WO2019227624A1

WO2019227624A1 - Monitoring method for call center, electronic apparatus, computer device and storage medium

Info

Publication number: WO2019227624A1
Application number: PCT/CN2018/095867
Authority: WO
Inventors: 徐墨
Original assignee: 平安科技（深圳）有限公司
Priority date: 2018-05-30
Filing date: 2018-07-17
Publication date: 2019-12-05
Also published as: CN108769435A

Abstract

A monitoring method for a call center, which relates to the field of visual monitoring. The method comprises the following steps: obtaining, from a call system, telephone traffic data corresponding to an agent (S1); storing, in a redis queue, real-time status data and telephony integration data associated with an agent ID (S2); obtaining the telephony integration data associated with the agent ID from within the redis queue according to the agent ID, and calculating telephone traffic indicator data according to the telephony integration data (S3); associating the calculated telephone traffic indicator data with the corresponding agent ID and then storing in the redis queue (S4); according to a received data acquisition request comprising the agent ID initiated by a front end, retrieving the telephone traffic data and the telephone traffic indicator data of the corresponding agent from within the redis queue, and displaying on a front end page (S5). The real-time status of the agent is visually displayed, which is convenient for an administrator to intuitively see the current status of each agent and thus facilitates management.

Description

Monitoring method for call center, electronic device, computer equipment and storage medium

This application affirms the priority of the Chinese patent application filed on May 30, 2018 with the application number 201810537975.6 and the name "monitoring method of call center, electronic device, computer equipment and storage medium", the entire content of the Chinese patent application This application is incorporated by reference.

Technical field

The present application relates to the field of visual monitoring, and relates to a monitoring method, electronic device, computer equipment and storage medium of a call center.

Background technique

The so-called call center is a comprehensive information service system based on CTI (Computer Telephony Integration) technology, making full use of the multiple functions of the communication network and computer network to integrate with the enterprise, which can effectively and quickly provide users with Multiple services. As the market competition becomes more and more fierce, the service quality of call center customer service staff is becoming higher and higher. However, customer service staff handles tens of thousands of calls every day, and business faults and customer complaints are often sent. In order to ensure and grasp the service quality of customer service personnel and improve customer satisfaction, it is usually necessary to control the service process of customer service personnel.

However, in large call centers, the number of agents at each site in the call center is large and the sites are scattered. It is difficult for the site administrators and call center operations managers to effectively and timely manage each customer service staff. First of all, traditional agent monitoring can only know the current status of the agent, it cannot confirm the physical location of the agent, and whether the current status is abnormal. Especially when the agents are distributed in different office areas, it is not convenient for the management personnel to make overall management. Second, traditional phone platforms cannot provide real-time statistics, forecasting, and display functions of various indicators of agents. Agent managers can only check team performance through daily or weekly reports, monthly reports provided by the service or business platform. Due to poor timeliness, it often leads to untimely control and loss of performance.

Summary of the Invention

The technical problem to be solved in this application is to overcome the problems of untimely management and control of agents in the prior art, which is inconvenient to manage large call centers. A monitoring method, electronic device, computer equipment and storage medium for a call center are proposed to realize The agent is visually monitored and the agent status is refreshed in real time.

This application solves the above technical problems through the following technical solutions:

A monitoring method for a call center includes the following steps:

S1. Obtain traffic data corresponding to an agent from a calling system, the traffic data is stored in the calling system in association with an agent ID and a device ID, and the traffic data includes real-time status data and basic traffic data of the agent;

S2. Store real-time status data and basic traffic data associated with the agent ID into the redis queue;

S3. Obtain the basic traffic data related to the agent ID from the redis queue according to the agent ID, and calculate the traffic indicator data according to the basic traffic data;

S4. Associate the calculated traffic indicator data with the corresponding agent ID and store it in the redis queue;

S5. According to the received data acquisition request including the agent ID initiated by the front end, the traffic data and traffic index data of the corresponding agent are retrieved from the redis queue and displayed on the front page.

This application also discloses an electronic device. The electronic device stores a monitoring system of the call center. The monitoring system of the call center includes:

A data acquisition module, configured to obtain traffic data corresponding to the agent from the calling system, the traffic data is stored in the calling system in association with the agent ID and the device ID, and the traffic data includes real-time status data of the agent and voice Service basic data;

A sorting module, configured to store real-time status data and traffic basic data associated with agent IDs into a redis queue;

A calculation module, configured to obtain basic traffic data related to the agent ID from the redis queue according to the agent ID, and calculate traffic indicator data according to the basic traffic data;

Association storage module, which is used to associate the calculated traffic indicator data with the corresponding agent ID and store it in the redis queue;

The data call display module is configured to retrieve the traffic data and traffic index data of the corresponding agent from the redis queue according to the received data acquisition request containing the agent ID and display it on the front-end page.

The present application also discloses a computer device including a memory and a processor. The memory stores a monitoring system of a call center that can be executed by the processor. When the system is executed by the processor, the following steps are implemented: operating:

The present application also discloses a computer-readable storage medium. The computer-readable storage medium stores computer program instructions, and the computer program instructions can be executed by at least one processor to enable the at least one processor to execute. The following steps:

S5. According to the received data acquisition request including the agent ID initiated by the front end, the traffic data and traffic index data of the corresponding agent are retrieved from the redis queue and displayed on the front page. .

The positive progress effect of this application lies in:

1) The real-time status of the agents is visually displayed, so that the manager can intuitively see the current status of each agent, which is convenient for management.

2) Monitor the abnormal state of the agent in real time. Once the abnormal state occurs, immediately alert in various ways for timely processing.

3) Asynchronous request technology (Ajax) is used for interaction between the front end and the queue without blocking the data channel.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a flowchart of a first embodiment of a monitoring method for a call center according to the present application;

FIG. 2 shows an example diagram of a real-time status of an agent displayed on the front page corresponding to the agent position;

Figure 3 shows an example of real-time status-icon correspondence;

4 shows a flowchart of a second embodiment of a monitoring method for a call center according to the present application;

5 shows a schematic diagram of a program module of a first embodiment of a monitoring system of a call center in an electronic device of the present application;

6 shows a schematic diagram of a program module of a second embodiment of a monitoring system of a call center in an electronic device of the present application;

FIG. 7 shows a schematic diagram of a hardware architecture of an embodiment of a computer device of the present application.

Detailed ways

The following further describes the present application by way of examples, but the present application is not limited to the scope of the examples.

First, this application proposes a monitoring method for a call center.

In the first embodiment, as shown in FIG. 1, the method for monitoring a call center includes the following steps:

S1. Obtain traffic data corresponding to an agent from a calling system. The traffic data is stored in the calling system in association with an agent ID and a device ID. The traffic data includes real-time status data and basic traffic data of the agent.

The development of the call system has more and more functions so far. The call system is not only used to answer customer calls, but also has a data storage function, which can record the working process of each agent in detail, including Traffic data.

The traffic data is mainly divided into real-time status data and basic traffic data. These data are stored in association with the agent ID and the device ID of the agent. The agent ID and the device ID can trace the source of the data and help manage the agent.

The real-time status data includes, but is not limited to, the following various data: not logged in, not ready, idle, calling, on hold, tea break, call dialing, and meal.

The basic traffic data includes, but is not limited to, the following data: current status, check-in time, total call duration, total number of calls, incoming call times, incoming call duration, outgoing call times, outgoing call duration, after-talk Sorting time, finishing number of calls, total number of calls, call loss, rest times, rest time, hold times, hold time, busy time, busy time, idle time, requests and calls.

The above-mentioned traffic data is directly recorded by the calling system and does not need to be calculated. It is equivalent to the original data. Therefore, these data are also recorded in the calling system in a record-by-record manner, and are not integrated data. For example: 12345 (agent ID) + call (real-time status), 12345 + (2min) call duration. These data related to agent ID 12345 are stored separately. In this example, there are two records.

The obtaining method is preferably cyclically acquired according to a preset interval. Since the data is stored in association with the agent ID, obtaining the corresponding traffic data of the agent requires providing the agent ID, and the corresponding traffic data is found by the agent ID.

S2. The real-time status data and basic traffic data associated with the agent ID are stored in the redis queue.

Specifically, the data is sequentially stored in the redis queue according to the acquisition time of the data, that is, the data obtained first is stored in the redis queue first.

S3. Obtain the basic traffic data related to the agent ID from the redis queue according to the agent ID, and calculate the traffic indicator data according to the basic traffic data.

When you need to calculate the traffic index data of a certain agent or a group of agents, you must first provide the agent ID of a certain agent or a group of agents involved in the calculation in order to obtain relevant data from the redis queue. The data related to a certain agent ID is extracted from the redis queue for calculation and use.

The traffic indicator data includes, but is not limited to, the following various data: the current state duration, check-in duration, call average length, incoming call average length, outgoing call average length, post-adjustment average length, piece processing time, Call loss rate, average length of rest, average length of stay and average length of busy time.

The traffic indicator data is calculated from the traffic basic data through a specific calculation method. The calculation method of the above traffic indicator data is as follows:

Duration of current state = current time-start time of current state;

Check-in duration = current time-start time of check-in;

Average call length = total call duration / total number of calls;

Incoming call length = Incoming call duration / Incoming calls times;

Outgoing call duration = outgoing call duration / incoming calls;

After-talk adjustment average length = After-talk adjustment duration / After-talk adjustment times;

The average processing time of each case = (average length of incoming calls + average processing length of outgoing calls) / 2+ adjustment of average length after the call

Call loss rate = number of call losses / number of requests;

Average length of rest = length of rest / number of rest;

Holding average length = holding duration / holding times;

Average busy length = busy length / busy times.

When calculating, each time is calculated for each traffic indicator data.

S4. The calculated traffic indicator data is associated with the corresponding agent ID and stored in the redis queue.

The data calculated each time must be stored in association with the agent ID for later retrieval and use.

When saving, the data is stored in the redis queue according to the calculation time of the data, that is, the data calculated first is stored in the redis queue first.

Because the redis queue stores several data of the same agent, in addition to the agent ID in the data acquisition request, it usually also contains the type of data to be obtained. For example, when looking at the processing time of all the pieces of a certain agent, the name of the data type should be included in the data acquisition request.

In an embodiment, in order to prevent data congestion from occurring when the front end interacts with the redis queue, the front end and the redis queue preferably interact through Ajax to obtain traffic data and traffic indicator data, so as to realize asynchronously obtaining the call. Traffic data and traffic indicator data.

The Ajax means asynchronous JavaScript and XML (Asynchronous JavaScript and XML). The core of Ajax is the JavaScript object XmlHttpRequest. This object was first introduced in Internet Explorer 5, and it is a technology that supports asynchronous requests. In short, XmlHttpRequest enables the web front end to use JavaScript to make requests to the backend server and process the response without blocking the user.

In an embodiment, in order to make the data display more intuitive, it is preferable to use a visual display, by matching and combining the traffic data, traffic indicator data and scene model according to the agent IP and device ID associated with the data, so as to display the The corresponding agent position shows the real-time status of the agent, see Figure 2. The scene model is established according to the on-site layout of the call center; the real-time status is displayed by icons, and each real-time status corresponds to an icon preset in the location. Refer to Figure 3 for the scenario model.

Through this visual display, managers can know the status of each seat at a glance at a glance.

In an embodiment, the traffic data and / or the traffic indicator data may also be displayed on the front-end page in the manner of a trend graph. For example, when a manager wants to view certain data for a certain period of time for a certain agent, simply enter the agent ID and the name of the data type, and the relevant data can be directly called up and displayed in the management as a trend graph. On the page of the personnel, it is convenient for them to view and judge.

In the second embodiment, based on the first embodiment, as shown in FIG. 4, the method for monitoring a call center includes the following steps:

S1-S5 are the same as the first embodiment, and will not be repeated here.

S6. Determine whether the agent is in an abnormal state by using the traffic data and / or traffic indicator data, and if so, perform an abnormal reminder on the front-end page, where the abnormal reminder method includes a pop-up screen, an audible alarm, and / or an icon blink.

Compared with the first embodiment, the second embodiment adds an abnormality reminding function. Specifically, by presetting a threshold value of certain data, when the data exceeds the threshold value, an abnormality reminding is performed for the corresponding agent. For example, it is stipulated that the length of a break for an agent cannot exceed 15 minutes, and when a break of a certain agent exceeds 15 minutes, an abnormal reminder is given to it.

In one embodiment, if the reminder is not eliminated after a few minutes after the abnormal reminder, the abnormal reminder is further sent to the relevant management personnel to prompt it to deal with it as soon as possible.

Secondly, the present application proposes an electronic device. The electronic device stores a monitoring system 20 of a call center, and the system 20 can be divided into one or more program modules.

For example, FIG. 5 shows a schematic diagram of a program module of the first embodiment of the monitoring system 20 of the call center. In this embodiment, the system 20 can be divided into a status determination module 201, a reservation selection module 202, and an instruction sending module 203. The information receiving module 204 and the reminding module 205. Among them, the program module referred to in the present application refers to a series of computer program instruction segments capable of performing specific functions. The following description will specifically introduce the specific functions of the program modules 201-205.

The data acquisition module 201 is configured to acquire traffic data corresponding to an agent from a calling system, the traffic data is stored in the calling system in association with the agent ID and the device ID, and the traffic data includes real-time status data of the agent And traffic basic data.

The above-mentioned traffic data is directly recorded by the call system and does not need to be calculated. It is equivalent to the original data. Therefore, these data are also recorded in the call system in a record-by-record manner, and are not integrated data. For example: 12345 (agent ID) + call (real-time status), 12345 + (2min) call duration. These data related to agent ID 12345 are stored separately. In this example, there are two records.

The acquisition method is preferably cyclically acquired according to a preset interval. Since the data is stored in association with the agent ID, obtaining the traffic data corresponding to the agent requires providing the agent ID, and the corresponding traffic data is found by the agent ID.

The sorting module 202 is configured to store real-time status data and traffic basic data associated with the agent ID into a redis queue.

The calculation module 203 is configured to obtain traffic basic data related to the agent ID from the redis queue according to the agent ID, and calculate traffic indicator data according to the traffic basic data.

Duration of current state = current time-start time of current state;

Check-in duration = current time-start time of check-in;

Average call length = total call duration / total number of calls;

Incoming call length = Incoming call duration / Incoming calls times;

Outgoing call duration = outgoing call duration / incoming calls;

Call loss rate = number of call losses / number of requests;

Average length of rest = length of rest / number of rest;

Holding average length = holding duration / holding times;

Average busy length = busy length / busy times.

When calculating, each time is calculated for each traffic indicator data indicator data.

The association storage module 204 is configured to associate the calculated traffic indicator data with a corresponding agent ID and store the calculated traffic indicator data in a redis queue.

The data call display module 205 is configured to retrieve the traffic data and traffic indicator data of the corresponding agent from the redis queue according to the received data acquisition request including the agent ID and display it on the front-end page.

In an embodiment, in order to make the data display more intuitive, the data call display module 205 preferably uses a visual display, and matches and combines the traffic data, traffic index data, and scene model according to the agent IP and device ID associated with the data. To display the real-time status of the agent on the front-end page corresponding to the agent's position, see Figure 2; the scene model is established according to the on-site layout of the call center; the real-time status is displayed by icons, each real-time status corresponds to a Icons are preset in the scene model, see FIG. 3.

As another example, FIG. 6 shows a schematic diagram of a program module of the second embodiment of the monitoring system 20 of the call center. In this embodiment, the monitoring system 20 of the call center can also be divided into a status determination module 201 and a reservation selection. Module 202, instruction sending module 203, information receiving module 204, reminder module 205, and reminder module 206.

The program modules 201-205 are the same as those in the first embodiment, and details are not described herein again.

The reminder module 206 is configured to determine whether the agent is in an abnormal state by using the traffic data and / or traffic indicator data, and if so, perform an abnormal reminder on the front-end page. The abnormal reminder method includes a pop-up screen, an audible alarm and / or The icon flashes.

Specifically, by presetting a threshold value of certain data, when the data exceeds the threshold value, an abnormal reminder is given to the corresponding agent. For example, it is stipulated that the length of a break for an agent cannot exceed 15 minutes, and when a break of a certain agent exceeds 15 minutes, an abnormal reminder is given to it.

Again, this application also proposes a computer device.

Refer to FIG. 7, which is a schematic diagram of a hardware architecture of a computer device according to an embodiment of the present application. In this embodiment, the computer device 2 is a device capable of automatically performing numerical calculation and / or information processing in accordance with an instruction set or stored in advance. For example, it can be a smart phone, a tablet computer, a notebook computer, a desktop computer, a rack server, a blade server, a tower server, or a rack server (including an independent server or a server cluster composed of multiple servers). As shown in the figure, the computer device 2 includes at least, but is not limited to, a memory 21, a processor 22, a network interface 23, and a monitoring system 20 of a call center that can communicate with each other through a system bus. among them:

The memory 21 includes at least one type of computer-readable storage medium. The readable storage medium includes a flash memory, a hard disk, a multimedia card, a card-type memory (for example, SD or DX memory, etc.), a random access memory (RAM), Static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, magnetic disks, optical disks, etc. In some embodiments, the memory 21 may be an internal storage unit of the computer device 2, such as a hard disk or a memory of the computer device 2. In other embodiments, the memory 21 may also be an external storage device of the computer device 2, such as a plug-in hard disk, a smart memory card (SMC), and a secure digital device. (Secure Digital, SD) card, Flash card, etc. Of course, the memory 21 may also include both an internal storage unit of the computer device 2 and an external storage device thereof. In this embodiment, the memory 21 is generally used to store an operating system and various application software installed on the computer device 2, such as program codes of the monitoring system 20 of the call center. In addition, the memory 21 may also be used to temporarily store various types of data that have been output or will be output.

The processor 22 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chips in some embodiments. The processor 22 is generally used to control the overall operation of the computer device 2, for example, to perform control and processing related to data interaction or communication with the computer device 2. In this embodiment, the processor 22 is configured to run program code or process data stored in the memory 21, for example, to run the monitoring system 20 of the call center.

The network interface 23 may include a wireless network interface or a wired network interface. The network interface 23 is generally used to establish a communication connection between the computer device 2 and other computer devices. For example, the network interface 23 is configured to connect the computer device 2 and an external terminal through a network, and establish a data transmission channel and a communication connection between the computer device 2 and the external terminal. The network may be an Intranet, the Internet, a Global System for Mobile Communication (GSM), a Wideband Code Division Multiple Access (WCDMA), a 4G network, 5G Wireless, wired or other networks such as Internet, Bluetooth, Wi-Fi.

It should be noted that FIG. 7 only shows the computer device 2 with components 21-23, but it should be understood that it is not required to implement all the illustrated components, and more or fewer components may be implemented instead.

In this embodiment, the monitoring system 20 of the call center stored in the memory 21 may be executed by one or more processors (processor 22 in this embodiment) to complete the operations of the monitoring method of the above-mentioned call center. .

In addition, the present application provides a computer-readable storage medium. The computer-readable storage medium is a non-volatile readable storage medium that stores therein computer program instructions that can be executed by at least one processor. To enable the at least one processor to execute the steps of the monitoring method of a call center according to any one of the foregoing.

Although the specific implementation of the present application is described above, those skilled in the art should understand that this is only an example, and the protection scope of the present application is defined by the appended claims. Those skilled in the art can make various changes or modifications to these embodiments without departing from the principle and essence of this application, but these changes and modifications all fall into the protection scope of this application.

Claims

A monitoring method for a call center is characterized in that it includes the following steps:

S1. Obtain traffic data corresponding to an agent from a calling system, the traffic data is stored in the calling system in association with an agent ID and a device ID, and the traffic data includes real-time status data and basic traffic data of the agent;

S2. Store real-time status data and basic traffic data associated with the agent ID into the redis queue;

S3. Obtain the basic traffic data related to the agent ID from the redis queue according to the agent ID, and calculate the traffic indicator data according to the basic traffic data;

S4. Associate the calculated traffic indicator data with the corresponding agent ID and store it in the redis queue;

S5. According to the received data acquisition request including the agent ID initiated by the front end, the traffic data and traffic index data of the corresponding agent are retrieved from the redis queue and displayed on the front page.
The monitoring method of a call center according to claim 1, wherein the real-time status data and the traffic basic data are sequentially stored in the redis queue according to the time of data acquisition, and the traffic indicator data According to the calculation time of the data, they are sequentially stored in the redis queue.
The monitoring method of a call center according to claim 1, wherein the call data and traffic index data of the corresponding agent retrieved from the redis queue and displayed on the front-end page include:

Match and combine traffic data, traffic indicator data, and scenario models according to the agent IP and device ID associated with the data to display the real-time status of the agent on the front-end page corresponding to the agent position;

The scene model is established according to the on-site layout of the call center;

The real-time status is displayed by an icon, and each real-time status corresponds to an icon preset in the scene model.
The method for monitoring a call center according to claim 3, further comprising the following steps:

S6. Determine whether the agent is in an abnormal state by using the traffic data and / or traffic indicator data, and if so, perform an abnormal reminder on the front-end page, where the abnormal reminder method includes a pop-up screen, an audible alarm, and / or an icon blink.
The monitoring method of a call center according to claim 1, wherein the front end and the redis queue interact through Ajax to obtain traffic data and traffic index data.
The method for monitoring a call center according to claim 1, wherein the traffic data and / or traffic indicator data is displayed on a front-end page in a trend graph.
An electronic device is characterized in that a monitoring system of a call center is stored on the electronic device, and the monitoring system of the call center includes:

A data acquisition module, configured to obtain traffic data corresponding to the agent from the calling system, the traffic data is stored in the calling system in association with the agent ID and the device ID, and the traffic data includes real-time status data of the agent and voice Service basic data;

A sorting module, configured to store real-time status data and traffic basic data associated with agent IDs into a redis queue;

A calculation module, configured to obtain basic traffic data related to the agent ID from the redis queue according to the agent ID, and calculate traffic indicator data according to the basic traffic data;

Association storage module, which is used to associate the calculated traffic indicator data with the corresponding agent ID and store it in the redis queue;

The data call display module is configured to retrieve the traffic data and traffic index data of the corresponding agent from the redis queue according to the received data acquisition request containing the agent ID and display it on the front-end page.
The electronic device according to claim 7, wherein the monitoring system of the call center further comprises:

A reminder module is used to judge whether the agent is in an abnormal state by using the traffic data and / or the traffic indicator data, and if so, an abnormal reminder is performed on the front-end page, and the abnormal reminder method includes a pop-up screen, an audible alarm, and / or an icon flashing .
A computer device includes a memory and a processor, wherein the memory stores a monitoring system of a call center that can be executed by the processor, and implements the following steps when the system is executed by the processor: :

S1. Obtain traffic data corresponding to an agent from a calling system, the traffic data is stored in the calling system in association with an agent ID and a device ID, and the traffic data includes real-time status data and basic traffic data of the agent;

S2. Store real-time status data and basic traffic data associated with the agent ID into the redis queue;

S3. Obtain the basic traffic data related to the agent ID from the redis queue according to the agent ID, and calculate the traffic indicator data according to the basic traffic data;

S4. Associate the calculated traffic indicator data with the corresponding agent ID and store it in the redis queue;

S5. According to the received data acquisition request including the agent ID initiated by the front end, the traffic data and traffic index data of the corresponding agent are retrieved from the redis queue and displayed on the front page.
The computer device according to claim 9, wherein the real-time status data and the traffic basic data are sequentially stored in the redis queue according to the data acquisition time, and the traffic indicator data is stored according to the data. The calculation time is sequentially stored in the redis queue.
The computer device according to claim 9, characterized in that the call data and the traffic index data of the corresponding agent retrieved from the redis queue and displayed on the front-end page include:

Match and combine traffic data, traffic indicator data, and scenario models according to the agent IP and device ID associated with the data to display the real-time status of the agent on the front-end page corresponding to the agent position;

The scene model is established according to the on-site layout of the call center;

The real-time status is displayed by an icon, and each real-time status corresponds to an icon preset in the scene model.
The computer device according to claim 11, further comprising operations of the following steps:

S6. Determine whether the agent is in an abnormal state by using the traffic data and / or traffic indicator data, and if so, perform an abnormal reminder on the front-end page, where the abnormal reminder method includes a pop-up screen, an audible alarm, and / or an icon blink.
The computer device according to claim 9, wherein the front end and the redis queue interact through Ajax to obtain traffic data and traffic indicator data.
The computer device according to claim 9, wherein the traffic data and / or traffic indicator data is displayed on a front-end page in a manner of a trend graph.
A computer-readable storage medium, wherein computer program instructions are stored in the computer-readable storage medium, and the computer program instructions are executable by at least one processor, so that the at least one processor executes Step operation:

S1. Obtain traffic data corresponding to an agent from a calling system, the traffic data is stored in the calling system in association with an agent ID and a device ID, and the traffic data includes real-time status data and basic traffic data of the agent;

S2. Store real-time status data and basic traffic data associated with the agent ID into the redis queue;

S3. Obtain the basic traffic data related to the agent ID from the redis queue according to the agent ID, and calculate the traffic indicator data according to the basic traffic data;

S4. Associate the calculated traffic indicator data with the corresponding agent ID and store it in the redis queue;

S5. According to the received data acquisition request including the agent ID initiated by the front end, the traffic data and traffic index data of the corresponding agent are retrieved from the redis queue and displayed on the front page.
The computer-readable storage medium according to claim 15, wherein the real-time status data and the traffic basic data are sequentially stored in the redis queue according to the data acquisition time, and the traffic indicator data According to the calculation time of the data, they are sequentially stored in the redis queue.
The computer-readable storage medium according to claim 15, wherein the call data and traffic index data of the corresponding agent retrieved from the redis queue and displayed on the front-end page include:

Match and combine traffic data, traffic indicator data, and scenario models according to the agent IP and device ID associated with the data to display the real-time status of the agent on the front-end page corresponding to the agent position;

The scene model is established according to the on-site layout of the call center;

The real-time status is displayed by an icon, and each real-time status corresponds to an icon preset in the scene model.
The computer-readable storage medium according to claim 17, further comprising operations of the following steps:

S6. Determine whether the agent is in an abnormal state by using the traffic data and / or traffic indicator data, and if so, perform an abnormal reminder on the front-end page, where the abnormal reminder method includes a pop-up screen, an audible alarm, and / or an icon blink.
The computer-readable storage medium according to claim 15, wherein the front end and the redis queue interact through Ajax to obtain traffic data and traffic indicator data.
The computer-readable storage medium according to claim 15, wherein the traffic data and / or traffic indicator data are displayed on a front-end page in a trend graph manner.