in customizing telecommunication service applications, namely, software for queuing, handling, logging, recording, monitoring, tracking, supervising, managing, routing, disposition and distribution of telephone calls, facsimile transmissions, emails, social media, and web based messages to or from in office or at home employees, contractors, subcontractors, parties, callers or customers for use in the field of customer service, customer support, inside sales, collections, outside sales, and marketing; technical support services, namely, troubleshooting of computer software problems; computer software consultation; providing information relating to computer software maintenance, use and development; Providing temporary use of online non-downloadable software for collecting, processing, integrating and displaying data from one or more sources for risk management and detecting, monitoring, managing and preventing fraud, financial crime, cybercrime, cyber threats and cyber-attacks; providing temporary use of online non-downloadable software for collecting, processing, integrating and displaying data from one or more sources to be used for managing legal, regulatory, risk and enterprise compliance, capital market compliance, anti-money laundering compliance, detecting breaches of compliance, third-party due diligence, and monitoring of financial transactions, financial trades, financial swaps and e-commerce transactions; providing temporary use of online non-downloadable software for collecting, processing, integrating and displaying data from one or more sources to be used for automating manual case management and workflow processes, and to monitor, prioritize, enrich, distribute and permit collaboration on case and workflow information; providing temporary use of online non-downloadable software for emergency communications incident data management, recording, transcribing, evaluating, and analyzing real time performance metrics for training and optimizing performance of emergency telecommunicators; providing temporary use of online non-downloadable software for collecting, analyzing and sharing digital evidence in the nature of video content, audio content, digital image files, digital text content, Records Management System (RMS), Computer Aided Dispatch (CAD) and Case Management System (CMS) data, and computer log files
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
Cloud-based computer software, namely, temporary use of online, non-downloadable computer software and non-downloadable computer applications for data management, analysis, interpretation, identification, and reporting for use in the fields of employee and customer computer software incorporating omnichannel routing, analytics, artificial intelligence, and automation to perform functions for workforce optimization, customer journey optimization, performance management; providing temporary use of online, non-downloadable software in the nature of application program interfaces for integrated voice infrastructure and turnkey telephony equipment; application service provider featuring software for queuing, handling, logging, recording, monitoring, tracking, supervising, managing, routing, disposition and distribution of telephone calls, facsimile transmissions, emails, social media, and web based messages to or from in office or at home employees, contractors, subcontractors, parties, callers or customers for use in the field of customer service, customer support, inside sales, collections, outside sales, and marketing; application service provider featuring software for scheduling, surveying, monitoring, supervising, rating, reviewing managing, performance forecasting, call, video recording, analyzing and training employees for use in the field of customer service, customer support, inside sales, collections, outside sales, and marketing; application service provider featuring an application software development tool for use in customizing telecommunication service applications, namely, software for queuing, handling, logging, recording, monitoring, tracking, supervising, managing, routing, disposition and distribution of telephone calls, facsimile transmissions, emails, social media, and web based messages to or from in office or at home employees, contractors, subcontractors, parties, callers or customers for use in the field of customer service, customer support, inside sales, collections, outside sales, and marketing; and technical support services, namely, troubleshooting of computer software problems; computer software consultation; providing information relating to computer software maintenance, use and development
5.
SYSTEM AND METHOD FOR AUTO-APPROVING PENDING REQUESTS OF AGENTS BASED IN A DYNAMIC ENVIRONMENT
Systems adapted to auto-approve pending requests of contact center agents based in a dynamic environment and methods, and non-transitory computer readable media, include monitoring operational parameters affecting staffing needs and automatic approval criteria; establishing that a new staffing situation is present based on the monitored operational parameters, automatic approval criteria, or both; determining that the new staffing situation meets a current staffing threshold; identifying a pending schedule change request submitted by a contact center agent; comparing the identified pending schedule change request with the automatic approval criteria; updating a schedule of the contact center agent based on the approved identified pending schedule change request or approved generated recommendation; and sending a schedule notification to the contact center agent.
G06Q 10/0631 - Planification, affectation, distribution ou ordonnancement de ressources d’entreprises ou d’organisations
6.
SYSTEM AND METHOD FOR ADJUSTING AGENTS STAFFING LEVELS OF A SUCCESSIVE WORK-SHIFT OF A PREASSIGNED ONGOING WORK-SHIFT, DURING THE PREASSIGNED ONGOING WORK-SHIFT, IN A CONTACT CENTER
A computer-implemented method for adjusting agents staffing levels of a successive work-shift of a preassigned ongoing work-shift, during the preassigned ongoing work-shift, in a contact center. The computer-implemented method includes: (i) during the preassigned ongoing work-shift, determining a number of agents to handle inbound-interactions that require one or more skills for the successive work-shift; (ii) comparing the number of agents to handle inbound-interactions that require one or more skills to a threshold; (iii) when the number of agents to handle inbound-interactions that require one or more skills is above the threshold, calculating a number of extra-agents; and (iv) operating a shift-extension module to: (a) select the calculated number of extra-agents from agents having the one or more skills which are assigned to the preassigned ongoing work-shift; and (b) update corresponding schedules of the selected number of extra-agents, in a database of a Workforce Management (WFM) system.
G06Q 10/0631 - Planification, affectation, distribution ou ordonnancement de ressources d’entreprises ou d’organisations
7.
SYSTEM AND METHOD FOR PROVIDING AN IDENTICAL RESPONSE TO A SIMILAR ISSUE THAT IS RECEIVED FROM DIFFERENT CUSTOMERS, VIA INBOUND-INTERACTION IN A DIGITAL MULTI-CHANNEL CONTACT CENTER
A computer-implemented method for providing an identical response to a similar issue that is received from different customers. The computer-implemented method includes when a contact-center occupancy-rate is above a first-preconfigured-threshold, for each inbound-interaction from a customer that is entering an interactions-queue: (i) creating a temporary-case for an issue raised in the inbound-interaction; (ii) operating a Similarity Detection Module on the created temporary-case and cases in a cases-queue to receive a similarity-score for the created temporary-case; (iii) when the received similarity-score is above a second-preconfigured-threshold, operating a category Qualifier Module on the temporary-case to provide an indication as to qualification of a category of the issue raised; (iv) when the provided indication as to qualification of the category of the issued raised is qualified, merging the temporary-case with cases in the cases-queue and retrieving a response of the cases in the cases-queue; and (v) sending the retrieved response to the customer.
A system is adapted to automatically optimize the routing of incoming calls. The system includes: a session controller; a first group of media servers; a second group of media servers; and a processor configured to perform operations. The operations include: regularly polling the first group of media servers to determine a first group of most-available servers, and regularly polling the second group of media servers to determine a second group of most-available servers. The operations also include, when the session controller receives an inbound call: selecting a server from the first group of most-available servers or the second group of most-available servers; and connecting the inbound call to the selected server.
H04L 65/1069 - Établissement ou terminaison d'une session
H04L 65/1104 - Protocole d'initiation de session [SIP]
H04M 3/42 - Systèmes fournissant des fonctions ou des services particuliers aux abonnés
9.
SYSTEM AND METHOD FOR OPTIMIZING A NUMBER OF SESSIONS OF A MULTI-SESSION MEETING BASED ON AGENTS SKILL REQUIREMENT DURING A TIME-RANGE OF SCHEDUELED WORK-SHIFTS IN A CLOUD-BASED CONTACT CENTER
A computer-implemented method for optimizing a number of sessions of a multi-session meeting based on agents skill requirement during a time-range of scheduled work-shifts, in a cloud-based contact center. The computer-implemented method includes receiving a time-range of scheduled work-shifts, a maximum number of agents in each session of the multi-session meeting, one or more skill-types and a buffer-level for each skill-type, operating a schedule manager MS to provide scheduled work-shifts of agents in the time-range of scheduled work-shifts that include open slots and net staffing data of each skill-type, determining a total number of agents, calculating a lower-bound of sessions and an upper-bound of sessions, iteratively determining a number of sessions of the multi-session meeting and allocating the total number of agents to the determined number of sessions of the multi-session meeting until an optimal number of sessions of the multi-session meeting is reached.
G06Q 10/0631 - Planification, affectation, distribution ou ordonnancement de ressources d’entreprises ou d’organisations
10.
A COMPUTER-IMPLEMENTED METHOD FOR CONSISTENTLY IDENTIFYING AN AGENT FOR A COACHING SESSION, AND ASSESSING RELEVANT COACHING SUBJECT TO THE COACHING SESSION, IN A CONTACT CENTER
A computer-implemented method for consistently identifying an agent for a coaching-session and assessing relevant-coaching-subject to the coaching-session. The computer-implemented method includes: (i) receiving agents having KPIs below a threshold; for each agent: (ii) receiving focus-area and related behaviors for the KPIs; (iii) retrieving interactions and associated categories and behaviors; (iv) retrieving evaluations of the retrieved interactions that are below a threshold, and related interactions; (v) marking each category that is having an evaluation below the threshold; (vi) retrieving associated focus-area with behaviors for each category that is classified as negative; (vii) determining a number of categories for the coaching-session; (viii) identifying behaviors from interactions related to the categories based on the associated focus-area; (ix) determining a number of behaviors; (x) calculating a co-relation score for each behavior and associated focus-area; and (xi) selecting a number of behaviors and associated focus-area having highest co-relation score to schedule a coaching-session therewith.
Agent utilization systems and methods, and non-transitory computer readable media, include receiving net staffing data for an organization; identifying opportunities for agents by: calculating available agents per interval (AAI) information based on the net staffing data, calculating total addressable contacts (TAC) information based on the AAI information, and calculating opportunity information for a calling list opportunity, a coaching opportunity, a re-allocation opportunity, or a combination thereof, based on the TAC information; displaying the calling list opportunity, the coaching opportunity, the re-allocation opportunity, or a combination thereof, alongside the opportunity information; receiving a selection of one of the calling list opportunity, the coaching opportunity, the re-allocation opportunity, or a combination thereof; and in response to the selection, automatically implementing the selected calling list opportunity, the selected coaching opportunity, the selected re-allocation opportunity, or a combination thereof, in a workforce management system.
Methods and systems for digital scheduling include periodically determining, from a datastore of agent profiles, a set of agents which satisfy a predefined time-off criterion; and notifying, via a digital message, one or more agents of the determined set of agents of a recommended list of dates on which to take a time-off, wherein the recommended list of dates is generated in accordance with staffing prediction data for the dates.
G06Q 10/1093 - Ordonnancement basé sur un agenda pour des personnes ou des groupes
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
13.
SYSTEMS AND METHODS FOR TRADING SHIFT OF UNAVAILABLE PREFERENCE USING TRADE QUEUES
Systems and methods for digital scheduling, include periodically checking a data storage for queued schedule trade requests; identifying two corresponding queued schedule trade requests; else, if two corresponding queued schedule trade requests are not identified: identifying a set of cyclic queued schedule trade requests; else, if a set of cyclic queued schedule trade requests are not identified: repeating the step of periodically checking; approving or rejecting the identified schedule trade requests based on one or more approval criteria; and if the identified schedule trade requests were approved, outputting one or more updated schedules reflecting the approved schedule trade requests.
A computerized system and method may calculate or update task or job execution schedules for a plurality of resources and perform automated actions based on the calculated or updated schedules. A computerized system including one or more processors, a memory, and a communication interface to communicate via a communication network with remote computing devices, may be used for forecasting or reforecasting task properties for relevant time intervals, where the properties may describe future tasks to be handled by a plurality of resources; calculating an allocation matrix for the time intervals based on the predicted properties; and calculating or updating a schedule based on the calculated allocation matrix—for example to automatically extend a break for one or more resources, where resources are not to handle tasks during the break. Some embodiments of the invention may perform, e.g., computer automated actions based on calculated or updated schedules.
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.
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.
H04M 3/51 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur
H04M 3/523 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur avec répartition ou mise en file d'attente des appels
17.
CALL COMPLEXITY COMPUTATION USING IDENTIFIED TOPICS AND TOPIC CHANGES
An event prioritization system and methods are provided that are configured to dynamically compute call complexity for voice data calls using topics identified from call transcripts. 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 call evaluation operations which include receiving a transcript of a voice data call, parsing the transcript for at least one topic, generating, based on the parsing, a list of topics, analyzing, by a call complexity evaluation engine, the list of topics for a complexity rating, determining, based on the complexity rating and a length of the voice data call, a deviation from an expectation, flagging the voice data call, and outputting the flagged voice data call via an interface.
Systems adapted to measure impact of supervisor actions and methods, and non-transitory computer readable media, include identifying an interaction where a contact center supervisor performed a supervisor action, where the supervisor supervised a contact center agent; identifying a supervisor intervention point in the interaction; determining an impact score for each of a plurality of behavioral factors; aggregating the impact scores for the plurality of behavioral factors and determining an average of the impact scores to provide an overall impact score for the supervisor action; and performing an action automatically based on the overall impact score to improve contact center performance.
A computerized system and method may provide automated clustering procedures where each clustered entity or node may be included in a plurality of clusters (e.g., more than a single cluster). Clustering procedures provided by some embodiments of the invention may involve measuring and/or quantifying degrees of relevance and/or generality for a plurality of entities or nodes. In some embodiments, a clustering procedure may be used, e.g., to generate a hierarchical, multi-tiered taxonomy of such entities. A computerized system comprising a processor, and a memory, may be used for ranking a plurality of nodes; select nodes based on the ranking; cluster selected nodes into intermediate clusters; calculate distances between unselected nodes and intermediate clusters; and cluster unselected nodes and intermediate clusters into final clusters based on the calculated distances. Some embodiments of the invention may allow routing interactions between remotely connected computer systems based on an automatically generated taxonomy.
G06F 16/30 - Recherche d’informationsStructures de bases de données à cet effetStructures de systèmes de fichiers à cet effet de données textuelles non structurées
G06F 16/3329 - Formulation de requêtes en langage naturel
G06F 16/355 - Création ou modification de classes ou de grappes
A system and a method of managing data transfer for a plurality of data centers may include identifying data transfer capacity and data transfer demand for each server of a plurality of data centers; calculating a data transfer distribution for the plurality of data centers that prioritizes data transfer between servers of a first data center of the plurality of data centers over data transfer between servers of the first data center and servers of the remaining data centers of the plurality of data centers based on the identified data transfer capacity and the data transfer demand; and allocating data transfers to the servers of the plurality of data centers.
H04L 12/24 - Dispositions pour la maintenance ou la gestion
H04L 67/1008 - Sélection du serveur pour la répartition de charge basée sur les paramètres des serveurs, p. ex. la mémoire disponible ou la charge de travail
H04L 67/101 - Sélection du serveur pour la répartition de charge basée sur les conditions du réseau
H04L 67/1023 - Sélection du serveur pour la répartition de charge basée sur un hachage appliqué aux adresses IP ou aux coûts
21.
CALIBRATING EVALUATOR FEEDBACK RELATING TO AGENT-CUSTOMER INTERACTION(S) BASED ON CORRESPONDING CUSTOMER FEEDBACK
Apparatus, systems, and methods for calibrating evaluator feedback relating to agent-customer interaction(s) based on corresponding customer feedback. An agent evaluation form is generated based on customer feedback provided via a customer questionnaire. By comparing evaluator feedback received via completion of the agent evaluation form by one or more user-selected evaluators to the customer feedback provided via the customer questionnaire, a customer feedback variance score is calculated for the one or more user-selected evaluators.
Embodiments are disclosed for securing internet-based transfer of voice call data. Embodiments may include: sending a primary-protocol-encoded communication, by a forwarding unit (FU), to a session border controller (SBC), when an indication is received at the FU that a secondary-protocol-encoded communication has been received at a gateway component, from a voice call data source, to propose transferring voice call data to the SBC; outputting by the SBC, in response to the primary-protocol-encoded communication an IP address encoded with the primary protocol; converting, by a gateway component, the IP address encoded with the primary protocol into an IP address encoded with the secondary protocol; and sending, by a gateway component, the IP address encoded with the secondary protocol to the voice call data source that is proposing to transfer the voice call data.
A method of managing interaction recordings of an interaction between agent devices and customer devices, the method comprising: initiating an interaction recording of the interaction between an agent device and a customer device, wherein the interaction recording comprises metadata items; storing one or more parts of the interaction recording in a local storage; identifying parts of the interaction recording whose metadata items fulfill archiving criteria; and archiving parts of the interaction recording stored in the local storage whose metadata items fulfill the archiving criteria and deleting parts of the interaction recording from the local storage whose metadata items do not fulfill the archiving criteria.
A computer-implemented method for unsupervised task segmentation. The computer-implemented method includes receiving a stream of data of desktop-actions. Each desktop-action relates to UI data-handling operations of applications, and labeled with an action-related integer id, operating an unsupervised task segmentation module on the stream of data of desktop-actions to identify sequences of desktop-actions. The unsupervised task segmentation module includes creating an integer sequence from the action related integer id, such that desktop-actions are consecutively concatenated, creating word embeddings of the UI data-handling operations of applications for each desktop-action based on the integer id thereof, to yield a vector of embeddings, and implementing unsupervised topic-segmentation NLP module on the created vector of embeddings to determine cutting-points in the integer sequence to yield segments such that semantic-similarity-level of embeddings in each yielded segment is maximized, and a number of non-complete business processes is reduced. Each cutting-point indicates an end of a segment.
Methods and systems for digital scheduling include, using a processor: identifying a set of target agents associated with a corresponding set of shift parameters that satisfy a set of preferences of a multi-day trade request initiated by a source agent; sending the multi-day trade request to a sub-set of the identified target agents selected by the source agent; and if a first target agent of the sub-set accepts the multi-day trade request, and if the multi-day trade request satisfies a pre-defined set of approval criteria, then automatically approving the multi-day trade request between the source agent and said first target agent, and automatically adjusting a schedule of the source agent and the first target agent to reflect the approved multi-day trade request; else: automatically rejecting the multi-day trade request.
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.
H04M 3/523 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur avec répartition ou mise en file d'attente des appels
27.
System and method of efficient selection of evaluation form
Agent evaluation systems and methods, and non-transitory computer readable media, include receiving a recorded interaction between a customer and a contact center agent; retrieving or determining an interaction divergence range for each of a plurality of interaction parameters for the recorded interaction; calculating a form divergence determinant (FDD) score for each of a plurality of evaluation forms, wherein the lower the FDD score, the more suitable an evaluation form is for the recorded interaction; filtering out evaluation forms having an FDD score greater than a predefined threshold; ranking evaluation forms having an FDD score lower than the predefined threshold based on their FDD score; and providing a list of the ranked evaluation forms to a supervisor of the contact center agent.
A computerized system and method may provide a robust, automated clustering procedure, including handling of outlier points, which may involve measuring and/or quantifying degrees of relevance and/or generality for a plurality of input entities. In some embodiments, a clustering procedure may be used, e.g., to generate a hierarchical, multi-tiered taxonomy of such entities. In some embodiments, a computerized system comprising a processor, and a memory, may be used for calculating a distance between nodes for each of a plurality of pairs of nodes, where the pairs may comprise a plurality of input entities and/or initial clusters; selecting one or more of the pairs based on the calculated distances; and merging one or more of the selected pairs, which may include a common node, into one or more final clusters. Some embodiments of the invention may allow routing interactions between remotely connected computer systems based on an automatically generated taxonomy.
A computer-implemented method for playing a personalized voice recording with a status update to follow-up customer on an inbound call in a contact center. The computer-implemented method includes marking one or more open tickets as predicted for follow-up inbound call and predicted date and time for the follow-up call in an inbound database; updating status of one or more open ticket marked as predicted for follow-up inbound call and predicted date and time; converting the updated status to a voice recording; and operating an inbound software to identify an inbound call as a follow-up inbound call of a customer received via a Voice over Internet Protocol (VoIP) network communicating with a customer's mobile device. The customer has an open ticket with an updated status and playing voice recording with the status update in the identified inbound call, thus reducing customers waiting time and agents' workload.
Systems and methods are provided for configuring a set of one or more contact centers, the set of one or more contact centers associated with a total number of agents and a number of regions. The systems and methods may include predicting or selecting a number of scheduling units or an optimal number of skills for the set of one or more contact centers based on the total number of agents and the number of regions.
G06Q 10/0637 - Gestion ou analyse stratégiques, p. ex. définition d’un objectif ou d’une cible pour une organisationPlanification des actions en fonction des objectifsAnalyse ou évaluation de l’efficacité des objectifs
31.
METHODS AND SYSTEMS FOR DETECTING STAMPS IN SCANNED DOCUMENTS
Systems and methods for detecting stamps include if at least one regular shape in an image of a document is detected then outputting said at least one regular shape as a stamp; else: removing at least one of text, lines, and noise in the image of the document; and if at least one closed shape is remaining in the image of the document, then inscribing said at least one closed shape and outputting said at least one inscribed closed shape as a stamp; else if at least one open shape is remaining in the image of the document, then enclosing said at least one open shape and outputting said at least one enclosed shape as a stamp.
A system for supporting effective campaign management in a cloud-based contact center platform. The system includes a campaign analytics engine. The campaign analytics engine includes retrieving campaign offerings of a running campaign; retrieving time-stamped text transcripts of interactions of agents of the running campaign; parsing the retrieved time-stamped text transcripts of interactions to yield parsed transcripts and related customer sentiment; comparing the yielded parsed transactions with the retrieved campaign offerings to generate analytical data. The generated analytical data includes at least one of: (i) agent campaign delivery effectiveness score; and (ii) probability of conversion. When an agent has an agent campaign delivery effectiveness score below a first threshold excluding the agent from the running campaign and sending the campaign delivery effectiveness score of the agent along with agent details and a preconfigured training list to be assigned to the agent by a QM application.
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.
H04L 41/5009 - Détermination des paramètres de rendement du niveau de service ou violations des contrats de niveau de service, p. ex. violations du temps de réponse convenu ou du temps moyen entre l’échec [MTBF]
G06Q 30/01 - Services de relation avec la clientèle
H04L 41/50 - Gestion des services réseau, p. ex. en assurant une bonne réalisation du service conformément aux accords
34.
SYSTEM AND METHOD FOR IMPROVED TRADING WITH AGENT RANKING AND SCHEDULE TAGGING
A computerized-method for trading a scheduled-working-shift, is provided herein. The computerized-method includes operating a trading-shifts module. The module includes: communicating with a computerized-device of a source-agent, to receive a trade-request for a scheduled-working-shift, via a trading-shift-interface; retrieving from a database, adequate target-agents, which have tagged a period including the scheduled-working shift as tradable and having a day off, during the scheduled-working-shift; calculating a trading-rank to each agent of the adequate target-agents, based on a number of trading actions in a preconfigured period of time in which the adequate target-agent has accepted a trade request, sorting the adequate target-agents, in descending order according to the calculated trading-rank of each agent of the adequate target-agents, to yield a sorted list of target-agents having a top-rated target-agent; and automatically updating the database, by assigning the scheduled-working-shift of the source-agent to the top-rated target-agent and the scheduled-working-shift of the top-rated target-agent to the source-agent.
Shift trading systems and methods, and non-transitory computer readable media, include receiving a shift trade request from a source agent, wherein the shift trade request comprises a shift day and a shift time; matching the shift trade request with a plurality of target agents that are available on the shift day and the shift time; for each target agent from the plurality of target agents, calculating a trade index score based on a trade history success index score, a matching skill index score, a skill proficiency index score, and a trade interval index score; ranking the plurality of target agents from highest to lowest trade index score; and displaying the ranked plurality of target agents with the target agent having the highest trade index score at the top of a list.
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.
H04M 3/00 - Centraux automatiques ou semi-automatiques
H04M 3/51 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur
H04M 3/523 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur avec répartition ou mise en file d'attente des appels
37.
SYSTEM AND METHOD TO DISTRIBUTE INTERACTIVE MEDIA WITH LOW LATENCY FOR EFFICIENT CONTACT CENTER
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.
G10L 13/08 - Analyse de texte ou génération de paramètres pour la synthèse de la parole à partir de texte, p. ex. conversion graphème-phonème, génération de prosodie ou détermination de l'intonation ou de l'accent tonique
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. The CSHAP-module includes: (a) operating an interactions-module to retrieve one or more interactions and metadata thereof of the agent; (b) for each interaction, determining if the interaction has been handled with concurrent interactions; (c) for each determined interaction as handled with concurrent interactions, checking in the metadata if the interaction has one or more defocused-events; (d) calculating a CSHAP-score for the agent based on one or more attributes from the metadata of the interaction to provide an indication as to an ability of the agent to address concurrent customer sessions; (e) storing the calculated CSHAP-score in a data-store; and (f) sending the CSHAP-score to one or more applications, to take one or more follow-up actions based on the CSHAP-score.
G06Q 10/0639 - Analyse des performances des employésAnalyse des performances des opérations d’une entreprise ou d’une organisation
H04M 3/523 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur avec répartition ou mise en file d'attente des appels
39.
METHOD AND SYSTEM FOR CALCULATING LEVEL OF FRICTION WITHIN A CUSTOMER AND AGENT INTERACTION, FOR QUALITY IMPROVEMENT THEREOF, IN A CONTACT CENTER
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.
A computerized system and method may automatically generate a hierarchical, multi-tiered taxonomy based on measuring and/or quantifying degrees of generality for a plurality of input entities. In some embodiments of the invention, a computerized system comprising a processor, and a memory including a plurality of entities such as documents or text files, may be used for extracting words from a plurality of documents; calculating generality scores for the extracted words; selecting some of the extracted words as exemplars based on the scores; and clustering unselected words under appropriate exemplars to produce or output a corresponding taxonomy. Some embodiments of the invention may allow categorizing interactions among remotely connected computers using a domain taxonomy, and routing interactions between remotely connected computer systems based on the taxonomy.
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.
Systems and methods for automatic real-time monitoring of interactions, carried out by at least one computer processor, including: producing a score for each text component of a text representation of an interaction; producing, based on the score for each text component, a score for each of a plurality of time periods of the interaction; producing a score history, including a plurality of the time period scores; and calculating, based on the score history, a real-time indication of the quality of the interaction.
Systems and methods for mapping a set of output values of a first learning model to a distribution of a set of output values of a second learning model include: calculating a distribution function for a set of source values; calculating a distribution function for a set of target values; calculating a set of quantiles for each distribution function; using the set of quantiles in a linear interpolation of the set of target values to obtain a source values array and a matched interpolated values array; calculating an absolute distance from each value in the source values array to the first set of output values of the first learning model; determining a corresponding value in the matched interpolated values array corresponding to a value in the source values array which has the smallest said absolute distance; and outputting a set of matched values.
G10L 15/10 - Classement ou recherche de la parole utilisant des mesures de distance ou de distorsion entre la parole inconnue et les gabarits de référence
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
44.
Methods for discovery of new automation routine types
A system to create new automation routines includes a processor to: Over time, store a group of actions taken by a group of agents within applications. From the stored group of actions, identify a repeating pattern of actions in a subset of the applications, and construct a binary vector, each position within the binary vector storing a 1 for an occurrence of any action within any application of the subset, and a 0 otherwise. From the binary vector and the repeating pattern, extract a sentence including at least one action within at least one application. Based on the repeating pattern, an application type, or a business goal, create a constraint. If the sentence meets the constraint, accept the sentence and add it to a pool of accepted sentences. From the pool of accepted sentences, identify a pattern of occurrences of the accepted sentence, and create a new automation routine.
Screen recording systems and methods, and non-transitory computer readable media, include receiving, from an applications server, a recording configuration including a local recording trigger, wherein the local recording trigger includes a start screen recording event and a stop screen recording event; monitoring activity on a device of a contact center agent; initiating recording of a screen of the device when the start screen recording event is detected; transmitting data captured in the recording to a recorder; and stopping transmission of the data captured in the recording to the recorder.
H04M 3/51 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06F 3/14 - Sortie numérique vers un dispositif de visualisation
46.
ANALYZING EMOTION IN ONE OR MORE VIDEO MEDIA STREAMS
Analyzing emotion in a videoconference includes receiving video media stream(s) of a user participating in the videoconference. A face of the user is detected in frame(s) of the video media stream(s). An emotional state of the user is classified. In one or more embodiments, an emotional score for the user is assigned and visualized on a display. In one or more embodiments, additional video media stream(s) of additional user(s) participating in the videoconference are also received, corresponding face(s) of the additional user(s) are also detected, and corresponding emotional state(s) of the additional user(s) are also classified. In one or more embodiments, emotional score(s) for the additional user(s) are also assigned and visualized on the display, together with the emotional score for the user. Additionally, or alternatively, a combined emotional score for the user and the additional user(s) may be assigned and visualized on the display.
G06V 40/16 - Visages humains, p. ex. parties du visage, croquis ou expressions
G06V 10/82 - Dispositions pour la reconnaissance ou la compréhension d’images ou de vidéos utilisant la reconnaissance de formes ou l’apprentissage automatique utilisant les réseaux neuronaux
G06V 20/40 - ScènesÉléments spécifiques à la scène dans le contenu vidéo
47.
METHOD AND SYSTEM FOR REDUCING UNDERSTAFFING CONDITIONS BY ENABLING SCHEDULING OF A FLEXIBLE ACTIVITY REQUEST IN A WORKFORCE MANAGEMENT (WFM) SYSTEM
A computerized-method for reducing understaffing conditions by enabling scheduling of a flexible-activity-request in a WFM system. The computerized-method includes operating a Flexible-Activity-Requestor module to enable an agent to enter a date-range for the flexible-activity-request. Receiving an agent date-range to be forwarded to a Schedule-Requests-Management (SRM) system and upon manager approval stored in a database. Generating one or more schedules to be assigned to one or more agents, forwarding the generated schedules to a Schedule-Manager MS. Having the SRM system retrieve preferences of future activity requests from the database and forward it to the Schedule-Manager MS and operating a scheduler MS to select a date which is in the entered date-range for each future activity request based on the retrieved preferences of future activity requests; and staffing plans retrieved from a staffing data database. Sending notifications to agents as to the selected date of each future activity request.
A system and method are provided to predict media playback requests of media files to decrease response times to the media playback requests. The system includes a processor and a computer readable medium operably coupled thereto, to perform predictive caching operations which include receiving metadata from an interaction stream after recording a media file of an interaction, determining contacts corresponding to users identified in the metadata that are recorded in the media file from the metadata, accessing an ML model for predictive caching of media files, determining, using the ML model and a plurality of model features for the ML model, a first prediction for a first playback of the media file, predicting the first playback of the media file by at least one of the contacts based on the first prediction, caching the media file in the data cache for a time period based on the predicting.
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.
A machine learning (ML) system and methods are provided that are configured to correlate text data with corresponding image data for image sentiment analysis. 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 image processing operations which include receiving image data for an image posted on a social networking platform, determining whether there is text data, performing image data extraction operations, analyzing the text data, determining and combining a score for the image and text data, determining an image sentiment or a text sentiment, calculating weighted metrics based on the image sentiment or the text sentiment, determining historical customer data interactions of the customer, and recommending one or more actions based on the weighted metrics.
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
G06V 30/262 - Techniques de post-traitement, p. ex. correction des résultats de la reconnaissance utilisant l’analyse contextuelle, p. ex. le contexte lexical, syntaxique ou sémantique
51.
SYSTEM AND METHOD FOR IMPROVING SURVEY RESPONSE RATE USING SURVEY OUTCAST WINDOW RECOMMENDATION ENGINE
Survey response systems and methods, and non-transitory computer readable media, including receiving, from a customer, a request for a customer survey, wherein the request comprises a plurality of attributes; evaluating each attribute against each feature on a feature importance matrix, wherein the feature importance matrix comprises a ranking of importance of a plurality of features affecting a survey response rate and a recommended time window associated with each feature; matching an attribute to a feature on the feature importance matrix; determining a matched feature having the highest ranked importance on the feature importance matrix; selecting a recommended time window associated with the matched feature having the highest ranked importance; and transmitting the customer survey to the customer in the recommended time window associated with the matched feature having the highest ranked importance to maximize the survey response rate.
A method and system for evaluating bot performance, including collecting, by a processor, bot performance data items, wherein the collecting includes directly collecting bot performance data items; and calculating bot performance data items based on collected bot performance metrics; producing a bot performance output including bot performance data items; and assessing the bot performance output. Assessment of the bot performance output may initiate bot quality management, wherein the bot quality management includes, assessing the bot update recommendations. Assessment of the bot update recommendations may result in initiating bot update.
G06Q 10/0639 - Analyse des performances des employésAnalyse des performances des opérations d’une entreprise ou d’une organisation
G06Q 30/015 - Fourniture d’une assistance aux clients, p. ex. pour assister un client dans un lieu commercial ou par un service d’assistance
53.
COMPUTERIZED-METHOD AND COMPUTERIZED-SYSTEM FOR GENERATING A COACHING SESSION HAVING COACHING CONTENT RELATED TO CUSTOMER EXPERIENCE, IN A WEB APPLICATION FOR MANAGING COACHING SESSIONS
A computerized-method for generating a coaching session having coaching content related to customer experience, in a web application for managing coaching sessions is provided herein. The computerized-method includes, based on received user selection of coaching content having first one or more groups, via a graphical User Interface (GUI), for an agent, operating a Customer Feedback Relevancy Score (CFRS) module, the CFRS module includes: (i) calculating a CFRS and presenting the calculated CFRS via the GUI. The CFRS indicates relevancy of user selection of coaching content having the first one or more groups to customer experience (CX); and (ii) determining second one or more groups of coaching content to maximize the CFRS and presenting the second one or more groups via the GUI and an increase in calculated CFRS to reach a maximum CFRS to improve CX.
G06Q 30/02 - MarketingEstimation ou détermination des prixCollecte de fonds
G06F 18/2413 - Techniques de classification relatives au modèle de classification, p. ex. approches paramétriques ou non paramétriques basées sur les distances des motifs d'entraînement ou de référence
G06Q 30/0282 - Notation ou évaluation d’opérateurs commerciaux ou de produits
54.
System and method for detecting agent sharing credentials
A computerized system and method may detect potentially fraudulent events where agent access credentials are used by an unauthorized party, based on calculations, comparisons, and analyses performed using recorded audio data, and execute corrective actions based on calculated results. A computerized system including a processor or a plurality of processors, a communication interface to communicate via a communication network with one or more remote computing devices, and a memory including a data store of a plurality of data items—which may, e.g., describe the remote computing devices and/or interactions involving the remote computing devices—may compare a plurality of voice signatures, which may describe calls from a plurality of remote computers, to a plurality of corresponding voice models—and, if the comparison results in a mismatch, perform a plurality of corrective actions (which may include, e.g., terminating one or more calls involving one or more remote computers).
A method and a system for revising a score associated with interaction feedback, wherein the method may include: traversing a score revision decision tree to categorize the interaction, based on interaction data and interaction feedback data associated with the interaction; and selecting, based on the categorization of the interaction, an indication of a probability that the score associated with the interaction feedback should be revised; wherein interaction data may include data extracted from the interaction; interaction feedback data may include data extracted from feedback about the interaction; and the score revision decision tree may include a decision tree data structure including at least one decision node, each decision node including to at least one data point of the interaction data or interaction feedback data.
Methods and systems of utilizing pursuit effectiveness scores to implement targeted employee training, provide specific employee feedback, improve employee training, and enhance employee motivation efforts. Gamification tactics, known as pursuits, are created with one or more key performance indicators (KPIs) to motivate customer service agents to perform well on the KPIs, evaluate agent engagement, and identify potential strengths and weaknesses for one or more agents. By utilizing a change score, completion score, and speed score for a pursuit, actionable insights can be generated for meaningful training and feedback actions while creating new pursuits on the same or similar objectives, assigning coaching programs, increasing the accuracy of pursuits with object calibration, identifying agents that require additional training, identifying agents that are excelling and may be potential mentors or role models for certain KPIs, and other actions related to the pursuit effectiveness.
G06Q 10/0639 - Analyse des performances des employésAnalyse des performances des opérations d’une entreprise ou d’une organisation
57.
COMPUTERIZED-METHOD AND COMPUTERIZED-SYSTEM FOR TRAINING AND APPLYING A MACHINE LEARNING (ML) TEXTUAL BEHAVIORAL IDENTIFICATION MODEL TO AUTHENTICATE AN AGENT, IN A DIGITAL MULTI-CHANNEL ENVIRONMENT
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. The ML-textual-behavioral-identification-model may be configured to process the retrieved textual responses of each agent to generate a profile-identity-data for each agent to be used to authenticate identity of the agent; (ii) receiving a textual-response of each agent, when the agent starts an interaction with a customer; (iii) applying the textual-response of the agent to the ML-textual-behavioral-identification-module to authenticate an identity of the agent in real-time by calculating an imposter-probability score for the agent and; (iv) sending the imposter-probability score to a file-management-system to take one or more actions when the imposter-probability score is above a preconfigured-threshold.
Evaluation parking systems and methods, and non-transitory computer readable media, including determining that an evaluator is on leave; based on evaluation tasks assigned to the evaluator, retrieving evaluation tasks selected by the evaluator for reassignment, or reading a parking configuration and determining that evaluation tasks meet a criteria of the parking configuration; parking the retrieved evaluation tasks and/or the determined evaluation tasks to an interaction sample segment datastore; obtaining the parked evaluation tasks; and reassigning the obtained parked evaluation tasks in an evaluation task assignment datastore.
42 - Services scientifiques, technologiques et industriels, recherche et conception
Produits et services
non-downloadable software for voicemail broadcasting; non-downloadable software for providing voicemail communication services in the field of telecommunications; Non-downloadable software for providing transmission and exchange of voice in the field of telecommunications; Non-downloadable software for telecommunications
60.
SYSTEM AND METHOD TO IDENTIFY AND QUANTIFY MONOTONY IN COMPUTER RELATED PROCESSES
A computerized system and method may quantify a level or degree of monotony associated with the execution of repetitive tasks involving a plurality of computing devices—and may accordingly determine or choose a task schedule for which the smallest degree of monotony is calculated. A computerized system comprising one or more processors, a communication interface to communicate via a communication network with remote computing devices, and a memory including data items describing tasks involving the remote computing devices, may be used for selecting remote computers based on the stored data items; calculate monotony indices for the selected computing devices based on, e.g., a plurality of tasks and corresponding time windows (in which, e.g., the tasks were performed or executed); automatically documenting the calculated monotony indices in a database; and transmitting instructions to automatically execute computer operations on a remote computer based on calculated monotony indices.
A computerized system and method may generate computer automation opportunities based on segmenting action sequences from action data and/or information items. A computerized system including a processor or a plurality of processors, and a memory including a data store of a plurality of data items describing actions input to a computer may be used to receive an input query or a plurality of actions input to a computer; segment action sequences from the stored data items based on the query; and produce automation candidates based on the segmented sequences. Embodiments of the invention may include generating, by a machine learning model, vector embeddings for action sequences, calculating similarity scores for sequences based on the embeddings, and mining a plurality of action subsequences based on, a group or set of similar sequences, as well as additional and/or auxiliary procedures and operations.
A computer-implemented method for displaying real-time code of embedded code in a browser-window of a software-application. The computer-implemented method includes collecting processes related to software applications running on an OS by using an API. For each process: searching for browser windows including elements used to collect or manipulate data on the browser-window to yield a list of browser-windows; receiving a selection of a browser-window; casting elements used to collect or manipulate data on the browser-window of the selected browser-window into a related object that is implementing an interface and storing it with an associated address of the browser-window in a database; and presenting real-time code of the elements used to collect or manipulate data on the browser-window to enable errors inspection therein and real-time updates of the code of the elements used to collect or manipulate data on the browser-window, via the interface of the related object.
Workforce management systems and methods, and non-transitory computer readable media, including receiving a time-off request from a first agent, wherein the time-off request comprises an agent ID of the first agent and a first requested date; providing, to a trained machine learning model, staffing data on the first requested date, skills of the first agent, pending time-off requests from other agents on the first requested date, and time-off taken by the first agent in the past; calculating, by the trained machine learning model, an approval probability of the time-off request; and displaying, on a graphical user interface, the approval probability of the time-off request to the first agent and to a manager.
Interval-specific, activity-based systems and methods, and non-transitory computer readable media, including activity-based data acquisition, activity-based forecasts, and activity-based staffing. Work items are automatically decomposed into data that is usable for workforce management purposes at the interval level. Volume/average handle time forecasts, staff requirement calculations, and schedules are driven by historical patterns of interval-specific activity required to resolve long duration work items.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
65.
SYSTEM AND METHOD FOR EFFICIENTLY DETERMINING TARGETED TRAINING OBJECTIVES FOR NEW HIRES
The present disclosure provides systems and methods for efficiently determining targeting training objectives for new hires. Employee performance is initially captured to provide a baseline performance, and is utilized, along with targeted performance goals, to determine an expected timeline for when an employee will reach a target performance threshold. This timeline can be used to generate SMART objectives (Specific agent attributes that can be Measured in their growth, which are Attainable and are Resource and Time bound), provide attainable goals and targets for employees, and develop a realistic and concrete training plan to implement.
Methods and systems for updating a first assignment of resources include: identifying, by a computing device, based on data describing a first assignment of resources, one or more time periods of the first assignment of resources for which there is an under-assignment of resources; and automatically generating, by the computing device, using data describing one or more auxiliary resources, data describing a second assignment of resources which assigns one or more of the auxiliary resources to the identified one or more time periods.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
67.
Computerized-method and computerized-system for sensitive data redaction from screenshots
A computerized-method for sensitive data redaction from screenshots, is provided herein. The computerized-method includes retrieving records of a sequence of screenshots from a database. Then, grouping the sequence-of-screenshots by one feature of one or more features to yield one or more groups. Each group includes screenshots having one common feature. Then, calculating a score for each pixel across all similar screenshots in each group. For each group of screenshots, blackening pixels in all screenshots having a score above a preconfigured threshold to yield data redacted screenshots. The score of each pixel above the preconfigured threshold indicates a high variance between screenshots in the group and a presence of sensitive data therein and then storing the data-redacted screenshots in a screenshots-database.
A computerized system and method may determine the recording and/or storing and/or deleting of data items received from remotely connected computer systems, which may be for example interaction recordings associated with a plurality of agents as part of their activity within a given system or organization, using a supervised classification machine learning based approach. A computerized system comprising one or more processors, a communication interface to communicate via a communication network with remote computing devices, and a memory including a data store of a plurality of data items, may be used for extracting features from a plurality of data items; predicting evaluation likelihood values based on the features; deriving storing percentages for a plurality of remote computing devices; and, based on likelihood values and storing percentages, recording and/or storing and/or deleting a plurality of data items from a data store or database.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
69.
METHOD FOR DETERMINING COGNITIVE LOAD-DRIVEN CONCURRENCY LIMITS BASED ON TEXT COMPLEXITY
A workforce management system and methods for managing a workload of an agent include receiving a first written interaction from a first customer; routing the first written interaction to an agent; determining a readability score of the first written interaction; aggregating the readability score with a plurality of past readability scores of written interactions assigned to the agent; creating a readability score scale based on the aggregated readability score with the plurality of past readability scores; creating a concurrency level scale based on a minimum concurrency level and a maximum concurrency level of the agent; correlating readability scores and concurrency levels using the readability score scale and the concurrency level scale; and adjusting the maximum concurrency level of the agent based on the correlation.
H04L 51/214 - Surveillance ou traitement des messages en utilisant le transfert sélectif
G06F 40/40 - Traitement ou traduction du langage naturel
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
70.
SYSTEM AND METHOD FOR AUTHORIZING TIME-OFF FOR A SKILL TO INCREASE AGENTS DIGITAL AVAILABILITY IN A CONTACT CENTER
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. When the agent time-off eligibility-quotient is below a preconfigured quotient-threshold the agent skill-based time-off request is rejected, and when the agent time-off eligibility-quotient is above the preconfigured quotient-threshold, operating an approver module to yield an authorization decision; and (b) sending the authorization decision, details of the skill and duration to a time-off recommendation module to forward the authorization decision, details of the skill and duration to one or more contact-center modules.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
Systems and methods for monitoring a quality of interactions include: receiving one or more quality metrics relating to one or more quality targets; determining, on a periodic basis, a current quality value for each of the one or more quality targets; calculating a deviation of the current quality value from a desired value of the quality target; weighting the one or more quality targets according to the calculated deviation; and determining a set of one or more interactions for review based on one or more quality metric deviations and the weighted quality targets.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
72.
System and methods to effectively route traffic and proactively scale infra in the partner region
Traffic routing and infrastructure scaling systems and methods, and non-transitory computer readable media, including receiving, by a primary region, incoming customer requests; determining, by a traffic control module, a traffic redirect quotient (TRQ) and a regional scale quotient (RSQ), wherein the TRQ indicates a percentage of the incoming customer requests needed to be redirected to a secondary partner region and the RSQ indicates a percentage of infrastructure scaling needed in the secondary partner region; receiving, by a recommendation processing module, the TRQ and the RSQ; automatically initiating, by the recommendation processing module, redirection of the percentage of the incoming customer requests indicated by the TRQ to the secondary partner region, scaling the percentage of infrastructure indicated by the RSQ in the secondary partner region, or both; and routing, by a network traffic manager service, the percentage of the incoming customer requests indicated by the TRQ to the secondary partner region.
H04L 41/5067 - Mesures de la qualité du service [QoS] centrées sur le client
G06Q 30/01 - Services de relation avec la clientèle
H04L 43/04 - Traitement des données de surveillance capturées, p. ex. pour la génération de fichiers journaux
H04L 47/2425 - Trafic caractérisé par des attributs spécifiques, p. ex. la priorité ou QoS pour la prise en charge de spécifications de services, p. ex. SLA
H04L 41/5009 - Détermination des paramètres de rendement du niveau de service ou violations des contrats de niveau de service, p. ex. violations du temps de réponse convenu ou du temps moyen entre l’échec [MTBF]
H04L 41/5025 - Pratiques de respect de l’accord du niveau de service en réagissant de manière proactive aux changements de qualité du service, p. ex. par reconfiguration après dégradation ou mise à niveau de la qualité du service
H04L 45/302 - Détermination de la route basée sur la qualité de service [QoS] demandée
73.
System and methods to derive knowledge base article relevancy score
Coaching systems and methods, and non-transitory computer readable media, include analyzing an agent's interactions to identify knowledge gaps and specific topics where an agent has difficulties. An algorithm uses bootstrap sampling to verify that an agent's scores are significantly different from other agents' scores. The algorithm further uses a mutual information score to find topics that are associated with interactions having a high knowledge gap score.
A system is adapted to automatically evaluate compliance to data masking rules by a service provider. The system includes a processor and a non-transitory computer readable medium carrying instructions. The instructions include receiving a list of private data elements for which masking is required, and receiving a transcript of a particular interaction between the service provider and a customer, where the transcript includes data elements, at least of which is a private data element. The instructions also include analyzing the transcript with natural language processing to identify times or locations within where private data elements are recorded; determining, based on a set of compliance rules and the analyzed transcript, whether any private data element are unmasked at the identified times or locations; and, if a private data element is unmasked, issuing an output related to the unmasked private data elements.
Agent credibility systems and methods, and non-transitory computer readable media, include receiving a recorded interaction between a customer and a contact center agent; retrieving or determining a credibility divergence determinant (CDD) score of the contact center agent, wherein the CDD score is based on values of a plurality of credibility assessment factors for a time interval that are stored in a historical agent database, and wherein the lower the CDD score, the higher a credibility of the contact center agent; filtering out the recorded interaction when the CDD score is less than or equal to a defined threshold; and providing the recorded interaction to a supervisor of the contact center agent or a quality management application when the CDD score is greater than the defined threshold.
H04M 3/00 - Centraux automatiques ou semi-automatiques
H04M 3/51 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur
76.
SYSTEM AND METHOD FOR INCREASING PRODUCTIVITY OF AGENTS IN A CONTACT CENTER BY IMPROVING AN AUTOMATIC-SCHEDULING GENERATION IN A WORKFORCE MANAGEMENT (WFM) APPLICATION
A computerized-method for increasing productivity of agents in a contact-center by improving an automatic-scheduling generation in a Workforce-Management (WFM) application, is provided herein. The computerized-method includes operating an Agent-Productivity-Score-Generator (APSG) module, for each agent. The APSG module includes: (i) receiving an activity-type and a period for agents shift-placement; (ii) retrieving historical-data of a preconfigured number of metrics for each scheduled-shift during a preconfigured period; (iii) calculating a weighted-sum of the retrieved historical-data of the preconfigured number of metrics and preconfigured attributed weight thereof to yield an Agent-Productivity-Score (APS) for each shift; and (iv) selecting a shift having a highest APS and adding the selected shift of the agent to a list-of-maximum-shifts. When the list-of-maximum-shifts is having all agents in a data-store then the list-of-maximum-shifts may be sent to the WFM for an automatic shift-schedule generation for the activity-type and a preconfigured period, based on the list-of-maximum-shifts and other input parameters.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
H04M 3/51 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur
77.
SYSTEM AND METHOD FOR MONITORING AN UNAVAILABILITY-INTERVAL TYPE TO ADJUST AGENT-SCHEDULE TO BE IN ADHERENCE AND TO BALANCE WORKFORCE, IN A CONTACT-CENTER
A computerized-method for monitoring an unavailability-interval type to adjust agent-schedule to be in adherence and to balance workforce, in a contact-center, is provided herein. The computerized-method includes operating a schedule-adjustment module. The schedule-adjustment module includes operating a rule-engine to carry out a rule, based on an unavailability-interval type for monitoring and a time-threshold; for each agent: (i) checking if the agent is in adherence by retrieving agent-state and comparing it with agent currently scheduled-activity. (ii) when the agent is in adherence, retrieving a scheduled-activity after the time-threshold from current-time to calculate an interval-range when the retrieved scheduled-activity is the same as the unavailability-interval type for monitoring operating an intervals-staffing-evaluation module to find an optimum interval, during the calculated interval-range; (iii) when an optimum interval has been found, sending the agent a notification a suggestion to postpone the next-interval-scheduled activity to the optimum interval and upon approval, adjusting the agent-schedule accordingly.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
78.
SYSTEMS AND METHODS FOR AUTOMATION DISCOVERY RECALCULATION USING DYNAMIC TIME WINDOW OPTIMIZATION
A system and method may identify computer-based processes which may be candidates for automation. Embodiments may involve a semi-supervised approach for identifying processes as automation opportunities. Transition probabilities for pairs of routines within a candidate process may be calculated based on a set of instances of the process (e.g., in a dataset of computer actions) using a dynamic time-window optimization procedure, where transition times may be measured for a plurality of instances of a first and second routines of a given pair of routines, and where statistical distributions may be calculated and used for deriving one or more time windows, describing a predetermined percentile (e.g., the 70th percentile) of the measured transitions and used for estimating a transition probability for the pair of routines. In some embodiments, the input set of transitions and routines may be generated by a user or business analyst using a graphical user interface (GUI).
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
79.
SYSTEMS AND METHODS FOR ADVANCED TEXT TEMPLATE DISCOVERY FOR AUTOMATION
A system and method may identify computer-based processes involving the use of text templates which may be candidates for automation. Using one or more computers, embodiments of the invention may sort low-level user action information for a given process which may be received as input; search for a plurality of strings pasted multiple times in the sorted information; discard one or more of the strings found from the search which correspond to a set of criteria (e.g., found to be shorter, or pasted, or edited fewer times than a predetermined threshold); group the strings according to an identifier of the target app where each string was pasted; iteratively calculate a similarity score for strings or groups of strings, and cluster strings or groups for which the similarity score is below a predetermined threshold, to form final clusters; and suggest the final clusters as automation opportunities to, e.g., a business analyst.
A computerized-system for converting a time-off request of an agent to a shift-trade with another agent or to a self-swap schedule, in a contact center is provided here in. Upon receiving a time-off request from a source-agent, operating a Time-off Convertor (TC) module. The TC module includes (i) searching open trade requests in dates where the source-agent doesn't have a scheduled-shift, to yield a list-of-trading-agents; (ii)retrieving from the yielded list-of-trading-agents, compatible-agents who do not have a scheduled-shift in the specified date; (iii) presenting the compatible-agents, via a display unit; (iv) enabling the source-agent a selection of an agent from the presented compatible-agents and upon selection of the agent by the source-agent, sending an approval request to the agent; and (v) upon acceptance of the agent, sending to the source-agent and to the agent a trade-success-notification, and operating change of scheduled shifts in one or more WFM MSs.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
A computer based system and method for automatically transmitting an electronic notice to a publisher of negative content, that includes: monitoring at least one electronic social media channel to identify content that is relevant to an entity; analyzing the identified content to identify content with negative sentiment, and an identity of the publisher of the content with the negative sentiment; and initiating an automated interaction with the publisher. Initiating the interaction may include posting an automatic reply to a message in the electronic social media channel that includes the content with the negative sentiment and/or initiating an automatic phone call.
G06Q 50/00 - Technologies de l’information et de la communication [TIC] spécialement adaptées à la mise en œuvre des procédés d’affaires d’un secteur particulier d’activité économique, p. ex. aux services d’utilité publique ou au tourisme
A computerized system and method for allocating multi-functional or multi-feature resources (which may handle multiple functions or tasks, e.g., simultaneously) for a plurality of time intervals, including: transforming an initial allocation matrix (which may associate each resource with a single function, task, or feature - and may not address simultaneous handling of tasks or task types by the resources) into an updated allocation matrix, where the updated allocation matrix includes a plurality of feature matrices describing different multi-feature resources to be allocated; predicting, using a machine learning (ML) model, expected service metrics for the updated allocation matrix; and providing a final allocation matrix based on the expected service metrics. Embodiments may perform iterative calculations and/or transformations of data to improve allocation matrices and provide a final allocation matrix for which predicted service metrics correspond to required or optimal service metrics.
Screen recording systems and methods, and non-transitory computer readable media, include receiving, from an applications server, a recording configuration including a local recording trigger, wherein the local recording trigger includes a start screen recording event and a stop screen recording event; monitoring activity on a device of a contact center agent; initiating recording of a screen of the device when the start screen recording event is detected; transmitting data captured in the recording to a recorder; stopping the recording of the screen of the device when the stop screen recording event is detected; and stopping transmission of the data captured in the recording to the recorder.
H04M 3/00 - Centraux automatiques ou semi-automatiques
G06F 3/0484 - Techniques d’interaction fondées sur les interfaces utilisateur graphiques [GUI] pour la commande de fonctions ou d’opérations spécifiques, p. ex. sélection ou transformation d’un objet, d’une image ou d’un élément de texte affiché, détermination d’une valeur de paramètre ou sélection d’une plage de valeurs
G06F 3/14 - Sortie numérique vers un dispositif de visualisation
H04M 3/51 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur
84.
METHOD FOR PRIORITIZING AGENTS FOR WORKING FROM OFFICE VIA A WFM APPLICATION IN A HYBRID CONTACT CENTER WORK ENVIRONMENT
A computerized-method for prioritizing agents for working from office via a WFM application, in a hybrid-contact-center work environment. The computerized-method includes: when creating a schedule for a period via the WFM application: getting skills for each day in the schedule, each skill having an associated priority; and allocating agents for each skill in descending order of priority associated to the skill by: for each skill that requires agents to work from office: getting forecast agents count for the skill; and allocating agents to office location based on office capacity and a calculated Agent Work From Office (AWFO) score in ascending order and Agent Health (AH) score greater than ‘0’ until office capacity is full or agent requirements for the skill are fulfilled; when the agents count for the skill is not fulfilled, allocating agents to work from home based on an associated Agent Home Productivity (AHP) score in descending order.
G06Q 10/0631 - Planification, affectation, distribution ou ordonnancement de ressources d’entreprises ou d’organisations
G06Q 10/0639 - Analyse des performances des employésAnalyse des performances des opérations d’une entreprise ou d’une organisation
G06Q 10/04 - Prévision ou optimisation spécialement adaptées à des fins administratives ou de gestion, p. ex. programmation linéaire ou "problème d’optimisation des stocks"
85.
System and method for predicting service metrics using historical data
A method for allocating resources for a plurality of time intervals, including: receiving a forecasted workload and at least one required service metric value; applying a search algorithm to identify an initial allocation assignment; inputting the assignment to a machine learning algorithm, the machine learning algorithm trained on historic data of past intervals; predicting an expected service metric value provided by the initial allocation assignment; adjusting the initial allocation assignment based on a difference between the expected service metric value and the corresponding required service metric value; iteratively repeating the applying, inputting, predicting, and adjusting operations until one of: the expected service metric value predicted for an adjusted allocation assignment is within a predetermined distance of the corresponding at least one required service metric value for the interval; or a predetermined time has elapsed.
Methods and systems for, upon receipt of a second computer data stream, predicting a change in processing a first computer data stream, include: receiving, at a computing device, the first computer data stream; generating a first data sequence comprising a time of receipt of the first computer data stream; receiving the second computer data stream; generating a second data sequence comprising a time of receipt of the second computer data stream; sending the first and second data sequences to a prediction model; predicting, by the prediction model, at least one change in at least one metric associated with processing the first computer data stream, the predicted change based at least in part on the first and second data sequences; and sending, by the prediction model, to the computing device, the at least one change in the at least one metric associated with processing the first computer data stream.
A computerized-method for operating an effective cloud-based gamification application pursuit is provided herein. In a cloud-computing environment comprising a plurality of tenants, a cloud-based gamification application, a data store of pursuit-data, and a database of pursuit-templates, the cloud-based gamification application is associated with each on-premise Performance Management (PM) application of each tenant and operating a pursuit-module. The pursuit-module includes: (a) receiving pursuit-data, (b) operating a pursuit-microservice to retrieve data from a data-store associated to the on-premise PM application of the tenant; and (c) operating a recommendation engine to: (i) operate machine learning models to predict a difficulty-level and a pursuit-type based on the received pursuit-data and the retrieved data; (ii) retrieve pursuit-templates and a related score of each pursuit-template, based on the predicted difficulty level and pursuit type; and (iii) select from the retrieved pursuit-templates a pursuit-template and schedule the selected pursuit-template, based on the related score.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
Semantic search systems and methods, and non-transitory computer readable media, include receiving divided text of at least two participants from a customer interaction; applying a clustering algorithm to the divided text to create a plurality of word clusters per participant, wherein each word cluster comprises topic words, phrases, or sentences; applying a word-embedding algorithm to the topic words, phrases, or sentences in each word cluster to produce a numeric representation of each word cluster; and storing the numeric representation of each word cluster and the topic words, phrases, or sentences in each word cluster in a document.
A computerized-method for calculating an agent skill-satisfaction-index and utilization thereof, is provided herein. The computerized-method includes operating an Agent-Skill-Satisfaction-Index (ASSI)-scoring module. The ASSI-scoring module may include: (a) operating an interaction microservice to retrieve one or more agent's interactions which were conducted during the first preconfigured-period and related interaction-level key performance indicator (KPI)s, from a data store of interactions; (b) organizing the retrieved one or more agent's interactions in one or more groups by one or more second-preconfigured-periods; (c) checking a duration of each skill from a set of skills of an agent if it is assigned to the agent above a preconfigured-period-threshold to be marked as a related-skill; (d) for each group, calculating a skill-core based on a calculated evaluation-sum of each interaction in the group that is associated with a related-skill; and (e) calculating an ASSI-score based on the calculated one or more skill scores.
A data storage system configured to optimize selection of a plurality of data storage devices. The system includes a processor and a computer readable medium operably coupled thereto, the computer readable medium including a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, to perform storage device selection operations which include detecting and gathering storage device information for storing data recordings to the plurality of data storage devices, determining, by a storage load balancer, a plurality of storage efficiency scores for the plurality of data storage devices using a loss function and the gathered storage device information, generating a storage efficiency table, and assigning, by the storage load balancer, a first data recording to one of the plurality of data storage devices based on the storage efficiency table and an efficiency score threshold for the plurality of storage efficiency scores.
A computerized-method for automatically pointing on an influencer on a measured performance change is provided herein. The method may include: receiving one or more metrics from a user to construct a Key Performance Indicators (KPI); retrieving data related to one or more agents during a predefined period for the one or more metrics from one or more performance management databases; calculating a change in KPI; when the calculated change in KPI is negative: calculating an influence of each metric on the calculated change in KPI; calculating an influence of each agent on the calculated change in KPI; checking each agent having a negative change of a goal-accomplished-percentage to downgrade a contribution-factor of an agent having a top-negative-influence on the calculated change in KPI; and forwarding the downgraded contribution factor of the agent having the top-negative-influence on the calculated change in KPI to a downstream application.
A computer based system and method for identifying complaint interactions, including: detecting appearances of linguistic structures related to complaints in an interaction; calculating at least one sentiment metric of the interaction; and classifying the interaction as being or not being a complaint interaction based on the detected linguistic structures and the at least one sentiment metric, for example using a trained supervised learning model.
G06N 20/10 - Apprentissage automatique utilisant des méthodes à noyaux, p. ex. séparateurs à vaste marge [SVM]
G06Q 30/016 - Fourniture d’une assistance aux clients, p. ex. pour assister un client dans un lieu commercial ou par un service d’assistance après-vente
G10L 15/16 - Classement ou recherche de la parole utilisant des réseaux neuronaux artificiels
H04M 3/493 - Services d'information interactifs, p. ex. renseignements sur l'annuaire téléphonique
H04M 3/51 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur
H04M 3/523 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur avec répartition ou mise en file d'attente des appels
H04M 11/10 - Systèmes de communication téléphonique spécialement adaptés pour être combinés avec d'autres systèmes électriques avec systèmes d'enregistrement et de reproduction de dictée
93.
STAFF REQUIREMENT GENERATION METHOD AND SYSTEM ACCOUNTING FOR MULTI-SKILL AND MULTI-SESSION EFFICIENCY
A fast, robust and efficient staff requirement calculation engine that estimates staffing requirements on the spot to account for multi-skill omni-channel efficiency. The calculation engine may be used off-line for pre-calculating staff requirements in a multi-skill environment for different queues at different intervals and on-line for instantaneous responses to demands for staff requirement calculation.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
94.
SYSTEM AND METHOD FOR MEASURING AN AGENT ENGAGEMENT INDEX AND ASSOCIATING ACTIONS TO IMPROVE THEREOF
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.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
A computerized-method for determining an agent-proficiency when addressing concurrent customer sessions via one or more channel types and utilization thereof is provided herein. The computerized-method includes operating a Concurrent-Sessions-Handling-Agent-Proficiency (CSHAP) module. The CSHAP-module includes: (a) operating an interactions-module to retrieve one or more interactions and metadata thereof of the agent; (b) for each interaction, determining if the interaction has been handled with concurrent interactions; (c) for each determined interaction as handled with concurrent interactions, checking in the metadata if the interaction has one or more defocused-events; (d) calculating a CSHAP-score for the agent based on one or more attributes from the metadata of the interaction to provide an indication as to an ability of the agent to address concurrent customer sessions; (e) storing the calculated CSHAP-score in a data-store; and (f) sending the CSHAP-score to one or more applications, to take one or more follow-up actions based on the CSHAP-score.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
H04M 3/51 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur
H04M 3/523 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur avec répartition ou mise en file d'attente des appels
96.
SYSTEM AND METHOD FOR PRIORITIZING AGENTS FOR WORKING FROM OFFICE IN A HYBRID CONTACT CENTER WORK ENVIRONMENT
A computerized-method for prioritizing agents for working from office, in a hybrid contact center work environment, is provided herein. The computerized-method includes operating an Agent Work From Office (AWFO) Prioritization Analytics module. The AWFO Prioritization Analytics module includes: (i) for each agent in the data store of agents’ metrics calculating an Agent Health (AH) score; (ii) when the AH score is ‘1’ then (a) calculating: (a.i) Agent Home Productivity (AHP) score; (a.ii) Agent Skills Prioritization (ASP) score; and (a.iii) agent’s preferences to work from office indicator; (b) determining an A WFO score based on the AHP score, the ASP score and the agent’s preferences to work from office indicator; and (c) sending the determined A WFO score to a Workforce Management (WFM) application to be presented via a User Interface (UI) thereof.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
97.
SYSTEM AND METHOD FOR IDENTIFYING NONADHERENCE TO CONTACT CENTER PRACTICE RULES
A computerized-method for identifying nonadherence to contact-center practice rules is provided herein. The computerized-method includes operating a data-analyzer module. The said data-analyzer module includes: (i) retrieving a set of rules; (ii) monitoring activities of each user via one or more product-applications by receiving a stream of data related to the activities from the one or more applications. The stream of data may include details of the monitored activities; (iii) comparing details of the monitored activities with each rule in the set of rules to identify one or more activities that are breaching a rule from the set of rules; (iv) for each activity of a related-user from the identified one or more activities: (a) notifying the related-user about a guideline-breaching via a computerized-device of the related-user; and (b) updating the data store of exceptions with the details of the activity that breached the rule from the set of rules.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
H04M 3/51 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur
98.
SYSTEMS AND METHODS FOR DECOMPOSITION IN WORKFORCE OPTIMIZATION WITH SEARCH SUB-PROBLEMS
Systems and methods are provided for solving workforce management scheduling optimization decomposing and iteratively. Execution of a master problem can occur to select a best schedule among generated schedules for each employee of a group of employees while enforcing one or more global constraints. The generated schedule can be determined by execution of one or more sub-problems, each of the one or more sub-problems can be enforced work rules for the respective employee through the use of reduced cost for the employee. A flexible objective function can be executed to account for workforce management schedule wide metrics, including fitness of schedule to demand, fairness among the group of employees, schedule preferences and others.
G06Q 10/06 - Ressources, gestion de tâches, des ressources humaines ou de projetsPlanification d’entreprise ou d’organisationModélisation d’entreprise ou d’organisation
A system and method for real-time fraud detection with a social engineering phoneme (SEP) watchlist of phoneme sequences may perform real-time fraud prevention operations including receiving incoming call interactions and grouping the call interactions into one or more clusters, each cluster associated with a speaker's voice based on voiceprints. For a pair of voiceprints in a cluster, a phoneme sequence is extracted for each voice print. From the extracted phoneme sequences, a similarity score is then calculated to determine if a match exists between the extracted phoneme sequences based on a threshold. If determined a match exists, the phoneme sequence may be added to a SEP watchlist.
A system and methods are provided to analyze audio signals from an incoming voice call. The system includes a processor and a computer readable medium operably coupled thereto, to perform voice analysis operations which include receiving a first audio signal comprising a first audio waveform of a first speech between at least two users during the incoming voice call, accessing speech segment parameters for analyzing the audio signals, determining one or more talk-over segments in the first audio waveform using the speech segment parameters, extracting audio features from each of the one or more talk-over segments, determining, using a machine learning (ML) model trained for interruption analysis of the audio signals, whether each of the one or more talk-over segments are a negative interruption or a non-negative interruption based on the audio features, and determining whether to output a first notification for the negative interruption or the non-negative interruption.
G10L 15/02 - Extraction de caractéristiques pour la reconnaissance de la paroleSélection d'unités de reconnaissance
G10L 15/04 - SegmentationDétection des limites de mots
G10L 15/20 - Techniques de reconnaissance de la parole spécialement adaptées de par leur robustesse contre les perturbations environnantes, p. ex. en milieu bruyant ou reconnaissance de la parole émise dans une situation de stress
G10L 15/22 - Procédures utilisées pendant le processus de reconnaissance de la parole, p. ex. dialogue homme-machine
G10L 25/78 - Détection de la présence ou de l’absence de signaux de voix
H04M 3/51 - Dispositions centralisées de réponse aux appels demandant l'intervention d'un opérateur
