CN117196399B - Customer service center operation supervision optimization system based on data analysis - Google Patents
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Abstract
The invention discloses a customer service center operation supervision optimization system based on data analysis, which belongs to the technical field of customer service center operation supervision optimization and comprises a monitoring module, a monitoring analysis module and a verification simulation module; the monitoring module is used for monitoring the operation of the customer service center station in real time to obtain corresponding monitoring data; the monitoring analysis module is used for analyzing the monitoring data to obtain each recommended mode corresponding to each monitoring item; the verification simulation module is used for performing simulation verification on each recommended mode, acquiring each recommended mode and generating simulation data corresponding to each recommended mode; the simulation data comprises a simulation process and a reference process; the simulation data are sent to customer service personnel and management personnel in a preset evaluation list; and obtaining scores corresponding to the customer service personnel and the manager, calculating corresponding application values according to the scores, and eliminating the recommended mode with the application value lower than a threshold value X2.
Description
Technical Field
The invention belongs to the technical field of supervision and optimization of customer service center operation, and particularly relates to a customer service center operation supervision and optimization system based on data analysis.
Background
With the development of the internet and the advancement of technology, more and more enterprises are aware of the importance of customer services. The customer service center serves as an important customer service platform and plays important roles in processing customer consultation, solving problems, providing support and other tasks. However, the conventional customer service center operation mode often has the problems of low efficiency, unstable service quality and the like, and particularly, as the service time goes, all customer service personnel and management personnel are used to the working mode of the current customer service center, and the working mode is basically cured and is difficult to obtain corresponding optimization; moreover, even if the manager makes a change in the working mode, some interference may be caused by the customer service personnel, so that it is difficult to exert the target effect;
Therefore, in order to solve the problem of operation solidification of the current customer service center, the invention provides a customer service center operation supervision optimization system based on data analysis, which realizes real-time supervision optimization of the customer service center.
Disclosure of Invention
In order to solve the problems of the scheme, the invention provides a customer service center operation supervision optimization system based on data analysis.
The aim of the invention can be achieved by the following technical scheme:
The customer service center operation supervision optimization system based on data analysis comprises a monitoring module, a monitoring analysis module, a verification simulation module and a platform analysis module;
The monitoring module is used for monitoring the operation of the customer service center station in real time to obtain corresponding monitoring data.
Further, the working method of the monitoring module comprises the following steps:
Acquiring the working content of the customer service center, and determining corresponding monitoring items according to the working content;
And carrying out corresponding data monitoring based on the monitoring items to obtain monitoring data corresponding to the monitoring items.
The monitoring analysis module is used for analyzing the monitoring data to obtain each recommended mode corresponding to each monitoring item.
Further, the working method of the monitoring and analyzing module comprises the following steps:
Acquiring monitoring data corresponding to each monitoring item in real time;
identifying each monitoring item, and matching corresponding reference retrieval ranges according to each monitoring item; retrieving a corresponding primary selection mode based on the reference retrieval range; screening the primary selection modes to obtain various modes to be selected;
and evaluating the mode to be selected based on the corresponding monitoring data to obtain a corresponding evaluation value, and marking the mode to be selected, of which the evaluation value is not lower than a threshold value X1, as a recommended mode.
Further, the method for evaluating the mode to be selected comprises the following steps:
Comparing and analyzing each mode to be selected with the monitoring data to obtain an optimized value corresponding to each mode to be selected; obtaining implementation values corresponding to the alternative modes;
And marking the optimized value and the implementation value as YH and SP respectively, and calculating a corresponding evaluation value PFG according to an evaluation formula PFG=YH-1.3 SP, wherein the value range of YH is [0, 30], and the value range of SP is [0, 10].
The verification simulation module is used for performing simulation verification on each recommended mode, acquiring each recommended mode and generating simulation data corresponding to each recommended mode; the simulation data comprises a simulation process and a reference process;
The simulation data are sent to customer service personnel and management personnel in a preset evaluation list; and obtaining scores corresponding to the customer service personnel and the manager, calculating a corresponding application value according to the scores, rejecting the recommended modes with the application value lower than a threshold value X2, sequencing the rest recommended modes according to the sequence from the high application value to the low application value to obtain a sequencing list, sending the sequencing list to the corresponding manager, and carrying out optimization decision by the manager.
Further, the calculation method of the application value includes:
Marking scores corresponding to the customer service personnel and the manager as PFi and PFj respectively, wherein i=1, 2, … …, n and n are positive integers; j=1, 2, … …, m being a positive integer;
Evaluating formulas according to applications And calculating a corresponding application value YMF, wherein b1 and b2 are weight coefficients corresponding to customer service personnel and management personnel respectively, and the value range is 0< b1<1,0< b2<1.
Further, b1> b2.
Further, the system also comprises a platform analysis module, wherein the platform analysis module is used for analyzing the current customer service center and judging whether the change is needed.
Further, the working method of the platform analysis module comprises the following steps:
Real-time recording is carried out on optimization of the customer service center, corresponding optimization modes are identified, and corresponding updated values are matched according to the identified optimization modes;
And accumulating the corresponding updated values in real time to obtain an integrated value, comparing the obtained integrated value with a threshold value X3 in real time, generating change information when the integrated value is larger than the threshold value X3, and sending the change information to corresponding management personnel.
Compared with the prior art, the invention has the beneficial effects that:
The monitoring module, the monitoring analysis module and the verification simulation module are matched with each other to realize real-time monitoring analysis of the existing customer service center station and find out corresponding optimization points; generating a corresponding optimization mode for evaluation; the method solves the problem of operation and solidification of the current customer service center, realizes dynamic analysis, and discovers an optimization point; the verification simulation of the optimization mode is carried out through the verification simulation module, so that the problem that staff contradicts possibly caused by direct application is avoided, the problem that the working efficiency is lower than that of the non-optimization mode is caused, and the application effect of the application can be exerted by the application optimization mode; the current optimization decision is avoided, and only the decision is made by the manager, so that the use experience of customer service personnel of the first-line application is fully considered.
By setting the platform analysis module, the current customer service center is evaluated in real time, whether updating is needed or not is judged, and safe and stable operation of the customer service center is ensured.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings can be obtained according to these drawings without inventive effort to a person skilled in the art.
Fig. 1 is a functional block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, 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.
As shown in fig. 1, a customer service center operation supervision optimization system based on data analysis comprises a monitoring module, a monitoring analysis module, a verification simulation module and a platform analysis module;
the monitoring module is used for monitoring the operation of the customer service center, and collecting the operation process of the customer service center in real time, and the specific method comprises the following steps:
Acquiring the working content of a customer service center, and determining corresponding monitoring items according to the working content; namely, according to various working contents, working flows and the like of the current customer service center, monitoring items suitable for the customer service center are determined, and the contents served by different customer service center may have differences, so that specific analysis is needed; in the actual application process, various customer service center stations currently existing can be summarized, monitoring items corresponding to working contents of the customer service center stations are analyzed, reference search ranges of the monitoring items are set, the reference search ranges are ranges similar to the working processing contents corresponding to the monitoring items, such as data summation, currently are manual summation, the reference search ranges are various summation modes, computer summation and the like; and establishing a corresponding matching library, and then rapidly determining monitoring items according to corresponding working contents.
And carrying out corresponding data monitoring according to the obtained monitoring items, and obtaining monitoring data corresponding to each monitoring item in real time.
The monitoring analysis module is used for analyzing the obtained monitoring data and judging whether an optimized flow exists or not, and the specific process is as follows:
Acquiring monitoring data corresponding to each monitoring item in real time;
Identifying each monitoring item, and matching corresponding reference retrieval ranges according to the identified monitoring items; based on the existing big data analysis technology and other modes, other processing modes except the working mode corresponding to the current monitoring item are searched according to the obtained reference search range, namely, the existing related technologies such as ChatGPT and the like are utilized to analyze which modes except the current processing mode can realize the processing effect; marking the obtained processing modes as primary selection modes, and screening the obtained primary selection modes to obtain various modes to be selected; the mode to be selected is a processing mode which can be applied based on the current client platform; based on the application analysis of the current customer service center, judging whether each primary selection mode can be applied, eliminating the application, and marking the rest primary selection modes as modes to be selected, wherein the application standard is not the direct application, but the application standard is adjusted to be applicable to meet the application requirements;
specifically, a corresponding screening model can be established based on a CNN network or a DNN network, a corresponding training set is established for training in a manual mode, the training set comprises customer service center information, each primary selection mode, each corresponding mode to be selected and corresponding implementation value, the implementation value is evaluated according to the change amount and the change difficulty of application, the larger the change amount and the change difficulty, the larger the implementation value, and the value range is [0, 10]; the screening model after successful training screens each primary selection mode to obtain a corresponding mode to be selected and a corresponding implementation value, and because the neural network is the prior art in the field, the specific establishment and training process is not described in detail in the invention.
Comparing and analyzing the obtained modes to be selected with the monitoring data, and analyzing whether the processing effect of each mode to be selected is better than the processing mode corresponding to the monitoring data and the corresponding optimizing value, wherein the optimizing value is evaluated according to the optimizing degree and is divided into three critical limits, the optimizing values respectively corresponding to 0, 10 and 20 are respectively, the optimizing value is between a first critical line and a second critical line, the optimizing value is between 0 and 10, the optimizing value lower than the first critical line is all regarded as 0 and is better than a third critical line, the optimizing value is between 20 and 30, the first critical line corresponds to the processing mode effect corresponding to the monitoring data, and the other two standards which are set according to the existing effect are set according to the optimizing working efficiency and the burden degree;
specifically, a corresponding evaluation model can be established based on a CNN network or a DNN network, a training set is established in a manual mode to train, the training set comprises combinations of various modes to be selected and monitoring data which are set in a simulation mode and optimized values which are set correspondingly, and the evaluation model after successful training is used for analyzing to obtain the optimized values of various modes to be selected relative to the monitoring data which are not read;
And respectively marking the obtained optimized value and implementation value as YH and SP, wherein the value range of YH is [0, 30], calculating a corresponding evaluation value PFG according to an evaluation formula PFG=YH-1.3 SP, eliminating the candidate modes with the evaluation values lower than a threshold value X1, and marking the rest candidate modes as recommended modes.
The verification simulation module is used for performing simulation verification on each recommended mode, and performing comprehensive analysis from the aspect of actual application evaluation, and the specific process is as follows:
Acquiring each recommendation mode and generating simulation data corresponding to each recommendation mode; the simulation data is simulated and converted in a corresponding recommendation mode, so that the simulation data is used for simulating the situation of application in a customer service center, for example, the data in one form is correspondingly recorded into other forms, the current mode is recorded in a manual mode, the recommendation mode is to run a corresponding intelligent program, the corresponding recording is automatically carried out, the mode is combined with the customer service center to form a simulation process, the process corresponding to the current manual recording is acquired and used as reference to form simulated data, namely, the simulated data comprises a simulation process and a reference process, and the simulated data is generated from two angles of the recommendation mode and the monitoring data with the same application background; the method can be combined with the existing related technology to generate, such as combining with the existing neural network technology, establishing a corresponding artificial intelligent model, establishing a corresponding training set in an artificial mode to train, performing intelligent generation through the artificial intelligent model after successful training, generating a corresponding reference process based on the monitoring data, and forming a simulation process according to the reference process and the corresponding recommendation mode;
The obtained simulation data are sent to customer service personnel and management personnel, and application evaluation is carried out by the management personnel and the customer service personnel to obtain scores of the simulation data of the management personnel and the customer service personnel; the customer service personnel and the manager are preset corresponding evaluation lists by enterprises, and are sent according to the evaluation lists;
labeling customer service personnel as i, wherein i=1, 2, … …, n is a positive integer; marking manager as j, wherein j=1, 2, … …, m is a positive integer; corresponding scores are labeled PFi and PFj; the weight coefficients, namely the occupied proportion, between customer service personnel and an enterprise preset manager are respectively marked as b1 and b2, and b1 is larger than b2, b1 is smaller than b2 and needs to be set according to actual conditions; b1> b2 generally, the specific gravity of first-line customer service personnel is larger; the value range is 0< b1<1,0< b2<1;
Evaluating formulas according to applications Calculating a corresponding application value YMF, eliminating recommended modes with application values lower than a threshold value X2, sequencing the rest recommended modes according to the sequence from high application values to low application values, obtaining a sequencing list, sending the sequencing list to corresponding management personnel, deciding by the management personnel, determining whether to optimize or not, and optimizing according to which mode.
The monitoring module, the monitoring analysis module and the verification simulation module are matched with each other to realize real-time monitoring analysis of the existing customer service center station and find out corresponding optimization points; generating a corresponding optimization mode for evaluation; the method solves the problem of operation and solidification of the current customer service center, realizes dynamic analysis, and discovers an optimization point; the verification simulation of the optimization mode is carried out through the verification simulation module, so that the problem that staff contradicts possibly caused by direct application is avoided, the problem that the working efficiency is lower than that of the non-optimization mode is caused, and the application effect of the application can be exerted by the application optimization mode; the current optimization decision is avoided, and only the decision is made by the manager, so that the use experience of customer service personnel of the first-line application is fully considered.
In one implementation, as the current customer service center will have more and more optimization updates over time, the difference between the currently applied customer service center and the customer service center of the initial version will be larger and larger along with the increase of the types and the number of the optimization updates, in the process, the current customer service center may have more holes, the situations of easy customer data leakage and the like are easy to send, and the difference between the current customer service center and the customer service center of the initial version is too large, and the original customer service center is not suitable for the current customer service use environment and needs updating; therefore, in this embodiment, a platform analysis module is provided, and the platform analysis module is used to analyze the current customer service center to determine whether the change, that is, update, is needed. The specific process is as follows:
Real-time recording is carried out on optimization of the customer service center, corresponding optimization modes are identified, and corresponding updated values are matched according to the identified optimization modes;
Setting corresponding updated values for each optimization mode according to possible optimization modes, wherein the updated values are set according to the influence of the optimization mode on the customer service center, and an expert group discusses and sets corresponding updated value tables to perform corresponding matching;
Accumulating corresponding updated values in real time, marking the accumulated updated values as integrated values, namely accumulating all the updated values corresponding to optimization; and comparing the obtained integrated value with a threshold value X3 in real time, and generating change information and sending the change information to corresponding management personnel when the integrated value is larger than the threshold value X3.
By setting the platform analysis module, the current customer service center is evaluated in real time, whether updating is needed or not is judged, and safe and stable operation of the customer service center is ensured.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas which are obtained by acquiring a large amount of data and performing software simulation to obtain the closest actual situation, and preset parameters and preset thresholds in the formulas are set by a person skilled in the art according to the actual situation or are obtained by simulating a large amount of data.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (3)
1. The customer service center operation supervision optimization system based on data analysis is characterized by comprising a monitoring module, a monitoring analysis module and a verification simulation module;
the monitoring module is used for monitoring the operation of the customer service center station in real time to obtain corresponding monitoring data;
the monitoring analysis module is used for analyzing the monitoring data to obtain corresponding recommendation modes;
The verification simulation module is used for performing simulation verification on each recommended mode, acquiring each recommended mode and generating simulation data corresponding to each recommended mode; the simulation data comprises a simulation process and a reference process;
The simulation data are sent to customer service personnel and management personnel in a preset evaluation list; obtaining scores corresponding to the customer service personnel and the manager, calculating corresponding application values according to the scores, rejecting the recommended modes with the application values lower than a threshold value X2, sorting the rest recommended modes according to the sequence from high to low of the application values to obtain a sorted list, sending the sorted list to the corresponding manager, and carrying out optimization decision by the manager;
the working method of the monitoring and analyzing module comprises the following steps:
Acquiring monitoring data corresponding to each monitoring item in real time;
identifying each monitoring item, and matching corresponding reference retrieval ranges according to each monitoring item; retrieving a corresponding primary selection mode based on the reference retrieval range; screening the primary selection modes to obtain various modes to be selected;
Evaluating the mode to be selected based on the corresponding monitoring data to obtain a corresponding evaluation value, and marking the mode to be selected, of which the evaluation value is not lower than a threshold value X1, as a recommended mode;
The method for evaluating the mode to be selected comprises the following steps:
Comparing and analyzing each mode to be selected with the monitoring data to obtain an optimized value corresponding to each mode to be selected; obtaining implementation values corresponding to the alternative modes;
Marking the optimized value and the implementation value as YH and SP respectively, and calculating a corresponding evaluation value PFG according to an evaluation formula PFG=YH-1.3 SP, wherein the value range of YH is [0, 30], and the value range of SP is [0, 10];
The calculation method of the application value comprises the following steps:
Marking scores corresponding to the customer service personnel and the manager as PFi and PFj respectively, wherein i=1, 2, … …, n and n are positive integers; j=1, 2, … …, m being a positive integer;
Evaluating formulas according to applications Calculating a corresponding application value YMF, wherein b1 and b2 are weight coefficients corresponding to customer service personnel and management personnel respectively, and the value range is 0< b1<1,0< b2<1;
The system also comprises a platform analysis module, wherein the platform analysis module analyzes the current customer service center and judges whether the change is needed;
The working method of the platform analysis module comprises the following steps:
Real-time recording is carried out on optimization of the customer service center, corresponding optimization modes are identified, and corresponding updated values are matched according to the identified optimization modes;
And accumulating the corresponding updated values in real time to obtain an integrated value, comparing the obtained integrated value with a threshold value X3 in real time, generating change information when the integrated value is larger than the threshold value X3, and sending the change information to corresponding management personnel.
2. A customer service center operation supervision optimization system based on data analysis as defined in claim 1, wherein the working method of the monitoring module comprises:
Acquiring the working content of the customer service center, and determining corresponding monitoring items according to the working content;
And carrying out corresponding data monitoring based on the monitoring items to obtain monitoring data corresponding to the monitoring items.
3. A customer service center operation supervision optimization system based on data analysis according to claim 1, wherein b1> b2.
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| US11599842B2 (en) * | 2021-01-15 | 2023-03-07 | Oracle International Corporation | Modeling expectation mismatches |
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Patent Citations (5)
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| CN109858754A (en) * | 2018-12-28 | 2019-06-07 | 慕贝尔汽车部件（太仓）有限公司 | Conductive suggestion management method and device |
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