CN110457578B

CN110457578B - Customer service demand identification method and device

Info

Publication number: CN110457578B
Application number: CN201910626193.4A
Authority: CN
Inventors: 张稀昂
Original assignee: Advanced New Technologies Co Ltd
Current assignee: Advanced Nova Technology Singapore Holdings Ltd
Priority date: 2019-07-11
Filing date: 2019-07-11
Publication date: 2023-07-18
Anticipated expiration: 2039-07-11
Also published as: CN110457578A

Abstract

One or more embodiments of the present disclosure provide a customer service requirement identifying method and apparatus, where the method includes: acquiring application use information of a target user, wherein the application use information comprises: at least one of application operation behavior data, application operation interface screenshot and application abnormality detection information; and based on application use information of the target user, whether the target user has customer service requirements is intelligently identified, and customer service is automatically pushed to the target user when the target user needs the customer service, so that the customer service inlet is not required 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 the customer service module, thereby ensuring that the target user can timely enjoy corresponding customer service, so that the problem encountered by the target user is solved through customer service intervention in time, and the user use experience is improved.

Description

Customer service demand identification method and device

Technical Field

One or more of the present disclosure relates to the technical field of intelligent recognition, and in particular, to a customer service requirement recognition method and device.

Background

At present, with the rapid development of internet technology and the increasing popularization of smart phones, users will install corresponding application programs in the smart phones according to respective actual demands, and the application programs can provide business services such as shopping, financial accounting, leasing and the like for the users, however, various problems are often encountered in the application and use process, so that online customer service is required to be provided for the users to solve the related problems of the users. Specifically, by setting the customer service entrance at the designated position of the application page, after the user enters the customer service module through the customer service entrance, the customer service 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 entrance is difficult to decide, if the customer service entrance is set at a more conspicuous position, for example, at the top or side rail in an application, or one customer service entrance is respectively set in each application page, thus a certain visual area is necessarily occupied, and the operation influence on a user is more obvious under the condition that the visual area of a mobile terminal is small; correspondingly, if the customer service entrance is arranged at a more concealed position, the difficulty of locating the customer service entrance by a user is increased, and the user experience is reduced. Therefore, the problem that the user cannot easily find the customer service entrance is not solved due to the fact that the customer service entrance is arranged at the easily found position and the visible area is occupied due to the fact that the customer service entrance is arranged at the too concealed position.

It is thus seen that there is a need to provide a solution that can both avoid occupation of the viewable area by customer service portals and ensure that users quickly enter the customer service module.

Disclosure of Invention

The aim of one or more embodiments of the present disclosure is to provide a customer service requirement identifying method and device, which can ensure that a target user quickly enters a customer service module even if a customer service entrance is set at a more concealed position without setting the customer service entrance at a significant position, thereby ensuring that the target user timely enjoys corresponding customer service, so as to solve the troublesome problem encountered by the target user through customer service intervention in time, and improve the user experience.

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

one or more embodiments of the present disclosure provide a customer service requirement identifying method, including:

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

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

Determining the demand degree of the target user for customer service according to the target influencing factors;

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

One or more embodiments of the present disclosure provide a customer service requirement identifying device, including:

the information acquisition module is used for acquiring application use information of a target user, wherein the application use information comprises: at least one of application operation behavior data, application operation interface screenshot and application abnormality 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 demand determining module is used for determining the demand degree of the target user for customer service according to the target influencing factors;

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

One or more embodiments of the present specification provide a customer service demand identification apparatus, 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 disclosure, a method and an apparatus for identifying a customer service requirement acquire application usage information of a target user, where the application usage information includes: at least one of application operation behavior data, application operation interface screenshot and application abnormality detection information; and based on application use information of the target user, whether the target user has customer service requirements is intelligently identified, and customer service is automatically pushed to the target user when the target user needs the customer service, so that the customer service inlet is not required 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 the customer service module, thereby ensuring that the target user can timely enjoy corresponding customer service, so that the problem encountered by the target user is solved through customer service intervention in time, and the user use experience is improved.

Drawings

For a clearer description of one or more embodiments of the present description or of the solutions of the prior art, the drawings that are necessary for the description of the embodiments or of the prior art will be briefly described, it being apparent that the drawings in the description below are only some of the embodiments described in one or more of the present description, from which other drawings can be obtained, without inventive faculty, for a person skilled in the art.

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

FIG. 2 is a schematic diagram of a first flow of a customer service requirement identification method according to one or more embodiments of the present disclosure;

FIG. 3 is a schematic diagram illustrating a second flow of a customer service requirement identification method according to one or more embodiments of the present disclosure;

FIG. 4 is a schematic diagram illustrating a third flow of a customer service requirement identification method according to one or more embodiments of the present disclosure;

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

FIG. 6 is a schematic diagram illustrating a first module composition of a customer service requirement identifying device according to one or more embodiments of the present disclosure;

fig. 7 is a schematic diagram illustrating a second module composition of a customer service requirement identifying device according to one or more embodiments of the present disclosure;

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

Detailed Description

In order for those skilled in the art to better understand the solutions in one or more embodiments of the present specification, the solutions in one or more embodiments of the present specification will be clearly and completely described below with reference to the drawings in one or more embodiments of the present specification, and it is apparent that the described embodiments are only a part of one or more embodiments of the present specification, not all embodiments. All other embodiments, which can be made by one or more persons of ordinary skill in the art without undue burden from the disclosure, are intended to be within the scope of one or more of the disclosure.

One or more embodiments of the present disclosure provide a customer service requirement identifying method and apparatus, which can ensure that a target user quickly enters a customer service module even if a customer service entrance is set in a more concealed position without setting the customer service entrance in a significant position, thereby ensuring that the target user timely enjoys corresponding customer service, so as to solve the troublesome problem encountered by the target user through customer service intervention in time, and improve the user experience.

Fig. 1 is a schematic application scenario diagram of a customer service requirement identifying system provided in one or more embodiments of the present disclosure, where, 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, a tablet personal computer and the like, the background server can be a server for responding to a service request of the user terminal, the customer service terminal can be terminal equipment for providing customer service for the user terminal, an execution main body of a customer service requirement identification process can be the user terminal or the background server, and a specific customer service requirement identification process is as follows:

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

(2) Carrying out key information identification on the acquired application use information to obtain target influence factors related to customer service requirements;

specifically, after application use information of a target user is obtained, 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 customer service according to the determined target influencing factors, namely identifying the customer service demand of the target user based on the determined target influencing factors, and judging whether the target user has the service demand of customer service intervention;

(4) When the target user is determined to have customer service requirements, automatically pushing a customer service inlet to the target user; when the user terminal detects that a target user enters the customer service module through the customer service entrance request, the customer service request is sent to a background server, so that the background server distributes the customer service request to a corresponding customer service terminal, and customer service is provided for the target user by the customer service terminal;

Specifically, in the case that the execution main body of the process of customer service requirement identification is a background server, the pushing the customer service portal to the target user specifically includes: when the background server determines that the target user has customer service requirements, sending pushing indication information to a corresponding user terminal so as to trigger the user terminal to push a customer service entrance to the target user;

therefore, whether the target user has customer service requirements or not is intelligently identified based on application use information of the target user, customer service is automatically pushed to the target user when the customer service is required by the target user, and therefore, even if the customer service inlet is arranged at a more concealed position, the target user can still be ensured to quickly enter the customer service module, so that the target user can be ensured to timely enjoy corresponding customer service, the troublesome problem encountered by the target user is solved through customer service intervention, the user use experience is improved, and in addition, the customer service module is not required to be arranged on a plurality of pages in the application by adopting a mode of pushing the customer service inlet to the user as required.

Fig. 2 is a first flowchart of a customer service requirement identifying method according to one or more embodiments of the present disclosure, where the method in fig. 2 may be performed by the ue in fig. 1 or may be performed by a background server in fig. 1, and as shown in fig. 2, the method at least includes the following steps:

S201, acquiring application use information of a target user, wherein the application use information comprises: at least one of application operation behavior data, application operation interface screenshot and application abnormality detection information;

specifically, the application operation behavior data may include: keyword query data, operation page query data, etc., the application operation interface screenshot may be image information generated by performing a screenshot operation on an application operation page, and the application anomaly detection information includes: the conventional application detection log and the application log of the key service node;

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

specifically, from the obtained application usage information, identifying key information representing that the user has a customer service requirement, and determining the identified key information as a target influence factor associated with the customer service requirement, wherein the target influence factor may include: at least one of search frequency of query keywords for representing customer service demands, view frequency of explanatory pages for representing customer service demands, repeated sliding frequency of the same application operation page, switching frequency of the same application operation page, content error reporting information belonging to a content error reporting class library and abnormal response results belonging to an abnormal response class library;

In addition, the application usage information may further include: the face image information of the target user is subjected to key information identification, and target influence factors associated with customer service requirements are obtained;

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

specifically, after a plurality of target influence factors associated with customer service demands are determined, customer service demands are scored by combining the target influence factors, corresponding scoring results are obtained, and the higher the obtained scoring value for the customer service demands is, the higher the current demand degree of a user for customer service is;

s204, judging whether the determined demand degree for customer service meets a preset condition; the preset condition may be that the demand level is greater than a preset threshold value, that is, when the determined demand level of the customer service is greater than the preset threshold value, the demand level of the customer service is determined to meet the preset condition;

if the result is no, continuing to execute the steps S201 to S204, namely, continuing to determine whether the target user has a customer service requirement;

If the result is yes, S205 is executed, and a customer service portal is pushed to the target user, specifically, a customer service portal icon can be displayed on the user terminal, a customer service portal prompt window can be popped up, and the user can directly jump to a customer service interface, so that the purpose of guiding the user to enter the customer service function quickly is achieved.

In one or more embodiments of the present disclosure, application usage information of a target user is obtained, where the application usage information includes: at least one of application operation behavior data, application operation interface screenshot and application abnormality detection information; and based on application use information of the target user, whether the target user has customer service requirements is intelligently identified, and customer service is automatically pushed to the target user when the target user needs the customer service, so that the customer service inlet is not required 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 the customer service module, thereby ensuring that the target user can timely enjoy corresponding customer service, so that the problem encountered by the target user is solved through customer service intervention in time, 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 in detail to the customer service, and the user preamble background is relatively long in exchange time, so as to improve the efficiency of customer service in processing the user problem, based on this, as shown in fig. 3, the customer service requirement identification method further includes:

s206, generating problem description data of the target user according to the determined target influence factors, wherein the problem description data is formed by summarizing problems to be solved by customer service, which are encountered by the target user;

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

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

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

After determining a plurality of target influence factors associated with customer service demands, identifying customer service demands based on the target influence factors, generating problem description data based on the target influence factors, and sending the problem description data to corresponding customer service terminals, so that the customer service terminals quickly know problem key points encountered by target users, quickly give out corresponding solutions, save links of problem statement of the target users to customer service, and improve the processing efficiency of customer service on user problems;

in one or more embodiments of the present disclosure, when the target user is intelligently identified as having a customer service requirement based on application usage information, a customer service portal is pushed to the user, and problem description data of the target user is automatically generated and sent to a corresponding customer service terminal, so that the customer service terminal can quickly understand and locate problems encountered by the target user, and thus, the target user does not need to perform preamble problem description introduction to the customer service after entering the customer service module, preamble redundancy information communication is reduced, and accordingly, the customer service can quickly provide a corresponding solution to the target user, the customer service efficiency for solving the user problems is improved, and the accuracy of the solution is improved.

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

s2031, determining the demand degree of the target user for the customer service by utilizing a pre-trained customer service demand degree recognition model and based on the determined target influence factors.

Specifically, the customer service demand recognition model is obtained by training in the following manner, and specifically comprises the following steps:

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 a corresponding relation between a sample influence factor and a customer service demand degree;

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

Specifically, aiming at the demand degree helpdigree=s (T, W, R) of the customer service, wherein S represents a customer service demand degree recognition model, T represents a target influence factor determined based on application operation behavior data, W represents a target influence factor determined based on application operation interface screenshot, and R represents a target influence factor determined based on application anomaly detection information;

In specific implementation, taking a customer service demand degree identification model as a linear regression model as an example, a calculation formula of the customer service demand degree is as follows:wherein HelpDIGRee represents the customer service demand degree, A _i Weight coefficient indicating ith target influencing factor, x _i Represents the i-th target influencing factor, n represents the kind of the target influencing factorA number.

The process of determining the target influence factor introduces application usage information, where the application usage information may be any one or combination of application operation behavior data, application operation interface screenshot, and application anomaly detection information, and the process of determining the target influence factor for each application usage information is described in detail below, specifically:

the first type of information identification analysis process includes, for an application, information: the case of applying operational behavior data; correspondingly, the step S202 of identifying the key information of the obtained application usage information to obtain the target influencing factor associated with the customer service requirement, specifically includes at least one of the following:

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

Specifically, analyzing behavior data related to keyword query in application operation behavior data, extracting query keywords which are input by a target user and represent customer service requirements, and determining the search frequency of each query keyword which represents the customer service requirements; for example, in a preset time period, the query keywords input by the user are the search frequencies of keywords such as customer service, help, application non-opening and the like;

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

specifically, analyzing behavior data related to information page viewing in application operation behavior data, extracting viewing behavior data of explanatory pages representing customer service requirements, and determining the viewing frequency of each explanatory page representing the customer service requirements; for example, in a preset time period, the user checks the application description and the help page;

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

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

Determining the switching frequency of a target user on the same application operation page based on the obtained application operation behavior data;

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

Thus, the target influencing factors determined based on the application operational behavior data include: at least one of search frequency of query keywords for representing customer service requirements, view frequency of explanatory pages for representing customer service requirements, repeated sliding frequency of the same application operation page and switching frequency of the same application operation page.

The second type of information identification analysis process includes, for the application use information: the condition of the screenshot of the application operation interface; correspondingly, the step S202 of identifying key information of the obtained application usage information to obtain a target influence factor associated with the customer service requirement specifically includes:

performing image recognition processing on the obtained application operation interface screenshot, and extracting content error reporting information belonging to a content error reporting class library;

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

Specifically, considering that the user performs screenshot on the operation interface, the user may need to perform abnormal consultation, so that the error reporting information can be identified by performing error reporting information identification on the screenshot on the application operation interface, and the identification result of the error reporting information is used as one of the influencing factors for determining the customer service demand level, for example, in the screenshot on the application operation interface, the error reporting information of contents such as form errors, failure identifications, error feedback and the like is extracted as a target influencing factor;

thus, the target influencing factors determined based on the application operation interface screenshot include: and reporting error information from the content identified in the interface screenshot.

The third type of information identification analysis process includes, for application usage information: the case of applying abnormality detection information; correspondingly, the step S202 of identifying key information of the obtained application usage information to obtain a target influence factor associated with the customer service requirement specifically includes:

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

and determining the determined abnormal response result as a target influence factor related to the customer service demand.

Specifically, considering that when the application responds abnormally to the user operation request, there is a possibility that the user needs to perform abnormal consultation, the abnormal response identification can be performed on the application abnormal detection information, the identification result with abnormal response is taken as one of the influencing factors for determining the customer service demand degree, for example, based on the application abnormal detection information, the abnormal response results such as page loading failure, application response crash, page response overtime and the like are identified as target influencing factors;

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

Further, after determining the target influencing factor based on the recognition analysis result of the application usage information, the problem description data of the target user may be determined based on the target influencing factor, and the determined target influencing factor is different and the corresponding problem description data is different due to different types of the application usage information, where the application usage information may be any one or combination of application operation behavior data, application operation interface screenshot, and application anomaly detection information, and the following detailed description is given for a process of generating the problem description data based on the target influencing factor determined for each application usage information, respectively:

The process for determining the description of the problem based on the recognition analysis result of the first type of information comprises the following steps of: the case of applying operational behavior data; correspondingly, the step S206 generates problem description data of the target user according to the determined target influencing factors, and specifically includes at least one of the following:

according to the determined target influencing factors, determining query keywords which are searched by a target user and characterize customer service requirements;

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

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

specifically, when the target influencing factor is the viewing frequency of the target user on the explanatory page representing the customer service requirement, the explanatory keywords in the explanatory page representing the customer service requirement are used as a part of the problem description data of the target user;

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

Specifically, when the target influencing factor is the repeated sliding frequency of the target user on the same application operation page, the keywords in the application operation page with the repeated sliding frequency larger than the preset sliding frequency threshold value are used as 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 influencing factor is the switching frequency of the target user on the same application operation page, the keywords in the application operation page with the switching frequency larger than the preset switching frequency threshold value are used as part of the problem description data of the target user;

thus, the generated problem description data includes: at least one of query keywords which are searched by a target user and used for representing customer service demands, explanation keywords in an explanatory page which is checked and used for representing the customer service demands, keywords in an application operation page with repeated sliding frequency being larger than a preset sliding frequency threshold value, and keywords in an application operation page with switching frequency being larger than a preset switching frequency threshold value.

The process for determining the problem description based on the recognition analysis result of the second type of information comprises the following steps of: the condition of the screenshot of the application operation interface; correspondingly, the step S206 generates problem description data of the target user according to the determined target influencing factors, which specifically includes:

And determining target influence factors belonging to the content error reporting class library and application operation interface screenshots corresponding to the target influence factors as problem description data of a target user.

Specifically, when the target influencing factor is 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 problem description data of the target user;

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

The process for determining the problem description based on the recognition analysis result of the third type of information comprises the following steps of: the case of applying abnormality detection information; correspondingly, the step S206 generates problem description data of the target user according to the determined target influencing factors, which specifically includes:

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

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

For example, taking the identified abnormal response results such as page loading failure, application response crash, page response timeout and the like as 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 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 usage information for the above application includes: the conditions of three types of information, namely application operation behavior data, application operation interface screenshot and application anomaly detection information; based on this, as shown in fig. 5, a schematic diagram of a specific implementation principle of a customer service requirement identification method is provided, and the specific process is as follows:

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

the key information identification is carried out on the obtained application operation behavior data, and a first target influence factor associated with customer service requirements is obtained, wherein the first target influence factor comprises: at least one of search frequency of query keywords for representing customer service demands, view frequency of explanatory pages for representing customer service demands, repeated sliding frequency of the same application operation page, and switching frequency of the same application operation page;

The acquired screenshot of the application operation interface is identified by key information to obtain a second target influence factor associated with customer service requirements, wherein the second target influence factor comprises: content error reporting information identified from the interface screenshot;

and carrying out key information identification on the acquired application abnormality detection information to obtain a third target influence factor related to customer service requirements, 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 degree identification model as the customer service demand degree of the target user;

generating problem description data of a 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 greater than a preset threshold, pushing a customer service entrance to a target user;

further, when the customer service demand is greater than a preset threshold, not only pushing a customer service entrance to a target user, but also sending problem description data of the target user to a customer service terminal allocated to the target user, so that customer service personnel corresponding to the customer service terminal can sense the current problems encountered by the user in advance, and long-time problem description is not needed after the target user enters the customer service module, and the processing efficiency of customer service on the user problems is improved; in addition, in order to reduce the workload of the customer service personnel, the generated problem description data may be sent to the corresponding customer service terminal after detecting the triggering operation of the target user on the pushed customer service entrance, that is, the problem description data of the target user may be sent to the customer service terminal allocated to the target user only after detecting that the target user clicks the customer service entrance.

According to one or more embodiments of the present disclosure, a customer service requirement identifying method obtains application usage information of a target user, where the application usage information includes: at least one of application operation behavior data, application operation interface screenshot and application abnormality detection information; and based on application use information of the target user, whether the target user has customer service requirements is intelligently identified, and customer service is automatically pushed to the target user when the target user needs the customer service, so that the customer service inlet is not required 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 the customer service module, thereby ensuring that the target user can timely enjoy corresponding customer service, so that the problem encountered by the target user is solved through customer service intervention in time, and the user use experience is improved.

In accordance with the foregoing customer service requirement identifying method described in fig. 2 to 5, based on the same technical concept, one or more embodiments of the present disclosure further provide a customer service requirement identifying device, and fig. 6 is a schematic diagram of a first module composition of the customer service requirement identifying device provided in one or more embodiments of the present disclosure, where the device is configured to perform the customer service requirement identifying 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, application operation interface screenshot and application abnormality detection information;

the information identifying module 602 is configured to identify key information of each application usage information, so as to obtain a target influencing factor associated with a customer service requirement;

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

and the customer service pushing module 604 is configured to push a customer service portal to the target user if the demand level meets a preset condition.

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

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

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

Optionally, the application usage information includes: applying operational behavior data;

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

determining the search frequency of the query keywords of the target user representing customer service requirements based on the application operation behavior data; or alternatively, the process may be performed,

determining the view frequency of the explanatory pages representing customer service requirements of the target user based on the application operation behavior data; or alternatively, the process may be performed,

determining the repeated sliding frequency of the target user on the same application operation page based on the application operation behavior data; or alternatively, the process may be performed,

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

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

the information identification module 602 is further specifically configured to:

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

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

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

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

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

the problem description generation module 605 is specifically configured to perform at least one of the following:

according to the target influencing factors, determining query keywords which are searched by the target user and characterize customer service requirements; or alternatively, the process may be performed,

Determining explanatory keywords in an explanatory page representing customer service requirements viewed by the target user according to the target influencing factors; or alternatively, the process may be performed,

according to the target influence factors, determining keywords in an application operation page with repeated sliding frequency larger than a preset sliding frequency threshold; or alternatively, the process may be performed,

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

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

and determining the screenshot of the application operation interface and the target influencing factors belonging to the content error reporting class library as problem description data of the target user.

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

The customer service requirement identifying device in one or more embodiments of the present disclosure obtains application usage information of a target user, where the application usage information includes: at least one of application operation behavior data, application operation interface screenshot and application abnormality detection information; and based on application use information of the target user, whether the target user has customer service requirements is intelligently identified, and customer service is automatically pushed to the target user when the target user needs the customer service, so that the customer service inlet is not required 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 the customer service module, thereby ensuring that the target user can timely enjoy corresponding customer service, so that the problem encountered by the target user is solved through customer service intervention in time, and the user use experience is improved.

It should be noted that, in the present specification, the embodiment of the customer service requirement identifying device and the embodiment of the customer service requirement identifying method in the present specification are based on the same inventive concept, so that the specific implementation of this embodiment may refer to the implementation of the foregoing corresponding customer service requirement identifying method, and the repetition is not repeated.

Further, according to the method shown in fig. 2 to 5, based on the same technical concept, one or more embodiments of the present disclosure further provide a customer service requirement identifying device, which is configured to perform the customer service requirement identifying method as shown in fig. 8.

The customer service requirement identifying device may have a relatively large difference due to different configurations or performances, and may include one or more processors 801 and a memory 802, where the memory 802 may store one or more stored applications or data. Wherein the memory 802 may be transient storage or persistent storage. The application programs stored in memory 802 may include one or more modules (not shown in the figures), each of which may include a series of computer-executable instructions in the customer service demand identification 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 demand identification device may also include one or more power sources 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 demand identification device includes 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 include one or more modules, and each module may include a series of computer-executable instructions for the customer service demand identification device, and configured to be executed by the one or more processors, the one or more programs including 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 influencing factors;

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

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

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

the key information identification is performed on the application use information to obtain target influence factors associated with customer service requirements, wherein the target influence factors comprise at least one of the following:

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

the step of carrying out key information identification on the application use information to obtain target influence factors associated with customer service requirements comprises the following steps:

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

the generating problem description data of the target user according to the target influencing factors comprises at least one of the following steps:

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

It should be noted that, in the present specification, the embodiment about the customer service requirement identifying device and the embodiment about the customer service requirement identifying method in the present specification are based on the same inventive concept, so that the specific implementation of this embodiment may refer to the implementation of the foregoing corresponding customer service requirement identifying method, and the repetition is not repeated.

Further, in accordance with the methods shown in fig. 2 to 5, based on the same technical concept, one or more embodiments of the present disclosure further provide a storage medium for storing computer executable instructions, where in a specific embodiment, the storage medium may be a U-disc, an optical disc, a hard disk, etc., and the computer executable instructions stored in the storage medium can implement the following flow when executed by a processor:

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

Optionally, the computer executable instructions stored on the storage medium, when executed by the processor, determine, according to the target influencing factor, a demand level of the target user for the customer service, including:

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

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

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 description stores computer-executable instructions that, when executed by a processor, obtain application usage information for a target user, wherein the application usage information includes: at least one of application operation behavior data, application operation interface screenshot and application abnormality detection information; and based on application use information of the target user, whether the target user has customer service requirements is intelligently identified, and customer service is automatically pushed to the target user when the target user needs the customer service, so that the customer service inlet is not required 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 the customer service module, thereby ensuring that the target user can timely enjoy corresponding customer service, so that the problem encountered by the target user is solved through customer service intervention in time, and the user use experience is improved.

It should be noted that, in the present specification, the embodiment about the storage medium and the embodiment about the customer service requirement identifying method in the present specification are based on the same inventive concept, so the specific implementation of this embodiment may refer to the implementation of the corresponding customer service requirement identifying method, and the repetition is omitted.

In the 90 s of the 20 th century, improvements to one technology could clearly be distinguished as improvements in hardware (e.g., improvements to circuit structures such as diodes, transistors, switches, etc.) or software (improvements to the process flow). However, with the development of technology, many improvements of the current method flows can be regarded as direct improvements of hardware circuit structures. Designers almost always obtain corresponding hardware circuit structures by programming improved method flows into hardware circuits. Therefore, an improvement of a method flow cannot be said to be realized by a hardware entity module. For example, a programmable logic device (Programmable Logic Device, PLD) (e.g., field programmable gate array (Field Programmable Gate Array, FPGA)) is an integrated circuit whose logic function is determined by the programming of the device by a user. A designer programs to "integrate" a digital system onto a PLD without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Moreover, nowadays, instead of manually manufacturing integrated circuit chips, such programming is mostly implemented with "logic compiler" software, which is similar to the software compiler used in program development and writing, and the original code before being compiled is also written in a specific programming language, which is called hardware description language (Hardware Description Language, HDL), but also HDL is not only one, but a plurality of, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), confluence, CUPL (Cornell University Programming Language), HD Cal, JHDL (Java Hardware Description Language), lava, lola, my HDL, palam, RHDL (Ruby Hardware Description Language), etc., VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog are currently most commonly used. It will also be apparent to those skilled in the art that a hardware circuit implementing the logic method flow can be readily obtained by merely slightly programming the method flow into an integrated circuit using several of 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, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable logic controllers, and embedded microcontrollers, 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 of the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller in a pure computer readable program code, it is well possible to implement the same functionality by logically programming the method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Such a controller may thus be regarded as a kind of hardware component, and means for performing various functions included therein may also be regarded as structures within the hardware component. Or even means for achieving the various functions may be regarded as either software modules implementing the methods or structures within hardware components.

The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. One typical implementation is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smart phone, 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 functionally divided into various units, respectively. Of course, the functions of each element may be implemented in one or more software and/or hardware elements when one or more of the present description are implemented.

One skilled in the relevant art will recognize that one or more of the embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, one or more of the present specification 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 can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

One or more of the present description is 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 flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations 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 one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.

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

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 storage media for a computer 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, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.

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 one … …" 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 description may 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 description may 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.

In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.

The foregoing description is merely illustrative of one or more embodiments of the present disclosure and is not intended to limit the one or more embodiments of the present disclosure. Various modifications and alterations to one or more of this description will become apparent to those skilled in the art. Any modifications, equivalent substitutions, improvements, or the like, which are within the spirit and principles of one or more of the present description, are intended to be included within the scope of the claims of one or more of the present description.

Claims

1. A customer service demand identification method, comprising:

if the demand degree meets the preset condition, pushing a customer service inlet to the target user;

the determining, according to the target influencing factor, the demand degree of the target user for the customer service includes:

2. The method of claim 1, further comprising:

3. The method of claim 1, wherein the application usage information comprises: applying operational behavior data;

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

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

6. The method of claim 2, wherein the application usage information comprises: applying operational behavior data;

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

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

9. A customer service demand identification device, comprising:

the customer service pushing module is used for pushing a customer service inlet to the target user if the demand degree meets a preset condition;

the customer service demand determining module is specifically configured to:

10. The apparatus of claim 9, further comprising:

the problem description generation module is used for generating 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 can determine a solution which needs to be provided for the target user based on the problem description data.

11. The apparatus of claim 9, wherein the application usage information comprises: applying operational behavior data;

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

12. The apparatus of claim 9, wherein the application usage information comprises: an application operation interface screenshot;

the information identification module is further specifically configured to:

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

The information identification module is further specifically configured to:

14. The apparatus of claim 10, wherein the application usage information comprises: applying operational behavior data;

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

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

The problem description generation module is further specifically configured to:

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

17. A customer service demand identification device comprising:

a processor; and

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