Method and system for real-time reporting of metrics to replaceable agents in a full-spectrum contact center

Abstract

A method and system for reporting metrics related to customer calls by replaceable multiple agents in a contact center environment, the replaceable multiple agents utilizing multiple service applications. The method includes: receiving a service request call from a customer; determining an application that can be used to respond to the service request call from a predetermined plurality of applications; monitoring the service request call to obtain information related to the call time and events that occurred during the call; when the service request call is completed, determining call-specific metrics such as hold time, number of transfers, and / or idle time based on the information obtained during the monitoring process; and reporting the metrics to a repository. Additional metrics specific to the agent assigned to handle the call may also be determined.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. Application No. 17 / 363,984, filed on June 30, 2021, which is incorporated herein by reference in its entirety. Technical Field

[0003] The present technology generally relates to methods and systems for reporting customer call related metrics, and more particularly to methods and systems for reporting customer call related metrics using replaceable agents for multiple service applications in a contact center environment. Background Art

[0004] For large organizations with many customers, customer service is an important aspect of business operations. Customers typically expect service requests to be handled in a timely and accurate manner, and if an organization fails to provide such customer service, it may negatively affect the organization's reputation.

[0005] Many customer service requests are made online over the Internet. For such requests, corporate organizations can utilize contact centers, which facilitate the provision of various service applications from different parts of the organization. However, due to the diversity of applications and the scale of the overall operation, software developers may encounter difficulties in integrating newly developed applications with the rest of the software suite serving the contact center.

[0006] Additionally, in a contact center, replaceable agents will answer calls from multiple business line service applications and switch services for customers for different service applications during the same call. When professionals handle different service applications to help customers during the same call, it is also challenging to track metrics such as average handling time, average talk time, etc. about professionals for a specific type of service application, which is one of many service applications handled by the replaceable professional during the same call. In contrast, typical contact center reporting solutions rely on routing-related information to calculate agent and queue statistics; these traditional reporting solutions rely on only one type of service application being used to help the customer, matching the call type identified by the routing system. When another type of service application is needed, the professional transfers the customer to another virtual queue of professionals with different skills. To reduce the number of transfers required and improve the customer experience, replaceable contact center professionals are able to handle different types of service requests that match the customer's inquiry intent, and they can use more than one service application.

[0007] Therefore, there is a need for a method and system for reporting customer call related metrics using replaceable agents for multiple service applications in a contact center environment. Summary of the invention

[0008] The present disclosure, through one or more of its various aspects, embodiments and / or specific features or subcomponents, particularly proposes various systems, servers, devices, methods, media, programs and platforms for reporting customer call-related metrics using replaceable agents for multiple service applications in a contact center environment.

[0009] According to one aspect of the present disclosure, a method for reporting customer call-related metrics using replaceable agents of multiple service applications in a contact center environment is provided. The method is implemented by at least one processor. The method includes: receiving a service request call from a first customer by at least one processor; determining at least one application that can be used to respond to the service request call from a predetermined plurality of applications by at least one processor; monitoring the service request call by at least one processor to obtain information related to the time of the service request call, at least one event occurring during the service request call, and at least one output of at least one application; when the service request call is completed, determining at least one call-specific metric by at least one processor based on the information obtained as a result of the monitoring; and reporting each of the at least one call-specific metric determined by at least one processor to a predetermined destination.

[0010] At least one call-specific metric may include at least one of: hold time, talk time, average handle time, call intent, call handling, answer speed, number of calls hung up, number of dropped calls, number of calls handled, average after-call work time, percentage of calls held, average duration of calls held, after-call work percentage of average handle time, number and percentage of calls transferred, number and percentage of conference calls, percentage of combined transferred or conference calls, service level percentage, number of transfers, idle time, call count, type of service application used by professionals and team leaders of each team for each service request during the call, and number of call records.

[0011] At least one call-specific metric may also include a daily total of service levels, average handling time, average speed of answer, number of calls served and number of calls handled, and a total and / or average of metrics within a predetermined interval (e.g., 30 minutes, 8 hours per day, a week, or a month). Each call and interval report has goals and thresholds, which are also calculated in real time and displayed to professionals and team leaders for monitoring and appropriate action.

[0012] The method may also include generating trends from such aggregations, which are then used for workforce management and forecasting.

[0013] The method may also include identifying an agent assigned to handle the service request call and calculating at least one agent-specific metric based on the determined at least one call-specific metric and previously stored agent-specific metric data.

[0014] The method may also include capturing at least one metadata item associated with the service request call. The at least one metadata item may include at least one of: phone data, user profile data associated with the identified agent, an identification of each of the at least one application, and information associated with whether the identified agent performed a search function during the service request call.

[0015] The method may also include displaying a user interface on a display associated with the identified agent, the user interface including information related to the service request call and information related to a historical sequence of interactions corresponding to the first customer.

[0016] The at least one application may include: a first application operable to respond to a first aspect of the service request call; and at least a second application operable to respond to a second aspect of the service request call.

[0017] The at least one call-specific indicator may include: a first call-specific indicator, the first call-specific indicator being related to a first aspect of the service request call; and at least a second call-specific indicator, the second call-specific indicator being related to a second aspect of the service request call.

[0018] The method may also include using a container application for monitoring and reporting, the container application being designed to facilitate interaction between respective applications of the predetermined plurality of applications.

[0019] Additionally, container apps can display the customer journey within the same call that a professional helped, with more than one app matching the customer’s intent or inquiry with each app’s treatment and linking it to the historical sequence of interactions along the customer journey when fulfilling the customer’s intent.

[0020] At least one call-specific metric may also include the amount of time spent and actions taken within the service application for transaction transacting. These metrics, along with other data including the customer's device, first-time usage, etc., may be collected as part of a clickstream event, which may be sent to a post-analysis big data system with business insight visualization.

[0021] According to another exemplary embodiment, a computing device for reporting metrics related to customer calls is provided. The computing device includes: a processor; a memory; and a communication interface coupled to each of the processor and the memory. The processor is configured to: receive a service request call from a first customer via the communication interface; determine at least one application that can be used to respond to the service request call from a predetermined plurality of applications; monitor the service request call to obtain information related to the time of the service request call, at least one event occurring during the service request call, and at least one output of at least one application; when the service request call is completed, determine at least one call-specific metric based on the information obtained as a result of the monitoring; and report each of the determined at least one call-specific metric to a predetermined destination.

[0022] At least one call-specific metric may include at least one of: hold time, talk time, average handle time, call intent, call handling, answer speed, number of calls hung up, number of dropped calls, number of calls handled, average after-call work time, percentage of calls held, average duration of calls held, after-call work percentage of average handle time, number and percentage of calls transferred, number and percentage of conference calls, percentage of combined transferred or conference calls, service level percentage, number of transfers, idle time, call count, type of service application used by professionals and team leaders of each team for each service request during the call, and number of call records.

[0023] The processor may be further configured to identify an agent assigned to handle the service request call and calculate at least one agent-specific metric based on the determined at least one call-specific metric and previously stored agent-specific metric data.

[0024] The processor may also be configured to capture at least one metadata item associated with the service request call. The at least one metadata item may include at least one of phone data, user profile data associated with the identified agent, an identification of each of the at least one application, and information associated with whether the identified agent performed a search function during the service request call.

[0025] The processor may be further configured to display a user interface on a display associated with the identified agent, the user interface including information related to the service request call and information related to the historical sequence of interactions corresponding to the first customer.

[0026] The at least one application may include: a first application operable to respond to a first aspect of the service request call; and at least a second application operable to respond to a second aspect of the service request call.

[0027] The at least one call-specific indicator may include: a first call-specific indicator, the first call-specific indicator being related to a first aspect of the service request call; and at least a second call-specific indicator, the second call-specific indicator being related to a second aspect of the service request call.

[0028] The processor may also be configured to perform monitoring and reporting using a container application designed to facilitate interaction between respective applications of the predetermined plurality of applications.

[0029] The container application can pass the reporting metrics collected for each group of applications to the contact center reporting system and attach them as metadata for identifying records and analytics, and use them as metadata to enrich the customer experience when the customer is transferred or contacts the company again.

[0030] According to another exemplary embodiment, a non-transitory computer-readable storage medium storing instructions for reporting indicators related to customer calls is provided. The storage medium includes executable code, which, when executed by a processor, causes the processor to: receive a service request call from a first customer; determine at least one application that can be used to respond to the service request call from a predetermined plurality of applications; monitor the service request call to obtain information related to the time of the service request call, at least one event occurring during the service request, and at least one output of at least one application; when the service request call is completed, determine at least one call-specific indicator based on the monitoring result; and report each of the determined at least one call-specific indicator to a predetermined destination.

[0031] The executable code may also be configured to cause the processor to identify an agent assigned to handle the service request call and calculate at least one agent-specific metric based on the determined at least one call-specific metric and previously stored agent-specific metric data.

[0032] The executable code may also be configured to cause the processor to display a user interface on a display associated with the identified agent, the user interface including information related to the service request call and information related to a historical sequence of interactions corresponding to the first customer.

[0033] The at least one application may include: a first application operable to respond to a first aspect of the service request call; and at least a second application operable to respond to a second aspect of the service request call. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In the following detailed description, the present disclosure is further described by way of non-limiting examples of preferred embodiments of the present disclosure with reference to the several accompanying drawings, wherein like reference numerals represent like elements throughout the several views of the drawings.

[0035] Figure 1 An exemplary computer system is shown.

[0036] Figure 2 An example diagram of a network environment is shown.

[0037] Figure 3 An exemplary system for implementing a method for reporting customer call related metrics using replaceable agents for multiple service applications in a contact center environment is shown.

[0038] Figure 4 is a flow chart of an exemplary process for implementing a method for reporting customer call related metrics using replaceable agents for multiple service applications in a contact center environment.

[0039] Figure 5 is an architectural diagram of a system for implementing a method for reporting customer call-related metrics using replaceable agents for multiple service applications in a contact center environment according to an exemplary embodiment. DETAILED DESCRIPTION

[0040] The present disclosure, through one or more of its various aspects, embodiments and / or specific features or subcomponents, is intended to illustrate one or more advantages specifically described above and below.

[0041] Examples may also be embodied as one or more non-transitory computer-readable media having stored thereon instructions for one or more aspects of the present technology as described and illustrated by examples herein. The instructions in some examples include executable code that, when executed by one or more processors, causes the processors to perform the steps necessary to implement the methods in the examples of the present technology described and illustrated herein.

[0042] Figure 1 is an exemplary system for use in accordance with the embodiments described herein. System 100 is generally shown and may include a computer system 102, which is generally indicated.

[0043] The computer system 102 may include a set of instructions that can be executed to cause the computer system 102 to perform any one or more of the methods or computer-based functions disclosed herein, either alone or in combination with other described devices. The computer system 102 may operate as a standalone device or may be connected to other systems or peripherals. For example, the computer system 102 may include or be included in any one or more computers, servers, systems, communication networks, or cloud environments. In addition, the instructions may be run in such a cloud-based computing environment.

[0044] In a networked deployment, the computer system 102 can be run as a server, or as a client user computer in a server-client user network environment, a client user computer in a cloud computing environment, or a peer computer system in a peer (or distributed) network environment. The computer system 102 or parts thereof can be implemented as or incorporated into various devices, such as a personal computer, a tablet computer, a set-top box, a personal digital assistant, a mobile device, a handheld computer, a laptop computer, a desktop computer, a communication device, a wireless smart phone, a personal trusted device, a wearable device, a global positioning satellite (GPS) device, a network device, or any other machine capable of executing a set of instructions (sequentially or in other orders) specifying the actions to be taken by the machine. In addition, although a single computer system 102 is described, any set of systems or subsystems that execute instructions or perform functions individually or jointly may be included in additional embodiments. The term "system" shall be used throughout this disclosure, including any set of systems or subsystems that execute one or more sets of instructions individually or jointly to perform one or more computer functions.

[0045] like Figure 1 As shown, the computer system 102 may include at least one processor 104. The processor 104 is tangible and non-transitory. As used herein, the term "non-transitory" should not be interpreted as a permanent feature of a state, but a feature that a state will last for a period of time. The term "non-transitory" specifically denies transient features, such as features of a specific carrier or signal or other forms of carriers or signals that only temporarily exist anywhere at any time. The processor 104 is an article of manufacture and / or a machine component. The processor 104 is configured to execute software instructions to perform functions as described in various embodiments of this article. The processor 104 may be a general-purpose processor, or may be part of an application-specific integrated circuit (ASIC). The processor 104 may also be a microprocessor, a microcomputer, a processor chip, a controller, a microcontroller, a digital signal processor (DSP), a state machine, or a programmable logic device. The processor 104 may also be a logic circuit including a programmable gate array (PGA) such as a field programmable gate array (FPGA), or another type of circuit including discrete gates and / or transistor logic. The processor 104 may be a central processing unit (CPU), a graphics processing unit (GPU), or both. Furthermore, any processor described herein may include multiple processors, parallel processors, or both. Multiple processors may be included in or coupled to a single device or multiple devices.

[0046] The computer system 102 may also include a computer memory 106. The computer memory 106 may include static memory, dynamic memory, or both in communication. The memory described herein is a tangible storage medium that can store data and executable instructions, and is non-transitory during the period when the instructions are stored therein. Likewise, as used herein, the term "non-transitory" should not be interpreted as a permanent feature of a state, but rather a feature that a state will last for a period of time. The term "non-transitory" specifically denies transient features, such as features of a specific carrier or signal or other forms of carriers or signals that only temporarily exist anywhere at any time. The memory is an article of manufacture and / or a machine component. The memory described herein is a computer-readable medium from which a computer can read data and executable instructions. The memory described herein may be a random access memory (RAM), a read-only memory (ROM), a flash memory, an electrically programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), a register, a hard disk, a cache, a removable disk, a tape, a compact disk read-only memory (CD-ROM), a digital versatile disk (DVD), a floppy disk, a Blu-ray disc, or any other form of storage medium known in the art. The memory may be volatile or non-volatile, secure and / or encrypted, unsecure and / or unencrypted.Of course, the computer memory 106 may include any combination of memories or a single memory.

[0047] Computer system 102 may also include a display 108, such as a liquid crystal display (LCD), an organic light emitting diode (OLED), a flat panel display, a solid state display, a cathode ray tube (CRT), a plasma display, or any other type of display, examples of which are known to skilled artisans.

[0048] The computer system 102 may also include at least one input device 110, such as a keyboard, a touch-sensitive input screen or tablet, voice input, a mouse, a remote control device with a wireless keyboard, a microphone coupled to a voice recognition engine, a camera such as a video camera or a still camera, a cursor control device, a global positioning system (GPS) device, an altimeter, a gyroscope, an accelerometer, a proximity sensor, or any combination thereof. It should be understood by those skilled in the art that various embodiments of the computer system 102 may include multiple input devices 110. In addition, it should be understood by those skilled in the art that the exemplary input devices 110 listed above are not meant to be exhaustive, and the computer system 102 may include any additional or alternative input devices 110.

[0049] The computer system 102 may also include a media reader 112 configured to read any one or more sets of instructions, such as software, from any memory described herein. The instructions, when executed by the processor, may be used to perform one or more of the methods and processes described herein. In certain embodiments, the instructions may reside completely or at least partially within the memory 106, the media reader 112, and / or the processor 110 during execution by the computer system 102.

[0050] Furthermore, the computer system 102 may include any additional devices, components, parts, peripherals, hardware, software, or any combination thereof that are well known and understood to be included in a computer system, such as, but not limited to, a network interface 114 and an output device 116. The output device 116 may be, but is not limited to, a speaker, an audio output, a video output, a remote control output, a printer, or any combination thereof.

[0051] The various components in the computer system 102 may be interconnected and communicate via a bus 118 or other communication links. Figure 1 As shown, the components can be interconnected and communicate via an internal bus. However, it will be appreciated by those skilled in the art that any of the components can also be connected via an expansion bus. In addition, the bus 118 can communicate via any standard or other specification known and understood, such as, but not limited to, Peripheral Component Interconnect, Peripheral Component Interconnect Express, Parallel Advanced Technology Attachment, Serial Advanced Technology Attachment, etc.

[0052] The computer system 102 can communicate with one or more additional computer devices 120 via a network 122. The network 122 can be, but is not limited to, a local area network, a wide area network, the Internet, a telephone network, a short-range network, or any other network known and understood in the art. The short-range network can include, for example, Bluetooth, ZigBee, infrared, near field communication, ultra-wideband, or any combination thereof. It should be understood by those skilled in the art that additional networks 122 known and understood can be used in addition or alternatively, and the exemplary network 122 is not limiting or exhaustive. In addition, although the network 122 is Figure 1 Although shown as a wireless network in the figure, those skilled in the art will appreciate that the network 122 may also be a wired network.

[0053] Additional computer equipment 120 in Figure 1102. It is shown as a personal computer. However, it will be appreciated by those skilled in the art that in an alternative embodiment of the present application, the computer device 120 may be a laptop computer, a tablet computer, a personal digital assistant, a mobile device, a palmtop computer, a desktop computer, a communication device, a wireless telephone, a personal trusted device, a network device, a server, or any other device capable of executing a set of instructions (sequentially or in other orders) specifying the actions to be taken by the device. Of course, it will be appreciated by those skilled in the art that the devices listed above are merely exemplary devices, and without departing from the scope of the present application, the device 120 may be any additional device or apparatus known and understood in the art. For example, the computer device 120 may be the same or similar to the computer system 102. In addition, it will be appreciated by those skilled in the art that the device may be any combination of various devices and apparatuses.

[0054] Of course, it will be appreciated by those skilled in the art that the components of the computer system 102 listed above are merely exemplary and not intended to be exhaustive and / or inclusive. In addition, the examples of the components listed above are also intended to be exemplary and are not intended to be exhaustive and / or inclusive.

[0055] According to various embodiments of the present disclosure, the methods described herein may be implemented using a hardware computer system that executes a software program. In addition, in an exemplary, non-limiting embodiment, implementations may include distributed processing, component / object distributed processing, and parallel processing. Virtual computer system processing may be configured to implement one or more of the methods or functions described herein, and the processors described herein may be used to support a virtual processing environment.

[0056] As described herein, various embodiments provide an optimized method and system for reporting customer call related metrics in a contact center environment utilizing replaceable agents for multiple service applications.

[0057] refer to Figure 2 , shows a schematic diagram of an exemplary network environment 200 for implementing a method for reporting customer call-related metrics using replaceable agents of multiple service applications in a contact center environment. In an exemplary embodiment, the method can be executed on any networked computer platform such as a personal computer (PC).

[0058] A method for reporting customer call related metrics using replaceable agents for multiple service applications in a contact center environment may be implemented by a service application call metrics reporting (SACMR) device 202. The SACMR device 202 may be used in conjunction with a contact center environment. Figure 1The SACMR device 202 may be the same or similar to the computer system 102 described above. The SACMR device 202 may store one or more applications that may include executable instructions that, when executed by the SACMR device 202, cause the SACMR device 202 to perform actions such as sending, receiving, or otherwise processing network messages, and to perform other actions described and illustrated below with reference to the figures. Applications may be implemented as modules or components of other applications. In addition, applications may be implemented as operating system extensions, modules, plug-ins, etc.

[0059] In addition, the application can be run in a cloud-based computing environment. The application can be executed in or as a virtual machine or virtual server managed in the cloud-based computing environment. In addition, the application, and even the SACMR device 202 itself, can be located in a virtual server running in a cloud-based computing environment rather than being bound to one or more specific physical network computing devices. In addition, the application can be run in one or more virtual machines (VMs) executed on the SACMR device 202. In addition, in one or more embodiments of the technology, the virtual machines running on the SACMR device 202 can be managed or supervised by a hypervisor.

[0060] exist Figure 2 In the network environment 200, a SACMR device 202 is coupled to a plurality of server devices 204(1)-204(n) hosting a plurality of databases 206(1)-206(n) via a communication network 210, and is also coupled to a plurality of client devices 208(1)-208(n). The communication interface of the SACMR device 202, for example, Figure 1 The network interface 114 of the computer system 102 can be operatively coupled to and communicate between the SACMR device 204, the server devices 204(1)-204(n) and / or the client devices 208(1)-208(n), all of which are coupled together via a communication network 210, although other types and / or numbers of communication networks or systems having other types and / or numbers of connectors and / or configurations for connecting and / or configuring to other devices and / or elements may also be used.

[0061] The communication network 210 can be connected to Figure 1The described network 122 is the same or similar, but the SACMR device 202, server devices 204(1)-204(n) and / or client devices 208(1)-218(n) can be coupled together via other topologies. In addition, the network environment 200 can include other network devices, such as one or more routers and / or switches, which are well known in the art and will not be described herein. The technology provides many advantages, including methods, non-transitory computer-readable media, and SACMR devices that effectively implement a method for reporting customer call-related metrics using replaceable agents for multiple service applications in a contact center environment.

[0062] By way of example only, the communication network 210 may include a local area network (LAN) or a wide area network (WAN), and may use Ethernet TCP / IP and industry standard protocols, but other types and / or numbers of protocols and / or communication networks may also be used. The communication network 210 in this example may use any suitable interface mechanism and network communication technology, including, for example, any suitable form of long-distance communication service (e.g., voice, modem, etc.), a public switched telephone network (PSTN), an Ethernet-based packet data network (PDN), a combination thereof, etc.

[0063] The SACMR device 202 may be a standalone device or may be integrated with one or more other devices or apparatuses, such as one or more of the server devices 204(1)-204(n). In a specific example, the SACMR device 202 may include or be hosted by one of the server devices 204(1)-204(n), and other devices may also be hosted by the server devices 204(1)-204(n). In addition, one or more of the SACMR devices 202 may be in the same communication network or in different communication networks, such as one or more public, private or cloud networks.

[0064] The plurality of server devices 204(1)-204(n) may be associated with Figure 1 The computer system 102 or computer device 120 described above is the same or similar, including the Figure 1Any feature or any combination of features described herein. For example, any of the server devices 204(1)-204(n) may include, among other features, one or more processors, memory, and communication interfaces coupled together via a bus or other communication link, although other numbers and / or types of network devices may also be used. The server devices 204(1)-204(n) in this example may process requests received from the SACMR device 202 via the communication network 210 according to, for example, HTTP and / or JavaScript Object Notation (JSON) protocols, although other protocols may also be used.

[0065] The server devices 204(1)-204(n) may be hardware or software and may represent a system having multiple servers in a pool, which may include an internal network or an external network. The server devices 204(1)-204(n) host databases 206(1)-206(n) configured to store data related to agent-specific call service metrics and customer-specific call services.

[0066] Although server devices 204(1)-204(n) are shown as a single device, one or more actions of each server device 204(1)-204(n) may be distributed to one or more different network computing devices that together comprise one or more of server devices 204(1)-204(n). Furthermore, server devices 204(1)-204(n) are not limited to a particular configuration. Thus, server devices 204(1)-204(n) may include multiple network computing devices that operate using a master / slave approach, whereby one of the network computing devices of server devices 204(1)-204(n) operates to manage and / or otherwise coordinate the operations of the other network computing devices.

[0067] Server devices 204(1)-204(n) may operate as multiple network computing devices within, for example, a cluster architecture, a peer-to-peer architecture, a virtual machine, or a cloud architecture. Thus, the technology disclosed herein should not be construed as limited to a single environment, and other configurations and architectures are also contemplated.

[0068] Multiple client devices 208(1)-208(n) may also communicate with each other regarding Figure 1 The computer system 102 or computer device 120 described above is the same or similar, including the Figure 1The invention also provides a method for implementing a method of implementing a SACMR device 202 in an embodiment of the present invention. The method further provides a method of implementing a method of implementing a SACMR device 202 in an embodiment of the present invention. For example, the client devices 208(1)-208(n) in this example may include any type of computing device that can interact with the SACMR device 202 via the communication network 210. Thus, the client devices 208(1)-208(n) may be mobile computing devices, desktop computing devices, laptop computing devices, tablet computing devices, virtual machines (including cloud-based computers), etc., which host applications such as chat, email, or speech-to-text. In an exemplary embodiment, at least one client device 208 is a wireless mobile communication device, i.e., a smartphone.

[0069] The client devices 208(1)-208(n) may run interface applications, such as standard web browsers or stand-alone client applications, that may provide an interface for communicating with the SACMR device 202 via the communication network 210 to communicate user requests and information. The client devices 208(1)-208(n) may include, among other features, a display device (e.g., a display screen or touch screen) and / or an input device (e.g., a keyboard).

[0070] Although an exemplary network environment 200 having a SACMR device 202, server devices 204(1)-204(n), client devices 208(1)-208(n), and a communication network 210 is described and illustrated herein, other types and / or numbers of systems, devices, components, and / or elements in other topologies may also be used. It should be understood that the systems in the examples described herein are for exemplary purposes, as many variations in the specific hardware and software used to implement the examples are possible, as will be appreciated by those skilled in the relevant art.

[0071] One or more devices described in the network environment 200, such as the SACMR device 202, the server devices 204(1)-204(n), or the client devices 208(1)-208(n), may be configured to run as virtual instances on the same physical machine. In other words, one or more of the SACMR device 202, the server devices 204(1)-204(n), or the client devices 208(1)-208(n) may run on the same physical device, rather than as separate devices communicating over the communication network 210. In addition, there may be more than one virtual instance. Figure 2 More or fewer SACMR devices 202, server devices 204(1)-204(n), or client devices 208(1)-208(n) as shown.

[0072] In addition, in any example, two or more computing systems or devices can replace any one system or device. Therefore, the principles and advantages of distributed processing can also be implemented as needed, such as redundancy and replication, to improve the robustness and performance of the devices and systems in the examples. These examples can also be implemented on a computer system extended on any suitable network using any suitable interface mechanism and communication service technology, and the interface mechanism and communication service technology include, by way of example only, any suitable form of long-distance communication service (e.g., voice, modem, etc.), wireless communication service network, cellular communication service network, packet data network (PDN), Internet, intranet, and combinations thereof.

[0073] SACMR equipment 202 Figure 3 302, but it may include, for example, other rules, policies, modules, databases, or applications. As described below, the contact center service structure container module 302 is configured to implement a method for reporting customer call-related metrics using replaceable agents of multiple service applications in a contact center environment.

[0074] For use by Figure 2 An exemplary process 300 for implementing a mechanism for reporting customer call-related metrics for replaceable agents utilizing multiple service applications in a contact center environment is described in detail in the network environment of FIG. Figure 3 . Specifically, a first client device 208(1) and a second client device 208(2) are shown as being in communication with the SACMR device 202. In this regard, the first client device 208(1) and the second client device 208(2) may be "clients" of the SACMR device 202 and described as such herein. However, it should be known and understood that the first client device 208(1) and / or the second client device 208(2) are not necessarily "clients" of the SACMR device 202, or any entity described in association therewith herein. Any additional or alternative relationships may exist between either or both of the first client device 208(1) and the second client device 208(2) and the SACMR device 202, or no relationship may exist.

[0075] In addition, the SACMR device 202 is shown as being able to access an agent-specific call metrics data repository 206(1) and a customer-specific call service database 206(2). The service application call metrics reporting module 302 can be configured to access these databases to implement a method for reporting customer call-related metrics using replaceable agents for multiple service applications in a contact center environment.

[0076] The first client device 208(1) may be, for example, a smartphone. Of course, the first client device 208(1) may also be any of the additional devices described herein. The second client device 208(2) may be, for example, a personal computer (PC). Of course, the second client device 208(2) may also be any of the additional devices described herein.

[0077] The process may be performed via the communication network 210, which may include a plurality of networks as described above. For example, in one exemplary embodiment, either or both of the first client device 208(1) and the second client device 208(2) may communicate with the SACMR device 202 via broadband or cellular communications. Of course, these embodiments are exemplary only and are not intended to be limiting or exhaustive.

[0078] Once the service application call metrics reporting module 302 is started, it will execute a process for reporting metrics related to customer calls using replaceable agents of multiple service applications in a contact center environment. Figure 4 An exemplary process for reporting customer call related metrics using replaceable agents for multiple service applications in a contact center environment is generally illustrated in flowchart 400 of FIG.

[0079] exist Figure 4 In the process 400, at step S402, the service application call metrics reporting module 302 receives a service request call from a customer. At step S404, the call is assigned to an agent, and the service application call metrics reporting module 302 determines the identity of the agent. In an exemplary embodiment, the service application call metrics reporting module 302 can display a user interface at a workstation associated with the agent, and can include information related to the call and the customer, such as information related to a historical sequence of interactions with the customer. Such information is generally referred to as a "customer journey."

[0080] Step S406, the service application call metrics reporting module 302 determines which available software applications will help respond to various aspects of the customer's service request. In an exemplary embodiment, the contact center may use a container application that is configured to facilitate interaction between multiple applications for various functions, wherein the various functions are designed to handle customer service inquiries. At this point, the service application call metrics reporting module 302 may select one or more applications integrated into the container application to handle specific service requests made by the customer. Alternatively, the agent handling the call can simply select which applications are most helpful. Importantly, in many cases, a customer service request call may make multiple requests and / or may include several aspects that are best handled by using different applications.

[0081] Step S408, the service application call metrics reporting module 302 monitors the calls. In an exemplary embodiment, the calls are monitored for the time, events, and outputs of the application used to process each individual aspect of the service request. For example, the start time and end time of the call may be recorded, and any other time-related aspects such as hold time and / or idle time may be recorded. As another example, if a customer is transferred from a first agent to a second agent, this event may be recorded. Other events and / or application outputs may vary greatly based on the details of the service request.

[0082] In step S410, the service application call metrics reporting module 302 determines a set of metrics related to the customer service request call. The metrics may include call-specific metrics, such as holding time, idle time, number of transfers, call counts, and / or call records. The metrics may also include agent-specific metrics that can be calculated with reference to previously stored agent-specific data. For example, as determined in step S408, the agent-specific average holding time (AHT) can be calculated by combining previously stored agent-specific AHT data with the holding time of the current call. In an exemplary embodiment, the metrics may also include metadata items related to the service request call, such as phone data, user profile data associated with the agent, an identification of the application used to respond to the service request, and whether a search function was performed during the call.

[0083] Step S412, the service application call metrics reporting module 302 reports the metrics to the call center central repository so that all stakeholders in the call center environment can access the metrics. In an exemplary embodiment, a container application can be used to route the metrics to an appropriate destination.

[0084] Figure 5 500 is an architectural diagram of a system for implementing a method for reporting customer call-related metrics using replaceable agents of multiple service applications in a contact center environment according to an exemplary embodiment. As shown in the architectural diagram 500, an Interactive Service Fabric (ISF) container technology prototype implements replaceable reporting through a container, wherein the container includes multiple service applications.

[0085] In an exemplary embodiment, during the same call (1a), a professional assists a customer with multiple service applications, also referred to herein as micro frontends, including: (2a) and (2b) retail accounts; (3) credit card inquiries; and (4) requests related to auto loans. Metrics are continuously updated in (1b). Different products can be pushed out via hot links from one micro frontend to another, or with the (5) overall view micro frontend. The container monitors the activity of each micro frontend and sends raw data to the ISF via a web socket. Web socket notifications pass service application events from the container to the ISF and computed metrics from the ISF to the container.

[0086] Metrics for each service application used during a call may include any one or more of the following: hold time, talk time, average handle time, call intent, call handling, answer speed, number of calls hung up, number of dropped calls, number of calls handled, average after-call work time, percentage of calls held, average duration of calls held, after-call work percentage of average handle time, number and percentage of calls transferred, number and percentage of conference calls, percentage of combined transferred or conference calls, service level percentage, number of transfers, idle time, call count, type of service application used for each service request by professionals and team leaders on each team during the call, and number of call records.

[0087] Interval reports: These may include any one or more of the following: daily sum of service levels, average handling time, average speed of answer, number of calls served and number of calls handled, sum and / or average of indicators within a certain interval (e.g., 30 minutes or 8 hours, a week or a month), targets and thresholds are also calculated in real time and displayed to professionals and team leaders for monitoring and appropriate action.

[0088] Trends: ISF can generate trends from this aggregation, which are then used for workforce management and forecasting.

[0089] Interfaces with other systems - data lake, traditional reporting systems, and analytics systems: Send metrics data and clickstream data (i.e., user first visit, device type, operating system, time spent, transaction details, time spent per click as per clickstream architecture) to the data lake for historical analysis, business insights, quality, and dashboarding, and to traditional contact center reporting systems. Customer journey visualizations can also be drawn by combining current calls and historical interactions.

[0090] Thus, utilizing this technique, an optimized process is provided for reporting customer call related metrics using replaceable agents for multiple service applications in a contact center environment.

[0091] Although the present invention has been described with reference to several exemplary embodiments, it is to be understood that the words that have been used are words of description and illustration rather than words of limitation. Changes may be made within the scope of the appended claims, as presently stated and as amended, without departing from the scope and spirit of the various aspects of the present disclosure. Although the present invention has been described with reference to particular means, materials, and embodiments, the invention is not intended to be limited to the details disclosed; on the contrary, the invention extends to all functionally equivalent structures, methods, and uses, which are within the scope of the appended claims.

[0092] For example, although a computer-readable medium may be described as a single medium, the term "computer-readable medium" includes a single medium or multiple media, such as a centralized or distributed database, and / or associated caches and servers storing one or more sets of instructions. The term "computer-readable medium" shall also include any medium capable of storing, encoding, or carrying a set of instructions to be executed by a processor or causing a computer system to perform any one or more embodiments disclosed herein.

[0093] The computer-readable medium may include one or more non-transitory computer-readable media and / or include one or more transient computer-readable media. In a specific non-limiting, exemplary embodiment, the computer-readable medium may include a solid-state memory, such as a memory card or other package that accommodates one or more non-volatile read-only memories. In addition, the computer-readable medium may be a random access memory or other volatile rewritable memory. In addition, the computer-readable medium may include magneto-optical or optical media, such as a disk or tape or other storage device to capture carrier signals, such as signals transmitted through a transmission medium. Therefore, the present disclosure is considered to include any computer-readable medium or other equivalents and successor media in which data or instructions can be stored.

[0094] Although the present application describes specific embodiments that can be implemented as computer programs or code segments in computer-readable media, it should be understood that dedicated hardware implementations, such as application-specific integrated circuits, programmable logic arrays, and other hardware devices, can be constructed to implement one or more embodiments described herein. The applications that may include the various embodiments set forth herein may widely include various electronic and computer systems. Therefore, the present application may include software, firmware, and hardware implementations, or a combination thereof. Nothing in the present application should be interpreted as being implemented or achievable using only software without hardware.

[0095] Although this specification describes components and functions that can be implemented in specific embodiments with reference to specific standards and protocols, the present disclosure is not limited to these standards and protocols. Such standards are periodically replaced by faster or more efficient equivalents having substantially the same functions. Therefore, replacement standards and protocols having the same or similar functions are considered to be their equivalents.

[0096] The illustrations of the embodiments described herein are intended to provide a general understanding of the various embodiments. These illustrations are not intended to be a complete description of all elements and features of the devices and systems utilizing the structures or methods described herein. Many other embodiments may be apparent to those skilled in the art upon review of this disclosure. Other embodiments may be utilized and derived from this disclosure, so that structural and logical substitutions and variations may be made without departing from the scope of this disclosure. In addition, these illustrations are representative only and may not be drawn to scale. Certain proportions in the illustrations may be exaggerated, while other proportions may be minimized. Therefore, this disclosure and the accompanying drawings should be considered illustrative rather than restrictive.

[0097] One or more embodiments of the present disclosure may be referred to herein individually and / or collectively as the term "invention", for convenience only, and are not intended to voluntarily limit the scope of the present application to any particular invention or inventive concept. In addition, although specific embodiments have been shown and described herein, it should be understood that any subsequent device designed to achieve the same or similar purpose can replace the specific embodiments shown. The present disclosure is intended to cover any and all subsequent adaptive changes or modifications of the various embodiments. Combinations of the above embodiments and other embodiments not specifically described herein will be apparent to those skilled in the art after reviewing the specification.

[0098] The Abstract of the present disclosure is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing detailed description, various features may be grouped together or described in a single embodiment for the purpose of simplifying the present disclosure. The present disclosure should not be interpreted as reflecting an intention that the claimed embodiments require more features than those explicitly recited in each claim. On the contrary, as reflected in the following claims, the subject matter of the present invention may be directed to less than all features of any disclosed embodiment. Therefore, the following claims are introduced into the detailed description, and each claim independently defines the subject matter that is separately claimed.

[0099] The above-disclosed subject matter is to be considered illustrative and not restrictive, and the appended claims are intended to cover all such modifications, enhancements, and other embodiments that fall within the true spirit and scope of the disclosure. Thus, to the maximum extent permitted by law, the scope of the present disclosure is to be determined by the broadest permissible interpretation of the following claims and their equivalents, and shall not be restricted or limited by the foregoing detailed description.

Claims

1. A method for reporting metrics related to customer calls, the method being implemented by at least one processor, the method comprising: receiving, by the at least one processor, a service request call from a first client; assigning, by said at least one processor, a single customer service agent to handle said service request call sent by said first customer; determining, by the at least one processor, a plurality of software applications to be used by the single customer service agent to respond to the service request call, the service request call including a plurality of requests of different types, wherein the plurality of software applications resolve the plurality of requests included in the service request call; monitoring, by the at least one processor, the service request call to obtain information related to a time of the service request call, an event occurring during the service request call, and at least one output of the plurality of software applications; when the service request call is completed, determining, by the at least one processor, for each of the plurality of software applications used by the single customer service agent in servicing the first customer during the service request call, at least one call-specific metric for the corresponding software application based on information obtained as a result of the monitoring; and The determined at least one call-specific metric is reported, by the at least one processor, to a central database for each of the plurality of software applications used by the single customer service agent in servicing the first customer during the service request call.

2. The method according to claim 1, wherein: The at least one call-specific metric includes at least one of: hold time, talk time, average handling time, call intent, call handling, answer speed, number of calls hung up, number of dropped calls, number of calls handled, average after-call work time, percentage of calls held, average duration of calls held, percentage of after-call work in average time, number and percentage of calls transferred, number and percentage of conference calls, percentage of combined transferred or conference calls, service level percentage, number of transfers, idle time, call count, type of service software application used by professionals and team leaders on each team for each service request during a call, and number of call records.

3. The method according to claim 1, further comprising: identifying the customer service agent assigned to handle the service request call, and At least one agent-specific metric is calculated based on the determined at least one call-specific metric and previously stored agent-specific metric data.

4. The method according to claim 3, further comprising: capturing at least one metadata item associated with the service request call, Wherein, the at least one metadata item includes at least one of: telephone data, user profile data associated with the identified agent, an identification of each of the multiple software applications used by the single customer service agent, and information related to whether the identified agent performed a search function during the service request call.

5. The method according to claim 3, further comprising: A user interface is displayed on a display associated with the identified customer service agent, the user interface including information related to the service request call and information related to a historical sequence of interactions corresponding to the first customer.

6. The method according to claim 1, wherein: The plurality of software applications include: a first software application operable to respond to the first aspect of the service request call, and at least A second software application may be used to respond to a second aspect of the service request call.

7. The method according to claim 6, wherein: The at least one call-specific indicator comprises: a first call-specific indicator associated with a first aspect of the service request call, and at least A second call-specific indicator related to a second aspect of the service request call.

8. The method according to claim 1, further comprising: The monitoring and the reporting are performed using a container software application designed to facilitate interaction between individual software applications of the plurality of software applications.

9. A computing device for reporting metrics related to customer calls, the computing device comprising: processor; Memory; as well as a communication interface coupled to each of the processor and the memory, Wherein, the processor is configured to: receiving a service request call from a first customer via the communication interface; assigning a single customer service agent to handle the service request call sent by the first customer; determining a plurality of software applications to be used by the single customer service agent to respond to the service request call, the service request call including a plurality of requests of different types, wherein the plurality of software applications resolve the plurality of requests included in the service request call; monitoring the service request call to obtain information related to a time of the service request call, an event occurring during the service request call, and at least one output of the plurality of software applications; when the service request call is completed, determining, for each of the plurality of software applications used by the single customer service agent in servicing the first customer during the service request call, at least one call-specific metric for the corresponding software application based on information obtained as a result of the monitoring; and The determined at least one call-specific metric is reported to a central database for each of the plurality of software applications used by the single customer service agent in servicing the first customer during the service request call.

10. The computing device according to claim 9, wherein: The at least one call-specific metric includes at least one of: hold time, talk time, average handling time, call intent, call handling, answer speed, number of calls hung up, number of dropped calls, number of calls handled, average after-call work time, percentage of calls held, average duration of calls held, percentage of after-call work in average time, number and percentage of calls transferred, number and percentage of conference calls, percentage of combined transferred or conference calls, service level percentage, number of transfers, idle time, call count, type of service software application used by professionals and team leaders on each team for each service request during a call, and number of call records.

11. The computing device according to claim 9, wherein: The processor is further configured to: identifying the customer service agent assigned to handle the service request call, and At least one agent-specific metric is calculated based on the determined at least one call-specific metric and previously stored agent-specific metric data.

12. The computing device according to claim 11, wherein: The processor is further configured to: capturing at least one metadata item associated with the service request call, and Wherein, the at least one metadata item includes at least one of: telephone data, user profile data associated with the identified agent, an identification of each of the multiple software applications used by the single customer service agent, and information related to whether the identified agent performed a search function during the service request call.

13. The computing device of claim 11, wherein: The processor is further configured to: A user interface is displayed on a display associated with the identified customer service agent, the user interface including information related to the service request call and information related to a historical sequence of interactions corresponding to the first customer.

14. The computing device of claim 9, wherein: The plurality of software applications include: a first software application operable to respond to the first aspect of the service request call, and at least A second software application may be used to respond to a second aspect of the service request call.

15. The computing device of claim 14, wherein: The at least one call-specific indicator comprises: a first call-specific indicator associated with a first aspect of said service request call; and at least A second call-specific indicator related to a second aspect of the service request call.

16. The computing device of claim 9, wherein: The processor is further configured to: The monitoring and the reporting are performed using a container software application designed to facilitate interaction between individual software applications of the plurality of software applications.

17. A non-transitory computer readable storage medium storing instructions for reporting metrics related to customer calls, the storage medium comprising executable code that, when executed by a processor, causes the processor to: receiving a service request call from a first customer; assigning a single customer service agent to handle the service request call sent by the first customer; determining a plurality of software applications to be used by the single customer service agent to respond to the service request call, the service request call including a plurality of requests of different types, wherein the plurality of software applications resolve the plurality of requests included in the service request call; monitoring the service request call to obtain information related to a time of the service request call, an event occurring during the service request call, and at least one output of the plurality of software applications; When the service request call is completed, for each of the plurality of software applications used by the single customer service agent in serving the first customer during the service request call, determining at least one call-specific metric for the corresponding software application based on the monitoring results; and The determined at least one call-specific metric is reported to a central database for each of the plurality of software applications used by the single customer service agent in servicing the first customer during the service request call.

18. The storage medium according to claim 17, wherein: The executable code is further configured to cause the processor to: identifying the customer service agent assigned to handle the service request call, and At least one agent-specific metric is calculated based on the determined at least one call-specific metric and previously stored agent-specific metric data.

19. The storage medium according to claim 18, wherein: The executable code is further configured to cause the processor to: A user interface is displayed on a display associated with the identified customer service agent, the user interface including information related to the service request call and information related to a historical sequence of interactions corresponding to the first customer.

20. The storage medium according to claim 17, wherein: The plurality of software applications include: a first software application operable to respond to a first aspect of the service request call; and a second software application operable to respond to at least a second aspect of the service request call.

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