CN116720692A - Customer service dispatching method and device, computer equipment and storage medium - Google Patents
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Abstract
The embodiment of the application belongs to the field of artificial intelligence and financial science and technology, and relates to a customer service dispatching method, which comprises the following steps: if a service request of a user is received, determining target personality data of the user based on the consultation voice information and the personality analysis model; acquiring a first customer service matched with the target character data from a customer service database based on the target character data; determining product information corresponding to the consultation voice information; screening second customer service matched with the product information from all the first customer service based on the product information; acquiring service processing scores of the second customer service; and determining target customer service from all the second customer service based on the service processing scores, and establishing a communication link between the user and the target customer service. The application also provides a customer service dispatching device, computer equipment and a storage medium. In addition, the present application relates to blockchain techniques in which service processing scores may be stored. The application can be applied to customer service dispatching scenes in the financial field, and improves the accuracy and the processing efficiency of customer service distribution.
Description
Technical Field
The application relates to the technical field of artificial intelligence and the technical field of finance, in particular to a customer service dispatching method, a customer service dispatching device, computer equipment and a storage medium.
Background
With the rapid development of the internet, people's service awareness is improved, and network customer service is popularized in various industries, particularly in insurance industry, and goes deep into various links of daily business service. Under the current market, service requests sent by users are generally randomly distributed to online customer service by a customer service platform in an insurance system, so that the waiting time of the users is uneven and the waiting time is too long, and different users cannot be distributed to customer service with matched service attributes, so that the user experience is poor, the working efficiency of the customer service is also influenced, and the communication efficiency between the users and the customer service is low, so that the waste of communication resources is caused. Therefore, the existing customer service dispatching method has the problems of low distribution accuracy and low distribution efficiency.
Disclosure of Invention
The embodiment of the application aims to provide a customer service dispatching method, a customer service dispatching device, computer equipment and a storage medium, so as to solve the technical problems of low distribution accuracy and low distribution efficiency of the existing customer service dispatching method.
In order to solve the technical problems, the embodiment of the application provides a customer service dispatching method, which adopts the following technical scheme:
judging whether a service request of a user is received or not; wherein, the service request carries consultation voice information;
if yes, determining target personality data of the user based on the consultation voice information and a preset personality analysis model;
acquiring a plurality of first customer services matched with the target character data from a preset customer service database based on the target character data;
determining product information corresponding to the consultation voice information;
screening second customer service matched with the product information from all the first customer service based on the product information;
acquiring service processing scores of the second customer service;
and determining target customer service from all the second customer service based on the service processing score, and establishing a communication link between the user and the target customer service.
Further, the step of determining the target personality data of the user based on the consultation voice information and a preset personality analysis model specifically includes:
invoking the character analysis model trained in advance;
Inputting the consultation voice information into the character analysis model, and analyzing and processing the consultation voice information through the character analysis model to obtain a corresponding character analysis result;
and taking the character analysis result as target character data of the user.
Further, the step of determining the target customer service from all the second customer services based on the service processing score specifically includes:
screening a preset number of third customer services with highest service processing scores from all the second customer services;
acquiring historical service record data corresponding to the third customer service;
inquiring the history service record data, and judging whether fourth customer service which provides service for the user exists in all the third customer service;
and if a fourth customer service providing service for the user exists, taking the fourth customer service as the target customer service.
Further, after the step of determining whether there is a fourth customer service that provides a service to the user in all the third customer services, the method further includes:
if the fourth customer service providing the service for the user does not exist, counting the current service number of each third customer service;
Determining a fifth customer service with the least number of current service people from all the third customer services;
and taking the fifth customer service as the target customer service.
Further, the step of obtaining the service processing score of each second customer service specifically includes:
acquiring the working years, average service satisfaction and average service processing duration of the appointed customer service; wherein the specified customer service is any one customer service among all the second customer services;
acquiring a first weight corresponding to the working years, a second weight corresponding to the average service satisfaction degree and a third weight corresponding to the average service processing duration;
and calling a preset calculation formula to calculate the working life, the average service satisfaction and the average service processing duration based on the first weight, the second weight and the preset weight, and generating the service processing score of the appointed customer service.
Further, before the step of determining the target personality data of the user based on the advisory voice information and the preset personality analysis model, the method further includes:
acquiring pre-acquired training data; wherein the training data comprises character data and character expression voice data corresponding to the character data;
Calling a preset initial model;
and taking the character expression voice data as input of the initial model, taking the character data as output of the initial model, and training the initial model so that the initial model recognizes the mapping relation between the character data and the character expression voice data to obtain the character analysis model.
Further, before the step of acquiring, from a preset customer service database, a plurality of first customer services matched with the target character data based on the target character data, the method further includes:
acquiring character evaluation data of all customer services;
acquiring preset character class information;
classifying each customer service based on the character class information and the character evaluation data to obtain a corresponding customer service set;
and storing the customer service set into the customer service database.
In order to solve the technical problems, the embodiment of the application also provides a customer service dispatching device, which adopts the following technical scheme:
the judging module is used for judging whether the service request of the user is received or not; wherein, the service request carries consultation voice information;
The first determining module is used for determining target personality data of the user based on the consultation voice information and a preset personality analysis model if yes;
the first acquisition module is used for acquiring a plurality of first customer services matched with the target character data from a preset customer service database based on the target character data;
the second determining module is used for determining product information corresponding to the consultation voice information;
the screening module is used for screening second customer services matched with the product information from all the first customer services based on the product information;
the second acquisition module is used for acquiring service processing scores of the second customer service;
and the third determining module is used for determining target customer service from all the second customer service based on the service processing score and establishing a communication link between the user and the target customer service.
In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical schemes:
judging whether a service request of a user is received or not; wherein, the service request carries consultation voice information;
if yes, determining target personality data of the user based on the consultation voice information and a preset personality analysis model;
Acquiring a plurality of first customer services matched with the target character data from a preset customer service database based on the target character data;
determining product information corresponding to the consultation voice information;
screening second customer service matched with the product information from all the first customer service based on the product information;
acquiring service processing scores of the second customer service;
and determining target customer service from all the second customer service based on the service processing score, and establishing a communication link between the user and the target customer service.
In order to solve the above technical problems, an embodiment of the present application further provides a computer readable storage medium, which adopts the following technical schemes:
judging whether a service request of a user is received or not; wherein, the service request carries consultation voice information;
if yes, determining target personality data of the user based on the consultation voice information and a preset personality analysis model;
acquiring a plurality of first customer services matched with the target character data from a preset customer service database based on the target character data;
determining product information corresponding to the consultation voice information;
Screening second customer service matched with the product information from all the first customer service based on the product information;
acquiring service processing scores of the second customer service;
and determining target customer service from all the second customer service based on the service processing score, and establishing a communication link between the user and the target customer service.
Compared with the prior art, the embodiment of the application has the following main beneficial effects:
when receiving a service request of a user, the embodiment of the application firstly determines target personality data of the user based on consultation voice information and a preset personality analysis model; then, based on the target character data, acquiring a plurality of first customer services matched with the target character data from a preset customer service database; then determining product information corresponding to the consultation voice information; screening second customer services matched with the product information from all the first customer services based on the product information; subsequently obtaining service processing scores of the second customer services; and finally, determining the target customer service from all the second customer service based on the service processing score, and establishing a communication link between the user and the target customer service. According to the embodiment of the application, the character data of the user and the product information which the user intends to consult can be determined according to the consultation voice information carried in the service request sent by the user, and further, the analysis and the processing are carried out based on the character data of the user, the product information which the user intends to consult and the service processing score of the customer service, so that the service customer service which is most suitable for the user can be found in a targeted manner for different users, the accuracy and the processing efficiency of customer service distribution are improved, and the efficiency and the quality of service customers are improved. Thereby being beneficial to improving the utilization rate of communication resources.
Drawings
In order to more clearly illustrate the solution of the present application, a brief description will be given below of the drawings required for the description of the embodiments of the present application, it being apparent that the drawings in the following description are some embodiments of the present application, and that other drawings may be obtained from these drawings without the exercise of inventive effort for a person of ordinary skill in the art.
FIG. 1 is an exemplary system architecture diagram in which the present application may be applied;
FIG. 2 is a flow chart of one embodiment of a customer service dispatch method according to the present application;
FIG. 3 is a schematic diagram of one embodiment of a customer service dispatch tool in accordance with the present application;
FIG. 4 is a schematic structural diagram of one embodiment of a computer device in accordance with the present application.
Detailed Description
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs; the terminology used in the description of the applications herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application; the terms "comprising" and "having" and any variations thereof in the description of the application and the claims and the description of the drawings above are intended to cover a non-exclusive inclusion. The terms first, second and the like in the description and in the claims or in the above-described figures, are used for distinguishing between different objects and not necessarily for describing a sequential or chronological order.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of such phrases in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
In order to make the person skilled in the art better understand the solution of the present application, the technical solution of the embodiment of the present application will be clearly and completely described below with reference to the accompanying drawings.
As shown in fig. 1, a system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used as a medium to provide communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, among others.
The user may interact with the server 105 via the network 104 using the terminal devices 101, 102, 103 to receive or send messages or the like. Various communication client applications, such as a web browser application, a shopping class application, a search class application, an instant messaging tool, a mailbox client, social platform software, etc., may be installed on the terminal devices 101, 102, 103.
The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smartphones, tablet computers, electronic book readers, MP3 players (Moving Picture Experts Group Audio Layer III, dynamic video expert compression standard audio plane 3), MP4 (Moving Picture Experts Group Audio Layer IV, dynamic video expert compression standard audio plane 4) players, laptop and desktop computers, and the like.
The server 105 may be a server providing various services, such as a background server providing support for pages displayed on the terminal devices 101, 102, 103.
It should be noted that, the customer service dispatching method provided by the embodiment of the present application is generally executed by a server/terminal device, and accordingly, the customer service dispatching device is generally disposed in the server/terminal device.
It should be understood that the number of terminal devices, networks and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
With continued reference to FIG. 2, a flow chart of one embodiment of a customer service dispatch method according to the present application is shown. The order of the steps in the flowchart may be changed and some steps may be omitted according to various needs. The customer service dispatching method provided by the embodiment of the application can be applied to any scene needing customer service dispatching, and can be applied to products in the scenes, for example, the customer service dispatching in the field of financial insurance. The customer service dispatching method comprises the following steps:
Step S201, judging whether a service request of a user is received; wherein the service request carries advisory voice information.
In this embodiment, the electronic device (e.g., the server/terminal device shown in fig. 1) on which the customer service dispatch method operates may acquire the service request through a wired connection manner or a wireless connection manner. It should be noted that the wireless connection may include, but is not limited to, 3G/4G/5G connection, wiFi connection, bluetooth connection, wiMAX connection, zigbee connection, UWB (ultra wideband) connection, and other now known or later developed wireless connection. The content of the consultation voice information can be 'I want to consult with XXX products', 'I want to purchase XXX insurance', and so on.
And step S202, if yes, determining target personality data of the user based on the consultation voice information and a preset personality analysis model.
In this embodiment, the query voice information may be input into the personality analysis model, and the query voice information may be analyzed by the personality analysis model to obtain a corresponding personality analysis result, and the personality analysis result may be used as the target personality data of the user.
Step S203, based on the target personality data, acquiring a plurality of first customer services matched with the target personality data from a preset customer service database.
In this embodiment, a target customer service set that matches the target character data may be queried from the customer service database based on the target character data, where all customer services included in the target customer service set are the first customer service. For the insurance marketing scenario of the insurance industry, the customer service database may be a database storing data of each insurance customer service in the insurance system.
Step S204, determining the product information corresponding to the consultation voice information.
In this embodiment, the corresponding text information may be obtained by performing voice recognition on the consultation voice information, and then product keyword extraction processing is performed on the text information to obtain a corresponding target product keyword, so that the target product keyword is used as the product information.
Step S205, screening out second customer service matched with the product information from all the first customer service based on the product information.
In this embodiment, different customer services correspond to different product service types, and customer services with good product service types matching the product information can be screened from the first customer service based on the product information and used as the second customer service.
Step S206, obtaining service processing scores of the second customer services.
In this embodiment, the above specific implementation process of obtaining the service processing score of each second customer service is described in further detail in the following specific embodiments, which will not be described herein.
And step S207, determining target customer service from all the second customer service based on the service processing score, and establishing a communication link between the user and the target customer service.
In this embodiment, after the target customer service is determined from all the second customer services, a communication link between the user and the target customer service is established, so that the communication between the user and the target customer service is realized. In addition, the specific implementation process of determining the target customer service from all the second customer service based on the service processing scores will be described in further detail in the following specific embodiments, which will not be described herein.
When a service request of a user is received, firstly, determining target personality data of the user based on consultation voice information and a preset personality analysis model; then, based on the target character data, acquiring a plurality of first customer services matched with the target character data from a preset customer service database; then determining product information corresponding to the consultation voice information; screening second customer services matched with the product information from all the first customer services based on the product information; subsequently obtaining service processing scores of the second customer services; and finally, determining the target customer service from all the second customer service based on the service processing score, and establishing a communication link between the user and the target customer service. According to the application, character data of the user and product information which the user intends to consult can be determined according to the consultation voice information carried in the service request sent by the user, and further analysis and processing are carried out based on the character data of the user, the product information which the user intends to consult and the service processing score of the customer service, so that service customer service which is most suitable for the user can be found in a targeted manner for different users, the accuracy and the processing efficiency of customer service distribution are improved, and the efficiency and the quality of service customers are improved. Thereby being beneficial to improving the utilization rate of communication resources.
In some alternative implementations, step S202 includes the steps of:
and calling the pre-trained character analysis model.
In this embodiment, the training generation process of the character analysis model is described in further detail in the following specific embodiments, which will not be described herein.
Inputting the consultation voice information into the character analysis model, and analyzing and processing the consultation voice information through the character analysis model to obtain a corresponding character analysis result.
And taking the character analysis result as target character data of the user.
According to the application, the pre-trained character analysis model is called, the consultation voice information is input into the character analysis model, and the character analysis model is used for analyzing and processing the consultation voice information, so that the target character data of the user can be obtained quickly and accurately, a plurality of first customer services matched with the target character data can be acquired from the preset customer service database based on the target character data, and the acquisition accuracy of the first customer service is improved.
In some optional implementations of this embodiment, the determining, in step S207, a target customer service from all the second customer services based on the service processing score includes the steps of:
And screening the third customer service with the preset number and highest service processing score from all the second customer service.
In this embodiment, the preset number of values is not specifically limited, and may be set according to actual service usage requirements, for example, may be set to 3.
And acquiring historical service record data corresponding to the third customer service.
In this embodiment, the history service record data corresponding to the third customer service may be obtained by querying a service record database created in advance.
And inquiring the historical service record data, and judging whether fourth customer service which provides service for the user exists in all the third customer service.
And if a fourth customer service providing service for the user exists, taking the fourth customer service as the target customer service.
After the service processing scores of the second customer service are obtained, the third customer service with the highest service processing score is screened out from all the second customer service, then the historical service record data corresponding to the third customer service is obtained, if the fourth customer service which provides the service for the user exists in all the third customer service based on the historical service record data, the fourth customer service is intelligently determined to be the target customer service for providing the service for the user, the service is continuously provided for the user by selecting the customer service which provides the service for the user, the use experience of the user can be improved, and the distribution intelligence of the customer service allocation is improved.
In some optional implementations, after the step of determining whether there is a fourth customer service that provides the service to the user in all the third customer service, the electronic device may further perform the following steps:
and if the fourth customer service providing the service for the user does not exist, counting the current service number of each third customer service.
And determining a fifth customer service with the minimum number of current service people from all the third customer services.
And taking the fifth customer service as the target customer service.
According to the application, when the fourth customer service which provides the service for the user does not exist in the third customer service, the current service number of each third customer service is intelligently counted, and then the fifth customer service with the minimum current service number is determined from all the third customer service to be used for providing the service for the user, and the user is provided with the service by selecting the customer service with the minimum current service number, so that the interaction experience between the user and the fifth customer service can be improved, and the distribution intelligence of customer service assignment is improved.
In some alternative implementations, step S206 includes the steps of:
acquiring the working years, average service satisfaction and average service processing duration of the appointed customer service; wherein the specified customer service is any one customer service among all the second customer services.
In this embodiment, relevant service information of the customer service may be obtained by querying a customer service information base constructed in advance, and information such as a service life, average service satisfaction, average service processing duration, etc. may be extracted from the relevant service information. The method includes the steps of obtaining personal information of an insurance customer service A, inquiring a customer service information base in an insurance business system according to the personal information, and inquiring information such as the service life, average service satisfaction, average service processing duration and the like of the insurance customer service A corresponding to the personal information from the customer service information base.
And acquiring a first weight corresponding to the working period, a second weight corresponding to the average service satisfaction degree and a third weight corresponding to the average service processing duration.
In this embodiment, the values of the first weight, the second weight, and the third weight are not specifically limited, and may be set according to actual use requirements.
And calling a preset calculation formula to calculate the working life, the average service satisfaction and the average service processing duration based on the first weight, the second weight and the preset weight, and generating the service processing score of the appointed customer service.
In this embodiment, the above-mentioned preset calculation formula specifically includes: score=n×a+m+b+w×c, where Score is a service processing Score of a specified customer service, N is a working period of the specified customer service, a is a first weight of the working period, M is an average service satisfaction degree of the specified customer service, b is a second weight of the average service satisfaction degree, W is an average service processing duration of the specified customer service, and c is a third weight of the average service processing duration.
According to the application, the second customer service matched with the product information is screened out from all the first customer service, the service processing score of each second customer service can be calculated intelligently based on the calculation formula corresponding to the service life, the average service satisfaction degree and the average service processing time length of the customer service, so that the target customer service can be determined from all the second customer service based on the obtained service processing score of each second customer service, the processing intelligence of the target customer service determination is realized, the processing efficiency of service requests is improved, and the use experience of users is improved.
In some optional implementations of this embodiment, before step S202, the electronic device may further perform the following steps:
acquiring pre-acquired training data; the training data comprises character data and character expression voice data corresponding to the character data.
In this embodiment, the character data refers to data describing the character of the individual, that is, what character type the individual belongs to, for example, the character of the individual is an inward character, "inward" refers to description of the character of the individual, and the data corresponding to "inward" refers to character data of the individual. Character representation speech data refers to speech data describing a character, i.e., which sound feature representations are used to describe the character, which sound feature representations can be attributed to the type of character that includes which sound feature representations when represented on a particular person.
And calling a preset initial model.
In this embodiment, the selection of the initial model is not particularly limited, and any deep learning model may be used, for example, a neural convolution model may be used, and a character analysis model may be built based on the model, that is, the initial model.
And taking the character expression voice data as input of the initial model, taking the character data as output of the initial model, and training the initial model so that the initial model recognizes the mapping relation between the character data and the character expression voice data to obtain the character analysis model.
In this embodiment, the character analysis model in the training process automatically learns the matching mapping relationship between character data in the training data and character expression voice data corresponding to the character data, and further the character analysis model identifies and establishes the matching relationship between the character data and the character expression voice data corresponding to the character data through the mapping relationship between the training data. For example, if the training data includes character data a and character expression voice data a corresponding to the character data a, the character recognition model automatically grasps the matching relationship between a and a through an algorithm, and then automatically matches a and a when encountering them.
According to the application, the pre-acquired training data are acquired, character expression voice data in the training data are used as input of a preset initial model, character data are used as output of the initial model, and the initial model is trained, so that the initial model can identify the mapping relation between the character data and the character expression voice data, the construction of a character analysis model is completed, the follow-up use of the character analysis model is facilitated, the target character data of a user can be determined quickly and accurately based on the consultation voice information of the user, and the intelligent acquisition of the character data of the user is improved.
In some optional implementations of this embodiment, before step S203, the electronic device may further perform the following steps:
and acquiring character evaluation data of all customer services.
In this embodiment, the manner of performing the personality evaluation on each customer service is not particularly limited, and for example, a personality evaluation roll may be preset, and the personality of each customer service may be automatically evaluated to obtain the personality evaluation data of each customer service. By evaluating the character of each customer service in the form of a questionnaire, the efficiency of character evaluation can be greatly improved.
And acquiring preset character class information.
In this embodiment, the character class information may be set according to actual service usage requirements.
And classifying the customer services based on the character class information and the character evaluation data to obtain corresponding customer service sets.
In this embodiment, a plurality of customer service sets are obtained by classifying each customer service according to the character class to which the character of each customer service belongs. Classifying customer service according to the characters of the customer service, wherein the customer service contained in each type of character forms a customer service set.
And storing the customer service set into the customer service database.
According to the application, through acquiring the character evaluation data of all customer service and the preset character category information, jier classifies each customer service based on the character category information and the character evaluation data to obtain the corresponding customer service set, and stores the customer service set into the customer service database, so that the follow-up data query can be based on the customer service database, a plurality of customer service data matched with the target character data to be queried can be quickly acquired, and the processing efficiency of the customer service data query is improved. In addition, customer service is classified according to characters to form different customer service sets, target customer service sets matched with characters of users are directly and intensively obtained, and compared with the method that a plurality of target first customer service matched with target character data of the users are obtained from all stored customer service data one by one, the efficiency of obtaining the first customer service data by the electronic equipment can be effectively improved, so that the whole customer service dispatching processing process is shortened, and the dispatching efficiency of the whole customer service is improved.
It is emphasized that to further guarantee the privacy and security of the service processing scores, the service processing scores may also be stored in a blockchain node.
The blockchain is a novel application mode of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanism, encryption algorithm and the like. The Blockchain (Blockchain), which is essentially a decentralised database, is a string of data blocks that are generated by cryptographic means in association, each data block containing a batch of information of network transactions for verifying the validity of the information (anti-counterfeiting) and generating the next block. The blockchain may include a blockchain underlying platform, a platform product services layer, an application services layer, and the like.
The embodiment of the application can acquire and process the related data based on the artificial intelligence technology. Among these, artificial intelligence (Artificial Intelligence, AI) is the theory, method, technique and application system that uses a digital computer or a digital computer-controlled machine to simulate, extend and extend human intelligence, sense the environment, acquire knowledge and use knowledge to obtain optimal results.
Artificial intelligence infrastructure technologies generally include technologies such as sensors, dedicated artificial intelligence chips, cloud computing, distributed storage, big data processing technologies, operation/interaction systems, mechatronics, and the like. The artificial intelligence software technology mainly comprises a computer vision technology, a robot technology, a biological recognition technology, a voice processing technology, a natural language processing technology, machine learning/deep learning and other directions.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by computer readable instructions stored in a computer readable storage medium that, when executed, may comprise the steps of the embodiments of the methods described above. The storage medium may be a nonvolatile storage medium such as a magnetic disk, an optical disk, a Read-Only Memory (ROM), or a random access Memory (Random Access Memory, RAM).
It should be understood that, although the steps in the flowcharts of the figures are shown in order as indicated by the arrows, these steps are not necessarily performed in order as indicated by the arrows. The steps are not strictly limited in order and may be performed in other orders, unless explicitly stated herein. Moreover, at least some of the steps in the flowcharts of the figures may include a plurality of sub-steps or stages that are not necessarily performed at the same time, but may be performed at different times, the order of their execution not necessarily being sequential, but may be performed in turn or alternately with other steps or at least a portion of the other steps or stages.
With further reference to fig. 3, as an implementation of the method shown in fig. 2, the present application provides an embodiment of a customer service dispatch device, where the embodiment of the device corresponds to the embodiment of the method shown in fig. 2, and the device may be specifically applied to various electronic devices.
As shown in fig. 3, the customer service dispatch device 300 in this embodiment includes: a judging module 301, a first determining module 302, a first obtaining module 303, a second determining module 304, a screening module 305, a second obtaining module 306 and a third determining module 307. Wherein:
a judging module 301, configured to judge whether a service request of a user is received; wherein, the service request carries consultation voice information;
a first determining module 302, configured to determine, if yes, target personality data of the user based on the advisory voice information and a preset personality analysis model;
a first obtaining module 303, configured to obtain, from a preset customer service database, a plurality of first customer services that match the target character data based on the target character data;
a second determining module 304, configured to determine product information corresponding to the advisory voice information;
a screening module 305, configured to screen, based on the product information, second customer services that match the product information from all the first customer services;
A second obtaining module 306, configured to obtain service processing scores of the second customer services;
a third determining module 307 is configured to determine a target customer service from all the second customer services based on the service processing scores, and establish a communication link between the user and the target customer service.
In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the customer service dispatch method in the foregoing embodiment one by one, which is not described herein again.
In some optional implementations of this embodiment, the first determining module 302 includes:
the invoking sub-module is used for invoking the character analysis model trained in advance;
the processing sub-module is used for inputting the consultation voice information into the character analysis model, and analyzing and processing the consultation voice information through the character analysis model to obtain a corresponding character analysis result;
and the first determining submodule is used for taking the character analysis result as target character data of the user.
In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the customer service dispatch method in the foregoing embodiment one by one, which is not described herein again.
In some alternative implementations of the present embodiment, the third determining module 307 includes:
the screening sub-module is used for screening the third customer service with the preset number and highest service processing score from all the second customer service;
the first acquisition sub-module is used for acquiring historical service record data corresponding to the third customer service;
the inquiring sub-module is used for inquiring the historical service record data and judging whether fourth customer service which provides service for the user exists in all the third customer service;
and the second determining submodule is used for taking the fourth customer service as the target customer service if the fourth customer service which provides services for the user exists.
In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the customer service dispatch method in the foregoing embodiment one by one, which is not described herein again.
In some optional implementations of this embodiment, the third determining module 307 further includes:
a statistics sub-module, configured to, if there is no fourth customer service that provides services for the user, count current service people number of each third customer service;
a third determining submodule, configured to determine a fifth customer service with the least number of current service people from all the third customer services;
And the fourth determining submodule is used for taking the fifth customer service as the target customer service.
In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the customer service dispatch method in the foregoing embodiment one by one, which is not described herein again.
In some optional implementations of the present embodiment, the second obtaining module 306 includes:
the second acquisition sub-module is used for acquiring the working years, the average service satisfaction degree and the average service processing duration of the appointed customer service; wherein the specified customer service is any one customer service among all the second customer services;
a third sub-module, configured to obtain a first weight corresponding to the working period, a second weight corresponding to the average service satisfaction, and a third weight corresponding to the average service processing duration;
and the calculating sub-module is used for calling a preset calculating formula to calculate and process the working years, the average service satisfaction degree and the average service processing duration based on the first weight, the second weight and the preset weight, and generating the service processing score of the appointed customer service.
In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the customer service dispatch method in the foregoing embodiment one by one, which is not described herein again.
In some optional implementations of this embodiment, the customer service dispatch fixture further includes:
the third acquisition module is used for acquiring pre-acquired training data; wherein the training data comprises character data and character expression voice data corresponding to the character data;
the calling module is used for calling a preset initial model;
the training module is used for taking the character expression voice data as the input of the initial model, taking the character data as the output of the initial model, and training the initial model so that the initial model recognizes the mapping relation between the character data and the character expression voice data to obtain the character analysis model.
In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the customer service dispatch method in the foregoing embodiment one by one, which is not described herein again.
In some optional implementations of this embodiment, the customer service dispatch fixture further includes:
the fourth acquisition module is used for acquiring character evaluation data of all customer services;
a fifth acquisition module, configured to acquire preset character class information;
the classification module is used for classifying each customer service based on the character class information and the character evaluation data to obtain a corresponding customer service set;
And the storage module is used for storing the customer service set into the customer service database.
In this embodiment, the operations performed by the modules or units respectively correspond to the steps of the customer service dispatch method in the foregoing embodiment one by one, which is not described herein again.
In order to solve the technical problems, the embodiment of the application also provides computer equipment. Referring specifically to fig. 4, fig. 4 is a basic structural block diagram of a computer device according to the present embodiment.
The computer device 4 comprises a memory 41, a processor 42, a network interface 43 communicatively connected to each other via a system bus. It should be noted that only computer device 4 having components 41-43 is shown in the figures, but it should be understood that not all of the illustrated components are required to be implemented and that more or fewer components may be implemented instead. It will be appreciated by those skilled in the art that the computer device herein is a device capable of automatically performing numerical calculations and/or information processing in accordance with predetermined or stored instructions, the hardware of which includes, but is not limited to, microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASICs), programmable gate arrays (fields-Programmable Gate Array, FPGAs), digital processors (Digital Signal Processor, DSPs), embedded devices, etc.
The computer equipment can be a desktop computer, a notebook computer, a palm computer, a cloud server and other computing equipment. The computer equipment can perform man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch pad or voice control equipment and the like.
The memory 41 includes at least one type of readable storage medium including flash memory, hard disk, multimedia card, card memory (e.g., SD or DX memory, etc.), random Access Memory (RAM), static Random Access Memory (SRAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), programmable Read Only Memory (PROM), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the storage 41 may be an internal storage unit of the computer device 4, such as a hard disk or a memory of the computer device 4. In other embodiments, the memory 41 may also be an external storage device of the computer device 4, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash Card (Flash Card) or the like, which are provided on the computer device 4. Of course, the memory 41 may also comprise both an internal memory unit of the computer device 4 and an external memory device. In this embodiment, the memory 41 is generally used to store an operating system and various application software installed on the computer device 4, such as computer readable instructions of a customer service dispatch method. Further, the memory 41 may be used to temporarily store various types of data that have been output or are to be output.
The processor 42 may be a central processing unit (Central Processing Unit, CPU), controller, microcontroller, microprocessor, or other data processing chip in some embodiments. The processor 42 is typically used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is configured to execute computer readable instructions stored in the memory 41 or process data, such as computer readable instructions for executing the customer service dispatch method.
The network interface 43 may comprise a wireless network interface or a wired network interface, which network interface 43 is typically used for establishing a communication connection between the computer device 4 and other electronic devices.
Compared with the prior art, the embodiment of the application has the following main beneficial effects:
in the embodiment of the application, when a service request of a user is received, firstly, determining target personality data of the user based on consultation voice information and a preset personality analysis model; then, based on the target character data, acquiring a plurality of first customer services matched with the target character data from a preset customer service database; then determining product information corresponding to the consultation voice information; screening second customer services matched with the product information from all the first customer services based on the product information; subsequently obtaining service processing scores of the second customer services; and finally, determining the target customer service from all the second customer service based on the service processing score, and establishing a communication link between the user and the target customer service. According to the embodiment of the application, the character data of the user and the product information which the user intends to consult can be determined according to the consultation voice information carried in the service request sent by the user, and further, the analysis and the processing are carried out based on the character data of the user, the product information which the user intends to consult and the service processing score of the customer service, so that the service customer service which is most suitable for the user can be found in a targeted manner for different users, the accuracy and the processing efficiency of customer service distribution are improved, and the efficiency and the quality of service customers are improved. Thereby being beneficial to improving the utilization rate of communication resources.
The present application also provides another embodiment, namely, a computer readable storage medium, where computer readable instructions are stored, where the computer readable instructions are executable by at least one processor, so that the at least one processor performs the steps of the customer service dispatch method as described above.
Compared with the prior art, the embodiment of the application has the following main beneficial effects:
in the embodiment of the application, when a service request of a user is received, firstly, determining target personality data of the user based on consultation voice information and a preset personality analysis model; then, based on the target character data, acquiring a plurality of first customer services matched with the target character data from a preset customer service database; then determining product information corresponding to the consultation voice information; screening second customer services matched with the product information from all the first customer services based on the product information; subsequently obtaining service processing scores of the second customer services; and finally, determining the target customer service from all the second customer service based on the service processing score, and establishing a communication link between the user and the target customer service. According to the embodiment of the application, the character data of the user and the product information which the user intends to consult can be determined according to the consultation voice information carried in the service request sent by the user, and further, the analysis and the processing are carried out based on the character data of the user, the product information which the user intends to consult and the service processing score of the customer service, so that the service customer service which is most suitable for the user can be found in a targeted manner for different users, the accuracy and the processing efficiency of customer service distribution are improved, and the efficiency and the quality of service customers are improved. Thereby being beneficial to improving the utilization rate of communication resources.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present application.
It is apparent that the above-described embodiments are only some embodiments of the present application, but not all embodiments, and the preferred embodiments of the present application are shown in the drawings, which do not limit the scope of the patent claims. This application may be embodied in many different forms, but rather, embodiments are provided in order to provide a thorough and complete understanding of the present disclosure. Although the application has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that modifications may be made to the embodiments described in the foregoing description, or equivalents may be substituted for elements thereof. All equivalent structures made by the content of the specification and the drawings of the application are directly or indirectly applied to other related technical fields, and are also within the scope of the application.
Claims (10)
1. The customer service dispatching method is characterized by comprising the following steps of:
judging whether a service request of a user is received or not; wherein, the service request carries consultation voice information;
if yes, determining target personality data of the user based on the consultation voice information and a preset personality analysis model;
acquiring a plurality of first customer services matched with the target character data from a preset customer service database based on the target character data;
determining product information corresponding to the consultation voice information;
screening second customer service matched with the product information from all the first customer service based on the product information;
acquiring service processing scores of the second customer service;
and determining target customer service from all the second customer service based on the service processing score, and establishing a communication link between the user and the target customer service.
2. The customer service dispatch method of claim 1, wherein the step of determining the target personality data of the user based on the advisory voice information and a preset personality analysis model specifically comprises:
invoking the character analysis model trained in advance;
Inputting the consultation voice information into the character analysis model, and analyzing and processing the consultation voice information through the character analysis model to obtain a corresponding character analysis result;
and taking the character analysis result as target character data of the user.
3. The customer service dispatch method of claim 1, wherein the step of determining a target customer service from all the second customer services based on the service processing score comprises:
screening a preset number of third customer services with highest service processing scores from all the second customer services;
acquiring historical service record data corresponding to the third customer service;
inquiring the history service record data, and judging whether fourth customer service which provides service for the user exists in all the third customer service;
and if a fourth customer service providing service for the user exists, taking the fourth customer service as the target customer service.
4. A customer service dispatch method according to claim 3, wherein after said step of determining whether there is a fourth customer service that has served said user among all of said third customer services, further comprising:
If the fourth customer service providing the service for the user does not exist, counting the current service number of each third customer service;
determining a fifth customer service with the least number of current service people from all the third customer services;
and taking the fifth customer service as the target customer service.
5. The customer service dispatch method of claim 1, wherein the step of obtaining the service processing score of each of the second customer service comprises:
acquiring the working years, average service satisfaction and average service processing duration of the appointed customer service; wherein the specified customer service is any one customer service among all the second customer services;
acquiring a first weight corresponding to the working years, a second weight corresponding to the average service satisfaction degree and a third weight corresponding to the average service processing duration;
and calling a preset calculation formula to calculate the working life, the average service satisfaction and the average service processing duration based on the first weight, the second weight and the preset weight, and generating the service processing score of the appointed customer service.
6. The customer service dispatch method of claim 1, further comprising, prior to the step of determining the user's target personality data based on the advisory voice information and a preset personality analysis model:
Acquiring pre-acquired training data; wherein the training data comprises character data and character expression voice data corresponding to the character data;
calling a preset initial model;
and taking the character expression voice data as input of the initial model, taking the character data as output of the initial model, and training the initial model so that the initial model recognizes the mapping relation between the character data and the character expression voice data to obtain the character analysis model.
7. The customer service dispatch method of claim 1, further comprising, prior to the step of obtaining, from a preset customer service database, a plurality of first customer services matching the target personality data based on the target personality data:
acquiring character evaluation data of all customer services;
acquiring preset character class information;
classifying each customer service based on the character class information and the character evaluation data to obtain a corresponding customer service set;
and storing the customer service set into the customer service database.
8. Customer service dispatch fixture, characterized by comprising:
The judging module is used for judging whether the service request of the user is received or not; wherein, the service request carries consultation voice information;
the first determining module is used for determining target personality data of the user based on the consultation voice information and a preset personality analysis model if yes;
the first acquisition module is used for acquiring a plurality of first customer services matched with the target character data from a preset customer service database based on the target character data;
the second determining module is used for determining product information corresponding to the consultation voice information;
the screening module is used for screening second customer services matched with the product information from all the first customer services based on the product information;
the second acquisition module is used for acquiring service processing scores of the second customer service;
and the third determining module is used for determining target customer service from all the second customer service based on the service processing score and establishing a communication link between the user and the target customer service.
9. A computer device comprising a memory and a processor, the memory having stored therein computer readable instructions which when executed by the processor implement the steps of the customer service dispatch method of any one of claims 1 to 7.
10. A computer readable storage medium having stored thereon computer readable instructions which when executed by a processor implement the steps of the customer service dispatch method of any one of claims 1 to 7.
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