CN116320166A - Multi-element-based customer service call system resource scheduling method and device - Google Patents
Multi-element-based customer service call system resource scheduling method and device Download PDFInfo
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Abstract
The embodiment of the disclosure relates to the field of call center resource scheduling, and provides a multi-element-based customer service call system resource scheduling method and device, wherein the method comprises the following steps: receiving a call request sent by at least one user terminal, and acquiring customer comprehensive information respectively corresponding to the at least one user terminal, wherein the customer comprehensive information comprises equipment state information, customer situation information and customer attribution information; respectively calculating a customer situation comprehensive score corresponding to at least one user terminal according to the equipment state information, the customer situation information and the customer place information; and dispatching customer service calling system resources based on the customer situation comprehensive score, and distributing the customer service calling system resources for at least one user terminal. The embodiment of the disclosure can fully evaluate the situation of the client, and based on the situation, the customer service calling system resources are allocated, so that the service efficiency is improved, the social responsibility is considered, the user experience is improved, and the customer service calling system resources can be preferentially allocated to the customers needing the service in an imperceptible condition.
Description
Technical Field
The disclosure relates to the technical field of call center resource scheduling, in particular to a multi-element-based customer service call system resource scheduling method and device.
Background
In modern service industries, typified by retail, financial, and traffic, call centers are important customer service departments. The telephone operators can improve the enterprise image and warm thousands of clients through professional, close and accurate service. However, with the gradual increase of the manpower cost, more and more commercial organizations share the working pressure of operators by introducing technologies such as semantic recognition, customer service robots and the like, so that the cost expenditure is reduced. However, it is undeniable that the customer service robot cannot replace the professional attendant in a short period of time.
Currently, traffic service resources tend to be a fly-over compared to the huge customer demand. Therefore, how to serve more customers with limited traffic service resources is a long felt problem for the industry.
In the prior art, in the traffic peak period, a customer service center queues incoming requests according to incoming time, and the idle traffic seat preferentially serves the earliest incoming customer in the queue. However, although this way can alleviate the business pressure of the customer service personnel to a certain extent, the waiting time of the customer is often prolonged, so that the customer's dissatisfaction is induced. For such contradiction between supply and demand, a common solution in the industry is to give VIP clients a treatment of avoiding queuing or giving priority to queue-up, etc. to obtain service preferentially. However, this approach, while improving the experience of some users, does not address social responsibility and may be counter-current to the original intent of the service customer in some emergency situations. In addition, the prior art can predict future telephone traffic through historical call data, and the online number of telephone operators is regulated in advance according to the prediction result so as to optimize the utilization efficiency of telephone traffic service resources. However, this approach also fails to achieve optimal allocation of traffic service resources when certain special conditions are encountered.
Disclosure of Invention
The present disclosure aims to solve at least one of the problems in the prior art, and provides a multi-element-based customer service call system resource scheduling method and apparatus.
In one aspect of the present disclosure, a multi-element-based customer service call system resource scheduling method is provided, where the scheduling method includes:
receiving a call request sent by at least one user terminal, and acquiring customer comprehensive information respectively corresponding to the at least one user terminal, wherein the customer comprehensive information comprises equipment state information, customer situation information and customer attribute information;
according to the equipment state information, the client situation information and the client attribute information, respectively calculating a client situation comprehensive score corresponding to the at least one user terminal;
and scheduling customer service call system resources based on the customer location comprehensive score, and distributing the customer service call system resources for the at least one user terminal.
Optionally, the calculating the comprehensive score of the customer situation corresponding to the at least one user terminal according to the equipment state information, the customer situation information and the customer attribute information includes:
for each user terminal, respectively evaluating the emergency score corresponding to the equipment state information, the client situation information and the client attribute information;
based on the emergency score corresponding to the equipment state information, the customer location information and the customer location information, respectively, calculating the customer location comprehensive score corresponding to each user terminal by adopting a weighted summation mode shown in the following formula (1):
score＝s_phone*w_phone+s_person*w_person+s_location*w_location(1)
the score represents the comprehensive score of the customer location, s_phone represents the emergency score corresponding to the equipment state information, w_phone represents the weight corresponding to the equipment state information, s_person represents the emergency score corresponding to the customer location information, w_person represents the weight corresponding to the customer location information, s_location represents the emergency score corresponding to the customer location information, and w_location represents the weight corresponding to the customer location information.
Optionally, the scheduling the customer service call system resource based on the customer situation comprehensive score, allocating the customer service call system resource to the at least one user terminal includes:
and preferentially distributing the customer service call system resources to the user terminal in response to that only one customer situation comprehensive score corresponding to the user terminal exceeds a preset threshold.
Optionally, the scheduling the customer service call system resource based on the customer situation comprehensive score, allocating the customer service call system resource to the at least one user terminal includes:
responding to the situation comprehensive scores of the clients corresponding to the user terminals exceeding a preset threshold, and sequencing the user terminals according to the situation comprehensive scores of the clients to generate a priority service queue;
and distributing the customer service call system resources to the user terminals based on the sequence of the user terminals in the priority service queue.
Optionally, the obtaining the customer integrated information corresponding to the at least one user terminal includes:
respectively sending an authorization request to the at least one user terminal, wherein the authorization request is used for requesting to acquire the use permission of the preset resource in the corresponding user terminal;
and responding to the receiving of the grant authorization response sent by at least one user terminal, and acquiring the corresponding comprehensive client information based on the corresponding preset resources.
Optionally, the preset resources include battery power, network signal quantity and geographic position of the user terminal;
the obtaining the corresponding comprehensive customer information based on the corresponding preset resources includes:
determining the device status information based on the battery level and the network semaphore;
based on the geographic position and the public opinion big data updated in real time, respectively determining the client position information and the client attribution information; the client location information is used for referring to the actual location of the user terminal, and the client attribute information is used for referring to the actual public opinion information of the client location indicated by the geographic position.
Optionally, the determining the client location information and the client attribute information based on the geographic location and the public opinion big data updated in real time includes:
based on the geographic position, respectively determining whether other call requests associated with the corresponding call requests exist or not and whether the geographic position is in a preset risk area or not, and obtaining the customer situation information;
based on the public opinion big data updated in real time, determining whether sudden events and preset risk events occur at the client location indicated by the geographic position, and determining whether a preset number of similar call requests from the client location are received to obtain the client location information.
In another aspect of the present disclosure, there is provided a multi-element-based customer service call system resource scheduling apparatus, the scheduling apparatus including:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for receiving a call request sent by at least one user terminal and acquiring customer comprehensive information respectively corresponding to the at least one user terminal, wherein the customer comprehensive information comprises equipment state information, customer situation information and customer affiliated information;
the calculation module is used for calculating the comprehensive score of the customer situation corresponding to the at least one user terminal according to the equipment state information, the customer situation information and the customer attribute information;
and the scheduling module is used for scheduling customer service calling system resources based on the customer situation comprehensive score and distributing the customer service calling system resources for the at least one user terminal.
In another aspect of the present disclosure, there is provided an electronic device including:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the multi-element based customer service call system resource scheduling method described above.
In another aspect of the disclosure, a computer readable storage medium is provided, storing a computer program, which when executed by a processor, implements the multi-element based customer service call system resource scheduling method described above.
Compared with the prior art, the embodiment of the disclosure calculates the comprehensive score of the customer situation according to the equipment state information, the customer situation information and the customer place information, so that the full evaluation of the customer situation can be realized, and customer service call system resources are allocated to the customer according to the customer situation on the basis, thereby improving the service efficiency, simultaneously taking social responsibility into account, conforming to the original purpose of serving the customer, improving the user experience, and preferentially allocating the customer service call system resources to the customer in urgent need of customer service under the condition that the customer is not felt.
Drawings
One or more embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings, in which like references indicate similar elements, and in which the figures do not depict a proportional limitation unless expressly stated otherwise.
Fig. 1 is a flowchart of a multi-element-based customer service call system resource scheduling method according to an embodiment of the present disclosure;
FIG. 2 is a schematic diagram of a customer premise assessment element provided by another embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of a multi-element-based resource scheduling device for a customer service call system according to another embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of an electronic device according to another embodiment of the present disclosure.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, the embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. However, those of ordinary skill in the art will understand that in various embodiments of the present disclosure, numerous technical details have been set forth in order to provide a better understanding of the present disclosure. However, the technical solutions claimed in the present disclosure can be implemented without these technical details and with various changes and modifications based on the following embodiments. The following divisions of the various embodiments are for convenience of description, and should not be construed as limiting the specific implementations of the disclosure, and the various embodiments may be mutually combined and referred to without contradiction.
One embodiment of the present disclosure relates to a multi-element-based customer service call system resource scheduling method, the flow of which is shown in fig. 1, including:
step S110, receiving a call request sent by at least one user terminal, and obtaining customer comprehensive information respectively corresponding to the at least one user terminal, wherein the customer comprehensive information comprises equipment state information, customer situation information and customer attribution information.
In particular, during the peak period of traffic, since a plurality of user terminals may send call requests to the customer service call system at the same time, the customer service call system may respond within an affordable range and receive call requests sent by at least one user terminal.
The present embodiment sets the resource scheduling target of the customer service call system as: customer service call system resources are preferentially allocated for providing service to customers in emergency situations. Therefore, the embodiment obtains the corresponding customer comprehensive information based on the user terminal, so as to evaluate the actual situation of the customer according to the obtained customer comprehensive information and the preset customer situation evaluation element.
Taking privacy protection and other factors into consideration, the acquisition of the customer comprehensive information needs to obtain the authorization of the user terminal, so that the operations of acquiring, using, storing and the like are performed on the data of the battery capacity, the network semaphore, the geographic position and the like of the user terminal on the premise of the consent of the user terminal, and the customer comprehensive information is determined by combining a big data technology on the basis of the operations, so that whether the customer is likely to be under an emergency or not is estimated according to the customer situation estimation factors.
In step S110, exemplary, the obtaining customer integrated information corresponding to at least one user terminal includes: and respectively sending authorization requests to at least one user terminal, wherein the authorization requests are used for requesting to acquire the use permission of the preset resources in the corresponding user terminals. And responding to the received grant authorization response sent by at least one user terminal, and acquiring corresponding customer comprehensive information based on corresponding preset resources.
Specifically, the preset resources may include data such as battery power, network signal quantity, geographical location, and the like of the user terminal. The authorization request is used for requesting to acquire the use permission of the preset resource of the corresponding user terminal.
The embodiment can respectively send the authorization request to the user terminal corresponding to each received call request, and when receiving the grant response sent by at least one user terminal, acquire the data of the battery power, the network signal quantity, the geographic position and the like of the user terminal based on the preset resources stored in the user terminal, so as to acquire the corresponding client comprehensive information on the basis, thereby the acquisition of the client comprehensive information is carried out on the premise of the user grant of the user terminal.
Exemplary, based on the corresponding preset resources, obtaining the corresponding customer comprehensive information includes: device status information is determined based on the battery level and the network semaphore. And respectively determining client situation information and client attribution information based on the geographic position and the public opinion big data updated in real time. The client situation information is used for indicating the actual situation of the user terminal, and the client attribute information is used for indicating the actual public opinion information of the client location indicated by the geographic position.
Specifically, the public opinion big data refers to massive network public opinion data information on the internet. According to the method, the real-time public opinion of the geographical location of the user terminal is obtained by combining a big data technology, and the client home information is determined according to the real-time public opinion, so that the public opinion of the client location is evaluated.
In conjunction with fig. 2, the customer premise assessment element may include the health status of the communication device, the customer's own premise, and the public opinion of the customer's premises. The health state of the communication device can be obtained according to the device state information such as the battery power and the network signal quantity in the comprehensive information of the client. The client's own context may be obtained from client context information determined based on the geographic location of the user terminal. The public opinion of the customer location may be obtained from the customer premises information determined based on the geographic location of the user terminal and the real-time public opinion of the location of the geographic location.
The embodiment can determine the equipment state information, the client situation information and the client attribution information in the client comprehensive information by utilizing the information such as the battery power, the network signal quantity, the geographic position, the public opinion big data updated in real time and the like so as to more fully evaluate the situation of the client on the basis.
Illustratively, determining the client context information and the client attribute information based on the geographic location and the public opinion big data updated in real time, respectively, includes: and respectively determining whether other call requests associated with the corresponding call requests exist or not and whether the geographic positions are in preset risk areas or not based on the geographic positions, so as to obtain the customer situation information. Based on the public opinion big data updated in real time, determining whether sudden events and preset risk events occur at the client location indicated by the geographic position, and determining whether a preset number of similar call requests from the client location are received or not to obtain client location information.
Specifically, the preset risk area may be an area where natural disasters such as earthquake, debris flow, typhoon, hail, flood, and snow occur, or may be an area where infectious diseases occur, or may be an area with specific other risks, which is not limited in this embodiment.
It should be noted that, in this embodiment, according to the risk degree, according to the principle from high to low, the risk area may be divided into a high risk area, a medium risk area, and a low risk area, and the risk event may be divided into a high risk event, a medium risk event, and a low risk event, and then the preset risk area may be set as the high risk area therein, and the preset risk event may be set as the high risk event therein.
For example, in conjunction with fig. 2, in the customer-situation assessment element, the assessment of the customer's own situation may include: and judging whether the client is in a high-risk area or not and whether the client has an associated service request or not through positioning. For this reason, the present embodiment determines whether the user terminal is in a preset risk area, such as a high risk area, based on the geographic location of the user terminal, and determines whether there are other call requests associated with the call request sent by the user terminal, based on the geographic location of the user terminal, so as to obtain the customer context information corresponding to the customer context. The other call request may be a history call request sent by the ue, or a call request sent by another ue in the same area as the ue.
For another example, in combination with fig. 2, in the client situation assessment element, the assessment of public opinion of the client location may include: and (5) evaluating whether a high risk event occurs at the place, whether an emergency occurs at the place, and whether a large number of similar customer services at the place request access. Therefore, the embodiment determines whether the customer location indicated by the geographic position of the user terminal has an emergency event or a preset risk event such as a high risk event according to the public opinion big data updated in real time and combining the big data technology, and determines whether other call requests with the same preset number as the call request type from the customer location are received within a time period of a preset duration before and after receiving the call request sent by the user terminal, so as to obtain the customer location information corresponding to the public opinion of the customer location. Here, the preset number may be set according to actual needs, for example, may be set to 50, 100, or the like.
The embodiment can further determine the client situation information and the client affiliated information based on the information such as the geographic position, the public opinion big data updated in real time and the like so as to further and fully evaluate the situation of the client on the basis.
Step S120, according to the equipment state information, the client context information and the client attribute information, the client context comprehensive score corresponding to at least one user terminal is calculated respectively.
Specifically, in this embodiment, according to the device state information, the client context information, and the client attribute information corresponding to each user terminal obtained in the foregoing steps, a client context composite score corresponding to each user terminal may be calculated, so as to evaluate an actual context of the client according to the client context composite score.
For example, step S120 may include: and evaluating the emergency score corresponding to the equipment state information, the client situation information and the client attribute information for each user terminal. Based on the emergency score corresponding to the equipment state information, the customer situation information and the customer place information, respectively, calculating the customer situation comprehensive score corresponding to each user terminal by adopting a weighted summation mode shown in the following formula (1):
score＝s_phone*w_phone+s_person*w_person+s_location*w_location(1)
wherein score represents a comprehensive score of customer situation, s_phone represents an emergency score corresponding to equipment state information, w_phone represents a weight corresponding to equipment state information, s_person represents an emergency score corresponding to customer situation information, w_person represents a weight corresponding to customer situation information, s_location represents an emergency score corresponding to customer area information, and w_location represents a weight corresponding to customer area information.
Specifically, the emergency score corresponding to each index, i.e. the state information of the evaluation device, the customer situation information and the customer attribute information, may be determined according to a preset evaluation standard, and the emergency represented by the relevant index is represented by the emergency score. For example, the urgency score may be 1-100 to characterize the urgency represented by the relevant index from low to high.
Here, the preset evaluation criteria should specify the correspondence between the various indexes, i.e., the evaluation device state information, the client context information, the different contents in the client attribute information, and the urgency score.
For example, for the device status information, if the battery power value is large, it indicates that it can support the device for a long time, the corresponding emergency score should be low, and if the battery power value is small, it indicates that it can support the device for a short time, the corresponding emergency score should be high, or if the network signal value is large, it indicates that the communication condition is good, the corresponding emergency score should be low, and if the network signal value is small, it indicates that the communication condition is poor, and the corresponding emergency score should be high.
For another example, for the customer location information, if it is determined that the geographic location of the user terminal is in a high risk area, it indicates that its corresponding urgency score should be high, and if it is determined that the geographic location of the user terminal is not in a high risk area, it indicates that its corresponding urgency score should be low, or if it is determined that there are other call requests associated with the call request issued by the user terminal, it indicates that its corresponding urgency score should be high, and if it is determined that there are no other call requests associated with the call request issued by the user terminal, it indicates that its corresponding urgency score should be low.
For another example, for the customer premises information, if it is determined that a high risk event occurs at the geographic location of the user terminal, or an emergency event occurs, or a large number of similar call requests from the location are received, the corresponding emergency score should be higher, and if it is determined that no high risk event occurs at the geographic location of the user terminal, or an emergency event does not occur, or a large number of similar call requests from the location are not received, the corresponding emergency score should be lower.
In the above formula (1), the weights, that is, the weights corresponding to the device state information, the weights corresponding to the customer location information, and the weights corresponding to the customer attribute information, may be empirical values calculated from the correlation by the history data.
According to the method, the comprehensive score of the customer situation is obtained through calculation by utilizing the emergency score and the corresponding weight, the evaluation of the customer situation is realized, the influence of the emergency score on the evaluation result can be considered, and therefore the final customer situation evaluation result is more scientific and reasonable.
And step S130, scheduling customer service call system resources based on the customer situation comprehensive score, and distributing the customer service call system resources for at least one user terminal.
Specifically, the step can allocate customer service call system resources to each user terminal according to the urgent degree of customer demand represented by the comprehensive score of customer situation.
For example, step S130 may include: and in response to the fact that the comprehensive score of the customer situation corresponding to only one user terminal exceeds a preset threshold, preferentially distributing customer service call system resources to the user terminal.
Specifically, the preset threshold may be set to a certain experience value, so as to indicate that when the customer situation comprehensive score exceeds the preset threshold, the user of the user terminal is under a special condition, that is, under a certain unfavorable environment, and the requirement for customer service resources is relatively urgent, so that the user terminal preferentially responds to the call request of the customer and allocates customer service call system resources to the customer service call system.
By preferentially distributing customer service calling system resources to the user terminals with high comprehensive scores in customer places, user experience can be further improved, and customers needing customer service are enabled to obtain customer service calling system resources preferentially under the condition that users feel no sense.
Illustratively, step S130 may further include: and responding to the client situation comprehensive scores corresponding to the plurality of user terminals exceeding a preset threshold, and sequencing the plurality of user terminals according to the size of the client situation comprehensive scores to generate a priority service queue. And distributing customer service calling system resources for the user terminals based on the sequence of the plurality of user terminals in the priority service queue.
Specifically, when the comprehensive scores of the customer locations corresponding to the plurality of user terminals sending the call requests exceed the preset threshold, in order to determine the response sequence of the call requests sent by the user terminals, the user terminals can be ordered according to the magnitude of the comprehensive scores of the customer locations to generate a priority service queue, and then customer service call system resources are allocated to the user terminals according to the sequence of the user terminals in the priority service queue, so that customer service is preferentially provided for customers with higher comprehensive scores of the customer locations.
Compared with the prior art, the embodiment of the disclosure calculates the comprehensive score of the customer situation according to the equipment state information, the customer situation information and the customer place information, so that the full evaluation of the customer situation can be realized, and customer service call system resources are allocated to the customer according to the customer situation on the basis, thereby improving the service efficiency, simultaneously taking social responsibility into account, conforming to the original purpose of serving the customer, improving the user experience, and preferentially allocating the customer service call system resources to the customer in urgent need of customer service under the condition that the customer is not felt.
Another embodiment of the present disclosure relates to a multi-element-based customer service call system resource scheduling apparatus, as shown in fig. 3, including:
an obtaining module 301, configured to receive a call request sent by at least one user terminal, and obtain customer integrated information corresponding to the at least one user terminal, where the customer integrated information includes device state information, customer situation information, and customer attribute information;
the calculating module 302 is configured to calculate, according to the device state information, the client context information, and the client attribute information, a client context composite score corresponding to at least one user terminal;
the scheduling module 303 is configured to schedule the customer service call system resources based on the customer situation comprehensive score, and allocate the customer service call system resources to at least one user terminal.
The specific implementation method of the device provided by the embodiment of the present disclosure may be described with reference to the method provided by the embodiment of the present disclosure, which is not described herein again.
Compared with the prior art, the embodiment of the disclosure calculates the comprehensive score of the customer situation according to the equipment state information, the customer situation information and the customer place information, so that the full evaluation of the customer situation can be realized, and customer service call system resources are allocated to the customer according to the customer situation on the basis, thereby improving the service efficiency, simultaneously taking social responsibility into account, conforming to the original purpose of serving the customer, improving the user experience, and preferentially allocating the customer service call system resources to the customer in urgent need of customer service under the condition that the customer is not felt.
Another embodiment of the present disclosure relates to an electronic device, as shown in fig. 4, comprising:
at least one processor 401; the method comprises the steps of,
a memory 402 communicatively coupled to the at least one processor 401; wherein,,
the memory 402 stores instructions executable by the at least one processor 401, the instructions being executable by the at least one processor 401 to enable the at least one processor 401 to perform the multi-element based customer service call system resource scheduling method described in the above embodiments.
Where the memory and the processor are connected by a bus, the bus may comprise any number of interconnected buses and bridges, the buses connecting the various circuits of the one or more processors and the memory together. The bus may also connect various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art, and therefore, will not be described any further herein. The bus interface provides an interface between the bus and the transceiver. The transceiver may be one element or may be a plurality of elements, such as a plurality of receivers and transmitters, providing a means for communicating with various other apparatus over a transmission medium. The data processed by the processor is transmitted over the wireless medium via the antenna, which further receives the data and transmits the data to the processor.
The processor is responsible for managing the bus and general processing and may also provide various functions including timing, peripheral interfaces, voltage regulation, power management, and other control functions. And memory may be used to store data used by the processor in performing operations.
Another embodiment of the present disclosure relates to a computer readable storage medium storing a computer program which, when executed by a processor, implements the multi-element-based customer service call system resource scheduling method described in the above embodiment.
That is, it will be understood by those skilled in the art that all or part of the steps of the method described in the above embodiments may be implemented by a program stored in a storage medium, including several instructions for causing a device (which may be a single-chip microcomputer, a chip or the like) or a processor (processor) to perform all or part of the steps of the method described in the various embodiments of the disclosure. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
It will be understood by those of ordinary skill in the art that the foregoing embodiments are specific embodiments for carrying out the present disclosure, and that various changes in form and details may be made therein without departing from the spirit and scope of the present disclosure.
Claims (10)
1. The customer service call system resource scheduling method based on multiple elements is characterized by comprising the following steps:
receiving a call request sent by at least one user terminal, and acquiring customer comprehensive information respectively corresponding to the at least one user terminal, wherein the customer comprehensive information comprises equipment state information, customer situation information and customer attribute information;
according to the equipment state information, the client situation information and the client attribute information, respectively calculating a client situation comprehensive score corresponding to the at least one user terminal;
and scheduling customer service call system resources based on the customer location comprehensive score, and distributing the customer service call system resources for the at least one user terminal.
2. The scheduling method according to claim 1, wherein the calculating the customer premise composite score corresponding to the at least one user terminal according to the device state information, the customer premise information, and the customer premises information includes:
for each user terminal, respectively evaluating the emergency score corresponding to the equipment state information, the client situation information and the client attribute information;
based on the emergency score corresponding to the equipment state information, the customer location information and the customer location information, respectively, calculating the customer location comprehensive score corresponding to each user terminal by adopting a weighted summation mode shown in the following formula (1):
score＝s_phone*w_phone+s_person*w_person+s_location*w_location(1)
the score represents the comprehensive score of the customer location, s_phone represents the emergency score corresponding to the equipment state information, w_phone represents the weight corresponding to the equipment state information, s_person represents the emergency score corresponding to the customer location information, w_person represents the weight corresponding to the customer location information, s_location represents the emergency score corresponding to the customer location information, and w_location represents the weight corresponding to the customer location information.
3. The scheduling method according to claim 2, wherein the scheduling the customer service call system resources based on the customer premise composite score, allocating the customer service call system resources to the at least one user terminal, comprises:
and preferentially distributing the customer service call system resources to the user terminal in response to that only one customer situation comprehensive score corresponding to the user terminal exceeds a preset threshold.
4. The scheduling method according to claim 2, wherein the scheduling the customer service call system resources based on the customer premise composite score, allocating the customer service call system resources to the at least one user terminal, comprises:
responding to the situation comprehensive scores of the clients corresponding to the user terminals exceeding a preset threshold, and sequencing the user terminals according to the situation comprehensive scores of the clients to generate a priority service queue;
and distributing the customer service call system resources to the user terminals based on the sequence of the user terminals in the priority service queue.
5. The scheduling method according to any one of claims 1 to 4, wherein the obtaining the client integrated information respectively corresponding to the at least one user terminal includes:
respectively sending an authorization request to the at least one user terminal, wherein the authorization request is used for requesting to acquire the use permission of the preset resource in the corresponding user terminal;
and responding to the receiving of the grant authorization response sent by at least one user terminal, and acquiring the corresponding comprehensive client information based on the corresponding preset resources.
6. The scheduling method of claim 5, wherein,
the preset resources comprise battery power, network semaphores and geographic positions of the user terminal;
the obtaining the corresponding comprehensive customer information based on the corresponding preset resources includes:
determining the device status information based on the battery level and the network semaphore;
based on the geographic position and the public opinion big data updated in real time, respectively determining the client position information and the client attribution information; the client location information is used for referring to the actual location of the user terminal, and the client attribute information is used for referring to the actual public opinion information of the client location indicated by the geographic position.
7. The scheduling method of claim 6, wherein the determining the client context information and the client place information based on the geographical location and the real-time updated public opinion big data, respectively, comprises:
based on the geographic position, respectively determining whether other call requests associated with the corresponding call requests exist or not and whether the geographic position is in a preset risk area or not, and obtaining the customer situation information;
based on the public opinion big data updated in real time, determining whether sudden events and preset risk events occur at the client location indicated by the geographic position, and determining whether a preset number of similar call requests from the client location are received to obtain the client location information.
8. A multi-element based customer service call system resource scheduling device, the scheduling device comprising:
the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for receiving a call request sent by at least one user terminal and acquiring customer comprehensive information respectively corresponding to the at least one user terminal, wherein the customer comprehensive information comprises equipment state information, customer situation information and customer affiliated information;
the calculation module is used for calculating the comprehensive score of the customer situation corresponding to the at least one user terminal according to the equipment state information, the customer situation information and the customer attribute information;
and the scheduling module is used for scheduling customer service calling system resources based on the customer situation comprehensive score and distributing the customer service calling system resources for the at least one user terminal.
9. An electronic device, comprising:
at least one processor; the method comprises the steps of,
a memory communicatively coupled to the at least one processor; wherein,,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the multi-element based customer service call system resource scheduling method of any one of claims 1 to 7.
10. A computer readable storage medium storing a computer program, wherein the computer program when executed by a processor implements the multi-element based customer service call system resource scheduling method of any one of claims 1 to 7.
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