CN115860252A - Intelligent monitoring and analyzing method and system for full-channel business - Google Patents
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Abstract
The invention provides a method and a system for intelligently monitoring and analyzing full-channel services, which relate to the technical field of intelligent monitoring and comprise the following steps: acquiring historical call data of workers and business handling data of users; carrying out call content identification on the historical call data to generate call characteristics of workers; performing service execution efficiency evaluation to generate service execution efficiency data of workers; constructing a business handling database of the staff; identifying real-time access call data, and matching the service handling database to obtain a staff matching value; acquiring real-time call information of a worker; and performing call access screening of the real-time access call data according to the real-time call information and the staff matching value, so that the technical problem that the service handling efficiency is low because no analysis application is performed on the call historical call data of the staff, and the proper staff cannot be matched for the client in the prior art is solved.
Description
Technical Field
The disclosure relates to the technical field of intelligent monitoring, in particular to a method and a system for intelligently monitoring and analyzing full-channel services.
Background
With diversification of customer service channels, industry supervision and requirements of customers on power supply service are continuously improved, and customer service risks caused by information differences among different channels are higher and higher. According to the requirements of central planning and service fusion development and the promotion of key work of companies such as marketing census and the like, the central sharing capability needs to be further improved to optimize the exertion space, and in the aspect of operation sharing capability, full-channel service monitoring data needs to be further shared, an operation regulation and control mode needs to be optimized, and full-channel full-service and index monitoring and early warning work needs to be carried out. In the aspect of full-channel operation regulation, field management specialty and process online research need to be deeply developed, a full-channel business intelligent prediction model is established, operation management and field management intelligent regulation are achieved, the full-channel customer service intelligent level is improved, regular business surge is eliminated, the emergency starting times are reduced, and the operation service risk is reduced.
At present, the technical problem that due to the fact that analysis application is not carried out on call historical call data of workers, proper workers cannot be matched for clients, and accordingly business handling efficiency is low exists in the prior art.
Disclosure of Invention
The disclosure provides a full-channel business intelligent monitoring and analyzing method and system, which are used for solving the technical problem that in the prior art, due to the fact that analysis application is not carried out on historical conversation data of workers, the proper workers cannot be matched for clients, and further the business handling efficiency is low.
According to a first aspect of the present disclosure, a full-channel business intelligent monitoring and analyzing method is provided, including: acquiring historical call data of workers and user transaction service data, wherein the historical call data and the user transaction service data have a corresponding relation; carrying out call content identification on the historical call data, and generating call characteristics of workers based on content identification results; performing service execution efficiency evaluation according to the call duration of the historical call data and the service handling data of the user to generate service execution efficiency data of the staff; constructing a business handling database of the staff according to the business execution efficiency data and the staff conversation characteristics; identifying real-time access call data, and matching the service handling database according to the service type of the real-time access call data to obtain a staff matching value; acquiring real-time call information of a worker; and performing call access screening of the real-time access call data according to the real-time call information and the staff matching value.
According to a second aspect of the present disclosure, there is provided a full channel business intelligent monitoring and analyzing system, including: the data acquisition module is used for acquiring historical call data of workers and user transaction service data, wherein the historical call data and the user transaction service data have a corresponding relation; the call content identification module is used for identifying call content of the historical call data and generating call characteristics of workers based on content identification results; the service execution efficiency evaluation module is used for evaluating service execution efficiency according to the call duration of the historical call data and the service handling data of the user to generate service execution efficiency data of the staff; the business handling database construction module is used for constructing a business handling database of the staff through the business execution efficiency data and the staff conversation characteristics; the service matching module is used for identifying real-time access call data, matching the service handling database according to the service type of the real-time access call data and obtaining a staff matching value; the real-time call information acquisition module is used for acquiring real-time call information of a worker; and the call access screening module is used for carrying out call access screening on the real-time access call data according to the real-time call information and the staff matching value.
According to a third aspect of the present disclosure, there is provided an electronic device comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of the first aspect.
According to the intelligent monitoring and analyzing method for the whole channel business, historical call data of workers and business handling data of users are acquired, wherein the historical call data and the business handling data of the users have a corresponding relation; carrying out call content identification on the historical call data, and generating call characteristics of workers based on content identification results; performing service execution efficiency evaluation according to the call duration of the historical call data and the service handling data of the user to generate service execution efficiency data of the staff; constructing a business handling database of the staff according to the business execution efficiency data and the staff conversation characteristics; identifying real-time access call data, and matching the service handling database according to the service type of the real-time access call data to obtain a staff matching value; acquiring real-time call information of a worker; and performing call access screening of the real-time access call data according to the real-time call information and the staff matching value. According to the method, historical call data of workers and business data handled by users are analyzed and researched, so that a business handling database of the workers is constructed, the workers are matched according to the business handling database, call access screening is carried out according to matching values of the workers, and the technical effects of selecting proper workers for the users and improving business handling efficiency are achieved.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
To more clearly illustrate the disclosure or prior art solutions, the drawings needed for 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 exemplary, and that other drawings can be obtained by those skilled in the art without inventive effort from the provided drawings.
Fig. 1 is a schematic flow chart of an intelligent monitoring and analyzing method for full-channel services according to an embodiment of the present disclosure;
FIG. 2 is a schematic flow chart illustrating a process for obtaining a call characteristic of a worker according to an embodiment of the present disclosure;
FIG. 3 is a schematic flow chart illustrating the optimization, supervision, evaluation and feedback of the staff in the embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of an intelligent monitoring and analyzing system for full-channel services according to an embodiment of the present disclosure;
fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure.
Description of the reference numerals: the system comprises a data acquisition module 11, a call content identification module 12, a service execution efficiency evaluation module 13, a service handling database construction module 14, a service matching module 15, a real-time call information acquisition module 16, a call access screening module 17, electronic equipment 800, a processor 801, a memory 802 and a bus 803.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In order to solve the technical problem that in the prior art, due to the fact that analysis application is not carried out on call history data of workers, proper workers cannot be matched for clients, and therefore business handling efficiency is low, the inventor of the present disclosure obtains the full-channel business intelligent monitoring and analysis method and system through creative labor.
Example one
Fig. 1 is a diagram of an intelligent monitoring and analyzing method for a full channel service according to an embodiment of the present application, and as shown in fig. 1, the method includes:
step S100: acquiring historical call data of workers and user transaction service data, wherein the historical call data and the user transaction service data have a corresponding relation;
specifically, the historical call data refers to call data of a worker in a past period of time, and includes information such as call duration and call content, the user transaction service data includes information such as a service type and service transaction efficiency handled by the user, and the historical call data and the user transaction service data have a corresponding relationship, and basic data is provided for subsequent service analysis by obtaining the historical call data and the user transaction service data of the worker.
Step S200: performing call content identification on the historical call data, and generating a call characteristic of a worker based on a content identification result;
specifically, the call content of the historical call data is identified, the call skill, accuracy, service handling efficiency and the like of the staff are identified, and then the call characteristics of the staff are generated according to the content identification result, wherein the call characteristics of the staff comprise the call skill, accuracy, efficiency and the like of each staff.
Step S300: performing service execution efficiency evaluation according to the call duration of the historical call data and the service handling data of the user to generate service execution efficiency data of the staff;
specifically, the service execution efficiency evaluation is performed based on the call duration of the historical call data and the service data handled by the user, the shorter the call duration is, and the higher the standard service handling of the user can be completed, the higher the service execution efficiency is.
Step S400: constructing a service handling database of the staff according to the service execution efficiency data and the staff conversation characteristics;
specifically, a business handling database of the worker is constructed according to the business execution efficiency data and the call characteristics of the worker, in other words, the business handling database comprises the business execution efficiency data and the call characteristics of the worker.
Step S500: identifying real-time access call data, and matching the service handling database according to the service type of the real-time access call data to obtain a staff matching value;
specifically, real-time access call data is identified, the service type of the real-time access call data is determined, matching is performed in a service handling database according to the service type of the real-time access call data, a proper worker is matched, and a worker matching value is obtained, wherein the worker matching value is a worker suitable for arranging a call.
Step S600: acquiring real-time call information of a worker;
specifically, real-time call information of the staff is obtained, wherein the real-time call information indicates whether the staff is calling, and if the staff is calling, the staff is not suitable for being arranged to make a call.
Step S700: and performing call access screening of the real-time access call data according to the real-time call information and the staff matching value.
Specifically, call access screening of real-time access call data is performed according to the real-time call information and the staff matching value, the staff matching value is a staff suitable for accessing a call, but the staff may be in a call, so after the staff matching value is obtained, the staff who do not currently have a call need to be screened out according to the real-time call information of the staff, and the staff is arranged to connect the real-time access call.
Based on the analysis, the present disclosure provides a full-channel business intelligent monitoring analysis method, in this embodiment, historical conversation data of workers and business data handled by users are analyzed and researched, so as to construct a business handling database of the workers, matching of the workers is performed according to the business handling database, conversation access screening is performed according to matching values of the workers, and a technical effect of selecting proper workers for the users and improving business handling efficiency is achieved.
Step S700 in the embodiment of the present application further includes:
step S710: acquiring accumulated call data of workers;
step S720: dividing the accumulated call data according to a multi-level call period to obtain a multi-level call period division result;
step S730: according to the preset weight distribution value of the multi-level call cycle division result;
step S740: performing weighting calculation on the multi-level call cycle division result through the preset weight distribution value, and acquiring call access influence data according to the weighting calculation result;
step S750: and performing call access screening of the real-time access call data through the call access influence data, the real-time call information and the staff matching value.
Specifically, accumulated call data of workers is obtained, the accumulated call data refers to the call making time of each worker, the accumulated call data is divided into multi-level call period evaluation data according to different periods, and multi-level call period division results are obtained.
As shown in fig. 2, the step S200 of the embodiment of the present application includes:
step S210: constructing a dialogistic feature set;
step S220: performing the dialect matching of the historical call data through the dialect feature set to obtain a dialect matching result;
step S230: performing matching analysis of the dialect according to the matching result of the dialect and the business data handled by the user to obtain an analysis result of matching degree of the dialect;
step S240: and analyzing a result according to the dialect matching result and the dialect matching degree.
Specifically, a dialect feature set is constructed, the dialect feature set comprises various dialect features, dialect matching of historical call data is carried out according to the dialect feature set, namely, matching is carried out in the dialect feature set according to call contents of the historical call data, a dialect matching result of the historical call data is obtained, the dialect matching result is the dialect feature of the historical call data, further, dialect matching analysis is carried out according to the dialect matching result and user transaction service data, namely whether the dialect matching result is matched with the user transaction service data or not is determined through analysis, the matching degree is high, a dialect matching analysis result is further obtained, staff call features are obtained according to the dialect matching result and the dialect matching analysis result, the staff call features comprise the dialect features of staff and the matching degree of the dialect features and the service transaction data, and proper staff can be subsequently matched for the user according to the staff call features.
Step S240 in the embodiment of the present application further includes:
step S241: obtaining user basic information of the user;
step S242: performing conversational adaptation evaluation according to the user basic information and the conversational matching result to obtain a conversational adaptation evaluation result;
step S243: adding the speech adaptation evaluation result to the staff speech characteristic.
Specifically, user basic information of a user is obtained, the user basic information comprises information such as an academic calendar and language features of the user, and a language and technology adaptation evaluation is carried out according to the user basic information and a language and technology matching result, namely whether the language and technology matching result is suitable for the user is determined according to the information such as the academic calendar and language features of the user, the adaptation degree is high, a language and technology adaptation evaluation result is further obtained and added to conversation features of workers, the adaptation and technology evaluation result is obtained and added to the conversation features of the workers, conversation features of the workers are improved, and the workers which are more suitable for the user can be matched according to the conversation features of the workers.
Step S800 in the embodiment of the present application further includes:
step S810: analyzing the service handling speed influence according to the user basic information to obtain a speed influence value analysis result;
step S820: and compensating the service execution efficiency data according to the speed influence value analysis result, and correcting the service handling database based on the compensation result.
Specifically, the influence analysis of the business handling speed is carried out according to the basic information of the user, and exemplarily, the language of the user may be dialect, which causes inconvenience in communication and influences the business handling speed; the learning and experience of the user is low, and the communication is difficult, so that the service handling speed is low; the method comprises the steps that a user language is relatively verbose and tedious, the service handling speed is also influenced, the service handling speed is low due to the fact that the user is difficult to communicate, a speed influence value analysis result is obtained based on the fact that the speed influence value analysis result is the influence value of the user on the service handling speed, further, service execution efficiency data are compensated according to the speed influence value analysis result, namely the service execution efficiency data of workers obtained in the step S300 are obtained only according to the call duration and the user service handling data, the problem that communication is difficult due to the user is not considered, the obtained service execution efficiency is inaccurate, the service execution efficiency data need to be compensated according to the speed influence value analysis result, then the service handling database is corrected based on the compensation result, the service execution efficiency data are compensated, the service handling database is corrected based on the compensation result, and the matching accuracy is improved when the workers are matched subsequently.
As shown in fig. 3, step S900 in the embodiment of the present application further includes:
step S910: constructing a training optimization direction database of the staff based on the business handling database;
step S920: feeding the training optimization direction database back to corresponding workers and generating a continuous monitoring interval;
step S930: and carrying out optimization supervision evaluation and feedback of workers through the continuous monitoring interval.
Specifically, a training optimization direction database of a worker is constructed according to a business handling database, the business handling database comprises business execution efficiency data and worker conversation characteristics, based on the business execution direction database, the training optimization direction of the worker is determined, for example, the business execution efficiency is improved, the conversation characteristics are changed, the training optimization direction database of the worker is further constructed, the training optimization direction database is fed back to the corresponding worker, a continuous monitoring interval is generated, continuous monitoring is to monitor the worker within a continuous period of time, the continuous monitoring time is divided into different time periods according to certain requirements, namely the continuous monitoring interval, the worker is optimized, supervised, evaluated and fed back according to the continuous monitoring interval, illustratively, in the continuous monitoring interval, the training optimization condition of the worker is supervised and evaluated according to the training optimization direction database of the worker, the supervision and evaluation result is fed back to the worker, and the business execution efficiency of the worker is improved through the supervision, evaluation and the feedback of the worker.
Wherein, step S1000 in the embodiment of the present application further includes:
step S1010: judging whether the real-time access call data is an access new user;
step S1020: when the real-time access call data is not to access a new user, obtaining historical connection data;
step S1030: and performing call access screening according to the call access priority evaluation result.
Specifically, whether real-time access call data is accessed to a new user is judged, when the real-time access call data is not accessed to the new user, historical connection data is obtained, connection priority evaluation is carried out according to the historical connection data, call access screening is carried out according to the connection priority evaluation result, namely, if the real-time access call data is not accessed to the new user, the historical connection data of the user is obtained, connection priority evaluation is carried out on a worker according to the historical connection data, the worker can be continuously arranged to be connected by the historical connection worker who is often connected to the user and has higher score, the call access screening is carried out according to the historical connection data, the suitable worker is screened out for service handling for the user, and the service handling efficiency of the user is improved.
Example two
Based on the same inventive concept as the intelligent monitoring and analyzing method for the full-channel service in the foregoing embodiment, as shown in fig. 4, the present application further provides an intelligent monitoring and analyzing system for the full-channel service, where the system includes:
the data acquisition module 11 is used for acquiring historical call data of a worker and user transaction data, wherein the historical call data and the user transaction data have a corresponding relationship;
the call content identification module 12, the call content identification module 12 is configured to perform call content identification on the historical call data, and generate a call characteristic of a worker based on a content identification result;
the service execution efficiency evaluation module 13 is configured to perform service execution efficiency evaluation according to the call duration of the historical call data and the service data handled by the user, and generate service execution efficiency data of a worker;
a service handling database construction module 14, wherein the service handling database construction module 14 is configured to construct a service handling database of the worker according to the service execution efficiency data and the worker conversation characteristics;
the service matching module 15 is used for identifying real-time access call data, matching the service handling database according to the service type of the real-time access call data, and obtaining a staff matching value;
the real-time call information acquisition module 16, the real-time call information acquisition module 16 is used for acquiring real-time call information of a worker;
and the call access screening module 17 is used for performing call access screening on the real-time access call data according to the real-time call information and the staff matching value.
Further, the system further comprises:
the system comprises an accumulated call data acquisition module, a call processing module and a call processing module, wherein the accumulated call data acquisition module is used for acquiring accumulated call data of workers;
the call period dividing module is used for dividing the accumulated call data according to a multi-level call period to obtain a multi-level call period dividing result;
a preset weight value obtaining module, configured to obtain a preset weight distribution value of the multi-level call cycle division result;
the weighting calculation module is used for performing weighting calculation on the multi-level call cycle division result through the preset weight distribution value and obtaining call access influence data according to the weighting calculation result;
and the access call data screening module is used for carrying out call access screening on the real-time access call data through the call access influence data, the real-time call information and the staff matching value.
Further, the system further comprises:
the phone operation feature set construction module is used for constructing a phone operation feature set;
the matching module of the dialect is used for matching the dialect of the historical call data through the characteristic set of the dialect to obtain a matching result of the dialect;
the voice and skill matching analysis module is used for carrying out voice and skill matching analysis according to the voice and skill matching result and the business data handled by the user to obtain a voice and skill matching degree analysis result;
and the conversation feature acquisition module is used for acquiring the conversation features of the workers according to the conversation matching result and the conversation matching degree analysis result.
Further, the system further comprises:
the user basic information acquisition module is used for acquiring the user basic information of the user;
the speech adaptation evaluation module is used for performing speech adaptation evaluation according to the user basic information and the speech matching result to obtain a speech adaptation evaluation result;
and the voice operation adaptation evaluation result adding module is used for adding the voice operation adaptation evaluation result to the conversation characteristics of the staff.
Further, the system further comprises:
the service handling speed analysis module is used for analyzing the service handling speed influence according to the user basic information to obtain a speed influence value analysis result;
and the service handling database correction module is used for compensating the service execution efficiency data according to the speed influence value analysis result and correcting the service handling database based on the compensation result.
Further, the system further comprises:
the training optimization direction database construction module is used for constructing a training optimization direction database of the staff based on the business handling database;
the continuous monitoring interval generation module is used for feeding the training optimization direction database back to corresponding workers and generating a continuous monitoring interval;
and the optimization supervision evaluation feedback module is used for performing optimization supervision evaluation and feedback of the workers through the continuous monitoring interval.
Further, the system further comprises:
the new user access judging module is used for judging whether the real-time access conversation data is a new user access;
the historical connection data acquisition module is used for acquiring historical connection data when the real-time access call data is not the new user;
and the connection priority evaluation module is used for carrying out connection priority evaluation according to the historical connection data and carrying out call access screening according to the connection priority evaluation result.
The specific example of the full-channel intelligent monitoring and analyzing method for the business in the first embodiment is also applicable to the full-channel intelligent monitoring and analyzing system for the business in the present embodiment, and through the detailed description of the full-channel intelligent monitoring and analyzing method for the business, a person skilled in the art can clearly know that the full-channel intelligent monitoring and analyzing system for the business in the present embodiment is not described in detail herein for the sake of brevity of the description. The device disclosed in the embodiment corresponds to the method disclosed in the embodiment, so that the description is simple, and the relevant points can be referred to the description of the method part.
EXAMPLE III
Fig. 5 is a schematic diagram according to a third embodiment of the present disclosure, and as shown in fig. 5, an electronic device 800 in the present disclosure may include: a processor 801 and a memory 802.
A memory 802 for storing programs; the Memory 802 may include a volatile Memory (RAM), such as a Static Random Access Memory (SRAM), a Double Data Rate Synchronous Dynamic random access Memory (DDR SDRAM), and the like; the memory may also include a non-volatile memory, such as a flash memory. The memory 802 is used to store computer programs (e.g., applications, functional modules, etc. that implement the above-described methods), computer instructions, etc., which may be stored in one or more of the memories 802 in a partitioned manner. And the above-described computer programs, computer instructions, data, and the like can be called by the processor 801.
The computer programs, computer instructions, etc. described above may be stored in one or more memories 802 in partitions. And the above-described computer program, computer data, or the like can be called by the processor 801.
A processor 801 for executing the computer program stored in the memory 802 to implement the steps of the method according to the above embodiments.
Reference may be made in particular to the description relating to the preceding method embodiment.
The processor 801 and the memory 802 may be separate structures or may be integrated structures integrated together. When the processor 801 and the memory 802 are separate structures, the memory 802 and the processor 801 may be coupled by a bus 803.
The electronic device of this embodiment may execute the technical solution in the method, and the specific implementation process and the technical principle are the same, which are not described herein again.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
According to an embodiment of the present disclosure, the present disclosure also provides a computer program product comprising: a computer program, stored in a readable storage medium, from which at least one processor of the electronic device can read the computer program, and the execution of the computer program by the at least one processor causes the electronic device to perform the solutions provided by any of the above embodiments.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in this disclosure may be performed in parallel, sequentially or in a different order,
the disclosure is not limited thereto so long as it achieves the desired results of the presently disclosed embodiments.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (9)
1. A full channel business intelligent monitoring and analyzing method is characterized by comprising the following steps:
acquiring historical call data of workers and user transaction service data, wherein the historical call data and the user transaction service data have a corresponding relation;
carrying out call content identification on the historical call data, and generating call characteristics of workers based on content identification results;
performing service execution efficiency evaluation according to the call duration of the historical call data and the service handling data of the user to generate service execution efficiency data of the staff;
constructing a business handling database of the staff according to the business execution efficiency data and the staff conversation characteristics;
identifying real-time access call data, and matching the service handling database according to the service type of the real-time access call data to obtain a staff matching value;
acquiring real-time call information of a worker;
and performing call access screening of the real-time access call data according to the real-time call information and the staff matching value.
2. The method of claim 1, wherein the method further comprises:
acquiring accumulated call data of workers;
dividing the accumulated call data according to a multi-level call period to obtain a multi-level call period division result;
obtaining a preset weight distribution value of the multi-level call cycle division result;
performing weighted calculation on the multi-level call cycle division result through the preset weight distribution value, and acquiring call access influence data according to the weighted calculation result;
and performing call access screening of the real-time access call data through the call access influence data, the real-time call information and the staff matching value.
3. The method of claim 1, wherein the call content recognition is performed on the historical call data, and wherein generating a staff call characteristic based on the content recognition result further comprises:
constructing a dialectical feature set;
performing the dialect matching of the historical call data through the dialect feature set to obtain a dialect matching result;
performing matching analysis of the dialect according to the matching result of the dialect and the business data handled by the user to obtain an analysis result of matching degree of the dialect;
and obtaining the conversation characteristics of the staff according to the conversation matching result and the conversation matching degree analysis result.
4. The method of claim 3, wherein the method further comprises:
obtaining user basic information of the user;
performing conversational adaptation evaluation according to the user basic information and the conversational matching result to obtain a conversational adaptation evaluation result;
adding the speech adaptation evaluation result to the staff speech characteristic.
5. The method of claim 4, wherein the method further comprises:
analyzing the service handling speed influence according to the user basic information to obtain a speed influence value analysis result;
and compensating the service execution efficiency data according to the speed influence value analysis result, and correcting the service handling database based on the compensation result.
6. The method of claim 1, wherein the method further comprises:
constructing a training optimization direction database of the staff based on the business handling database;
feeding the training optimization direction database back to corresponding workers and generating a continuous monitoring interval;
and carrying out optimization supervision evaluation and feedback of workers through the continuous monitoring interval.
7. The method of claim 1, wherein the method further comprises:
judging whether the real-time access call data is an access new user;
when the real-time access call data is not to access a new user, obtaining historical connection data;
and performing call access screening according to the call access priority evaluation result.
8. A full channel business intelligent monitoring analysis system, the system comprising:
the data acquisition module is used for acquiring historical call data of workers and user transaction service data, wherein the historical call data and the user transaction service data have a corresponding relation;
the call content identification module is used for identifying call contents of the historical call data and generating call characteristics of workers based on content identification results;
the service execution efficiency evaluation module is used for evaluating the service execution efficiency according to the call duration of the historical call data and the service handling data of the user to generate the service execution efficiency data of the staff;
the business handling database construction module is used for constructing a business handling database of the staff through the business execution efficiency data and the staff conversation characteristics;
the service matching module is used for identifying real-time access call data, matching the service handling database according to the service type of the real-time access call data and obtaining a staff matching value;
the real-time call information acquisition module is used for acquiring real-time call information of a worker;
and the call access screening module is used for carrying out call access screening on the real-time access call data according to the real-time call information and the staff matching value.
9. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-7.
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202211629709 | 2022-12-19 | ||
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