CN109245994B - Robot customer service method - Google Patents
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- CN109245994B CN109245994B CN201811073663.0A CN201811073663A CN109245994B CN 109245994 B CN109245994 B CN 109245994B CN 201811073663 A CN201811073663 A CN 201811073663A CN 109245994 B CN109245994 B CN 109245994B
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
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- H04L51/00—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail
- H04L51/02—User-to-user messaging in packet-switching networks, transmitted according to store-and-forward or real-time protocols, e.g. e-mail using automatic reactions or user delegation, e.g. automatic replies or chatbot-generated messages
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Abstract
A robotic customer service method, the method comprising: identifying content of a conversation message when the conversation message is received from a customer client; determining whether the session message can be processed autonomously or not according to the content of the session message; when determining that the session message can be autonomously processed, extracting a response message matched with the content of the session message from the stored service resource and sending the response message to the customer client; when determining that the session message cannot be autonomously processed or identified, setting the state of the client in the subsequent session service with the client as a session suspension state, extracting a placation response message matched with the content of the session message, sending the placation response message to the client, and sending the session message which cannot be autonomously processed or identified to the customer service client. By adopting the robot customer service method, the effectiveness of customer service can be enhanced, and the user experience can be improved.
Description
The invention provides a divisional application named robot customer service and a customer service method thereof and an intelligent customer service system with an application date of 2015, 12, month and 30 and an application number of 201511024389.4.
Technical Field
The invention relates to the technical field of instant messaging, in particular to a robot customer service method and a computer readable storage medium.
Background
With the rapid development of the internet and the improvement of service consciousness of people, network customer service has been popularized in various industries and goes deep into various links of daily business service.
The existing customer service system generally comprises machine customer service and artificial customer service, wherein the machine customer service is generally an instant messaging tool based on a webpage, the artificial customer service is generally an instant messaging tool embedded in the webpage, and each artificial customer service client is manually maintained. In the customer service process, when a session message from a customer is received, the session message is served by a machine customer service. And when the customer thinks that the machine customer service cannot solve the problem provided by the machine customer service, the customer clicks the manual customer service manually again to consult the manual customer service.
The customer service system can quickly respond to the requirements of customers to a certain extent. However, in the actual application process, the machine customer service identifies the content of the conversation message input by the customer, searches the stored resource database for data matching with the content of the conversation message, and sends the matched data to the user client for response, and for the same question, repeated answers are usually performed mechanically, which is easy to irritate the customer and affect the customer experience. However, the manual customer service cannot be on-line all the time, and usually faces a plurality of customers at the same time, so that the customer service cannot respond in time. Therefore, the current customer service system is difficult to effectively meet the service requirements of customers, and the user experience is influenced.
Disclosure of Invention
The technical problem solved by the invention is how to enhance the effectiveness of the customer service and improve the user experience.
In order to solve the technical problem, an embodiment of the present invention provides a robot customer service method, where the method includes:
when a conversation message from a customer client is received, identifying the content of the conversation message;
determining whether the session message can be processed autonomously according to the content of the session message;
when it is determined that the session message can be autonomously processed, extracting a response message matched with the content of the session message from the stored service resource and transmitting the response message to the customer client;
when determining that the session message cannot be autonomously processed or identified, setting the state of the client in the subsequent session service of the client as a session suspension state, extracting a placating response message matched with the content of the session message, sending the placating response message to the client, and sending the session message which cannot be autonomously processed or identified to a customer service client;
when the client is in a session state in the session service with the client and receives the session message from the customer service client, switching the session state of the client in the session service with the client to a session suspension state, and executing the transmission operation of the session message between the customer service client and the client.
Optionally, the service resource includes: language experience data and customer service resource data; the determining whether the session message can be autonomously processed according to the content of the session message includes:
determining whether the content of the session message can autonomously reply according to the language experience data;
when determining that the answer cannot be made according to the language experience data autonomously, determining a scene category to which the content of the session message belongs;
and when determining that the answer can be made autonomously according to the language experience data or the scene category to which the content of the session message belongs exists, determining that the session message can be processed autonomously.
Optionally, the extracting, when it is determined that the session message can be autonomously processed, a response message matched with the content of the session message from the stored service resource includes:
extracting a response message matched with the content of the conversation message from the stored language-experience data when it is determined that the response can be autonomously answered according to the language-experience data;
and when determining that the answer cannot be made according to the language experience data autonomously, extracting an answer message matched with the content of the conversation message in the scene from the stored customer service resource data.
Optionally, the method further comprises: when receiving a session message from a customer client, if the state of the user in the session service with the customer client is determined to be a non-session suspension state, executing the operation of identifying the content of the session message.
Optionally, the method further comprises: and when the conversation service with the customer client is in a conversation suspension state and does not receive the conversation message from the customer service client, identifying the content of the conversation message, extracting a placating response message matched with the content of the conversation message and sending the placating response message to the customer client.
Optionally, the method further comprises: and when the session between the customer service client and the customer client is determined to be finished, restoring the state of the customer service client in the session service with the customer client to be a session state.
Optionally, the determining that the session between the customer service client and the customer client is over includes at least one of:
determining that no session message is transmitted between the customer service client and the customer client for a preset duration;
a session completion signal from the customer service client is detected.
Optionally, the detecting a session completion signal from the customer service client includes:
and sending the conversation completion signal when detecting that the customer service client closes the conversation window or detecting that the conversation message sent by the customer service client comprises the content for displaying the completion of the conversation.
Optionally, the method further comprises: and sending the soothing response message corresponding to the session message which cannot be autonomously processed or identified and the session message which cannot be autonomously processed or identified to the customer service client.
To solve the above problem, an embodiment of the present invention further provides a computer-readable storage medium, on which a program is stored, where the program is executed to implement the steps of the robot customer service method described above.
Compared with the prior art, the technical scheme of the embodiment of the invention has the following beneficial effects:
the robot service, upon receiving a conversation message from a customer client, identifies the content of the conversation message and determines whether the conversation message can be processed. And when the conversation message is determined to be capable of being autonomously processed, extracting a response message matched with the content of the conversation message from the stored service resource and sending the response message to the client side of the customer, so that the customer can obtain a timely and effective response. When the session message cannot be processed or identified, on one hand, the state of the robot customer service in the subsequent session service with the customer client is set to be a session suspension state, so that the processing resources of the robot customer service can be saved; on the other hand, the soothing response message matched with the content of the conversation message is sent in time, so that the phenomenon that customers cannot obtain reasonable response to generate a fussy mood can be avoided, the conversation message which cannot be identified or autonomously processed by the robot can be sent to the customer service client side without manual selection of the customers, and when the robot customer service cannot effectively process, the timely intervention of manual customer service can be realized, and the problems of the customers can be effectively solved. In a word, the scheme can timely and effectively solve the problem of the customer through the cooperative work of the robot customer service automation and the manual customer service, the customer cannot feel the difference between the robot customer service and the manual customer service, the emotion in the process of waiting for response can be effectively placated, and better interactive experience is obtained.
Furthermore, the robot customer service is subjected to big data training, so that the robot customer service can identify the scene type of the session message, and can rapidly determine whether the session message can be processed and carry out subsequent processing, thereby improving the response speed of the customer service and further enhancing the interactive experience of customers.
Further, when the robot customer service determines that the robot customer service can autonomously answer according to the language experience data, the response message matched with the content of the session message is extracted from the stored language experience data, and when the robot customer service determines that the robot customer service cannot autonomously answer according to the language experience data, the response message matched with the content of the session message in the belonging scene is selected, so that the robot customer service can answer according to the language experience data and the customer service resource data, and the matched resource data corresponds to the scene of the customer service, so that the breadth of the response message which can be answered by the robot customer service and the accuracy of response can be improved.
Further, when receiving the session message from the client, the robot service firstly detects whether the robot service is in the session suspension state, and when determining that the robot service is not in the session suspension state, the robot service executes the operation of identifying the content of the session message, and when determining that the robot service is in the session suspension state, the robot service performs session interaction with the client through the service client, so as to realize better cooperative work of the manual and robot services, on one hand, when the robot service is in the session suspension state, only the transmission of the session message is needed without any autonomous processing, so that the service resources of the robot service can be saved, on the other hand, the robot service can only work when the robot service is not in the session suspension state, so that the priority of the robot service is higher, so that the robot service can be prevented from seizing the session midway, therefore, the customer can obtain consistent service experience, and the user experience of the customer is improved.
Further, when the robot customer service is in a session suspension state, if the session message from the customer service client is not received, that is, the manual customer service is not yet intervened, the content of the session message is identified, and when the content of the session message can be identified, the corresponding soothing response message is extracted from the stored service resources, and in the process of interaction between the manual customer service and the customer, the robot customer service does not perform any identification, autonomous processing or response on the session message, but only transmits the session between the customer service client and the customer client, so that the degree of coordination between the robot customer service and the manual customer service can be further improved, and the anxiety of the customer in the waiting process can be further relieved.
Further, when the robot customer service is in a session state in the session service with the customer client and receives a session message from the customer service client, the session state of the robot customer service in the session service with the customer client is switched to a session suspension state, and the transmission operation of the session message between the customer service client and the customer client is executed.
Further, when the robot customer service determines that the session between the customer service client and the customer client is finished, the state of the robot customer service in the subsequent session service between the robot customer service client and the customer client is recovered to be a session state, namely, when the intervention of the manual customer service is finished, the state of the robot customer service is automatically switched back, the seamless connection between the manual customer service and the robot customer service is realized, and therefore the service experience of the customer can be further optimized.
Further, by determining that no session message is transmitted between the customer service client and the client for a preset time, or when a session window is detected to be closed or when a session message sent by the customer service client contains content for displaying session completion, a session completion signal automatically sent by the customer service client can automatically identify completion of manual customer service intervention, so that the manual customer service operation can be reduced, the workload of manual customer service is reduced, and convenience is provided for the manual customer service.
Further, the soothing response message corresponding to the session message which cannot be processed or identified autonomously and the session message which cannot be processed or identified autonomously are sent to the customer service client together, so that the artificial customer service can see the content of the response message replied by the robot customer service to the customer, the consistency and consistency of response are convenient to maintain, the consistent service experience can be optimized, and the user experience of the customer is improved.
Further, a soothing response message representing that the customer service is in a state of searching for answers to the problems is fed back to the customer and is executed simultaneously with the process that the customer service client searches for the contents of the session message and gives a solution, so that on one hand, the actual state of the customer service can be reflected without manual input of the customer service, the response operation time of the manual customer service is saved, and the mood of the customer can be placated; on the other hand, the manual customer service can put more time into solving the problems of the customers, so that the responses which are more satisfied to the customers can be more quickly given.
Drawings
FIG. 1 is a flow chart of a robot customer service method in an embodiment of the present invention;
FIG. 2 is a flow chart of another method of robot servicing in an embodiment of the present invention;
FIG. 3 is a schematic diagram of a customer client interactive interface in accordance with an embodiment of the present invention;
FIG. 4 is a schematic diagram of a robot service architecture in an embodiment of the present invention;
FIG. 5 is a schematic diagram of an alternative robot service architecture in accordance with an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an intelligent customer service system in an embodiment of the present invention.
Detailed Description
As described above, in the customer service process of the current customer service system, the machine customer service and the manual customer service independently serve the customer, that is, the machine customer service first serves the customer. And when the customer thinks that the machine customer service cannot solve the problem provided by the machine customer service, the customer clicks the manual customer service manually again to consult the manual customer service. According to the scheme, the robot customer service system has the problems that mechanical repeated answering is easy to irritate customers, manual customer service cannot be online all the time, the customers are numerous in general, and the customers cannot reply in time, so that the service requirements of the customers cannot be effectively met by the existing customer service system.
Aiming at the problems, the embodiment of the invention adopts the cooperation of the robot customer service and the manual customer service, the robot customer service uniformly receives the session message from the client, identifies the content of the session message and determines whether the session message can be processed autonomously or not, when the autonomous processing is determined, the message is responded directly, and when the autonomous processing is determined or the content of the message cannot be processed autonomously, on one hand, the state of the self in the subsequent session service of the client is set to be a session suspension state, on the other hand, a soothing response message matched with the content of the session message is sent in time, so that the problem that the client can not respond reasonably without manual selection of the client can be avoided, and meanwhile, the session message of the client is sent to the customer service client to be responded manually, when the robot customer service cannot process effectively, can realize timely intervention of artifical customer service and effectively solve customer's problem, and customer can not experience the difference of robot customer service and artifical customer service, can effectively placate the mood in the process of waiting for the response, obtains better interactive experience.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in detail below.
The embodiment of the invention provides a robot customer service method, which is described in detail by referring to fig. 1 and through specific steps.
S11, receiving the session message from the customer client.
In particular implementations, the session message may take a variety of forms. For example, it may be a sentence composed of natural language words.
The customer can describe the description object through the sentence composed by the natural language. For example, if the description object is a product, the session message may be a consultation message of product-related information such as size, shape, color, texture, production date, and shelf life of the product, or a consultation message of after-market service of the product. If the description object is a service, the session message may be service content, service duration, notice, and consulting information of service-related content such as service staff providing the service.
In a specific implementation, the conversation message can be presented in a form of voice, image or video besides being presented in a text form. For example, the customer may have a conversation with the customer service in the form of an audio or instant audio conversation or a video conversation.
In a specific implementation, the customer can also have a conversation with the customer service in the form of pictures through the customer client. The picture may be a static picture, a dynamic picture, or a combination thereof with semantic information, or a photograph or screen shot of the product or service object for which the customer session is directed.
In particular implementations, the customer may also send a link containing a product or service object in the form of a session message.
It is understood that, in a specific implementation, the conversation message may also be implemented by combining two or more forms of sentences composed of natural language words, data links, voice, images or videos. For example, a customer communicates with a customer service via voice or video, while sending the corresponding data link to the customer service via the customer client.
S12, identifying the content of the session message, executing step S13 when the content of the session message is identified, and executing step S15 when the content of the session message cannot be identified.
In a specific implementation, the content of the conversation message can be identified by the robot customer service, and different identification methods can be adopted for identification processing according to different conversation message forms. For example, a sentence composed of natural language words may be recognized by word segmentation and semantic recognition. For another example, received voice can be converted into text, and then word segmentation and semantic recognition are further performed. If the conversation message contains images, the text or pattern lines in the images can be extracted and further identified for waiting.
S13, according to the content of the session message, determining whether the session message can be processed autonomously, when determining that the session message can be processed autonomously, executing step S14; when it is determined that the session message cannot be autonomously processed or recognized, step S15 is performed.
In particular implementations, some conversational messages may not be recognizable, such as video, or images in large or complex message formats that may exceed the recognition capabilities of the robot customer service. Or, the content robot service of some conversation messages can identify but the content robot service finds that the content robot service exceeds the self-autonomous processing capability after identification. For the session message that can be autonomously processed, step S13 may be performed, and for the session message that cannot be autonomously processed or identified, step S15 may be performed.
And S14, extracting the response message matched with the content of the conversation message from the stored service resource and sending the response message to the customer client.
In particular implementations, the service resources may include language experience data and customer service resource data. After recognizing the content of the conversation message, the robot service may extract the matched response message from the stored language experience data or extract the matched response message from the stored service resource data according to the content of the conversation message. For example, when the content of the conversation message is identified as "hello", the response message that results in a match by extracting in the stored language experience data is: "good, on woollen cloth. What can you be served? ". As another example, when the content of the identified conversation message is: "did i ask me to purchase a blue dress for shipment? And if so, extracting order information corresponding to the customer from the language experience data and the customer service resource data to obtain a response message: "you are just! Your purchased dress has been shipped ". The response message may also be attached with logistics information of the order.
And S15, setting the state of the user in the subsequent session service of the client as a session suspension state, extracting a placation response message matched with the content of the session message, sending the placation response message to the client, and sending the session message which cannot be processed autonomously or identified to the customer service client.
In some implementations, the robot customer service may not be able to process or identify itself with some message content. For such a situation, on one hand, the robot may set the state of the robot itself in the subsequent session service with the client to the session suspension state, and after the state is set to the session suspension state, when the session message from the client is received subsequently, the robot service will not process any more, so that the processing resource of the robot service can be saved; on the other hand, a placating response message matched with the content of the session message is extracted and sent to the customer client to placate the emotion of the customer, and meanwhile, the session message which cannot be processed autonomously or identified is sent to a customer service client for intervention processing by manual customer service. When the robot is in a conversation suspension state, in the process of manual customer service processing, the robot customer service directly transmits conversation messages received from the customer client and the customer service client to the opposite side without any identification or processing.
When the robot cannot process the conversation message independently or cannot identify the conversation message, the machine customer service extracted soothing response message matched with the conversation message content is a message capable of stabilizing the uneasy and negative emotions of the customer, and can be presented through natural word language, pictures, voice, music and the like. In particular implementations, the soothing response message is adapted to characterize the customer service as being in a state of seeking answers to questions in order to avoid a petitious mood resulting from the customer's conversation messages failing to respond for a long period of time. For example, when the content of the conversation message is identified as: when the robot customer service determines that the robot customer service cannot autonomously process the leather shoes, on one hand, the robot customer service sets the robot customer into a session suspension state in subsequent session service with the customer client; on the other hand, the matching result is that: kaki, good. Wait a little to see your shoes. Sending the placating response message to the customer client so that the customer can reply in time and have patience to wait, and sending a session message of 'I want to buy the double man leather shoes' to the customer service end so that manual service is handled. Some soothing response messages corresponding to the situation that the robot customer service cannot recognize the content of the specific conversation message can also be set in advance, for example, for the received pictures, when the contents cannot be recognized, the corresponding soothing response messages can be set to be 'please look for a little, and i see first'.
According to the embodiment, the problem of the customer can be timely and effectively solved through the cooperative work of the robot customer service automation and the manual customer service, the customer cannot feel the difference between the robot customer service and the manual customer service, the emotion in the process of waiting for response can be effectively soothed, and better interactive experience is obtained.
In specific implementation, the customer service method can be further expanded or optimized according to needs. The following is a detailed description of specific examples.
Referring to fig. 2, another robot customer service method is provided in the embodiment of the present invention, which is described in detail below by means of specific steps.
S21, receiving the session message from the customer client.
In particular implementations, the session message may take a variety of forms, as previously described. For example, the language may be any one of a sentence, a data link, a voice, an image, or a video composed of natural language words, or a combination of multiple forms, which is not described herein again.
S22, determining the state of the user in the session service, and if the state is the session suspension state, executing the step S27; if the non-session suspended state exists, step S23 is executed.
In order to save the processing resources of the robot customer service and realize the cooperative work of the robot customer service and the manual customer service, the state that the robot customer service autonomously processes the session message from the client can be set as a "session state" or a "non-suspended state", and the state that the robot customer service cannot autonomously process or cannot identify the content of the session message can be set as a "session suspended state".
If the robot service determines that the state of the robot service in the session service with the customer client is a non-session suspended state, step S23 is executed. If the robot service determines that the state of the robot service in the session service of the client is the session suspended state, the subsequent client questions from the client under the current session are not automatically replied, but are sent to the service client for manual service processing, i.e., step S27 is executed.
S23, identifying the content of the conversation message, if it can be identified, executing step S24; otherwise, step S26 is executed.
In a specific implementation, the content of the conversation message can be identified by the robot customer service, and different identification methods can be adopted for identification processing according to different conversation message forms. For example, a sentence composed of natural language words may be recognized by word segmentation and semantic recognition. For another example, received voice can be converted into text, and then word segmentation and semantic recognition are further performed. If the conversation message contains an image, the text or pattern lines in the image can be extracted and further identified. If it can be identified, step S24 is performed.
It should be noted that some conversation messages may not be recognized, such as video or images with large information amount or complicated message form, which may exceed the recognition capability of the robot customer service, and then step S26 may be executed.
S24, determining whether autonomous processing is possible, if so, executing step S25; if not, step S26 is performed.
The robot service may determine whether autonomous processing is possible according to the contents of the recognized conversation message.
In particular implementations, the robot may confirm whether autonomous processing is enabled based on stored service resources, which may include stored linguistic empirical data and customer service resource data.
Specifically, it may be determined first whether the content of the session message can be answered autonomously from the language-experience data, and when it is determined that the content of the session message can be answered autonomously from the language-experience data, it is determined whether autonomous processing is possible; when it is determined that the robot customer service cannot autonomously answer the conversation message according to the language experience data, it may be further determined that a scene category to which the content of the conversation message belongs exists.
In order to improve the autonomous processing capability of the robot, big data machine training can be performed on the robot customer service to identify the scene type of the session message. In specific implementation, the session messages with the client side can be classified and split according to scenes in advance to obtain the customer service resource data of different scene categories.
In an embodiment of the invention, in the scene classification and machine training process, the session message not only comprises the session message between the robot customer service and the customer client, but also comprises the session message between the artificial customer service and the customer client, all the session messages are classified and split according to scenes, and the artificial customer service is not regarded as an independent individual but is used as an element of a specific scene in the whole service link, so that the whole customer service working mode is reconstructed, the working efficiency of the artificial customer service can be effectively improved under the condition of a large number of customers, and the customer service experience is optimized. Wherein elements of a scenario may include customer and customer service and session message content for both different service scenarios.
And S25, extracting the matched response message from the stored service resource and sending the response message to the customer client.
As previously described, the service resources may include stored language experience data and customer service resource data. Accordingly, in a specific implementation, when it is determined that a response can be autonomously made based on the language-experience data, extracting a response message matching the content of the conversation message from the stored language-experience data; and when determining that the answer cannot be made according to the language experience data autonomously, extracting an answer message matched with the content of the conversation message in the scene from the stored customer service resource data.
And S26, setting the self in a suspended state in the subsequent session service of the customer client, replying a soothing response message corresponding to the session message to the customer client, and sending the session message and the soothing response message to the customer service client.
In specific implementation, the soothing response message corresponding to the session message which cannot be processed or identified autonomously and the session message which cannot be processed or identified autonomously can be sent to the customer service client together, so that the artificial customer service can see the content of the response message replied by the robot customer service to the customer, the consistency and consistency of response can be conveniently maintained, the consistent service experience can be optimized, and the user experience of the customer can be improved.
And S27, transmitting the session message to the corresponding customer service client.
When the robot customer service is in a conversation suspension state, the conversation messages from the customer client and the customer service client are respectively forwarded to the other side without any autonomous processing, and the robot customer service only forwards the conversation messages without any identification, processing or response through the intervention of the manual customer service, so that the service resources of the robot customer service can be saved.
It can be known from the above embodiments that, when receiving a session message from a client, a robot service first detects whether the robot service is in a session suspended state, and when determining that the robot service is not in the session suspended state, the robot service performs an operation of identifying the content of the session message, and when determining that the robot is in the session suspended state, the robot service performs session interaction with the client through the service client, thereby implementing better cooperative work between the robot service and the robot service, on one hand, when the robot service is in the session suspended state, only the transmission of the session message is required without performing any autonomous processing, which can save the service resources of the robot service, on the other hand, the robot service can work only when the robot service is not in the session suspended state, so that the priority of the robot service is higher, which can avoid the robot service seizing the midway session, therefore, the customer can obtain consistent service experience, and the user experience of the customer is improved.
In specific implementation, in order to further relieve the anxiety of customers in the waiting process, when the robot customer service is in a conversation suspension state, if the conversation message from the customer service client is not received, namely the manual customer service has not been subjected to intervention processing, the content of the conversation message can be identified, and when the content of the conversation message can be identified, a corresponding soothing response message is extracted from the stored service resources; after receiving the session message from the customer service client, namely the manual intervention processing, in the process of interaction between the manual customer service and the customer, the robot customer service does not perform any identification, autonomous processing or response on the session message, but only transmits the session between the customer service client and the customer client.
In a specific implementation, when it is determined that the session between the customer service client and the customer client is ended, the robot service may autonomously restore its own state in the session service with the customer client to a session state, i.e., a non-session suspended state.
When the intervention of the manual customer service is finished, the seamless connection between the manual customer service and the robot customer service is realized by automatically switching the state of the robot customer service back, so that the service experience of customers can be further optimized. In particular implementations, there are a number of ways to determine that a session between the customer service client and the customer client is over. For example, it is determined whether there is no session message transmission between the customer service client and the customer client for a preset duration, and when the preset duration is reached, it is determined that the session between the customer service client and the customer client is ended. For another example, whether a session completion signal from the customer service client is detected, when the session completion signal from the customer service client is detected, it is determined that the session between the customer service client and the customer client is ended. In an embodiment of the present invention, the customer service client may send the session completion signal when detecting that the customer service client closes the session window. In another embodiment of the present invention, the customer client may also send the session completion signal when detecting that the session message sent by the customer service client includes content indicating that the session is completed.
It will be appreciated that in particular embodiments, the methods described in the different embodiments above may be used in combination, as desired.
The method comprises the steps that whether conversation information is transmitted between the customer service client and the customer client for a preset time length or not is determined, or when a conversation window is detected to be closed or when a conversation message sent by the customer service client contains content for displaying conversation completion, a conversation completion signal sent by the customer service client automatically identifies completion of manual customer service intervention, so that manual customer service operation can be reduced, workload of manual customer service is reduced, and convenience is brought to manual customer service.
In specific implementation, when the client is in a session state in a session service with the client and receives a session message from the customer service client, the session state of the client in the session service with the client is switched to a session suspension state, and a transmission operation of the session message between the customer service client and the customer service client is executed, that is, in a process of cooperative work of manual customer service and robot customer service, the priority of the manual customer service is higher, and the manual customer service can actively intervene at any time as required, so that better service can be provided for the customer.
It is to be understood that, in the above embodiments, the processing flow when a session message is received from a client is described, and each received session message may be processed according to the above flow.
In order to enable those skilled in the art to better understand and implement the present invention, the following detailed description is provided by way of a specific session scenario.
Referring to fig. 3, a schematic diagram of a customer client interaction interface is shown. The interactive interface is a session interactive interface of the customer A and the customer service B, and is displayed through a customer client of the customer A. In the intelligent customer service system, no matter robot customer service or manual customer service, the customer A is displayed as a uniform image customer service B, and an actual service person may be the robot customer service or some manual customer service behind a customer service client. The boxes a and B respectively represent identification information of the customer a and the customer service B, and in a specific implementation, the boxes a and B can be displayed by using information such as customized head images and nicknames of the customer a and the customer service B. The time information "5:44 pm" and "5:50 pm" in the dashed boxes 38, 39 indicate the time at which the session displayed on the customer client interface of customer a occurred. The right-side session message is the session message content sent by the customer A, and the left-side session message is the response message content of the customer service B. The following describes in detail the processing procedure executed by the intelligent customer service system during the session interaction process:
the method comprises the steps that a customer A sends a conversation message 'hello' through a customer client, when the robot customer service confirms that the robot customer service does not stay in a conversation suspension state, the conversation message is identified, after identification is obtained, whether a response can be made according to language experience data is confirmed, and when the response can be made according to the language data, a matched response message 'hello', where the response can be made, is extracted. What can you be served? "and sent to customer client of customer a. And then the customer A sends a conversation message of ' i want to buy double-leather shoes ' through the customer client, and after the robot customer service confirms that the robot is not in a conversation suspension state and identifies the state, and confirms that the robot cannot process the information autonomously, the comfort response message ' kahou matched with the conversation message of ' i want to buy double-leather shoes ' is extracted. Wait a little to see your shoes. Meanwhile, the robot customer service may set a session state of the robot in a subsequent session service with the customer client of the customer a to a session suspended state, and simultaneously send the session message "i want to buy double leather shoes" to the customer service client to be processed by the manual customer service. Customer a replies to the session message "good, thank you".
It should be noted that, the manual customer service may not be in place, or because too many customers need to be serviced by the manual customer service cannot intervene in the process in time, after a while, customer a sends a session message "ask for a question" through the customer client? "is the robot service received the session message" asked? And after the message is detected to be in the session suspension state, identifying the content of the message, extracting and replying a corresponding soothing response message, namely 'slightly waiting, i still look like' and sending the message to the customer client of the customer A.
Then, a manual customer service intervenes, a conversation message "hello" is sent through a customer service client, and I feel that the following shoe is very suitable for you. http// www.tmall.com/", the robot customer service transmits the message sent by the artificial customer service to the customer client of the customer A without any processing, the customer A replies the session message of kay, good, i consider seeing after seeing the session message, and the artificial customer service replies the reply session message of kay, good after the customer service client receives the session message. You can just read you to contact me at any time ", and" thank you for you being on, 88 ".
According to the above processing flow, the session messages 31 and 32 are messages processed and responded by the robot, the session messages 33 and 34 are placating response messages generated by the robot customer service, and the session messages 35, 36 and 37 are session messages responded by the human customer service.
It will be appreciated that in particular implementations, the session messages 36 and 37 may also be automatically generated response messages for the robot service. For example, if the robot service does not receive the response message from the service client within a preset time after receiving the session message "kayeto, good, i consider to see" and can confirm that the manual intervention is finished, the session message of the service response may be identified. After identifying the content of the session message, in one embodiment of the invention, the "kay, ok" may be answered directly from the stored linguistic empirical data. You can just like to contact me at any time "and" thank you for you being on, 88 ". In another embodiment of the invention, after the content of the session message is identified, if the self-answering cannot be carried out according to the language experience data, the scene type corresponding to the session message is matched, and the matched answer message is extracted from the stored service resources. You can just like to contact me at any time "and" thank you for your light, 88 "and send them to the customer client of customer a in turn.
In order to enable those skilled in the art to better understand and implement the present invention, the embodiment of the present invention further provides a robot customer service capable of implementing the customer service method. Referring to fig. 4, a specific structure of a robot service in the embodiment of the present invention is described below.
As shown in fig. 4, the robot customer service 40 includes: a first message interaction unit 41, an identification unit 42, a capability judgment unit 43, a storage unit 44, a first response message generation unit 45, a state control unit 46, a second response message generation unit 47, and a second message interaction unit 48, wherein:
the first message interaction unit 41 is adapted to receive a session message from a customer client, and return a response message matched with the content of the session message, including a soothing response message when the state of the robot service in a subsequent session service with the customer client is a session suspension state.
An identifying unit 42 adapted to identify the content of the conversation message received by the first messaging interaction unit 41.
A capability judging unit 43, adapted to determine whether the session message can be processed autonomously according to the content of the session message identified by the identifying unit 42.
A storage unit 44 adapted to store service resources.
A first reply message generating unit 45 adapted to extract a reply message matching the content of the session message from the service resource stored in the storage unit 44 when the capability judging unit 43 determines that the session message can be processed.
A state control unit 46 adapted to control a state of the robot service in a subsequent session service with the customer client to be a session suspended state when the capability judgment unit 43 determines that the autonomous processing is impossible or the recognition unit 42 cannot recognize the session message.
A second response message generating unit 47, adapted to extract a soothing response message matching with the content of the session message from the service resource stored in the storage unit 44 when the state control unit 46 controls the state of the robot service in the subsequent session service with the customer client to be a session suspended state.
A second message interaction unit 48 adapted to send the session message from the customer client to the customer service client when the state of the robot service in the subsequent session service with the customer client is a session suspended state.
By adopting the scheme of the embodiment, the problem of the customer can be effectively solved in time through the cooperative work of the robot customer service automation and the manual customer service, the customer cannot feel the difference between the robot customer service and the manual customer service, the emotion in the process of waiting for response can be effectively soothed, and better interactive experience is obtained.
In a specific implementation, the service resources stored by the storage unit 44 may include: language experience data and customer service resource data.
In particular implementations, a message that characterizes the customer service as being in a state of looking for answers to questions may be taken as a soothing response message.
In particular implementations, the form of the session message may include any one or more of: sentences composed of natural language words, data links, voice, images and video.
In specific implementations, the image may be in various forms, for example, a static or dynamic picture with semantic information, or a photo or screenshot information of a product or service object targeted by a customer session, or a group or sequence of pictures formed by a combination of any two or more of the above forms.
In specific implementation, the robot service may be further expanded or optimized as needed, and referring to fig. 5, an embodiment of the present invention further provides another robot service. The same parts as those of the above embodiment will not be described again.
The difference from the robot service in the above embodiment is that, as shown in fig. 5, the robot service 50 may further include, in addition to the robot service 40: and the machine training unit 51 is suitable for performing big data machine training on the robot so as to identify the scene category to which the session message belongs, wherein the scene category is obtained by classifying and splitting the session message with the client according to the scene.
In a specific implementation, the capability determining unit 43 may include a first determining subunit 431 and a second determining subunit 432, where:
the first judging subunit 431 is adapted to determine whether the robot customer service can autonomously answer the content of the session message according to the language experience data;
the second judging subunit 432 is adapted to, when the first judging subunit 431 determines that the robot customer service cannot autonomously answer according to the language experience data, determine a scene type to which the content of the conversation message belongs.
In a specific implementation, the first reply message generating unit 45 may include a first generating sub-unit 451 and a second generating sub-unit 452, where:
the first generation subunit 451 is adapted to, when it is determined that the robot customer service can autonomously answer based on the language-experience data, extract an answer message matching the content of the conversation message from the language-experience data stored in the storage unit;
a second generating subunit 452, adapted to, when it is determined that the robot customer service cannot autonomously answer according to the language-experience data, extract, from the customer service resource data stored in the storage unit, a response message matching the content of the session message in the belonging scene.
In a specific implementation, as shown in fig. 5, the robot customer service 50 may further include: a state detection unit 52, adapted to detect the state of the robot service in the session service with the customer client when the first message interaction unit 41 receives the session message from the customer client, and trigger the identification unit to perform the operation of identifying the content of the session message when detecting that the state of the robot service in the session service with the customer client is not in the session suspended state.
By adopting the robot customer service in the embodiment of the invention, better cooperative work of the manual work and the robot customer service can be realized, on one hand, when the robot customer service is in a conversation suspension state, only the transmission of a conversation message is needed without any autonomous processing, the service resources of the robot customer service can be saved, on the other hand, the robot customer service can work only when the robot customer service is not in the conversation suspension state, so that the priority of the robot customer service is higher, the midway occupation of the conversation by the robot customer service can be avoided, the customer can obtain consistent service experience, and the user experience of the customer is improved.
In a specific implementation, to further improve the coordination degree between the robot customer service and the manual customer service and alleviate the anxiety of the customer during waiting, the identifying unit 42 is further adapted to identify the session message received by the first message interacting unit from the customer client when the robot customer service is in a session suspended state in the session service with the customer client and the second message interacting unit does not receive the session message from the customer client; the second response message generating unit 47 is further adapted to extract a soothing response message matching with the content of the session message from the service resource stored in the storage unit 44 according to the content of the session message identified by the identifying unit.
In a specific implementation, the state control unit 46 is further adapted to switch the state of the robot service in the subsequent session service with the customer client to a session suspended state and control the second message interaction unit to perform a message interaction operation when the robot service is in a session state in the session service with the customer client and the second message interaction unit receives the session message from the customer client. Through the control of the state control unit 46, the priority of the manual customer service is higher in the cooperative working process of the manual customer service and the robot customer service, and the manual customer service can actively intervene at any time according to needs, so that better service can be provided for customers.
In a specific implementation, as shown in fig. 5, the robot service 50 may further comprise an end-of-session detection unit 53 adapted to determine whether the session between the service client and the customer client is ended; accordingly, the state control unit 52 is further adapted to restore the state of the robot service in a subsequent session service with the customer client to a session state when it is determined that the session between the service client and the customer client is ended.
Through the cooperation of the session ending detection unit 53 and the state control unit 52, when the intervention of the manual customer service is completed, the state of the robot customer service can be automatically switched back, so that the seamless connection between the manual customer service and the robot customer service is realized, and the service experience of customers can be further optimized.
In a specific implementation, the session end detection unit 53 may include at least one of the following detection units:
a first detecting subunit 531 adapted to detect whether the second message interaction unit 48 is idle for a preset time duration, and determine that the session between the customer service client and the customer client is ended when the preset time duration is reached;
a second detection subunit 532, adapted to detect a session completion signal from the customer service client and to determine that the session between the customer service client and the customer client is ended when the session completion signal from the customer service client is detected.
The method comprises the steps that whether conversation information is transmitted between the customer service client and the customer client for a preset time length or not is determined, or when a conversation window is detected to be closed or when a conversation message sent by the customer service client contains content for displaying conversation completion, a conversation completion signal sent by the customer service client automatically identifies completion of manual customer service intervention, so that manual customer service operation can be reduced, workload of manual customer service is reduced, and convenience is brought to manual customer service.
In a specific implementation, the second message interacting unit 48 is further adapted to send a soothing response message corresponding to the session message that cannot be processed or identified by itself and the session message that cannot be processed or identified by itself to the customer service client, so that the artificial customer service can see the content of the response message replied by the robot customer service to the customer, which is convenient for maintaining consistency and consistency of the response, thereby optimizing consistent service experience and improving user experience of the customer.
In order to make the person skilled in the art better understand and implement the present invention, the following detailed description of the intelligent customer service system capable of implementing the customer service method is provided by specific embodiments.
Referring to fig. 6, the intelligent service system in the embodiment of the present invention may include: a customer client 61, a customer service client 62 adapted to have a session with said customer client 61, and a robotic service 63, said customer service client and said customer client communicating through said robotic service.
In implementations, the customer client and the customer service client may each be presented in a variety of forms. For example, the customer client and the customer service client may be built into a program in a browser and run automatically upon detecting that a browser page is opened. For another example, the client and the service client are independent application clients, are built in a desktop computer, a tablet computer, a mobile phone, and a vehicle-mounted terminal having a general computer function, and can be started and operated under the operation of the client. For another example, the customer client and the customer service client may also be built in a dedicated device customized for the customer by a product provider or a service provider, and the dedicated device may be used for the customer to consult and feedback with the product provider or the service provider during the sales exhibition or the service experience, so as to better meet the customer needs.
It is understood that the customer client and the customer service client performing the call may be implemented in the same or different manners, as long as the session can be implemented by using the same communication protocol.
Specific implementation manners such as specific structures and working principles of the customer client 61, the customer service client 62, and the robot customer service 63 can be referred to the descriptions in the above embodiments, and are not described herein again.
In a specific implementation, one robot service may simultaneously talk to a plurality of customer clients, and the robot service may also forward the received session message to different customer service clients. When a plurality of client sides and a plurality of service client sides are in a session state, when the robot service determines that the session message cannot be processed independently or identified, the session message of the client can be replied as soon as possible, and the session message from the client side and the corresponding appeasing response message can be sent to the service client side with the least task amount according to the task amount of the service client side in the session state. For example, the background has 10 manual customer services, which correspond to 10 different customer service clients, respectively, and the customer service robot may uniformly distribute the received session message to each customer service client according to the number of the customer clients corresponding to the session message processed by each current customer service client.
In a specific implementation, in order to enable a customer to obtain better consistent service and improve the service efficiency of each manual customer service, when a plurality of customer clients and customer service clients in a session state are provided, and the robot customer service determines that the session message cannot be processed autonomously or identified, the robot customer service may send the session message that cannot be processed or identified to the customer service client that has previously processed the session message of the customer client according to the session message record. In an embodiment of the present invention, the robot customer service may further send the soothing response message corresponding to the session message that cannot be processed or identified to the customer service client that has processed the session message of the customer client before, so as to avoid that the experience of the customer is affected by the fact that the manual customer service does not know the communication condition with the customer.
It can be understood that, according to needs, in the process of forwarding the message to the customer service client by the robot customer service, multiple allocation policies may be considered at the same time, each allocation policy may be configured with different priorities, and in a specific forwarding process, matching may be performed according to a priority order, which is not described in detail herein.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable storage medium, and the storage medium may include: ROM, RAM, magnetic or optical disks, and the like.
Although the present invention is disclosed above, the present invention is not limited thereto. Various changes and modifications may be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (10)
1. A robot customer service method, comprising:
when a conversation message from a customer client is received, identifying the content of the conversation message;
determining whether the session message can be processed autonomously according to the content of the session message;
when it is determined that the session message can be autonomously processed, extracting a response message matched with the content of the session message from the stored service resource and transmitting the response message to the customer client;
when determining that the session message cannot be autonomously processed or identified, setting the state of the client in the subsequent session service of the client as a session suspension state, extracting a placating response message matched with the content of the session message, sending the placating response message to the client, and sending the session message which cannot be autonomously processed or identified to a customer service client;
when the client is in a session state in the session service with the client and receives a session message from the customer service client, switching the session state of the client in the session service with the client to a session suspension state, and executing a transmission operation of the session message between the customer service client and the client;
the customer service client provides manual customer service, and in the process, the customer cannot feel the difference between the robot customer service and the manual customer service all the time.
2. The robotic customer service method of claim 1, wherein the service resources comprise: language experience data and customer service resource data; the determining whether the session message can be autonomously processed according to the content of the session message includes:
determining whether the content of the session message can autonomously reply according to the language experience data;
when determining that the answer cannot be made according to the language experience data autonomously, determining a scene category to which the content of the session message belongs;
and when determining that the answer can be made autonomously according to the language experience data or the scene category to which the content of the session message belongs exists, determining that the session message can be processed autonomously.
3. The robotic customer service method of claim 2, wherein extracting from the stored service resource a response message matching the content of the conversation message when it is determined that the conversation message can be handled autonomously comprises:
extracting a response message matched with the content of the conversation message from the stored language-experience data when it is determined that the response can be autonomously answered according to the language-experience data;
and when determining that the answer cannot be made according to the language experience data autonomously, extracting an answer message matched with the content of the conversation message in the scene from the stored customer service resource data.
4. The robotic customer service method of claim 1, further comprising: when receiving a session message from a customer client, if the state of the user in the session service with the customer client is determined to be a non-session suspension state, executing the operation of identifying the content of the session message.
5. The robotic customer service method of claim 1, further comprising:
and when the conversation service with the customer client is in a conversation suspension state and does not receive the conversation message from the customer service client, identifying the content of the conversation message, extracting a placating response message matched with the content of the conversation message and sending the placating response message to the customer client.
6. The robotic customer service method of claim 5, further comprising:
and when the session between the customer service client and the customer client is determined to be finished, restoring the state of the customer service client in the session service with the customer client to be a session state.
7. The robotic customer service method of claim 6, wherein the determining that the session between the customer service client and the customer client is over comprises at least one of:
determining that no session message is transmitted between the customer service client and the customer client for a preset duration;
a session completion signal from the customer service client is detected.
8. The robotic customer service method of claim 7, wherein the detecting a session completion signal from the customer service client comprises:
and sending the conversation completion signal when detecting that the customer service client closes the conversation window or detecting that the conversation message sent by the customer service client comprises the content for displaying the completion of the conversation.
9. The robotic customer service method of claim 1, further comprising: and sending the soothing response message corresponding to the session message which cannot be autonomously processed or identified and the session message which cannot be autonomously processed or identified to the customer service client.
10. A computer-readable storage medium, on which a program is stored, characterized in that the program, when executed, realizes the steps of the robot servicing method of any one of claims 1 to 9.
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| Publication number | Publication date |
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| CN105577529A (en) | 2016-05-11 |
| CN109194568B (en) | 2020-07-14 |
| CN109194568A (en) | 2019-01-11 |
| CN109245994A (en) | 2019-01-18 |
| CN105577529B (en) | 2019-03-05 |
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