128 results about "Call centre" patented technology

The invention relates to the technical field of call center control, and discloses an unmanned vehicle formation control and obstacle avoidance reconstruction system based on complex road conditions. The system call data acquisition module is used for acquiring multi-source interaction data in real time; the dynamic feature extraction module is used for performing semantic intention hierarchical analysis on the voice stream text conversion data, performing event fragment segmentation on the user behavior time sequence data, and generating an operation track feature vector; the scene clustering engine module is used for performing space-time alignment on the semantic intention hierarchical analysis result and the event fragment segmentation result to generate a multi-dimensional scene clustering tag; the strategy matching core module is used for retrieving an interaction strategy set matched with the current scene from a distributed strategy library according to the multi-dimensional scene clustering label and generating a dynamic control instruction sequence; and the instruction distribution execution module is used for distributing the dynamic control instruction sequences to corresponding seat terminals and voice routing equipment after sorting the dynamic control instruction sequences according to priorities.

The embodiment of the present specification provides a kind of gas resource scheduling method and Internet of Things system based on wisdom gas call center, the method is realized by the gas resource scheduling Internet of Things system based on wisdom gas call center, comprising: obtaining the gas use data of different types of gas users, and determining gas use characteristics;Obtain gas demand data;Based on gas use characteristics, gas demand data and the gas maintenance data of wisdom gas call center, predict whether the gas supply of multiple second times meets the gas demand;In response to the gas demand that the gas supply of at least one second time in multiple second times cannot meet, adjust gas allocation scheme.

The embodiment of the specification provides a gas operation method and an Internet of Things system based on a smart gas call center. The method comprises the following steps: acquiring gas user call data of the call center; predicting demand information of different types of users based on the gas user call data, wherein the demand information at least comprises gas product demand and gas service demand; determining and pushing gas operation push features based on the demand information of different types of users, wherein the gas operation push features comprise push type features and push content features.

Systems and methods are disclosed for transitioning multi-channel call center customer experience via user interfaces. An example method includes obtaining, by a communications server, contact information of a contact. The example method includes establishing, by the communications server, a first connection between a contact and an agent terminal over a first communication channel. The example method includes establishing, by the communications server, a second connection between the contact and the agent terminal over a second communication channel. The example method includes sending a first communication to the contact from the agent terminal across the second communication channel. The example method includes receiving, at the agent terminal, a second communication from the contact across the second communication channel.

A system, device, and method to reconnect a terminated communication to the original queue and provide queue status over a different communication channel. The method includes receiving a first communication over a first communication channel and placing the first communication in a contact center queue. The method also includes providing a user with an option to terminate the first communication over the first communication channel and receive queue status information over a second communication channel, and in response to the user selecting the option: terminating the first communication while maintaining a queue status in the contact center queue for the first communication; providing the queue status information; in response to the queue status of the first communication being within a threshold, notifying the user to initiate a second communication over the first communication channel; and replacing the first communication in the contact center queue with the second communication.

A method of leveraging machine learning to predict empathy for improved contact center interactions according to an embodiment includes receiving, by a computing system, at least one user message from a real-time contact center interaction with a user, generating, by an artificial intelligence system of the computing system, at least one empathy score based on the at least one message using the machine learning, wherein each of the at least one empathy score is indicative of a real-time empathy of the user, generating, by the artificial intelligence system of the computing system, an empathetic text response to the at least one user message based on the at least one empathy score, and responding to the at least one user message in the real-time contact center interaction based on the empathetic text response generated by the artificial intelligence system of the computing system.

Embodiments are directed to systems and techniques to perform authentication operations in a call center computing environment with transcoded encrypted data.

Systems and methods for improving query creation and AQM are provided. A user interface is provided that allows an analyst to generate and test queries. After the analyst provides a query, one or more subsets of previous call center interactions are selected to test the provided query using methods such as a large language model or string vectorization. Once the subsets of interactions are selected, an LLM is used to evaluate the query against the subset. The evaluations may indicate interactions which were positive and which interactions were negative and may include quotes from the interactions that support the evaluations. The evaluations are presented to the analyst for review, and the analyst may revise the query in view of the evaluations. Once the analyst is satisfied with the performance of the query, the query may be used by the LLM to perform AQM for new interactions in the call center.

Embodiments are directed to systems and techniques to perform device matching during a customer service call. In some examples, the techniques provided herein include receiving, at a call center system, a communication from a device associated with a user account. The method further includes, in response to receiving the communication, sending a message to the device associated with the user account, the message including a link for a user to interact with on a user interface of the device, wherein interaction with the link by the user causes initiation of an application on the device for receiving encrypted data from a contactless card associated with the user account. The method further includes receiving, by the call center system, from an authentication server, an authorization message indicating whether the user account is authorized to maintain the communication based on an evaluation of the encrypted data by the authentication server.

A system for authenticating the identity of a caller (i) receiving one or more online credentials of a caller initiating a phone call, where the one or more online credentials include one or more pieces of biometric information associated with the caller, and the one or more online credentials are received from a mobile device associated with the caller; (ii) requesting one or more additional online credentials associated with the mobile device; (iii) receiving the one or more additional online credentials; (iv) receiving telephone authentication information associated with the phone call; (v) authenticating the caller based, at least in part upon, the one or more online credentials, the one or more additional credentials, and the telephone authentication information; (vi) generating authentication status information based on the authentication of the caller; and (vii) transferring the authentication status information and the phone call to a call recipient.

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.

Systems, devices, and methods for determining whether a segment of speech was generated by a human or by a machine, such as a robotic voice that is synthesized and used as part of an IVR system. The disclosed approach can be used to assist in implementing a process to automate the detection of the start and end of a hold time during a call to a call center and in response execute a desired action.

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.

To appropriately assess customer emotions in a call center. [Solution] An information processing device comprising: an acquisition unit that acquires text data indicating the content of a conversation between a customer and an operator in a call center; an evaluation unit that inputs evaluation data based on the text data and a prompt including a request to select from multiple candidates that categorize the customer's emotions into a large language model (LLM) and acquires the output of the large language model to evaluate the customer's emotions; and an output unit that outputs the processing result of the evaluation unit.

A user of a user device initiates a contact center engagement with a first contact center. The first contact center processes a prompt received, by a first contact center software service associated with a first entity. Determine, by the first contact center software service and based on stored data associated with the prompt or an account of the contact center user device, that the prompt relates to a second contact center software service associated with a second entity. Train, using online learning techniques, an artificial intelligence agent of the first contact center software service based on prior responses received from the second contact center software service during a merged contact session. The artificial intelligence agent is capable of providing a resolution to a user of the contact center user device without contacting the second contact center software service after a response is provided to questions in the merged contact session.

Some aspects relate to technologies for generating persona simulators and employing the persona simulators for interaction simulation. The persona simulators can comprise user persona simulators that act as end users during simulated interactions and agent persona simulators that act as agent users during simulated interactions. To generate a persona simulator, interaction data for an end user or an agent user is accessed. The interaction data can be based on, for instance, transcript(s) from interaction(s) involving the end user or agent user. Parameter scores for different interaction parameters are generated from the interaction data, and in some cases, the parameter scores are used to determine an index score. The scores define the persona of the end user or agent user and are used to provide an input to a generative model to provide a persona simulator. The persona simulator is then used to generate text for messages during a simulated interaction.

A computing system can obtain health record data of a user from health record sources. The system can generate, on a computing device of a call agent, an interactive agent interface comprising prepopulated data based on the health record data. Based on an interaction between the call agent and the user during a call session, the system can receive input data from the computing device of the call agent. Based on at least one of the health record data or the input data, the system can generate a set of health outcome predictions for the user, and based on the set of health outcome predictions, the input data, and the health record data, the system can generate a set of health care plan rankings for the user.

The invention provides a call center queuing system performance prediction method and device, a terminal and a storage medium, and relates to the technical field of queuing theory and system performance evaluation. The method comprises the following steps: acquiring system parameters of a target queuing system, wherein the system parameters comprise a stage type distribution parameter, a service rate, an intolerance rate, a negative customer arrival rate and a feedback probability; based on the system parameters of the target queuing system, constructing a birth simulation process; rG decomposition is carried out on the birth and death simulating process, performance indexes of the target queuing system are calculated, and the performance indexes comprise the average queue length and the average customer staying time. The calculation accuracy of the performance index of the queuing system can be improved, so that the accuracy of the prediction result of the existing queuing system is improved.

1. The name of the design product: telephone handset. 2. The use of the design product: for call center, customer service center or other work environment that needs to frequently answer the phone, to facilitate the staff to keep hands free when answering the phone, and facilitate other operations. 3. The design points of the design product: in shape. 4. The picture or photo that can best show the design points: perspective view 1.

A computing system can generate a claim interface for a call representative to interact with a user during a call session, the claim interface providing the call representative with an intelligent search feature that corresponds to one or more claim file databases. The system can detect character inputs within the intelligent search feature by the call representative during the call session. For each detected character, the system filter a set of results from the one or more databases that match the detected character and provide a ranked list of results in a selectable menu. Based on a selection input by the call representative of a result in the selectable menu, the system can generate a static filter object within the intelligent search feature.

The application provides a communication connection method, system and device. The method comprises the following steps: a call center receives a call request initiated by a calling client; the call center acquires at least one channel variable of a first call channel according to a client identifier corresponding to the calling client, wherein the at least one channel variable comprises a calling client number and a called client number corresponding to the calling client, and the first call channel is a communication channel between the calling client and the call center; the call center calls the called client through the called client number, establishes a communication connection between the calling client and the called client, and displays a virtual number on the called client, wherein the virtual number is obtained by the call center according to the calling client number and the called client number. The technical scheme of the application can hide the calling client number and the called client number at the same time, reduces the risk of information leakage of the calling and called information, and the calling client does not need to bear the cost of outbound call.

Systems and methods are provided for monitoring and managing call center operations within a virtual reality environment. A processing system generates a virtual call center comprising virtual workstations associated with respective agents. Each workstation includes a monitor displaying call information, a call health panel presenting real-time call status, and an agent health panel presenting agent condition or performance data. The system receives call audio and related data, performs transcription and signal analysis, and applies machine learning models to determine call sentiment, agent status, and recommended actions. Based on the analysis, the system dynamically updates the virtual reality environment, including visual indicators, supervisor alerts, and interactive panels. Supervisors may navigate the environment, monitor multiple agents, and interact with calls using virtual tools such as notes, scoring, or intervention modes. The disclosed embodiments improve real-time awareness, training, and decision-making in contact center environments.

The invention discloses a call center information pushing system and method based on big data analysis, and belongs to the field of big data analysis. A transaction information abnormity evaluation model is constructed, customer basic information and customer transaction information are imported into the transaction information abnormity evaluation model for transaction abnormity analysis, and a customer abnormity judgment model is constructed; and substituting the obtained transaction abnormity analysis result, the historical sales data and the score data after each transaction of the customer into a customer abnormity judgment model for customer abnormity analysis, comparing the obtained customer abnormity analysis result with a set customer loss threshold value, and performing customer loss level analysis. And the customer loss grade analysis result obtained through judgment is pushed to the customer service terminal, customer loss early warning is carried out, the customer loss grade is estimated according to the sales characteristics of customer loss, and the accuracy of customer loss early warning is improved.

A computerized-method for matching customer queries across diverse digital channels with a response in a multichannel contact center. The computerized-method includes: (i) continuously receiving queries from customers via digital communication channels; in each preconfigured time-window: (ii) converting each customer query in the received queries into a high-dimensional vector representation and scoring the customer query to yield a similarity score by operating a semantic embedder module; (iii) clustering each customer query based on the high-dimensional vector representation and the similarity score by operating a AIQA module to yield clusters of customer queries with semantic similarity; (iv) matching each cluster of customer queries with the response based on a preconfigured threshold by operating a CVSE; (v) automatically generating a notification for each customer query based on the matched response by operating a notification module; and (vi) automatically sending the notification to each customer that is associated with the customer query.

Provided is a method for pairing contacts with agents in a contact center system, including: determining a threshold statistic; determining an ordered set of contacts; determining a set of first statistics that correspond to the ordered set of contacts; determining a set of second statistics that correspond to the ordered set of contacts and is based on the set of first statistic, in which the set of second statistics is based on a cumulative summation of the set of first statistics; determining a subset of the set of contacts based on the ordered set of second statistics and the threshold statistic; and pairing a selected contact from the subset of the ordered set of contacts with an available agent based on a pairing strategy.

This application provides a method, apparatus, and computer-readable storage medium for constructing a call volume prediction model. The method includes: obtaining the total call volume before the transfer from a first call center and the total call volume before the transfer from a second call center; obtaining the transfer ratio of the first call center within a first time period, where the transfer ratio is the ratio of the target call volume to the total call volume before the transfer from the first call center; determining call transfer information from the first call center to the second call center within the first time period based on the total call volume before the transfer from the first call center and the transfer ratio; summing the total call volume before the transfer from the second call center and the call transfer information to reconstruct the first historical call volume information of the second call center, obtaining the reconstructed target historical call volume data; and constructing a target call volume prediction model based on the target historical call volume data. The embodiments of this application result in higher prediction accuracy for the reconstructed call volume prediction model.

Described herein are examples of a sales training and recruitment utility with an autodialer configured to record, display, and analyze sales pitches and pitch battles between contestants. Further, the autodialer is configured to operate with the utility as a standalone system separate from a dedicated call center. The sales training and recruitment utility with an autodialer can assist with training sale personal and identifying sales personnel for particular industry and / or expertise level. The sales training and recruitment utility with an autodialer can provide an interactive experience for users as well as training and recruitment benefits for employers.

We provide a contact center system that can smoothly connect users to human operators if their requests cannot be resolved by automated responses such as chatbots. [Solution] In a contact center system equipped with a processor, when the processor receives a user request from a user terminal, it performs the following processes: extracting a standard response sentence corresponding to the request from a storage unit that stores standard response sentences and presenting it to the user terminal; and, if the request is not resolved by the standard response sentence, presenting an interactive element to the user terminal along with the standard response sentence for the user to start verbal communication with an operator. When the interactive element is operated by the user, it provides the user terminal with a connection to a pre-registered destination associated with the standard response sentence presented together with the interactive element.

Embodiments of the present application disclose a pressure test method and a pressure test system, the method comprising: playing a recording in a call room with a preset room identifier through a calling simulation terminal; sending a call request to a service logic processing module through a flow control module; in response to receiving the call request, generating a call command through the service logic processing module and sending the call command to an outbound module in a call center system; calling a called simulation terminal with a called identifier through the outbound module to make the called simulation terminal join the call room; making a reply in the call room through the called simulation terminal; and monitoring transmission data on a link of the service logic processing module, the outbound module and the called simulation terminal to perform pressure test on the call process. The present application simulates a real call scene and performs pressure test on a whole link by introducing a simulation double terminal and a flow control module without affecting an external system.