CN116822886A - Customer service scheduling method, device, equipment and medium - Google Patents
Customer service scheduling method, device, equipment and medium Download PDFInfo
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Abstract
The application discloses a customer service scheduling method, a customer service scheduling device, customer service scheduling equipment and a customer service scheduling medium, which can be applied to the field of big data or the field of finance. Inputting the first reception times into a customer service prediction model to predict the second reception times; determining the number of required customer service personnel according to the second reception times and the average reception times; inputting the first service duration and the first saturation of each first customer service into a personnel service duration and personnel cost prediction model to predict the first personnel cost of each first customer service; selecting a preset number of second customer services from the first customer service set according to the fact that the first labor cost is from small to large, and generating a personnel scheduling plan; the preset number is the same as the number of the required customer service personnel, and the second customer service with lower first personnel cost is selected to process the second reception times, so that the customer requirements of customers on customer service use are met, the customer service cost can be reduced, and the cost reduction and synergy are further realized for the customer service.
Description
Technical Field
The application relates to the field of big data, in particular to a customer service scheduling method, a customer service scheduling device, customer service scheduling equipment and a customer service scheduling medium.
Background
With the penetration of digital transformation of financial services, more refined personnel cost efficiency management is becoming an important means for the financial institutions to promote their own competitiveness. At present, the scale of financial customer service personnel is large, and the existing financial customer service personnel scheduling mechanism cannot meet customer requirements of customers on customer service use and can reduce customer service cost.
Disclosure of Invention
Therefore, the application aims to provide a customer service scheduling method, device, equipment and medium, so that customer requirements of customers on customer service are met, customer service cost is reduced, and cost reduction and synergy are further realized for the customer service. The specific scheme is as follows:
in one aspect, the application provides a customer service scheduling method, which comprises the following steps:
acquiring a first reception time; the first reception times are total reception times of the first customer service set in a first time period; the first set of customer services includes a plurality of first customer services;
inputting the first reception times into a customer service prediction model to predict second reception times; the second reception times are total reception times of the first customer service set in a second time period; the second time period is located after the first time period;
determining the number of required customer service personnel according to the second reception times and the average reception times;
inputting the first service duration and the first saturation of each first customer service into a personnel service duration and personnel cost prediction model to predict the first personnel cost of each first customer service; the first saturation is the ratio of the first service duration to the upper limit of the service duration;
selecting a preset number of second customer services from the first customer service set according to the fact that the first labor cost is from small to large, and generating a personnel scheduling plan; the preset number is the same as the number of the required customer service personnel.
On the other hand, the embodiment of the application also provides a customer service scheduling device, which comprises:
the first acquisition unit is used for acquiring the first reception times; the first reception times are total reception times of the first customer service set in a first time period; the first set of customer services includes a plurality of first customer services;
the first prediction unit is used for inputting the first reception times into a customer service prediction model and predicting second reception times; the second reception times are total reception times of the first customer service set in a second time period; the second time period is located after the first time period;
the first determining unit is used for determining the number of required customer service personnel according to the second reception times and the average reception times;
the second prediction unit is used for inputting the first service duration and the first saturation of each first customer service into a personnel service duration and personnel cost prediction model to predict the first personnel cost of each first customer service; the first saturation is the ratio of the first service duration to the upper limit of the service duration;
the second determining unit is used for selecting a preset number of second customer services from the first customer service set according to the fact that the first labor cost is from small to large, and generating a personnel scheduling plan; the preset number is the same as the number of the required customer service personnel.
In another aspect, an embodiment of the present application further provides a computer device, including a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is used for executing the customer service scheduling method according to the instructions in the program codes.
In another aspect, an embodiment of the present application further provides a computer readable storage medium, where the computer readable storage medium is used to store a computer program, and the computer program is used to execute the customer service scheduling method.
The embodiment of the application provides a customer service scheduling method, a customer service scheduling device, customer service scheduling equipment and a customer service scheduling medium, wherein first reception times are obtained; the first reception times are the total reception times of the first customer service set in the first time period; the first set of customer services includes a plurality of first customer services; inputting the first reception times into a customer service prediction model to predict the second reception times; the second reception times are the total reception times of the first customer service set in a second time period; the second time period is located after the first time period; determining the number of required customer service personnel according to the second reception times and the average reception times; inputting the first service duration and the first saturation of each first customer service into a personnel service duration and personnel cost prediction model to predict the first personnel cost of each first customer service; the first saturation is the ratio of the first service duration to the upper limit of the service duration; selecting a preset number of second customer services from the first customer service set according to the fact that the first labor cost is from small to large, and generating a personnel scheduling plan; the preset number is the same as the number of required customer service personnel.
In the embodiment of the application, the second reception times in a second time period, which is a future period, can be predicted according to the historical first reception times by using the customer service prediction model, so that the number of customer service personnel required for processing the second reception times can be conveniently determined later, the first personnel cost of each first customer service is predicted according to the personnel service time length and the labor cost prediction model, the second customer service with lower first personnel cost is selected to process the second reception times, and the generated labor scheduling plan can not only arrange a proper number of second customer service to process the second reception times, but also reduce the labor cost, thereby not only meeting customer requirements of customers on customer service, but also reducing the customer service cost and further improving the efficiency of customer service cost.
Drawings
In order to more clearly illustrate the embodiments of the application or the technical solutions in the prior art, the drawings that are needed in the embodiments or the description of the prior art will be briefly described below, it being obvious that the drawings in the following description are some embodiments of the application and that other drawings may be obtained from these drawings without inventive effort for a person skilled in the art.
Fig. 1 shows a schematic flow chart of a customer service scheduling method according to an embodiment of the present application;
fig. 2 is a schematic flow chart of another customer service scheduling method according to an embodiment of the present application;
FIG. 3 is a schematic diagram of a customer service scheduling system according to an embodiment of the present application;
fig. 4 is a block diagram of a customer service scheduling device according to an embodiment of the present application;
fig. 5 is a block diagram of a computer device according to an embodiment of the present application.
Detailed Description
In order that the above objects, features and advantages of the application will be readily understood, a more particular description of the application will be rendered by reference to the appended drawings.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present application, but the present application may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present application is not limited to the specific embodiments disclosed below.
In order to facilitate understanding, the following describes in detail a customer service scheduling method, device, equipment and medium provided by the embodiment of the application with reference to the accompanying drawings.
Referring to fig. 1, a schematic flow chart of a customer service scheduling method according to an embodiment of the present application is shown, and the method may include the following steps.
S101, acquiring a first reception time.
In the embodiment of the present application, the first reception time may be obtained, where the first period is a period of time in the past, and the first customer service set includes a plurality of first customer services, for example, may include all customer services, and the first reception time may be a total reception time of the first customer service set in the first period, that is, the first reception time is a sum of reception times of the plurality of first customer services in the first period. The number of times of receiving a call from a customer service or receiving a session sent from the customer can be understood as one time of receiving the call from the customer.
S102, inputting the first reception times into a customer service prediction model, and predicting the second reception times.
In the embodiment of the application, the customer service prediction model can predict the reception times in a period of time in the future according to the historical reception times, and the first reception times can be input into the customer service prediction model so as to output the second reception times.
Specifically, the second reception time is the total reception time of the first service set in a second time period, and the second time period is located after the first time period, that is, the first time period is a period of time before the current time point, and the second time period is a period of time after the current time point. Therefore, the total reception times of a plurality of first customer service in a future period can be predicted, the number of the reception times in the future period is grasped on the whole, and a proper number of customer service personnel can be conveniently arranged to carry out duty.
S103, determining the number of required customer service personnel according to the second reception times and the average reception times.
In the embodiment of the application, the average number of reception times can be the number of reception times of each customer service person in a period of time, for example, the average number of reception times can be 15 times per hour or 120 times per day, and the number of customer service persons required for processing the second reception times can be determined according to the second reception times and the average number of reception times.
S104, inputting the first service duration and the first saturation of each first customer service into a personnel service duration and labor cost prediction model, and predicting the first labor cost of each first customer service.
In the embodiment of the present application, each first customer service corresponds to a first service duration, where the first service duration may be 8 hours per day or may be 40 hours per week, and the first saturation is a ratio of the first service duration to an upper limit of the service duration, for example, the first saturation is 0.5 when the first customer service a works for 4 hours a day, and the first saturation is 1.5 when the first customer service B works for 12 hours a day. For customer service with saturation exceeding 1, the labor cost may increase, such as paying additional overtime.
Specifically, the first service duration of each first customer service and the first saturation of each first customer service may be input into a personnel service duration and personnel cost prediction model, so as to predict the first personnel cost of each first customer service, so as to control the personnel cost.
In addition, according to the first saturation, relevant guidance opinions can be given to the first customer's request for holidays, human performance assessment guidance opinions are given, and the like, so that human cost is reduced.
In one possible implementation, not only labor costs, but also customer satisfaction may be considered when scheduling customer service shifts, thereby enhancing the customer's handling experience. The personnel service duration and service satisfaction prediction model can predict service satisfaction according to the service duration. Specifically, generally, the longer the personnel service duration, the less satisfied the service will gradually decrease, affecting the customer handling experience.
Specifically, each first customer service corresponds to a first service duration, and the first service duration may be input into a personnel service duration and service satisfaction prediction model to predict the first service satisfaction of each first customer service, so as to obtain the service satisfaction of each first customer service.
Specifically, for the customer service with lower service satisfaction, the operator may not be on duty, that is, a third customer service with the first service satisfaction greater than the preset threshold is selected from the first customer service set, and a second customer service set is formed, so that operators on duty are selected from the second customer service set later, and the customer satisfaction is improved as much as possible.
Specifically, when considering the service satisfaction degree, the second customer service set includes customer service with the service satisfaction degree larger than a preset threshold value in the first customer service set, and third customer service with the preset number is selected from the second customer service set according to the fact that the first personnel cost is from small to large, so that a personnel scheduling plan is generated. Therefore, for the customer service personnel with the remaining service satisfaction up to standard, customer service personnel with lower labor cost are selected, and the personnel scheduling plan can reduce labor cost and ensure the service satisfaction of customers.
In the embodiment of the application, the selection can be further carried out according to the vacation requesting information of the customer service, and the on-duty is not arranged for the vacation requesting personnel, so that the scheduling plan is more accurate.
Specifically, the third customer service with the first service satisfaction degree greater than the preset threshold value is selected from the first customer service set to form a second customer service set, and the third customer service set which normally works in the second time period can be determined according to the first customer service set and the vacation requesting personnel information. The vacation requesting person information may include a vacation requesting person name and a vacation requesting time period, and if the vacation requesting time period is within the second time period, the person is not on duty, and the vacation requesting person name is deleted from the first customer service set, so as to obtain a third customer service set that can work.
Specifically, third customer service with the first service satisfaction degree larger than a preset threshold value can be selected from the third customer service set to form a second customer service set. In this way, customer service with higher service satisfaction is selected from the list of staff capable of working, so that a second customer service set is formed, not only the labor cost is reduced, but also the service satisfaction of customers is improved.
And S105, selecting a preset number of second customer services from the first customer service set according to the fact that the first labor cost is from small to large, and generating a personnel scheduling plan.
In the embodiment of the application, the second customer service with the preset number can be selected from the first customer service set from small to large according to the first personnel cost, the preset number is the same as the number of required customer service personnel, and the personnel scheduling plan is generated, that is, when the number of required customer service personnel is N, the first N customer service with low personnel cost can be selected from the first customer service set and recorded as the second customer service, so that the personnel scheduling plan is generated.
In the embodiment of the application, the second reception times in a second time period, which is a future period, can be predicted according to the historical first reception times by using the customer service prediction model, so that the number of customer service personnel required for processing the second reception times can be conveniently determined later, the first personnel cost of each first customer service is predicted according to the personnel service time length and the labor cost prediction model, the second customer service with lower first personnel cost is selected to process the second reception times, and the generated labor scheduling plan can not only arrange a proper number of second customer service to process the second reception times, but also reduce the labor cost, thereby not only meeting customer requirements of customers on customer service, but also reducing the customer service cost and further improving the efficiency of customer service cost.
In the embodiment of the application, the customer service prediction model, the personnel service duration and service satisfaction prediction model and the personnel service duration and labor cost prediction model can be obtained by training the preset model.
Specifically, historical data can be obtained as a first training set, a second training set and a third training set, wherein the first training set comprises third reception times, customer service time distribution information and each reception time length; the third reception times can be the number of financial customer service used by the customer, namely, how many times the customer uses the financial customer service, the time distribution information of the customer service comprises specific distribution conditions of the third reception times in different time periods, and each reception time can be the processing time of each customer service on the customer problem, for example, the call time of each call when the customer consults through a telephone. And training the first preset model by using the first training set to obtain a customer service prediction model.
In addition, the time distribution information of the first reception times can be input into the customer service prediction model, so that the time distribution information of the second reception times is predicted, the personnel on duty quantity in different time periods is thinned in the personnel scheduling plan, and the labor cost is reduced in a targeted manner.
The second training set comprises a second service duration and a second service satisfaction degree corresponding to the second service duration, and the third training set comprises a second service duration, a second saturation degree and a second manpower cost, wherein the second saturation degree is the ratio of the second service duration to the upper limit of the service duration.
Specifically, training a second preset model by using a second training set to obtain a personnel service duration and service satisfaction prediction model; and training a third preset model by using a third training set to obtain a personnel service duration and labor cost prediction model.
In the embodiment of the present application, referring to fig. 2, a schematic flow chart of another customer service scheduling method provided in the embodiment of the present application is shown.
Step 1: the scheduling staff starts a service agent through the interaction module, inputs or maintains the feature and the learning algorithm model to the machine learning module through the interaction module, and executes the step 2;
step 2: the service agent acquires historical information such as the quantity of financial customer service used by a customer, the working service time length of personnel, the labor cost and the like and forwards the historical information to the calculation storage module; the computing and storing module is used for carrying out standard and standard integration and summarization processing on the received historical information such as the quantity of financial customer service used by a customer, the personnel working service time length, the labor cost and the like, so as to form integrated summarization information for the machine learning module to use;
step 3: the machine learning module is used for reading the integrated and summarized information extraction characteristic data in the calculation storage module and training a learning algorithm model to form analysis and identification capabilities which accord with the customer's use financial customer service prediction capability, personnel service duration and labor cost and personnel service duration and service satisfaction;
step 4: the scheduling staff inputs or maintains the information of the customer service staff, the holiday requesting information and the emergency event to the customer service intelligent scheduling module through the interaction module; the customer service intelligent scheduling module synchronizes customer service personnel information and holiday requesting information to the machine learning module;
step 5: the machine learning module is used for comprehensively analyzing and identifying the quantity of financial customer service, personnel service time, working saturation and personnel vacation requesting conditions of the current customer by using the trained learning algorithm model, predicting the quantity of financial customer service requirements (second reception times) used by the customer, and calculating the number of customer service personnel requirements matched with the quantity of requirements by combining the service time occupied ratio (first saturation) of the working period of the former customer service personnel; screening available customer service personnel by combining personnel information about holiday requesting personnel; calculating service cost of the screened available personnel, selecting a personnel scheduling plan with optimal cost and customer satisfaction, generating a customer service personnel scheduling plan and customer service cost analysis result, and transmitting the customer service personnel scheduling plan and customer service cost analysis result to a customer service intelligent scheduling module;
step 6: the customer service intelligent scheduling module receives and analyzes the customer service personnel scheduling plan and the customer service cost analysis result of the machine learning module, generates a final personnel scheduling plan in combination with emergency situations, generates scheduling notification information and transmits the scheduling notification information to the message service; generating a cost analysis report for subsequent review;
step 7: the message service receives a scheduling message notice of the intelligent scheduling module of the customer service and forwards the scheduling message notice to the customer service personnel;
step 8: and the scheduling staff checks the scheduling result and the cost analysis report through the interaction module.
In the embodiment of the application, the method can be executed by using a customer service scheduling system, and the customer service scheduling system structure diagram provided by the embodiment of the application is shown by referring to fig. 3, and comprises an interaction module, a message service module, a customer service intelligent scheduling module, a machine learning module, a calculation storage module, a service agent module financial customer service system and a basic resource module.
Specifically, the interaction module provides an interaction access function, including enabling/stopping a service agent, inputting/maintaining a machine learning library, managing and maintaining customer service personnel information, requesting vacation information, emergencies, consulting analysis reports and the like, wherein the emergencies can be temporary leave for the customer service personnel and can not be on duty. And the message service module is used for providing message notification capability and forwarding the scheduling condition message notification to customer service personnel.
Specifically, the customer service intelligent scheduling module provides functions of customer service personnel information management, emergency management, cost analysis and review and the like, and comprises the steps of receiving and recording customer service personnel information, emergency information of an interaction module, synchronizing the customer service personnel information and the emergency information to a machine learning module, receiving a personnel scheduling plan and a cost analysis result of the machine learning module, forming a final personnel scheduling plan in combination with an emergency, sending a message notification to the customer service personnel through a message service, generating a cost analysis report, receiving an operation analysis query request of the interaction module and the like.
Specifically, the machine learning module is used for performing model training on a machine learning algorithm by using historical information of the quantity of financial customer service, the personnel working service time length and the labor cost of a customer collected by a service agent, forming analysis and identification capacity which accords with the prediction capacity of the financial customer service, the personnel service time length and the labor cost of the customer, and providing analysis results of a customer service personnel scheduling plan and the customer service cost by combining the quantity of financial customer service, the personnel service time length, the working saturation and the personnel leave condition; the method comprises the steps of receiving a feature and learning algorithm model input and maintained by an interaction module, reading integrated summary information of a calculation storage module, performing feature extraction and learning algorithm model training, predicting customer use financial customer service demand, and calculating the number of customer service personnel required persons matched with the demand by combining the service duration occupation ratio of a working period of the former customer service personnel; screening available customer service personnel by combining personnel information about holiday requesting personnel; and calculating service cost of the screened available personnel, selecting a personnel scheduling plan with optimal cost and customer satisfaction, generating a customer service personnel scheduling plan and customer service cost analysis result, and transmitting the customer service personnel scheduling plan and customer service cost analysis result to a customer service intelligent scheduling module.
Specifically, the calculation storage module provides a data information integration and summarization function, receives historical information of the quantity of financial customer service, personnel working service time and labor cost collected and acquired by the service agent, and sends the integrated and summarized information to the machine learning module.
Specifically, the service agent provides an information acquisition function of the service duration and the labor cost of the customer using the financial customer service and the personnel work, and comprises the steps of acquiring historical information of the service duration and the labor cost of the customer using the financial customer service and the personnel work and forwarding the historical information to a calculation storage; collecting the quantity of financial customer service used by the current customer and sending the working service time of personnel to a machine learning module; and the financial customer service system provides a financial customer service function. And the basic resource module is used for providing basic resources required by the system operation and comprises calculation, storage, network and the like.
The embodiment of the application provides a customer service scheduling method, which comprises the steps of obtaining first reception times; the first reception times are the total reception times of the first customer service set in the first time period; the first set of customer services includes a plurality of first customer services; inputting the first reception times into a customer service prediction model to predict the second reception times; the second reception times are the total reception times of the first customer service set in a second time period; the second time period is located after the first time period; determining the number of required customer service personnel according to the second reception times and the average reception times; inputting the first service duration and the first saturation of each first customer service into a personnel service duration and personnel cost prediction model to predict the first personnel cost of each first customer service; the first saturation is the ratio of the first service duration to the upper limit of the service duration; selecting a preset number of second customer services from the first customer service set according to the fact that the first labor cost is from small to large, and generating a personnel scheduling plan; the preset number is the same as the number of required customer service personnel.
In the embodiment of the application, the second reception times in a second time period, which is a future period, can be predicted according to the historical first reception times by using the customer service prediction model, so that the number of customer service personnel required for processing the second reception times can be conveniently determined later, the first personnel cost of each first customer service is predicted according to the personnel service time length and the labor cost prediction model, the second customer service with lower first personnel cost is selected to process the second reception times, and the generated labor scheduling plan can not only arrange a proper number of second customer service to process the second reception times, but also reduce the labor cost, thereby not only meeting customer requirements of customers on customer service, but also reducing the customer service cost and further improving the efficiency of customer service cost.
Based on the customer service scheduling method, the embodiment of the application also provides a customer service scheduling device, and referring to fig. 4, a structural block diagram of the customer service scheduling device provided by the embodiment of the application is shown, where the device may include:
a first acquiring unit 201, configured to acquire a first reception number; the first reception times are total reception times of the first customer service set in a first time period; the first set of customer services includes a plurality of first customer services;
a first prediction unit 202, configured to input the first reception number into a customer service prediction model, and predict a second reception number; the second reception times are total reception times of the first customer service set in a second time period; the second time period is located after the first time period;
a first determining unit 203, configured to determine the number of required customer service personnel according to the second reception times and the number of people average reception times;
a second prediction unit 204, configured to input a first service duration and a first saturation of each first customer service into a personnel service duration and personnel cost prediction model, and predict a first personnel cost of each first customer service; the first saturation is the ratio of the first service duration to the upper limit of the service duration;
a second determining unit 205, configured to select a preset number of second customer services from the first customer service set according to the first labor cost from small to large, and generate a personnel scheduling plan; the preset number is the same as the number of the required customer service personnel.
Specifically, the second determining unit is configured to:
inputting the first service duration of each first customer service into a personnel service duration and service satisfaction prediction model, and predicting the first service satisfaction of each first customer service;
selecting a third customer service with the first service satisfaction degree larger than a preset threshold value from the first customer service set to form a second customer service set;
and selecting a preset number of second customer services from the second customer service set according to the fact that the first personnel cost is from small to large, and generating the personnel scheduling plan.
Specifically, the third determining unit is configured to:
determining a third customer service set which normally works in the second time period according to the first customer service set and the vacation requesting personnel information;
and selecting the third customer service with the first service satisfaction degree larger than the preset threshold value from the third customer service set to form the second customer service set.
Specifically, the device further comprises:
the second acquisition unit is used for acquiring the first training set, the second training set and the third training set; the first training set comprises second reception times, customer service time distribution information and each reception duration; the second training set comprises a second service duration and a second service satisfaction corresponding to the second service duration; the third training set includes the second service duration, a second saturation, and a second labor cost; the second saturation is the ratio of the second service duration to the upper limit of the service duration;
the training unit is used for training a first preset model by using the first training set to obtain the customer service prediction model; training a second preset model by using the second training set to obtain the personnel service duration and service satisfaction prediction model; and training a third preset model by using the third training set to obtain the personnel service duration and labor cost prediction model.
The embodiment of the application provides a customer service scheduling device, which can predict second reception times in a second time period in future according to historical first reception times by using a customer service prediction model, is convenient for determining the number of customer service personnel required for processing the second reception times, predicts the first personnel cost of each first customer service according to a personnel service time length and a labor cost prediction model, selects the second customer service with lower first personnel cost to process the second reception times, and generates a labor scheduling plan which not only can schedule a proper number of second customer service to process the second reception times, but also can reduce labor cost, thereby meeting customer requirements of customers on customer service, reducing customer service cost and further reducing customer service cost.
In yet another aspect, an embodiment of the present application provides a computer device, referring to fig. 5, which shows a structural diagram of the computer device provided by the embodiment of the present application, where the device includes a processor 310 and a memory 320:
the memory 310 is used for storing program codes and transmitting the program codes to the processor;
the processor 320 is configured to execute the customer service scheduling method provided in the foregoing embodiment according to an instruction in the program code.
The computer device may include a terminal device or a server, and the foregoing customer service scheduling apparatus may be configured in the computer device.
In still another aspect, an embodiment of the present application further provides a storage medium, where the storage medium is used to store a computer program, where the computer program is used to execute the customer service scheduling method provided in the foregoing embodiment.
Additionally, embodiments of the present application provide a computer program product or computer program comprising computer instructions stored in a computer readable storage medium. The processor of the computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions to cause the computer device to perform the customer service scheduling method provided in various alternative implementations of the above aspects.
It should be noted that the customer service scheduling method, device, equipment and medium provided by the application can be used in the big data field or the financial field. The foregoing is merely an example, and the application fields of the customer service scheduling method, the apparatus, the device and the medium provided by the present application are not limited.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by program instruction hardware, and the above program may be stored in a computer readable storage medium, where the program when executed performs steps including the above method embodiments; and the aforementioned storage medium may be at least one of the following media: read-only Memory (ROM), RAM, magnetic disk or optical disk, etc.
The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the application described herein may be implemented, for example, in sequences other than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," and "includes" and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for the device embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments for relevant points.
The foregoing is merely a preferred embodiment of the present application, and the present application has been disclosed in the above description of the preferred embodiment, but is not limited thereto. Any person skilled in the art can make many possible variations and modifications to the technical solution of the present application or modifications to equivalent embodiments using the methods and technical contents disclosed above, without departing from the scope of the technical solution of the present application. Therefore, any simple modification, equivalent variation and modification of the above embodiments according to the technical substance of the present application still fall within the scope of the technical solution of the present application.
Claims (10)
1. A customer service scheduling method, comprising:
acquiring a first reception time; the first reception times are total reception times of the first customer service set in a first time period; the first set of customer services includes a plurality of first customer services;
inputting the first reception times into a customer service prediction model to predict second reception times; the second reception times are total reception times of the first customer service set in a second time period; the second time period is located after the first time period;
determining the number of required customer service personnel according to the second reception times and the average reception times;
inputting the first service duration and the first saturation of each first customer service into a personnel service duration and personnel cost prediction model to predict the first personnel cost of each first customer service; the first saturation is the ratio of the first service duration to the upper limit of the service duration;
selecting a preset number of second customer services from the first customer service set according to the fact that the first labor cost is from small to large, and generating a personnel scheduling plan; the preset number is the same as the number of the required customer service personnel.
2. The method of claim 1, wherein the selecting a predetermined number of second customer services from the first set of customer services based on the first labor cost being from small to large, generating a personnel scheduling plan, comprises:
inputting the first service duration of each first customer service into a personnel service duration and service satisfaction prediction model, and predicting the first service satisfaction of each first customer service;
selecting a third customer service with the first service satisfaction degree larger than a preset threshold value from the first customer service set to form a second customer service set; and selecting a preset number of third customer services from the second customer service set according to the fact that the first personnel cost is from small to large, and generating the personnel scheduling plan.
3. The method of claim 2, wherein the selecting a third customer service from the first customer service set that has the first service satisfaction greater than a preset threshold, to form a second customer service set, comprises:
determining a third customer service set which normally works in the second time period according to the first customer service set and the vacation requesting personnel information;
and selecting the third customer service with the first service satisfaction degree larger than the preset threshold value from the third customer service set to form the second customer service set.
4. A method according to claim 2 or 3, characterized in that the method further comprises:
acquiring a first training set, a second training set and a third training set; the first training set comprises third reception times, customer service time distribution information and reception duration of each time; the second training set comprises a second service duration and a second service satisfaction corresponding to the second service duration; the third training set includes the second service duration, a second saturation, and a second labor cost; the second saturation is the ratio of the second service duration to the upper limit of the service duration;
training a first preset model by using the first training set to obtain the customer service prediction model; training a second preset model by using the second training set to obtain the personnel service duration and service satisfaction prediction model; and training a third preset model by using the third training set to obtain the personnel service duration and labor cost prediction model.
5. A customer service shift arrangement device, comprising:
the first acquisition unit is used for acquiring the first reception times; the first reception times are total reception times of the first customer service set in a first time period; the first set of customer services includes a plurality of first customer services;
the first prediction unit is used for inputting the first reception times into a customer service prediction model and predicting second reception times; the second reception times are total reception times of the first customer service set in a second time period; the second time period is located after the first time period;
the first determining unit is used for determining the number of required customer service personnel according to the second reception times and the average reception times;
the second prediction unit is used for inputting the first service duration and the first saturation of each first customer service into a personnel service duration and personnel cost prediction model to predict the first personnel cost of each first customer service; the first saturation is the ratio of the first service duration to the upper limit of the service duration;
the second determining unit is used for selecting a preset number of second customer services from the first customer service set according to the fact that the first labor cost is from small to large, and generating a personnel scheduling plan; the preset number is the same as the number of the required customer service personnel.
6. The apparatus according to claim 5, wherein the second determining unit is configured to:
inputting the first service duration of each first customer service into a personnel service duration and service satisfaction prediction model, and predicting the first service satisfaction of each first customer service;
selecting a third customer service with the first service satisfaction degree larger than a preset threshold value from the first customer service set to form a second customer service set;
and selecting a preset number of third customer services from the second customer service set according to the fact that the first personnel cost is from small to large, and generating the personnel scheduling plan.
7. The apparatus according to claim 6, wherein the third determining unit is configured to:
determining a third customer service set which normally works in the second time period according to the first customer service set and the vacation requesting personnel information;
and selecting the third customer service with the first service satisfaction degree larger than the preset threshold value from the third customer service set to form the second customer service set.
8. The apparatus according to claim 6 or 7, characterized in that the apparatus further comprises:
the second acquisition unit is used for acquiring the first training set, the second training set and the third training set; the first training set comprises third reception times, customer service time distribution information and reception duration of each time; the second training set comprises a second service duration and a second service satisfaction corresponding to the second service duration; the third training set includes the second service duration, a second saturation, and a second labor cost; the second saturation is the ratio of the second service duration to the upper limit of the service duration;
the training unit is used for training a first preset model by using the first training set to obtain the customer service prediction model; training a second preset model by using the second training set to obtain the personnel service duration and service satisfaction prediction model; and training a third preset model by using the third training set to obtain the personnel service duration and labor cost prediction model.
9. A computer device, the computer device comprising a processor and a memory:
the memory is used for storing program codes and transmitting the program codes to the processor;
the processor is configured to perform the method of any of claims 1-4 according to instructions in the program code.
10. A computer readable storage medium, characterized in that the computer readable storage medium is for storing a computer program for executing the method of any one of claims 1-4.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117391400A (en) * | 2023-12-07 | 2024-01-12 | 天津大学 | Intelligent attendant scheduling method based on time sequence prediction data of served crowd |
| CN117689073A (en) * | 2023-12-07 | 2024-03-12 | 天津大学 | Method for monitoring and early warning of dynamic number of served personnel and resource allocation |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117391400A (en) * | 2023-12-07 | 2024-01-12 | 天津大学 | Intelligent attendant scheduling method based on time sequence prediction data of served crowd |
| CN117689073A (en) * | 2023-12-07 | 2024-03-12 | 天津大学 | Method for monitoring and early warning of dynamic number of served personnel and resource allocation |
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