SYSTEMS AND METHODS RELATING TO A CONTACT CENTER MEDIA SERVICES

    公开(公告)号:US20240205334A1

    公开(公告)日:2024-06-20

    申请号:US18121213

    申请日:2023-03-14

    CPC classification number: H04M3/5175 G06Q30/016 H04M3/5191

    Abstract: A method of providing customer relations services to customer on behalf of a contact center by utilizing agent devices, the agent devices being updated over a network with content items and the content items being processed by the agent devices so to provide the customer relation services. The method includes: receiving a request for a first content item from a first agent device of the agent devices; identifying candidate agent devices from the agent devices as ones of the agent devices capable of providing the first content item; selecting, via selection rules included in control logic, a selected agent device from the candidate agent devices for sharing the first content item with the first agent device; and transmitting instructions to the selected agent device initiating the selected agent device to transfer the first content item with the first agent device.

    SYSTEMS AND METHODS RELATING TO PREDICTIVE ANALYTICS USING MULTIDIMENSIONAL EVENT REPRESENTATION IN CUSTOMER JOURNEYS

    公开(公告)号:US20240202096A1

    公开(公告)日:2024-06-20

    申请号:US18545105

    申请日:2023-12-19

    CPC classification number: G06F11/3447 G06F11/3438

    Abstract: A method that includes the steps of: generating, via a training data process, training data samples from respective journey data samples, the journey data samples comprising a customer journey represented by a sequence of events, values associated with respective event attributes, and journey outcome; and training a machine learning model using the training data samples. The training data process includes generating a vector embedding for each of the events included within the journey data samples that captures the value for each of the event attributes by: dividing the list of event into low and high cardinality groups via a cardinality threshold; for the low cardinality groups, categorically encoding the values according to a total number of unique values appearing therein; for the high cardinality groups: clustering the values and categorically encoding the values according to the group it resides in.

    SYSTEM AND METHOD OF TRAINING MACHINE-LEARNING-BASED MODEL

    公开(公告)号:US20240119370A1

    公开(公告)日:2024-04-11

    申请号:US17962729

    申请日:2022-10-10

    Inventor: IGAL MAZOR

    CPC classification number: G06N20/20 G06K9/6257

    Abstract: A system and method of training a machine-learning (ML) based model by at least one processor may include receiving an initial dataset, including a plurality of annotated data samples; based on the initial dataset, training at least one ML-based first-level model to perform a first-level task; based on training the at least one ML-based first-level model, calculating at least one characteristic, representing, for each data sample, a value of contribution into a training of a ML-based second-level model to perform a second-level task; omitting a subset of data samples from the initial dataset based on the at least one characteristic, to obtain a target dataset; and training ML-based second-level model, to perform the second-level task, based on the target dataset.

    ANALYZING LEARNING CONTENT VIA AGENT PERFORMANCE METRICS

    公开(公告)号:US20220398682A1

    公开(公告)日:2022-12-15

    申请号:US17344191

    申请日:2021-06-10

    Abstract: A method of automated analysis of learning content's impact on agent performance according to an embodiment includes automatically determining a first set of performance metrics for an agent for a predefined first period before the agent participated in a learning module in response to notification of completion in the learning module, automatically determining a second set of performance metrics for the agent for a predefined second period after the agent participated in the learning module in response to determining that the predefined second period has elapsed, computing a first set of performance metric differences between those sets of metrics, and performing correlation analysis to determine whether the learning module significantly effects one or more performance metrics of the agent based on a plurality of performance metric differences computed for a plurality of agents, wherein the plurality of performance metric differences includes the first set of performance metric differences.

    SYSTEMS AND METHODS RELATING TO ARTIFICIAL INTELLIGENCE LONG-TAIL GROWTH THROUGH GIG CUSTOMER SERVICE LEVERAGE

    公开(公告)号:US20220366427A1

    公开(公告)日:2022-11-17

    申请号:US17742090

    申请日:2022-05-11

    Abstract: A method of training an artificial intelligence system to handle long-tail interactions according to an embodiment includes receiving a user question from a user, analyzing the user question with a natural language understanding engine to determine whether an intent of the user question matches an answer in an answer knowledgebase of the system, transferring at least the user question of the interaction to a primary subject matter expert in response to determining that the intent of the user question does not match an answer in the answer knowledgebase, receiving an expert answer to the user question from the primary subject matter expert, transferring an interaction package including the user question and the expert answer to at least one evaluator for validation, and automatically training the natural language understanding engine based on the user question and the expert answer in response to successful validation of the expert answer.

    AUTOMATED INCENTIVIZER FOR CONTACT CENTER AGENTS USING VARIABLE POINTS VALUATION

    公开(公告)号:US20250148386A1

    公开(公告)日:2025-05-08

    申请号:US18387923

    申请日:2023-11-08

    Abstract: A method for incentivizing agents with scheduling perks that includes: receiving a workload forecast; receiving a staffing plan; receiving data describing a service level target; receiving data describing the scheduling perks; performing a valuation routine for determining a value of points in relation to trading for the scheduling perks during; and performing an offer routine offering the scheduling perks to the current agents per the determined value of the points. The valuation routine includes: measuring current shift performance data; providing the staffing plan, the workload forecast, and the current shift performance data as inputs to a predictive model and calculating therewith an actual forecasted target adherence for the service level target; comparing the actual forecasted target adherence against an acceptable threshold to determine a valuation parameter; and valuing the points according to a direct relationship with the valuation parameter.

    AUTOMATED INCENTIVIZING TOOL FOR CONTACT CENTER AGENTS

    公开(公告)号:US20250148385A1

    公开(公告)日:2025-05-08

    申请号:US18387915

    申请日:2023-11-08

    Abstract: A method for incentivizing contact center agents with scheduling perks that includes: receiving a workload forecast and staffing plan for a current shift; receiving a service level target; receiving types of scheduling perks; performing a selection routine for determining a select scheduling perk for offering to a select agent; and sending a scheduling perk offer via electronic communication to the select agent. The selection routine may include: selecting a proposed scheduling perks and a proposed agent; modifying the staffing plan to create a proposed staffing plan that reflects the proposed scheduling perk; predicting a proposed forecasted target adherence using the modified staffing plan; determining whether the proposed forecasted target adherence satisfies a threshold defined by an acceptable forecasted target adherence and, if so, deeming the proposed scheduling perk as select scheduling perk and proposed agent as select agent.

    Technologies for blockchain-based data transparency and authentication

    公开(公告)号:US12273463B2

    公开(公告)日:2025-04-08

    申请号:US18452446

    申请日:2023-08-18

    Abstract: A method according to one embodiment includes transmitting, by an enterprise system, a data request for user data stored in a software wallet to a software wallet provider, transmitting, by the software wallet provider, an authorization request to an end user device of the user in association with the data request, creating, by the end user device, a transaction signed with a first private cryptographic key to generate a signed transaction, transmitting, by the end user device, the signed transaction to the software wallet provider, signing, by the software wallet provider, the signed transaction with a second private cryptographic key to generate a multi-signed transaction, transmitting, by the software wallet provider, the multi-signed transaction to the enterprise system, and validating, by the enterprise system, the multi-signed transaction using a public cryptographic key associated with the first private cryptographic key and the second private cryptographic key.

    Systems and methods relating to evaluating and measuring an experience using an experience index

    公开(公告)号:US12265938B2

    公开(公告)日:2025-04-01

    申请号:US17890952

    申请日:2022-08-18

    Abstract: A method for measuring experience quality. The method including: receiving key experience aspects (“KEAs”); administering pre-surveys to a representative subset of the experience audience, including an importance pre-survey requesting relative importance between the KEAs; and perception pre-survey requesting how closely perceptions align with each KEAs; calculating importance weights and perception weights based on the pre-surveys; performing a general survey process that includes surveying the experience audience to provide a quality rating indicating how well each of the KEAs was delivered based on their own experience; and calculating an Experience Index score as a measure of the quality of the experience that is an aggregation of the received quality ratings weighted by at least one of the importance weights or the perception weights.

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