CN117726231A - Video customer service quality analysis method - Google Patents
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Abstract
The invention relates to the technical field of video customer service, and discloses a video customer service quality analysis method, wherein a computer comprises a data acquisition module, a data analysis module and a data processing module, and the video customer service quality analysis method comprises the following steps: step one, classifying service quality evaluation by a data acquisition module, and transmitting a data set to a data analysis module; step two, the data analysis module numbers the service quality evaluation data set according to the characteristics of the service quality evaluation data set, establishes a judgment data set through a network connection database, numbers the judgment data set, calculates a satisfaction index Myzs according to the service quality evaluation data set and the judgment data set, and transmits the satisfaction index Myzs to the data processing module through a network; and thirdly, the data processing module judges the maintenance mode according to the satisfaction index Myzs, generates a signal and outputs data through the return visit unit and the prompt unit.
Description
Technical Field
The invention relates to the technical field of video customer service, and discloses a video customer service quality analysis method.
Background
With the continuous development of technology, people's life style and consumption habits are also continuously changing. In this process, the customer service industry is also continually undergoing innovations and upgrades. Video customer service, an emerging form of customer service, has become an important choice for many businesses and organizations in providing customer service. Video customer service refers to providing real-time and face-to-face consultation services for clients by means of video call. Compared with the traditional telephone customer service, the video customer service can enable the customer to more intuitively know the image and attitude of the service personnel, and meanwhile, the service personnel can more clearly know the demands and problems of the customer. In addition, the video customer service can realize the simultaneous online communication of multiple people, and the communication efficiency is improved. The video customer service has the characteristics of real-time performance, interactivity and visualization. The real-time performance of the video customer service can be achieved, and the customer can communicate with service personnel in real time in a video call mode, so that the problem is solved. This real-time performance is not comparable to telephone customer service. Secondly, video customer service has interactivity. The clients can communicate with the service personnel face to face in a video call mode, so that the demands and the problems of the clients are better expressed. In addition, the video customer service also has the characteristic of visualization. The customer can see the image and expression of the service personnel through the video call mode, so that the meaning of the service personnel can be better understood. Video customer service can improve customer satisfaction. Through the video call mode, the customer can more intuitively know the image and attitude of the service personnel, thereby improving the satisfaction degree of the service. Secondly, the video customer service can improve the communication efficiency. The clients can communicate with service personnel face to face in a video call mode, so that the problems can be solved more quickly. In addition, video customer service can also reduce the misunderstanding rate. By means of the video call, clients and service personnel can know the meaning of the other party more clearly, and therefore the possibility of misunderstanding is reduced. In practical applications, video customer service may be applied to a variety of scenarios. For example, in the e-commerce industry, customers can communicate with customer service personnel face to face in a video call manner, so as to know commodity details, consult shopping problems and the like. In the financial industry, customers can communicate with bank staff face to face in a video call mode, transact business, consult financial problems and the like. In the education industry, students can communicate face to face with teachers in a video call mode, and answer academic questions, consultation courses and the like. In the medical industry, patients can communicate face to face with doctors in a video call mode, consult illness conditions, subscribe to register and the like.
Aiming at video customer service, a video customer service quality analysis system collects statistical customer satisfaction data, and then a conclusion is obtained through system analysis, so that enterprises are helped to improve customer satisfaction and enhance competitive advantage. The video customer service quality analysis system is a tool for effectively improving the video customer service level, and has the significance of improving customer satisfaction. It covers a number of aspects from monitoring of customer interactions to employee performance assessment. In practice, such systems may employ advanced "audio and video+ai" techniques to optimize the existing customer service patterns of the enterprise. For example, the AnyChat video customer service scheme provides rich video service functions such as real-time audio and video call, video tag dotting, screen sharing, intelligent guiding, remote assistance and the like so as to meet the audio and video real-time communication requirements of enterprises in different application scenes. In addition, some solutions also have the capability of multi-channel access, such as full-channel access of webpages, weChat public numbers, applets, APP, H5 and the like, break time and service network restriction, support real-time one-key video request initiation, realize remote customer service and transact business at any time. These functions enable the video customer service quality of service analysis system to accommodate diverse customer needs and complex business scenarios. For quality of service assessment, the system typically records and analyzes various data that interact with the customer, including call quality, latency, problem-solving efficiency, etc. Through these data, the enterprise can learn about the needs and pain points of the clients, further optimizing the products and services. Meanwhile, through evaluation of staff performance, enterprises can also improve the service level and the working efficiency of staff.
At present, when a video is about to hang up, the traditional video customer service quality analysis method guides a customer to select a star grade on an interactive interface to evaluate service satisfaction, and cannot collect statistical detailed feedback content, so that real service quality cannot be analyzed in detail.
Disclosure of Invention
(one) solving the technical problems
Aiming at the defects of the prior art, the invention provides a video customer service quality analysis method which has the advantages of comprehensive service evaluation, no dead angle, better service experience optimization and the like, and solves the problems that statistical detailed feedback content cannot be collected for analysis and customer complaint service experience is poor.
(II) technical scheme
In order to achieve the purposes of comprehensively evaluating the service without dead angles and optimizing the service experience, the invention provides the following technical scheme: the video customer service quality analysis method is characterized in that the video customer service quality analysis method is analyzed through a recording element, a database and a computer, the computer comprises a data acquisition module, a data analysis module and a data processing module, and the video customer service quality analysis method comprises the following steps:
step one, classifying service quality evaluation by a data acquisition module, and transmitting a data set to a data analysis module;
step two, the data analysis module numbers the service quality evaluation data set according to the characteristics of the service quality evaluation data set, establishes a judgment data set through a network connection database, numbers the judgment data set, and calculates a satisfaction index Myzs according to the service quality evaluation data set and the judgment data set;
and thirdly, the data processing module judges the maintenance mode according to the satisfaction index Myzs, generates a signal and outputs data through the return visit unit and the prompt unit.
Preferably, the recording element adopts a stepwise acquisition method, and the data acquisition module acquires the service quality evaluation data set in real time through the recording element and classifies the service quality evaluation data set.
Through the technical scheme, the recording element is used for periodically collecting customer pre-sale service evaluation and after-sale service evaluation to help enterprises to better know the demands and the expectations of customers, so that more personalized services are provided, feedback opinions before and after-sale of the customers are collected through classification, and the enterprises can timely adjust own service strategies to meet the demands of the customers.
Preferably, the collected service quality evaluation data set is composed of an before-sale service data set and an after-sale service data set, and the data collection module transmits the collected service quality evaluation data set to the data analysis module through a network.
Through the technical scheme, the enterprise can intuitively know the real evaluation of the client on the commodity quality, the service attitude and the logistics speed through the pre-sale evaluation of the client before purchasing the commodity or the service, the pre-sale service is optimized to be beneficial to improving the sales, the post-sale evaluation can help the enterprise to know the satisfaction of the client on the commodity or the service, the improvement is performed according to the feedback of the client, the enterprise is beneficial to maintaining good brand public praise, the acquisition service evaluation is comprehensive, no dead angle exists, and the service experience feeling is better.
Preferably, the data analysis module numbers the pre-sales service data set and the after-sales service data set according to the service quality evaluation data set characteristics, wherein the pre-sales service data set numbers are SQ 1 、SQ 2 、SQ 3 SQn, after-sales service dataset number SH 1 、SH 2 、SH 3 、...SH n 。
Through the technical scheme, the service quality evaluation data set features number the pre-sale service data set and the after-sale service data set, and the service quality evaluation data set features number after classified statistics, so that the subsequent rapid analysis and processing are facilitated.
Preferably, the data analysis module establishes a decision data set through a network connection database and numbers the decision data set number and the service quality evaluation data set numberOne-to-one correspondence, the number of the judging data set is Y sq 、Y sh 、L sq And L sh 。
By the technical scheme, the data set numbers are judged to correspond to the service quality evaluation data set numbers one by one, and the classification numbers correspond to the pre-sale satisfaction evaluation, the after-sale satisfaction evaluation, the pre-sale dissatisfaction evaluation and the after-sale dissatisfaction evaluation.
Preferably, the data analysis module calculates the satisfaction index Myzs according to the service quality evaluation data set and the decision data set, and the calculation formula is as follows:
in the formula, myzs represents a satisfaction index,representing the pre-sales quality of service satisfaction rating-ratio, < >>Indicating the post-sale quality of service satisfaction rating.
Through the technical scheme, the satisfaction index Myzs simultaneously comprises two values of the pre-sale service quality satisfaction evaluation ratio and the after-sale service quality satisfaction evaluation ratio, and according to the satisfaction index Myzs, a manager can quickly know the analysis result of the video customer service quality.
Preferably, the data processing module judges the maintenance mode according to the satisfaction index Myzs, when any one of the satisfaction indexes Myzs is smaller than 0.6, a return visit signal is generated, and when any one of the satisfaction indexes Myzs is larger than or equal to 0.6, a prompt signal is generated.
Through the technical scheme, the data processing module judges the maintenance mode according to the satisfaction index Myzs, generates the return visit signal and the prompt signal, is beneficial to enterprises to maintain customer groups, improves customer satisfaction and loyalty, and improves the competitive advantage of the enterprises.
Preferably, the data processing module performs telephone return visit through the return visit unit according to the return visit signal.
Through the technical scheme, any one of the satisfaction indexes Myzs is smaller than 0.6, so that the customer is high in dissatisfaction of pre-sale or after-sale service, high in complaint risk is shown, the customer has complaint demands because the hope problem is solved, the customer is expected to pay attention and importance to the enterprise after effective feedback, the complaint is effectively and timely processed, the good customer relationship is maintained by the enterprise, and the customer can be earned for the enterprise.
Preferably, the data processing module sends thank you short messages through the prompt unit according to the prompt signal.
According to the technical scheme, any one of the satisfaction indexes Myzs is larger than or equal to 0.6, so that the satisfaction of the customers for the pre-sale or after-sale service is high, and the customers can maintain good customer relations by thanking the customers for evaluating the service quality through the thanking short message.
Preferably, the data processing module is connected with the database through a network, and transmits the satisfaction index Myzs to the database for storage.
Through the technical scheme, each satisfaction index Myzs is stored, so that after the enterprises adjust and optimize product service, the satisfaction indexes Myzs before and after optimization are compared, the effectiveness of optimization adjustment is ensured, customer satisfaction indexes are measured regularly, and high-quality video customer service is ensured.
Compared with the prior art, the invention provides a video customer service quality analysis method, which has the following beneficial effects:
1. according to the invention, a recording element adopts a staged collection method, a data collection module classifies a service quality evaluation data set into a pre-sale service data set and an after-sale service data set, a data analysis module numbers the service quality evaluation data set according to the characteristics of the service quality evaluation data set, a data analysis module establishes a judgment data set through a network connection database and numbers the judgment data set, and the data analysis module calculates a satisfaction index Myzs according to the service quality evaluation data set and the judgment data set, wherein the satisfaction index Myzs comprises two numerical values of the satisfaction evaluation duty ratio of the pre-sale service quality and the satisfaction evaluation duty ratio of the after-sale service quality, and a manager can quickly know the analysis result of the service quality of video customer service according to the satisfaction index Myzs, so that the comprehensive dead angle-free beneficial effect of service evaluation is achieved.
2. According to the invention, a return visit signal or a prompt signal is generated according to the satisfaction index Myzs by the data processing module, when any one of the satisfaction indexes Myzs is smaller than 0.6, the unsatisfied occupation of customers for pre-sale or after-sale service is indicated to be higher, the complaint risk is higher, the customers have complaint demands because the hope problem is solved, the customers expect to pay attention to and attach importance to enterprises after effective feedback, the complaints are effectively and timely processed, the enterprises are helped to maintain good customer relations, when any one of the satisfaction indexes Myzs is larger than or equal to 0.6, the satisfied occupation of the customers for the pre-sale or after-sale service is indicated to be higher, the evaluation of the service quality by the thanking short message thank customers is favorable for the enterprises to maintain good customer relations, and the beneficial effects of optimizing the service experience are achieved.
Drawings
FIG. 1 is a schematic diagram of an analytical method according to the present invention;
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a method for analyzing quality of service of a video customer service includes the steps of:
step one, classifying service quality evaluation by a data acquisition module, and transmitting a data set to a data analysis module;
the recording element adopts a staged collection method, the data collection module collects service quality evaluation data sets in real time through the recording element and classifies the service quality evaluation data sets, the recording element is used for staged collection of customer pre-sale service evaluation and after-sale service evaluation to help enterprises to better know the demands and expectations of customers, so that more personalized service is provided, the enterprises can timely adjust own service strategies through sorting and collecting feedback ideas of the customers, the collected service quality evaluation data sets are composed of the pre-sale service data sets and the after-sale service data sets, the data collection module transmits the collected service quality evaluation data sets to the data analysis module through a network, the enterprises can intuitively know real evaluation of the quality, service attitude and logistics speed of the customers before purchasing the commodities or the services, the after-sale evaluation is beneficial to improving sales amount, the enterprises can know the satisfaction degree of the customers to the commodities or the services, and the enterprises can improve the feedback according to the customers, the collected service evaluation is beneficial to comprehensively maintaining good brand public praise, the service evaluation has no dead angle, and the service experience is better.
Step two, the data analysis module numbers the service quality evaluation data set according to the characteristics of the service quality evaluation data set, establishes a judgment data set through a network connection database, numbers the judgment data set, and calculates a satisfaction index Myzs according to the service quality evaluation data set and the judgment data set;
the data analysis module numbers the before-market service data set and the after-market service data set according to the service quality evaluation data set characteristics, wherein the number of the before-market service data set is SQ 1 、SQ 2 、SQ 3 、...SQ n After-sales service data set number SH 1 、SH 2 、SH 3 、...SH n The data analysis module establishes a judging data set through a network connection database, and carries out numbering, wherein the judging data set number corresponds to the service quality evaluation data set number one by one, and the judging data set number is Y sq 、Y sh 、L sq And L sh Classified braidingThe number corresponds to the pre-sale satisfaction evaluation, the after-sale satisfaction evaluation, the pre-sale dissatisfaction evaluation and the after-sale dissatisfaction evaluation, and the data analysis module calculates a satisfaction index Myzs according to the service quality evaluation data set and the judgment data set, wherein the calculation formula is as follows:
in the formula, myzs represents a satisfaction index,representing the pre-sales quality of service satisfaction rating-ratio, < >>The after-sales service quality satisfaction evaluation duty ratio is represented, the satisfaction index Myzs simultaneously comprises two values of the before-sales service quality satisfaction evaluation duty ratio and the after-sales service quality satisfaction evaluation duty ratio, and according to the satisfaction index Myzs, a manager can quickly know the analysis result of the video customer service quality.
And thirdly, the data processing module judges the maintenance mode according to the satisfaction index Myzs, generates a signal and outputs data through the return visit unit and the prompt unit.
The data processing module judges the maintenance mode according to the satisfaction indexes Myzs, generates a return visit signal and a prompt signal, is beneficial to enterprises to maintain customer groups, improves customer satisfaction and loyalty, improves enterprise competitive advantage, generates the return visit signal when any one of the satisfaction indexes Myzs is smaller than 0.6, and generates the prompt signal when any one of the satisfaction indexes Myzs is larger than or equal to 0.6.
The data processing module carries out telephone return visit through the return visit unit according to the return visit signal, and the return visit signal is less than 0.6 because any item in the satisfaction index Myzs, indicates that customers are dissatisfied with pre-sale or after-sale service and occupy higher, have higher complaint risks, and customers have complaint demands because hope that the problems are solved, expect to get the attention and the attention of enterprises after effective feedback, effectively and timely process complaints, help enterprises maintain good customer relations, and win the high loyalty of customers for the enterprises.
The data processing module sends thank you short messages through the prompt unit according to prompt signals, wherein any item in the satisfaction index Myzs is larger than or equal to 0.6, the prompt signals indicate that the customer is satisfied with the pre-sale or after-sale service more than the pre-sale service, and the good customer relationship is maintained by the evaluation of the thank you short messages thank you customers on the service quality.
The data processing module is connected with the database through a network, transmits the satisfaction index Myzs to the database for storage, stores the satisfaction index Myzs each time, and is convenient for enterprises to adjust and optimize product service, and the satisfaction index Myzs before and after optimization is compared, so that the effectiveness of optimization adjustment is ensured, the customer satisfaction index is measured regularly, and high-quality video customer service is ensured.
Although embodiments of the present invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made therein without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. A video customer service quality analysis method is characterized in that: the video customer service quality analysis method is characterized in that the analysis is carried out through a recording element, a database and a computer, the computer comprises a data acquisition module, a data analysis module and a data processing module, and the video customer service quality analysis method comprises the following steps:
step one, classifying service quality evaluation by a data acquisition module, and transmitting a data set to a data analysis module;
step two, the data analysis module numbers the service quality evaluation data set according to the characteristics of the service quality evaluation data set, establishes a judgment data set through a network connection database, numbers the judgment data set, calculates a satisfaction index Myzs according to the service quality evaluation data set and the judgment data set, and transmits the satisfaction index Myzs to the data processing module through a network;
and thirdly, the data processing module judges the maintenance mode according to the satisfaction index Myzs, generates a signal and outputs data through the return visit unit and the prompt unit.
2. The video customer service quality analysis method as claimed in claim 1, wherein: the recording element adopts a staged collection method, and the data collection module collects the service quality evaluation data set in real time through the recording element and classifies the service quality evaluation data set.
3. The video customer service quality analysis method as claimed in claim 2, wherein: the data acquisition module transmits the acquired service quality evaluation data set to the data analysis module through a network.
4. A method for analyzing the quality of service of a video customer service according to claim 3, wherein: the data analysis module numbers the pre-sales service data set and the after-sales service data set according to the service quality evaluation data set characteristics, wherein the number of the pre-sales service data set is SQ 1 、SQ 2 、SQ 3 、...SQ n The after-sales service data set number is SH 1 、SH 2 、SH 3 、...SH n 。
5. The method for analyzing the quality of service of video customer service according to claim 4, wherein: the data analysis module establishes a judging data set through a network connection database and numbers the judging data set, wherein the judging data set numbers correspond to the service quality evaluation data set numbers one by one, and the judging data set numbers are Y sq 、Y sh 、L sq And L sh 。
6. The method for analyzing the quality of service of video customer service according to claim 5, wherein: the data analysis module calculates a satisfaction index Myzs according to the service quality evaluation data set and the judgment data set, and the calculation formula is as follows:
in the formula, myzs represents a satisfaction index,representing the pre-sales quality of service satisfaction rating-ratio, < >>Indicating the post-sale quality of service satisfaction rating.
7. The video customer service quality analysis method as defined in claim 6, wherein: the data processing module judges a maintenance mode according to satisfaction indexes Myzs, when any one of the satisfaction indexes Myzs is smaller than 0.6, a return visit signal is generated, and when any one of the satisfaction indexes Myzs is larger than or equal to 0.6, a prompt signal is generated.
8. The video customer service quality analysis method as defined in claim 7, wherein: and the data processing module performs telephone return visit through the return visit unit according to the return visit signal.
9. The video customer service quality analysis method as defined in claim 7, wherein: and the data processing module sends thank you short messages through the prompting unit according to the prompting signals.
10. The video customer service quality analysis method as defined in claim 7, wherein: the data processing module is connected with the database through a network and transmits the satisfaction index Myzs to the database for storage.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108564968A (en) * | 2018-04-26 | 2018-09-21 | 广州势必可赢网络科技有限公司 | A kind of method and device of evaluation customer service |
| CN111324865A (en) * | 2020-02-24 | 2020-06-23 | 浪潮天元通信信息系统有限公司 | Storefront satisfaction intelligent analysis method and system based on Internet of things |
| CN112966568A (en) * | 2021-02-09 | 2021-06-15 | 中国工商银行股份有限公司 | Video customer service quality analysis method and device |
| CN114254885A (en) * | 2021-12-07 | 2022-03-29 | 中信银行股份有限公司 | Intelligent scoring method and system based on VR customer service |
| CN114372701A (en) * | 2022-01-07 | 2022-04-19 | 中国工商银行股份有限公司 | Method and device for evaluating customer service quality, storage medium and equipment |
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- 2023-12-20 CN CN202311763278.XA patent/CN117726231A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108564968A (en) * | 2018-04-26 | 2018-09-21 | 广州势必可赢网络科技有限公司 | A kind of method and device of evaluation customer service |
| CN111324865A (en) * | 2020-02-24 | 2020-06-23 | 浪潮天元通信信息系统有限公司 | Storefront satisfaction intelligent analysis method and system based on Internet of things |
| CN112966568A (en) * | 2021-02-09 | 2021-06-15 | 中国工商银行股份有限公司 | Video customer service quality analysis method and device |
| CN114254885A (en) * | 2021-12-07 | 2022-03-29 | 中信银行股份有限公司 | Intelligent scoring method and system based on VR customer service |
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