Online customer service intelligent balanced distribution method and system based on big data real-time calculation

Abstract

The invention provides an online customer service intelligent balanced distribution method and system based on big data real-time calculation, and the method comprises the following steps: S1, building an interface for a third-party system to access a manual customer service system, and obtaining the system information of user login through the interface; s2, marking the login state of the manual customer service in a related database according to the online state of the manual customer service of the corresponding system; querying whether the system to which the user belongs has the manual customer service online or not according to the flag bit indicating whether the customer service is online or not in the corresponding database; the corresponding idle customer service staff is automatically dispatched to serve the user according to the system to which the login user belongs, so that the queuing time of the user is shortened, the unbalanced distribution of the customer service staff is reduced, and meanwhile, the condition that the customer service staff is too busy or too idle is also avoided. More professional question answering is provided for the user, and the use experience of the user is improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and more specifically, to a method and system for intelligent balanced allocation of online customer service based on real-time calculation of big data. Background Art

[0002] Online customer service consultation systems are often mounted on multiple access systems through clients. When a user makes a consultation, the corresponding human customer service staff will provide manual answers to the questions. Summary of the invention

[0003] The technical problem to be solved by the present invention is to provide an intelligent balanced allocation method for online customer service based on real-time calculation of big data, which can reduce the waiting time of users, reduce the imbalance in the allocation of manual customer service, and avoid the situation where the manual customer service is too busy or too idle, in response to the shortcomings of the above-mentioned technical solutions.

[0004] The present invention provides a method for intelligent balanced allocation of online customer service based on real-time calculation of big data, the method comprising the following steps:

[0005] S1, establish an interface for the third-party system to access the manual customer service system, and obtain the system information of the user login through the interface;

[0006] S2, according to the online status of the manual customer service of the corresponding system, mark the login status of the manual customer service in the relevant database; and query whether there is a manual customer service online in the system to which the user belongs according to the flag of whether the customer service is online in the corresponding database; S3, after judging the idle status of the manual customer service according to the flag of whether the manual customer service is online in the corresponding system, obtain the current number of manual customer service and the current access volume, and set the reception limit according to the number of users served by the manual customer service and the number of visitors; the manual customer service corresponding to the current system sorts the VIP weight of the user according to the set reception limit, and judges the access priority from high to low. If it is a VIP, it will enter the matching queue first to allocate the manual customer service.

[0007] In the method for intelligent balanced allocation of online customer service based on real-time calculation of big data described in the present invention; in the step S1, the system information includes the system name, access time and login account name.

[0008] In the method for intelligent balanced allocation of online customer service based on real-time calculation of big data described in the present invention; in the step S2, if there is no customer service online, the user is prompted that there is currently no manual customer service online, and the user is asked to conduct self-service Q&A.

[0009] In the method for intelligent balanced allocation of online customer service based on real-time calculation of big data according to the present invention, step S3 further includes the following steps:

[0010] S31, judging whether there is a manual customer service online according to the flag of whether the manual customer service in the corresponding system is online, and if there is a manual customer service online, further querying the idle status of the customer service.

[0011] In the method for intelligent balanced allocation of online customer service based on real-time calculation of big data according to the present invention, step S3 further includes the following steps:

[0012] S32, when the number of users served by the manual customer service has not reached the upper limit of the number of visitors, and the number of users who have been connected to the manual customer service corresponding to the current system is less than the set reception upper limit, it is determined whether the current manual customer service can be accessed.

[0013] In the method for intelligent balanced allocation of online customer service based on real-time calculation of big data according to the present invention, step S3 further includes the following steps:

[0014] S33, when the number of people received by the manual customer service corresponding to the current system has not reached the upper limit, and the VIP weight of the current user is high enough in the ranking, the user can access this manual customer service.

[0015] In the method for intelligent balanced allocation of online customer service based on real-time calculation of big data according to the present invention, step S3 further includes the following steps:

[0016] S34, when the number of users served by the manual customer service has not reached the maximum number of visitors, the current user is put into a queue, and the user is prompted with the current number of people in the queue and the number of users in the queue.

[0017] According to a second aspect of an embodiment of the present invention, there is provided a system for intelligent balanced allocation of online customer service based on real-time calculation of big data, comprising an information acquisition module, an online status judgment module for human customer service, and an allocation and queuing module; the information acquisition module is used to establish an interface for a third-party system to access the human customer service system, and obtain system information of a user login through the interface; the online status judgment module for human customer service is used to mark the login status of the human customer service in a relevant database according to the online status of the human customer service of the corresponding system; and query whether there is a human customer service online in the system to which the user belongs according to the flag of whether the customer service is online in the corresponding database; the allocation module is used to determine the idle state of the human customer service according to the flag of whether the human customer service is online in the corresponding system, and then obtain the current number of human customer service and the current access volume, and set a reception upper limit according to the number of users served by the human customer service and the number of visitors; the human customer service corresponding to the current system sorts the VIP weight of the user according to the set reception upper limit, and determines the access priority from high to low. If it is a VIP, it will enter the matching queue first to allocate the human customer service.

[0018] According to a third aspect of an embodiment of the present invention, a computer-readable medium is provided, on which a computer program is stored. When the program is executed by a processor, any of the above methods is implemented.

[0019] The method for intelligent balanced allocation of online customer service based on real-time calculation of big data of the present invention automatically allocates the corresponding idle manual customer service personnel to serve the user according to the system to which the logged-in user belongs, thereby reducing the user's queuing time and the imbalanced allocation of manual customer service, and also avoiding the situation that the manual customer service is too busy or too idle. It provides users with more professional answers to questions and improves the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flow chart of an embodiment of a method for intelligent balanced allocation of online customer service based on real-time calculation of big data according to the present invention;

[0021] Figure 2 It is a flowchart of the workflow of the online customer service intelligent balanced distribution system based on big data real-time calculation of the present invention. DETAILED DESCRIPTION

[0022] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0023] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0024] like Figure 1-2 The figure is a flow chart of an embodiment of a method for intelligent balanced allocation of online customer service based on big data real-time calculation. A method for intelligent balanced allocation of online customer service based on big data real-time calculation is provided, comprising the following steps:

[0025] S1, establish an interface for the third-party system to access the manual customer service system, and obtain the system information of the user login through the interface;

[0026] S2, according to the online status of the manual customer service of the corresponding system, mark the login status of the manual customer service in the relevant database; and query whether there is a manual customer service online in the system to which the user belongs according to the flag of whether the customer service is online in the corresponding database; S3, after judging the idle status of the manual customer service according to the flag of whether the manual customer service is online in the corresponding system, obtain the current number of manual customer service and the current access volume, and set the reception limit according to the number of users served by the manual customer service and the number of visitors; the manual customer service corresponding to the current system sorts the VIP weight of the user according to the set reception limit, and judges the access priority from high to low. If it is a VIP, it will enter the matching queue first to allocate the manual customer service.

[0027] In one embodiment, the system information in step S1 includes a system name, access time, and a login account name.

[0028] In one embodiment, if there is no customer service online in step S2, the user is prompted that there is currently no manual customer service online, and the user is asked to conduct self-service Q&A.

[0029] In one embodiment, the step S3 further includes the following steps:

[0030] S31, judging whether there is a manual customer service online according to the flag of whether the manual customer service in the corresponding system is online, and if there is a manual customer service online, further querying the idle status of the customer service.

[0031] In one embodiment, the step S3 further includes the following steps:

[0032] S32, when the number of users served by the manual customer service has not reached the upper limit of the number of visitors, and the number of users who have been connected to the manual customer service corresponding to the current system is less than the set reception upper limit, it is determined whether the current manual customer service can be accessed.

[0033] In one embodiment, the step S3 further includes the following steps:

[0034] S33, when the number of people received by the manual customer service corresponding to the current system has not reached the upper limit, and the VIP weight of the current user is high enough in the ranking, the user can access this manual customer service.

[0035] In one embodiment, the step S3 further includes the following steps:

[0036] S34, when the number of users served by the manual customer service has not reached the maximum number of visitors, the current user is put into a queue, and the user is prompted with the current number of people in the queue and the number of users in the queue.

[0037] The embodiment of the present invention provides an intelligent balanced allocation system for online customer service based on real-time calculation of big data, including an information acquisition module, an online status judgment module for manual customer service, and an allocation and queuing module; the information acquisition module is used to establish an interface for a third-party system to access a manual customer service system, and obtain system information of a user login through the interface; the online status judgment module for manual customer service is used to mark the login status of the manual customer service in a related database according to the online status of the manual customer service of the corresponding system; and query whether there is a manual customer service online in the system to which the user belongs according to a flag of whether the customer service is online in the corresponding database; the allocation module is used to determine the idle state of the manual customer service according to the flag of whether the manual customer service is online in the corresponding system, and then obtain the current number of manual customer service and the current access volume, and set a reception upper limit according to the number of users served by the manual customer service and the number of visitors; the manual customer service corresponding to the current system sorts the VIP weight of the user according to the set reception upper limit, and determines the access priority from high to low. If it is a VIP, it will enter the matching queue first to allocate the manual customer service.

[0038] An embodiment of the present invention provides a computer-readable medium on which a computer program is stored. When the program is executed by a processor, any of the above methods is implemented.

[0039] Specifically, the reception line in this application can be customized. In this application, 20 people are configured per person. When the maximum number of visitors to customer service A is configured to be 50 and the maximum number of service people is 30, if the current customer service reception is less than 30 people, it can be directly connected. If it is greater than 30 and less than 50, it will enter the queue sequence. If it is greater than 50, it will be assigned to other customer services.

[0040] The users include VIP and ordinary users. If they are VIP, they will be given priority to enter the matching queue and be assigned customer service.

[0041] The third-party system is connected to the manual customer service system by mounting the URL connection address, and then the communication window is opened by clicking the customer service icon to receive user service requests. The user service request contains relevant third-party system information and user information. When allocating online customer service personnel, after the customer service logs in to the system, the associated service request permissions are processed according to the association between the login account and the third-party system.

[0042] The relevant customer service can only handle service tasks of related third-party systems (such as consultation, complaints, etc.), but cannot operate unrelated third-party system data.

[0043] When the system receives a user service request, it will query the identity priority information of the relevant user (for example, whether the user is a VIP, whether the third-party system with priority service is used), and process the related services. When requesting access rights, it will be sorted according to the principle of identity priority to obtain the service queue, and access will be made in turn.

[0044] When a user service request is closed and received, the system can receive the corresponding service end request and then recalculate the service queue information based on this status information.

[0045] In practical applications, once the customer service is always in a high-load working state, the reception quality will also decline, which will indirectly affect the customer service satisfaction. Therefore, an online customer service allocation method that can improve the allocation balance under the principle of optimal allocation is designed. This application can intelligently identify the system to which the user logs in, and then intelligently allocate idle manual customer service users according to the busyness of the manual customer service; the maximum number of visitors and the maximum number of service users of the manual customer service can be configured, and a busy threshold is set. When the customer service is in a busy state, it means that there are too many people currently consulting. The AI ​​algorithm prediction ability can be used to predict the number of user accesses in the subsequent period of time based on the current access volume and historical data, so that it can be predicted in advance whether the manual customer service is saturated, and the management can be reminded to increase the number of manual customer service personnel by early warning emails. The present invention determines whether to access this manual customer service by the user's VIP weight, whether the customer service is online, and the current access volume, and quickly recommends the preferred manual service customer service, thereby improving the flexibility and adaptability of application-related applications. The AI ​​algorithm predicts a growth rate of (yesterday's access volume-the day before yesterday's access volume) / the day before yesterday's access volume, and then calculates up to 15 data in turn, takes the average value, and obtains a final average growth rate. The estimated number of visits today is calculated by multiplying (average growth rate + 1) by yesterday's visits. This is similar to the calculation method of the month-on-month growth, but it is calculated on a daily basis, and then the average is taken as the predicted growth rate.

[0046] It should be noted that, for the above-mentioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should know that the present invention is not limited by the described action sequence, because according to the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required by the present invention.

[0047] Through the description of the above implementation methods, those skilled in the art can clearly understand that the method according to the above embodiment can be implemented by means of software plus a necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0048] Therefore, the above is only a preferred specific implementation mode of the present invention, and the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily thought of by any technician familiar with the technical field within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention. The protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for intelligent balanced allocation of online customer service based on real-time calculation of big data, characterized in that: The method comprises the following steps: S1, establish an interface for the third-party system to access the manual customer service system, and obtain the system information of the user login through the interface; S2, according to the online status of the manual customer service of the corresponding system, mark the login status of the manual customer service in the relevant database; and query whether there is a manual customer service online in the system to which the user belongs according to the flag bit of whether the customer service is online in the corresponding database; S3, after judging the idle state of the manual customer service according to the flag of whether the manual customer service in the corresponding system is online, obtain the current number of manual customer service and the current access volume, and set the reception limit according to the number of users served by the manual customer service and the number of visitors; the manual customer service corresponding to the current system sorts the VIP weights of the users according to the set reception limit, and judges the access priority from high to low. If it is a VIP, it will enter the matching queue first to allocate the manual customer service.

2. The method for intelligent balanced allocation of online customer service based on real-time calculation of big data according to claim 1 is characterized in that: In step S1, the system information includes the system name, access time and login account name.

3. The method for intelligent balanced allocation of online customer service based on real-time calculation of big data according to claim 2 is characterized in that: In step S2, if there is no customer service online, the user is prompted that there is currently no manual customer service online, and the user is asked to conduct self-service Q&A.

4. The method for intelligent balanced allocation of online customer service based on real-time calculation of big data according to claim 3 is characterized in that: The step S3 further comprises the following steps: S31, judging whether there is a manual customer service online according to the flag of whether the manual customer service in the corresponding system is online, and if there is a manual customer service online, further querying the idle status of the customer service.

5. The method for intelligent balanced allocation of online customer service based on real-time calculation of big data according to claim 4 is characterized in that: The step S3 further comprises the following steps: S32, when the number of users served by the manual customer service has not reached the upper limit of the number of visitors, and the number of users who have been connected to the manual customer service corresponding to the current system is less than the set reception upper limit, it is determined whether the current manual customer service can be accessed.

6. The method for intelligent balanced allocation of online customer service based on real-time calculation of big data according to claim 5 is characterized in that: The step S3 further comprises the following steps: S33, when the number of people received by the manual customer service corresponding to the current system has not reached the upper limit, and the VIP weight of the current user is high enough in the ranking, the user can access this manual customer service.

7. The method for intelligent balanced allocation of online customer service based on real-time calculation of big data according to claim 6 is characterized in that: The step S3 further comprises the following steps: S34, when the number of users served by the manual customer service has not reached the maximum number of visitors, the current user is put into a queue, and the user is prompted with the current number of people in the queue and the number of users in the queue.

8. An intelligent balanced distribution system for online customer service based on real-time calculation of big data, characterized in that: It includes an information acquisition module, a manual customer service online status judgment module and an allocation and queuing waiting module; the information acquisition module is used to establish an interface for the third-party system to access the manual customer service system, and obtain the system information of the user login through the interface; the manual customer service online status judgment module is used to mark the login status of the manual customer service in the relevant database according to the online status of the manual customer service of the corresponding system; And according to the flag of whether the customer service is online in the corresponding database, check whether there is a manual customer service online in the system to which the user belongs; The allocation module is used to determine the idle state of the manual customer service according to the flag bit indicating whether the manual customer service in the corresponding system is online, and then obtain the current number of manual customer service and the current access volume, and set the reception limit according to the number of users served by the manual customer service and the number of visitors; The manual customer service corresponding to the current system sorts the user's VIP weight according to the set reception limit, and determines the access priority from high to low. If the user is a VIP, he / she will be given priority to enter the matching queue and be assigned manual customer service.

9. A computer readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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