CN110457578A

CN110457578A - A kind of customer service demand recognition methods and device

Info

Publication number: CN110457578A
Application number: CN201910626193.4A
Authority: CN
Inventors: 张稀昂
Original assignee: Alibaba Group Holding Ltd
Current assignee: Advanced Nova Technology Singapore Holdings Ltd
Priority date: 2019-07-11
Filing date: 2019-07-11
Publication date: 2019-11-15
Anticipated expiration: 2039-07-11
Also published as: CN110457578B

Abstract

This specification one or more embodiment provides a kind of customer service demand recognition methods and device, this method comprises: obtain target user using information, it wherein, should include: application operating behavioral data, application operating interface screenshot, using at least one of abnormality detection information using information；And identify whether the target user has customer service demand using information intelligent based on target user, when determining that target user needs customer service, automatically customer service is pushed for target user, in this way it is not necessary that customer service entrance is set to significant position, even if customer service entrance is set to than more covert position, it still is able to ensure that target user rapidly enters customer service module, so that it is guaranteed that target user enjoys corresponding customer service in time, so that the thorny problem for solving target user and being encountered is intervened by customer service in time, improve user experience.

Description

Customer service demand identification method and device

Technical Field

One or more of the descriptions relate to the technical field of intelligent identification, and in particular to a customer service demand identification method and device.

Background

At present, with the rapid development of internet technology and the increasing popularization of smart phones, smart phones have been integrated into various aspects of life, users will install corresponding application programs in smart phones according to their respective actual needs, and the application programs can provide business services such as shopping, financing, leasing and the like for the users. Specifically, by setting a customer service entrance at a designated position of the application page, after a user enters a customer service module through the customer service entrance, the user can interact with the online customer service in a problem description mode, so that the online customer service provides a corresponding solution for the user based on the problem described by the user.

Currently, the setting position of the customer service entry is difficult to decide, if the customer service entry is set at a more prominent position, such as the top or the side bar in the application, or one customer service entry is set in each application page, then a certain visible area will be occupied, and the influence on the operation of the user is more obvious under the condition that the visible area of the mobile terminal is small; correspondingly, if the customer service entrance is arranged at a hidden position, the difficulty of positioning the customer service entrance by the user is increased, and the user experience is reduced. Therefore, the problem that the user is not easy to find due to the fact that the customer service entrance is arranged at the position easy to find and occupies the visible area cannot be simultaneously considered, and the problem that the user is difficult to find due to the fact that the customer service entrance is arranged at the position too hidden.

Therefore, a solution is needed to prevent the customer service entrance from occupying the visible area, and ensure that the user can quickly enter the customer service module.

Disclosure of Invention

One or more embodiments of the present disclosure provide a method and an apparatus for identifying a customer service demand, which do not need to set a customer service entrance at a significant position, and even if the customer service entrance is set at a relatively hidden position, the target user can still be ensured to quickly enter a customer service module, so as to ensure that the target user can timely enjoy corresponding customer service, so as to timely solve a problem of inconvenience encountered by the target user through customer service intervention, and improve user experience.

To solve the above technical problem, one or more embodiments of the present specification are implemented as follows:

one or more embodiments of the present specification provide a customer service demand identification method, including:

acquiring application use information of a target user, wherein the application use information comprises: at least one of application operation behavior data, an application operation interface screenshot and application anomaly detection information;

performing key information identification on each application use information to obtain a target influence factor associated with customer service requirements;

determining the demand degree of the target user for the customer service according to the target influence factors;

and if the demand degree meets a preset condition, pushing a customer service entrance to the target user.

One or more embodiments of the present specification provide a customer service need identification apparatus, including:

an information obtaining module, configured to obtain application usage information of a target user, where the application usage information includes: at least one of application operation behavior data, an application operation interface screenshot and application anomaly detection information;

the information identification module is used for carrying out key information identification on the application use information to obtain target influence factors related to customer service requirements;

the customer service requirement determining module is used for determining the requirement degree of the target user for customer service according to the target influence factors;

and the customer service pushing module is used for pushing a customer service entrance to the target user if the requirement degree meets a preset condition.

One or more embodiments of the present specification provide a customer service need identification device, including: a processor; and

a memory arranged to store computer executable instructions that, when executed, cause the processor to:

One or more embodiments of the present specification provide a storage medium storing computer-executable instructions that, when executed, implement the following:

In one or more embodiments of the present specification, a method and an apparatus for identifying a customer service requirement acquire application use information of a target user, where the application use information includes: at least one of application operation behavior data, an application operation interface screenshot and application anomaly detection information; whether the target user has customer service requirements or not is intelligently identified based on application use information of the target user, and when the target user needs the customer service is determined, the customer service is automatically pushed to the target user, so that a customer service inlet does not need to be arranged at a remarkable position, and even if the customer service inlet is arranged at a more concealed position, the target user can still be ensured to quickly enter a customer service module, so that the target user is ensured to timely enjoy corresponding customer service, the problem of difficulty met by the target user is timely solved through customer service intervention, and the user use experience is improved.

Drawings

In order to more clearly illustrate one or more embodiments or prior art solutions of the present specification, the drawings that are needed in the description of the embodiments or prior art will be briefly described below, it is obvious that the drawings in the following description are only some of the embodiments described in one or more of the specification, and that other drawings can be obtained by those skilled in the art without inventive exercise.

FIG. 1 is a schematic diagram of an application scenario of a customer service requirement identification system provided in one or more embodiments of the present disclosure;

FIG. 2 is a first flowchart of a method for identifying customer service requirements according to one or more embodiments of the present disclosure;

FIG. 3 is a second flowchart of a customer service requirement identification method provided in one or more embodiments of the present disclosure;

FIG. 4 is a third flowchart of a customer service requirement identification method provided in one or more embodiments of the present disclosure;

FIG. 5 is a schematic diagram illustrating an implementation principle of a customer service requirement identification method according to one or more embodiments of the present disclosure;

FIG. 6 is a schematic diagram illustrating a first module of an apparatus for identifying customer service requirements according to one or more embodiments of the present disclosure;

FIG. 7 is a schematic diagram illustrating a second module of an apparatus for identifying customer service requirements according to one or more embodiments of the present disclosure;

fig. 8 is a schematic structural diagram of a customer service requirement identification device according to one or more embodiments of the present disclosure.

Detailed Description

In order to make the technical solutions in one or more embodiments of the present disclosure better understood, the technical solutions in one or more embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in one or more embodiments of the present disclosure, and it is obvious that the described embodiments are only a part of one or more embodiments of the present disclosure, but not all embodiments. All other embodiments that can be derived by one of ordinary skill in the art from the embodiments in one or more of the specification without inventive faculty are intended to fall within the scope of one or more of the specification.

One or more embodiments of the present disclosure provide a method and an apparatus for identifying a customer service demand, which do not need to set a customer service entrance at a significant position, and even if the customer service entrance is set at a relatively hidden position, a target user can still be ensured to quickly enter a customer service module, so as to ensure that the target user can timely enjoy corresponding customer service, so as to timely solve a problem of inconvenience encountered by the target user through customer service intervention, and improve user experience.

Fig. 1 is a schematic view of an application scenario of a customer service demand identification system according to one or more embodiments of the present disclosure, as shown in fig. 1, the system includes: the system comprises a user terminal, a background server and a customer service terminal, wherein the user terminal can be a mobile terminal such as a smart phone and a tablet personal computer, the background server can be a server for responding to a service request of the user terminal, and the customer service terminal can be a terminal device for providing customer service for the user terminal, wherein an execution main body of a process of customer service demand identification can be the user terminal, and can also be the background server, and specifically, the specific process of the customer service demand identification is as follows:

(1) acquiring application use information of a target user, wherein the application use information comprises: application operation behavior data, an application operation interface screenshot and application anomaly detection information;

specifically, the user terminal monitors an operation request of a target user in real time, generates application operation behavior data or an application operation interface screenshot corresponding to the operation request, monitors a request response condition of an application program in real time, and generates corresponding application anomaly detection information, wherein the user terminal can upload application use information to a background server, and the background server receives the application use information uploaded by the user terminal;

(2) performing key information identification on the obtained application use information to obtain a target influence factor associated with the customer service demand;

specifically, after application use information of a target user is acquired, key influence information associated with customer service requirements is extracted from the application use information;

(3) determining the demand degree of a target user for the customer service according to the determined target influence factors, namely identifying the customer service demand of the target user based on the determined target influence factors, and judging whether the target user has the service demand of customer service intervention;

(4) when the target user is determined to have the customer service requirement, automatically pushing a customer service entrance to the target user; when detecting that a target user requests to enter a customer service module through the customer service entrance, the user terminal sends a customer service request to the background server, so that the background server distributes the customer service request to the corresponding customer service terminal, and the customer service terminal provides customer service for the target user;

specifically, in a case that an execution subject of the process of customer service demand identification is a background server, the pushing of the customer service entrance to the target user specifically includes: the method comprises the steps that when a background server determines that a target user has a customer service requirement, pushing indication information is sent to a corresponding user terminal to trigger the user terminal to push a customer service entrance to the target user;

therefore, whether the target user has a customer service requirement is intelligently identified based on the application use information of the target user, when the target user needs the customer service is determined, the customer service is automatically pushed to the target user, a customer service inlet does not need to be arranged at a remarkable position, even if the customer service inlet is arranged at a hidden position, the target user can still be ensured to quickly enter a customer service module, so that the target user can timely enjoy the corresponding customer service, the problem of the target user in trouble can be timely solved through customer service intervention, the user use experience is improved, in addition, a mode of pushing the customer service inlet to the user according to needs is adopted, and the customer service module does not need to be arranged on a plurality of pages in the application.

Fig. 2 is a first flowchart of a customer service demand identification method provided in one or more embodiments of the present specification, where the method in fig. 2 may be executed by the user terminal in fig. 1, or may be executed by the background server in fig. 1, as shown in fig. 2, the method at least includes the following steps:

s201, obtaining application use information of a target user, wherein the application use information comprises: at least one of application operation behavior data, an application operation interface screenshot and application anomaly detection information;

specifically, the application operation behavior data may include: the application operation interface screenshot may be image information generated by executing screenshot operation on an application operation page, and the application anomaly detection information includes: detecting logs of conventional applications and application logs of key service nodes;

s202, performing key information identification on the obtained application use information to obtain target influence factors associated with customer service requirements;

specifically, from the obtained application use information, key information representing that the user has a customer service demand is identified, and the identified key information is determined as a target influence factor associated with the customer service demand, where the target influence factor may include: at least one of search frequency of query keywords representing customer service demands, viewing frequency of explanatory pages representing customer service demands, repeated sliding frequency of the same application operation page, switch switching frequency of the same application operation page, content error reporting information belonging to a content error reporting category library and abnormal response results belonging to an abnormal response category library;

in addition, the application use information may further include: the face image information of the target user is subjected to key information identification to obtain target influence factors associated with customer service requirements;

s203, determining the demand degree of the target user for the customer service according to the determined target influence factors, wherein the demand degree can be a numerical value used for representing the customer service demand degree of the target user;

specifically, after a plurality of target influence factors associated with the customer service demand are determined, the customer service demand is scored by combining the plurality of target influence factors to obtain a corresponding scoring result, and the higher the obtained scoring value aiming at the customer service demand, the higher the current demand degree of the customer service of the user is;

s204, judging whether the determined demand degree for the customer service meets a preset condition or not; the preset condition can be that the requirement degree is greater than a preset threshold value aiming at the condition that the requirement degree is a specific requirement degree numerical value, namely when the determined customer service requirement degree is greater than the preset threshold value, the requirement degree aiming at the customer service is determined to meet the preset condition;

if the determination result is negative, continuing to execute the steps S201 to S204, that is, continuing to determine whether the target user has a customer service requirement;

if the result is yes, S205 is executed to push the customer service entrance to the target user, specifically, a customer service entrance icon may be displayed on the user terminal, a customer service entrance prompt window may also be popped up, or a user may directly jump to a customer service interface, so as to achieve the purpose of guiding the user to quickly enter the customer service function.

In one or more embodiments of the present specification, application usage information of a target user is obtained, where the application usage information includes: at least one of application operation behavior data, an application operation interface screenshot and application anomaly detection information; whether the target user has customer service requirements or not is intelligently identified based on application use information of the target user, and when the target user needs the customer service is determined, the customer service is automatically pushed to the target user, so that a customer service inlet does not need to be arranged at a remarkable position, and even if the customer service inlet is arranged at a more concealed position, the target user can still be ensured to quickly enter a customer service module, so that the target user is ensured to timely enjoy corresponding customer service, the problem of difficulty met by the target user is timely solved through customer service intervention, and the user use experience is improved.

Further, considering that in order to let the customer service know and locate the consultation problem encountered by the user, the user needs to describe the problem to the customer service in detail, the time consumed for the user to preorder the background is relatively long, and in order to improve the efficiency of the customer service in processing the user problem, as shown in fig. 3, the method for identifying the customer service requirement further includes:

s206, generating problem description data of the target user according to the determined target influence factors, wherein the problem description data is a bedding summary of problems to be solved by the target user;

s207, sending the generated problem description data to a customer service terminal so that the customer service terminal determines a solution required to be provided for a target user based on the problem description data;

specifically, the executing main body of the process of generating the problem description data may be a background server, or may be a user terminal, and for a case where the executing main body is the user terminal, the sending the generated problem description data to the customer service terminal specifically includes: uploading the generated problem description data to a background server, and sending the problem description data to a corresponding customer service terminal by the background server;

in addition, in order to further improve the efficiency of the customer service staff in positioning the problems encountered by the user, the background server can also perform preset problem database matching based on all items of information in the problem description data, determine the matching degree between the problem description data and all preset consultation problems in the preset problem database, determine the preset consultation problems with the matching degree larger than a preset threshold value as target consultation problems based on the problem matching result, and send the target consultation problems to the corresponding customer service terminals, so that the customer service terminals show the target consultation problems to the customer service staff.

After a plurality of target influence factors associated with customer service requirements are determined, customer service requirement degree identification is carried out based on the target influence factors, problem description data are generated based on the target influence factors and are sent to corresponding customer service terminals, so that the customer service terminals can quickly know key points of problems encountered by target users, corresponding solutions are quickly given, links of problem statement of the target users to the customer services are omitted, and the processing efficiency of the customer services on user problems is improved;

in one or more embodiments of the present disclosure, when the target user is intelligently identified to have a customer service requirement based on the application usage information, the problem description data of the target user is automatically generated and sent to the corresponding customer service terminal, so that the customer service terminal can quickly know and locate the problem encountered by the target user, and thus, the target user does not need to introduce the preorder problem description to the customer service after entering the customer service module, thereby reducing preorder redundant information communication, so that the customer service can quickly provide a corresponding solution for the target user, improving the efficiency of the customer service in solving the problem of the user, and improving the accuracy of the solution.

In the process of determining the degree of demand for the customer service, as shown in fig. 4, in step S203, determining the degree of demand of the target user for the customer service according to the determined target influence factor specifically includes:

s2031, the pre-trained customer service demand degree recognition model is used, and the demand degree of the target user for the customer service is determined based on the determined target influence factors.

Specifically, the customer service demand recognition model is obtained by training in the following way, and specifically includes:

obtaining a model training sample set, wherein the model training sample set comprises a plurality of model training samples, and each model training sample represents the corresponding relation between a sample influence factor and the customer service demand degree;

and training to obtain a customer service demand recognition model by adopting a deep learning method and based on the model training sample set.

Specifically, the demand level helper for the customer service is S (T, W, R), where S represents a customer service demand level identification model, T represents a target influence factor determined based on the application operation behavior data, W represents a target influence factor determined based on the application operation interface screenshot, and R represents a target influence factor determined based on the application abnormality detection information;

in specific implementation, taking the customer service demand recognition model as a linear regression model as an example, the calculation formula of the customer service demand degree is as follows:wherein HelpDegree represents the customer service demand degree, A_iWeight coefficient, x, representing the ith target influencing factor_iIndicates the ith kind of target influencing factor, and n indicates the number of kinds of target influencing factors.

The application use information is introduced in the process of determining the target influence factor, and the application use information may be any one or a combination of application operation behavior data, an application operation interface screenshot and application anomaly detection information, and the following describes in detail the process of determining the target influence factor for each item of application use information, specifically:

the first type of information identifies an analysis process, and the information for application use comprises: the case of application operational behavior data; correspondingly, the step S202 of performing key information identification on the obtained application use information to obtain a target influence factor associated with the customer service demand specifically includes at least one of the following steps:

determining the search frequency of a target user for query keywords representing customer service requirements based on the acquired application operation behavior data;

specifically, by analyzing behavior data related to keyword query in the application operation behavior data, query keywords representing customer service requirements input by a target user are extracted, and the search frequency of each query keyword representing customer service requirements is determined; for example, in a preset time period, the search frequency of the keywords such as customer service keywords, help keywords, application keywords, etc. input by the user is set;

determining the viewing frequency of a target user on an explanatory page representing customer service requirements based on the acquired application operation behavior data;

specifically, by analyzing behavior data related to information page viewing in the application operation behavior data, viewing behavior data of an explanatory page representing customer service requirements is extracted, and the viewing frequency of each explanatory page representing customer service requirements is determined; for example, the viewing frequency of the application description and the help page by the user within a preset time period;

determining the repeated sliding frequency of the target user to the same application operation page based on the acquired application operation behavior data;

specifically, the repeated sliding frequency of the same application operation page in a preset time period is determined by analyzing behavior data related to operation page viewing in the application operation behavior data;

determining the switching frequency of a target user to the same application operation page based on the acquired application operation behavior data;

specifically, the switching frequency of the same application operation page within a preset time period is determined by analyzing behavior data related to the operation page switching operation in the application operation behavior data.

Therefore, the target influence factors determined based on the application operation behavior data include: the search frequency of the query key words representing the customer service demands, the viewing frequency of the explanatory page representing the customer service demands, the repeated sliding frequency of the same application operation page and the switch switching frequency of the same application operation page.

The second type of information identification analysis process comprises the following steps aiming at application use information: the condition of screenshot of an application operation interface; correspondingly, the step S202 of performing key information identification on the obtained application use information to obtain a target influence factor associated with the customer service demand specifically includes:

carrying out image recognition processing on the acquired application operation interface screenshot, and extracting content error reporting information belonging to a content error reporting category library;

and determining the extracted content error reporting information as a target influence factor associated with the customer service requirement.

Specifically, considering that the user captures the operation interface, the possibility that the user needs to perform abnormal consultation exists, so that the user can recognize error reporting information by capturing the application operation interface screenshot, and the recognition result of the error reporting information is used as one of the influence factors for determining the customer service requirement degree, for example, in the application operation interface screenshot, error reporting information such as form errors, failure identifications and error feedback is extracted as a target influence factor;

therefore, the target influence factors determined based on the screenshot of the application operation interface include: and reporting error information of the content identified from the interface screenshot.

A third type of information recognition analysis process, for application usage information, comprising: a case where abnormality detection information is applied; correspondingly, the step S202 of performing key information identification on the obtained application use information to obtain a target influence factor associated with the customer service demand specifically includes:

performing abnormal response identification on the obtained application abnormal detection information, and determining an abnormal response result belonging to an abnormal response category library;

and determining the determined abnormal response result as a target influence factor associated with the customer service requirement.

Specifically, considering that when the application responds to the user operation request abnormally, the possibility that the user needs to perform abnormal consultation exists, the identification result of the abnormal response can be used as one of the influence factors for determining the customer service requirement degree by performing abnormal response identification on the application abnormal detection information, for example, based on the application abnormal detection information, the abnormal response results such as page loading failure, application response crash, page response timeout and the like are identified as target influence factors;

thus, the target influencing factors determined based on the application abnormality detection information include: an anomalous response result is identified based on the application anomaly detection information.

Further, after determining the target influence factor based on the recognition analysis result of the application use information, the problem description data of the target user may be determined based on the target influence factor, where the determined target influence factor is different and the corresponding problem description data is also different due to different types of the application use information, where the application use information may be any one or a combination of application operation behavior data, an application operation interface screenshot, and application abnormality detection information, and the following respectively describes in detail a process of generating the problem description data based on the target influence factor determined for each application use information, specifically:

the process of determining the problem description based on the identification and analysis result of the first type of information comprises the following steps aiming at the application use information: the case of application operational behavior data; correspondingly, in the step S206, according to the determined target influence factor, generating the problem description data of the target user, specifically including at least one of the following:

determining query keywords representing customer service requirements searched by a target user according to the determined target influence factors;

specifically, when the target influence factor is the search frequency of the target user on the query keyword representing the customer service demand, the query keyword representing the customer service demand is used as a part of the problem description data of the target user;

determining an explanation keyword in an explanatory page representing customer service requirements viewed by a target user according to the determined target influence factors;

specifically, when the target influence factor is the viewing frequency of the target user on the explanatory page representing the customer service demand, the explanation keyword in the explanatory page representing the customer service demand is used as a part of the problem description data of the target user;

determining keywords in the application operation page with the repeated sliding frequency greater than a preset sliding frequency threshold according to the determined target influence factors;

specifically, when the target influence factor is the repeated sliding frequency of the target user on the same application operation page, the keyword in the application operation page with the repeated sliding frequency greater than a preset sliding frequency threshold value is used as a part of the problem description data of the target user;

and determining keywords in the application operation page with the switching frequency larger than a preset switching frequency threshold according to the determined target influence factors.

Specifically, when the target influence factor is the switching frequency of the target user to the same application operation page, the keyword in the application operation page with the switching frequency greater than the preset switching frequency threshold is used as a part of the problem description data of the target user;

thus, the generated problem description data includes: at least one of query keywords representing customer service requirements searched by the target user, explanation keywords in a checked explanatory page representing customer service requirements, keywords in an application operation page with a repeated sliding frequency greater than a preset sliding frequency threshold value, and keywords in an application operation page with a switch switching frequency greater than a preset switching frequency threshold value.

And performing problem description determination based on the identification and analysis result of the second type of information, wherein the application use information comprises: the condition of screenshot of an application operation interface; correspondingly, the step S206 generates the problem description data of the target user according to the determined target influence factor, and specifically includes:

and determining the target influence factors belonging to the content error report category library and the application operation interface screenshots corresponding to the target influence factors as problem description data of the target user.

Specifically, when the target influence factor is the content error reporting information extracted from the interface screenshot, the corresponding interface screenshot and the extracted content error reporting information are used as a part of the problem description data of the target user;

for example, the extracted error information such as form error, failure flag, error feedback, etc. is used as a part of the question description data of the target user.

And performing problem description determination based on the identification and analysis result of the third type of information, wherein the application use information comprises: a case where abnormality detection information is applied; correspondingly, the step S206 generates the problem description data of the target user according to the determined target influence factor, and specifically includes:

determining target influence factors belonging to the abnormal response category library as problem description data of a target user;

specifically, when the target influence factor is an abnormal response result identified from the detection information, the abnormal response result is taken as a part of the question description data of the target user;

for example, the identified abnormal response results such as page loading failure, application response crash, page response timeout and the like are used as a part of the problem description data of the target user;

in addition, the current operation page of the target user can be determined as a part of the problem description data of the target user, namely, the link or the identification information of the page operated when the target user enters the customer service module is sent to the customer service terminal.

In a specific embodiment, the application use information includes: the conditions of three types of information, namely application operation behavior data, an application operation interface screenshot and application anomaly detection information; based on this, as shown in fig. 5, a specific implementation principle schematic diagram of the customer service demand identification method is provided, and the specific process is as follows:

acquiring application operation behavior data, an application operation interface screenshot and application anomaly detection information of a target user, wherein the application operation behavior data comprises the following steps: at least one of keyword query data, page click behavior data, page sliding behavior data and page switching behavior data;

performing key information identification on the acquired application operation behavior data to obtain a first target influence factor associated with the customer service demand, wherein the first target influence factor comprises: at least one of search frequency of query keywords representing customer service requirements, viewing frequency of an explanatory page representing customer service requirements, repeated sliding frequency of the same application operation page and switch switching frequency of the same application operation page;

performing key information identification on the acquired application operation interface screenshot to obtain a second target influence factor associated with the customer service requirement, wherein the second target influence factor comprises: error information of the content identified from the interface screenshot;

performing key information identification on the obtained application anomaly detection information to obtain a third target influence factor associated with the customer service demand, wherein the third target influence factor comprises: an abnormal response result identified based on the application abnormality detection information;

inputting the first target influence factor, the second target influence factor and the third target influence factor into a pre-trained customer service demand recognition model; determining the output result of the customer service demand recognition model as the customer service demand of the target user;

generating problem description data of the target user based on the first target influence factor, the second target influence factor and the third target influence factor;

if the customer service demand degree is larger than a preset threshold value, pushing a customer service entrance to a target user;

furthermore, when the customer service demand degree is greater than a preset threshold value, a customer service entrance is pushed to a target user, and problem description data of the target user is also sent to a customer service terminal distributed to the target user, so that a customer service worker corresponding to the customer service terminal can sense the current problems of the user in advance, the target user does not need to perform long-time problem description after entering a customer service module, and the processing efficiency of the customer service on the user problems is improved; in addition, in order to reduce the workload of the customer service staff, after detecting the trigger operation of the target user to the pushed customer service entrance, the generated problem description data can be sent to the corresponding customer service terminal, that is, only after detecting that the target user clicks the customer service entrance, the problem description data of the target user is sent to the customer service terminal allocated to the target user.

In one or more embodiments of the present specification, a method for identifying a customer service requirement acquires application usage information of a target user, where the application usage information includes: at least one of application operation behavior data, an application operation interface screenshot and application anomaly detection information; whether the target user has customer service requirements or not is intelligently identified based on application use information of the target user, and when the target user needs the customer service is determined, the customer service is automatically pushed to the target user, so that a customer service inlet does not need to be arranged at a remarkable position, and even if the customer service inlet is arranged at a more concealed position, the target user can still be ensured to quickly enter a customer service module, so that the target user is ensured to timely enjoy corresponding customer service, the problem of difficulty met by the target user is timely solved through customer service intervention, and the user use experience is improved.

On the basis of the same technical concept, corresponding to the customer service demand identification method described in fig. 2 to 5, one or more embodiments of the present specification further provide a customer service demand identification device, and fig. 6 is a schematic diagram of a first module composition of the customer service demand identification device provided in one or more embodiments of the present specification, where the device is configured to execute the customer service demand identification method described in fig. 2 to 5, and as shown in fig. 6, the device includes:

an information obtaining module 601, configured to obtain application usage information of a target user, where the application usage information includes: at least one of application operation behavior data, an application operation interface screenshot and application anomaly detection information;

an information identification module 602, configured to perform key information identification on each piece of application usage information to obtain a target influence factor associated with a customer service demand;

a customer service requirement determining module 603, configured to determine, according to the target influence factor, a requirement degree of the target user for a customer service;

and a customer service pushing module 604, configured to push a customer service entry to the target user if the requirement level meets a preset condition.

Optionally, as shown in fig. 7, the apparatus further includes:

a question description generation module 605, configured to generate question description data of the target user according to the target influence factor;

a problem description sending module 606, configured to send the problem description data to a customer service terminal, so that the customer service terminal determines, based on the problem description data, a solution that needs to be provided for the target user.

Optionally, the customer service requirement determining module 603 is specifically configured to:

and determining the demand degree of the target user for the customer service based on each target influence factor by utilizing a pre-trained customer service demand degree identification model.

Optionally, the application usage information includes: application operation behavior data;

the information identifying module 602 is specifically configured to execute at least one of the following:

determining the search frequency of the target user for query keywords representing customer service requirements based on the application operation behavior data; or,

determining the viewing frequency of the target user on an explanatory page representing customer service requirements based on the application operation behavior data; or,

determining the repeated sliding frequency of the target user to the same application operation page based on the application operation behavior data; or,

and determining the switching frequency of the target user to the same application operation page based on the application operation behavior data.

Optionally, the application usage information includes: screenshot of an application operation interface;

the information identifying module 602 is further specifically configured to:

carrying out image recognition processing on the application operation interface screenshot, and extracting content error reporting information belonging to a content error reporting category library;

and determining the content error reporting information as a target influence factor associated with the customer service requirement.

Optionally, the application usage information includes: applying anomaly detection information;

the information identifying module 602 is further specifically configured to:

carrying out abnormal response identification on the application abnormal detection information, and determining an abnormal response result belonging to an abnormal response category library;

and determining the abnormal response result as a target influence factor associated with the customer service requirement.

the problem description generating module 605 is specifically configured to execute at least one of the following:

determining query keywords representing customer service requirements searched by the target user according to the target influence factors; or,

determining an explanation keyword in an explanatory page representing customer service requirements viewed by the target user according to the target influence factors; or,

determining keywords in the application operation page with the repeated sliding frequency greater than a preset sliding frequency threshold according to the target influence factors; or,

and determining keywords in the application operation page with the switching frequency greater than a preset switching frequency threshold according to the target influence factors.

the problem description generating module 605 is further specifically configured to:

and determining the screenshot of the application operation interface and the target influence factor belonging to the content error reporting category library as the problem description data of the target user.

and determining the target influence factors belonging to the abnormal response category library as the problem description data of the target user.

In one or more embodiments of the present specification, a customer service requirement identification device obtains application usage information of a target user, where the application usage information includes: at least one of application operation behavior data, an application operation interface screenshot and application anomaly detection information; whether the target user has customer service requirements or not is intelligently identified based on application use information of the target user, and when the target user needs the customer service is determined, the customer service is automatically pushed to the target user, so that a customer service inlet does not need to be arranged at a remarkable position, and even if the customer service inlet is arranged at a more concealed position, the target user can still be ensured to quickly enter a customer service module, so that the target user is ensured to timely enjoy corresponding customer service, the problem of difficulty met by the target user is timely solved through customer service intervention, and the user use experience is improved.

It should be noted that the embodiment of the customer service requirement identification apparatus in this specification and the embodiment of the customer service requirement identification method in this specification are based on the same inventive concept, and therefore, for specific implementation of this embodiment, reference may be made to implementation of the customer service requirement identification method corresponding to the foregoing description, and repeated details are not described again.

Further, corresponding to the methods shown in fig. 2 to fig. 5, based on the same technical concept, one or more embodiments of the present specification further provide a customer service requirement identification device, which is configured to execute the customer service requirement identification method, as shown in fig. 8.

The customer service need identification device may have a large difference due to different configurations or performances, and may include one or more processors 801 and a memory 802, and one or more stored applications or data may be stored in the memory 802. Wherein the memory 802 may be a transient storage or a persistent storage. The application program stored in memory 802 may include one or more modules (not shown), each of which may include a series of computer-executable instructions for identifying a need for customer service in a device. Still further, the processor 801 may be configured to communicate with the memory 802 to execute a series of computer-executable instructions in the memory 802 on the customer service need identification device. The customer service need identification apparatus may also include one or more power supplies 803, one or more wired or wireless network interfaces 804, one or more input-output interfaces 805, one or more keyboards 806, and the like.

In one particular embodiment, the customer service need identification apparatus comprises a memory, and one or more programs, wherein the one or more programs are stored in the memory, and the one or more programs may comprise one or more modules, and each module may comprise a series of computer-executable instructions for the customer service need identification apparatus, and the one or more programs configured for execution by the one or more processors comprise computer-executable instructions for:

Optionally, the computer executable instructions, when executed, further comprise computer executable instructions for:

generating problem description data of the target user according to the target influence factors;

and sending the problem description data to a customer service terminal so that the customer service terminal determines a solution required to be provided for the target user based on the problem description data.

Optionally, when executed, the determining the degree of demand of the target user for the customer service according to the target influence factor includes:

Optionally, the application usage information comprises, when executed, computer executable instructions for: application operation behavior data;

the key information identification is carried out on each application use information to obtain a target influence factor associated with customer service requirements, and the target influence factor comprises at least one of the following items:

Optionally, the application usage information comprises, when executed, computer executable instructions for: screenshot of an application operation interface;

the key information identification is carried out on each application use information to obtain a target influence factor associated with customer service requirements, and the method comprises the following steps:

Optionally, the application usage information comprises, when executed, computer executable instructions for: applying anomaly detection information;

generating problem description data of the target user according to the target influence factors, wherein the problem description data comprises at least one of the following items:

generating the problem description data of the target user according to the target influence factors comprises the following steps:

It should be noted that the embodiment of the customer service requirement identification device in this specification and the embodiment of the customer service requirement identification method in this specification are based on the same inventive concept, and therefore, specific implementation of this embodiment may refer to implementation of the customer service requirement identification method corresponding to the foregoing description, and repeated details are not repeated.

Further, based on the same technical concept, corresponding to the methods shown in fig. 2 to fig. 5, one or more embodiments of the present specification further provide a storage medium for storing computer-executable instructions, where in a specific embodiment, the storage medium may be a usb disk, an optical disk, a hard disk, and the like, and the storage medium stores computer-executable instructions that, when executed by a processor, implement the following processes:

Optionally, the storage medium stores computer executable instructions that, when executed by the processor, further implement the following process:

Optionally, the computer-executable instructions stored in the storage medium, when executed by the processor, determine a degree of demand of the target user for the customer service based on the target influencing factor, including:

Optionally, the storage medium stores computer-executable instructions that, when executed by the processor, the application usage information includes: application operation behavior data;

Optionally, the storage medium stores computer-executable instructions that, when executed by the processor, the application usage information includes: screenshot of an application operation interface;

Optionally, the storage medium stores computer-executable instructions that, when executed by the processor, the application usage information includes: applying anomaly detection information;

The storage medium in one or more embodiments of the present specification stores computer-executable instructions that, when executed by the processor, obtain application usage information for a target user, wherein the application usage information includes: at least one of application operation behavior data, an application operation interface screenshot and application anomaly detection information; whether the target user has customer service requirements or not is intelligently identified based on application use information of the target user, and when the target user needs the customer service is determined, the customer service is automatically pushed to the target user, so that a customer service inlet does not need to be arranged at a remarkable position, and even if the customer service inlet is arranged at a more concealed position, the target user can still be ensured to quickly enter a customer service module, so that the target user is ensured to timely enjoy corresponding customer service, the problem of difficulty met by the target user is timely solved through customer service intervention, and the user use experience is improved.

It should be noted that the embodiment of the storage medium in this specification and the embodiment of the method for identifying a customer service requirement in this specification are based on the same inventive concept, so that specific implementation of this embodiment may refer to implementation of the method for identifying a customer service requirement, and repeated details are not described herein.

In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD), such as a Field Programmable Gate Array (FPGA), is an integrated circuit whose Logic functions are determined by programming the Device by a user. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Language Description Language), traffic, pl (core unified Programming Language), Cal, jhdware Description Language, langua, mylar, pams, Hardware (Hardware Description Language), langva, Lola, HDL, palmware, Hardware (Hardware Description Language), VHDL (Hardware Description Language), and the like, which are currently used in the most popular languages. It will also be apparent to those skilled in the art that hardware circuitry that implements the logical method flows can be readily obtained by merely slightly programming the method flows into an integrated circuit using the hardware description languages described above.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the various elements may be implemented in the same one or more software and/or hardware implementations of one or more of the present descriptions.

As will be appreciated by one skilled in the art, one or more embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, one or more of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, one or more of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied in the medium.

One or more of the present specification has been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to one or more embodiments of the specification. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

One or more of the present specification can be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. One or more of the present specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The above description is merely illustrative of one or more embodiments of the present disclosure and is not intended to limit one or more embodiments of the present disclosure. Various modifications and alterations to one or more of the present descriptions will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement or the like made within the spirit and principle of one or more of the present specification should be included in the scope of one or more claims of the present specification.

Claims

1. A customer service demand identification method comprises the following steps:

2. The method of claim 1, further comprising:

3. The method of claim 1, wherein said determining a level of demand of the target user for customer service based on the target impact factor comprises:

4. The method of claim 1, wherein the application usage information comprises: application operation behavior data;

5. The method of claim 1, wherein the application usage information comprises: screenshot of an application operation interface;

6. The method of claim 1, wherein the application usage information comprises: applying anomaly detection information;

7. The method of claim 2, wherein the application usage information comprises: application operation behavior data;

8. The method of claim 2, wherein the application usage information comprises: screenshot of an application operation interface;

9. The method of claim 2, wherein the application usage information comprises: applying anomaly detection information;

10. A customer service need identification device comprising:

11. The apparatus of claim 10, further comprising:

the problem description generation module is used for generating the problem description data of the target user according to the target influence factors;

and the problem description sending module is used for sending the problem description data to a customer service terminal so that the customer service terminal determines a solution required to be provided for the target user based on the problem description data.

12. The apparatus of claim 10, wherein the customer service need determination module is specifically configured to:

13. The apparatus of claim 10, wherein the application usage information comprises: application operation behavior data;

the information identification module is specifically configured to perform at least one of the following:

14. The apparatus of claim 10, wherein the application usage information comprises: screenshot of an application operation interface;

the information identification module is further specifically configured to:

15. The apparatus of claim 10, wherein the application usage information comprises: applying anomaly detection information;

the information identification module is further specifically configured to:

16. The apparatus of claim 11, wherein the application usage information comprises: application operation behavior data;

the problem description generation module is specifically configured to perform at least one of the following:

17. The apparatus of claim 11, wherein the application usage information comprises: screenshot of an application operation interface;

the problem description generation module is further specifically configured to:

18. The apparatus of claim 11, wherein the application usage information comprises: applying anomaly detection information;

19. A customer service need identification device, comprising:

a processor; and

20. A storage medium storing computer-executable instructions that, when executed, implement the following: