Water service customer service supervision system based on cloud platform

Abstract

The invention discloses a water service customer service supervision system based on a cloud platform, which belongs to the technical field of water service customer service and comprises a water service timeliness module, a monitoring module, a monitoring analysis module and a management module. The water affair timeliness module is used for carrying out service supervision on water affair tasks of customer service staff, carrying out dynamic timeliness evaluation and adjustment on data of the water affair tasks and setting timeliness coefficients corresponding to the water affair tasks; the monitoring module is used for monitoring the service process of customer service staff in real time to obtain service monitoring data of each customer service staff for each water task; the monitoring analysis module is used for monitoring and analyzing each water affair task of each customer service, acquiring evaluation data of each water affair task in real time, and evaluating a task service value of the corresponding water affair task according to the evaluation data and service monitoring data; generating a service evaluation curve according to each task service value; evaluating the customer service according to the service evaluation curve to obtain a comprehensive service score of the customer service; and the management module is used for performing management according to the comprehensive service score of each customer service.

Description

Technical Field

[0001] The present invention belongs to the technical field of water affairs customer service, and specifically is a water affairs customer service supervision system based on a cloud platform. Background Art

[0002] With the rapid development of information technology and the growing demand for customer service, efficient and accurate customer service has become an important part of corporate competitiveness in the modern service system. Traditional service systems often rely on manual allocation of work orders and simple time monitoring, which is inadequate when faced with large-scale, high-concurrency customer service requests. Specifically, there are the following problems:

[0003] Inefficient work order allocation: Under traditional methods, work order allocation is often based on a simple polling or random allocation mechanism, lacking intelligent and personalized considerations. As a result, some customer service staff are overloaded while others are relatively idle, affecting overall service efficiency.

[0004] Service timeliness is difficult to guarantee: Due to the lack of an effective work order timeliness supervision mechanism, some urgent or important work orders may be delayed due to untimely processing, seriously affecting customer satisfaction and corporate image.

[0005] Lack of data support for service optimization: Due to the lack of detailed work order processing data and analysis, it is difficult for enterprises to accurately identify bottlenecks and deficiencies in the service process, and thus cannot implement effective service optimization measures.

[0006] Based on this, the present invention provides a water customer service supervision system based on a cloud platform. Summary of the invention

[0007] In order to solve the problems existing in the above-mentioned solutions, the present invention provides a water customer service supervision system based on a cloud platform.

[0008] The purpose of the present invention can be achieved through the following technical solutions:

[0009] A water service customer service supervision system based on a cloud platform, including a water service timeliness module, a monitoring module, a monitoring and analysis module, and a management module;

[0010] The water service timeliness module is used to perform service supervision on the water service tasks of each customer service, identify the water service task data of each customer service in real time, perform dynamic timeliness evaluation and adjustment on each water service task data, and set the timeliness coefficient corresponding to each water service task for each customer service according to the adjustment record.

[0011] Furthermore, the method for dynamically evaluating and adjusting the timeliness of each water task data includes:

[0012] Step SA1: Obtain customer service task rules; set timeliness standards;

[0013] Step SA2: Establishing a timeliness judgment model according to the timeliness standard, wherein the timeliness judgment model is used to evaluate the water service task data of each customer service to determine whether each water service task meets the timeliness standard;

[0014] Step SA3: Analyze the water task data of each customer service through the timeliness judgment model to obtain the timeliness evaluation result corresponding to each water task, wherein the timeliness evaluation result includes a qualified timeliness evaluation and a failed timeliness evaluation;

[0015] Mark each water affairs task with a timeliness assessment result of unqualified timeliness assessment as an adjustment task;

[0016] Step SA4: reallocate each adjustment task according to the customer service task rules;

[0017] Step SA5: loop from step SA3 to step SA4.

[0018] Furthermore, the expression of the aging judgment model in step SA2 is:

[0019]

[0020] Where: s is the input data, the input data is the water task; the output data is the timeliness judgment value PX(s);

[0021] Analyze each water affairs task in the water affairs task data through the timeliness judgment model to obtain the timeliness judgment value corresponding to each water affairs task;

[0022] Mark the timeliness evaluation result with a timeliness judgment value of 1 as qualified

[0023] The aging evaluation result with an aging judgment value of 0 is marked as unqualified aging evaluation.

[0024] Furthermore, the method of setting the time efficiency coefficient corresponding to each type of water service task for each customer service according to the adjustment record includes:

[0025] Classify each water affairs task in the water affairs task data of each customer service to obtain classification data of each water affairs task;

[0026] Obtain the adjustment records of each customer service, classify the adjustment records according to each water service classification data, obtain the adjustment records corresponding to each water service classification data, and mark them as classification adjustment records;

[0027] Identify the corresponding classification timeliness value and adjustment timeliness value in real time according to the classification adjustment record;

[0028] According to the formula Calculate the time efficiency coefficient corresponding to each water service classification;

[0029] In the formula: μ is the aging coefficient; FZ is the classification aging value; TZ is the adjusted aging value; λ is the adjustment amplification value, λ≥1; BZ is the aging standard value.

[0030] The monitoring module is used to monitor the service process of the customer service in real time and obtain the service monitoring data of each customer service for each water task.

[0031] The monitoring and analysis module is used to monitor and analyze each water task of each customer service, obtain the corresponding customer's evaluation data on each water task in real time, evaluate the task service value of the corresponding water task based on the evaluation data and service monitoring data; generate a service evaluation curve based on the task service value corresponding to each water task of the customer; evaluate the customer service according to the service evaluation curve to obtain a comprehensive service score of the customer service.

[0032] Furthermore, the method for evaluating the task service value of the corresponding water affairs task based on the evaluation data and the service monitoring data includes:

[0033] Evaluate the corresponding water affairs tasks according to the evaluation data to obtain the initial evaluation value;

[0034] When the initial evaluation value is not less than the threshold value X1, the initial adjustment coefficient is marked as 1;

[0035] When the initial evaluation value is less than the threshold value X1, the service monitoring data corresponding to the water task is obtained, and the service monitoring data is analyzed to obtain the initial adjustment coefficient corresponding to the water task;

[0036] Identify the time efficiency coefficient, initial assessment value and initial adjustment coefficient corresponding to each water task;

[0037] Calculate the corresponding task service value according to the formula PA = μ × η × CP;

[0038] Where: PA is the task service value; μ is the timeliness coefficient; η is the initial adjustment coefficient; CP is the initial evaluation value.

[0039] Furthermore, the method for analyzing the service monitoring data includes:

[0040] Set each service evaluation indicator and the corresponding weight coefficient of each service evaluation indicator, and set each evaluation segment according to the value range of the initial evaluation value and the threshold value X1;

[0041] According to each service evaluation index, corresponding reference features are set for each evaluation segment; the evaluation segment corresponding to the initial evaluation value is identified, marked as a benchmark segment, and the reference features corresponding to the benchmark segment are identified;

[0042] Perform feature recognition on the service monitoring data according to each service evaluation indicator to obtain the monitoring features corresponding to each service evaluation indicator;

[0043] Combine each monitoring feature with the corresponding reference feature to obtain a feature evaluation combination corresponding to each service evaluation indicator, and mark a corresponding weight coefficient for each feature evaluation combination;

[0044] An adjustment evaluation model is established, and each characteristic evaluation combination is analyzed through the adjustment evaluation model to obtain a corresponding initial adjustment coefficient.

[0045] Furthermore, the method of evaluating according to the service evaluation curve includes:

[0046] Setting an evaluation period, dividing the service evaluation curve into a plurality of curve segments according to the evaluation period, marking the curve segments that have not been evaluated as unit segments; identifying the variable interval corresponding to the unit segment, and marking the variable interval as [t1, t2];

[0047] Fitting each unit segment to obtain a corresponding unit function, and marking the unit function as DY(t);

[0048] According to the formula Calculate the corresponding comprehensive service score;

[0049] Where: PB is the comprehensive service score.

[0050] The management module is used to manage according to the comprehensive service score of each customer service and establish a management library, and the management library is used to store the management measures corresponding to each comprehensive service score;

[0051] The comprehensive service score of each customer service is identified, corresponding management measures are matched from a management library according to the comprehensive service score, and the corresponding customer service is managed according to the management measures.

[0052] Compared with the prior art, the present invention has the following beneficial effects:

[0053] Through the cooperation between the water service time efficiency module, monitoring module, monitoring and analysis module and management module, the intelligent supervision of water service customer service is realized; through the mechanical energy time efficiency evaluation and adjustment, the inefficiency and delay problems that may be caused by traditional services are avoided. This significantly improves the overall service efficiency, shortens the customer waiting time, and enhances customer satisfaction; for the evaluation data with low scores, optimization and adjustment are carried out in terms of problem solving ability, service attitude, professional ability and other aspects to obtain a real customer service evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0055] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0056] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0057] like Figure 1 As shown, a water service customer service supervision system based on a cloud platform includes a water service timeliness module, a monitoring module, a monitoring analysis module and a management module;

[0058] The water service timeliness module is used to perform service supervision on the water service tasks of each customer service, and to identify the water service task data of each customer service in real time. The water service task data is composed of various water service tasks, such as various work order processing, customer calls, complaint feedback, etc.; dynamic timeliness evaluation and adjustment are performed on each water service task data, and the timeliness coefficient corresponding to each type of water service task is set for each customer service according to the adjustment records.

[0059] In one embodiment, a method for dynamically evaluating and adjusting each water task data includes:

[0060] Step SA1: Acquire customer service task rules, i.e., task allocation rules of the customer service system, priority processing rules of each water service task, and other related information, so as to subsequently allocate corresponding water service tasks according to the customer service task rules;

[0061] Set time efficiency standards. Time efficiency standards are set based on the platform's requirements for the time efficiency of various water affairs tasks. For example, different water affairs tasks or the same type of water affairs tasks may have different time efficiency due to different urgency of the tasks. These standards are manually set based on the platform's needs.

[0062] Step SA2: Establish a timeliness judgment model according to the timeliness standard. The timeliness judgment model is used to evaluate the water task data of each customer service to determine whether each water task can be completed under the premise of meeting the timeliness standard;

[0063] Step SA3: Analyze the water task data of each customer service by using the timeliness judgment model to obtain the timeliness evaluation results corresponding to each water task, where the timeliness evaluation results include qualified timeliness evaluation and unqualified timeliness evaluation; mark the water task with unqualified timeliness evaluation results as an adjustment task;

[0064] Step SA4: reallocate each adjustment task according to the customer service task rules;

[0065] Step SA5: looping step SA3 to step SA4 to achieve continuous adjustment.

[0066] In one embodiment, the timeliness judgment model is established based on a neural network such as a CNN network or a DNN network, and a corresponding training set is established manually for training. The training set includes input data and output data. The input data is the timeliness standard and water affairs task; the output data is the timeliness evaluation result; and the timeliness judgment model after successful training is used for analysis.

[0067] In one embodiment, the expression of the aging judgment model is: Where: s is the input data, and the input data is the water affairs task; the output data is the timeliness judgment value PX(s); the existing judgment technology is used to judge whether the water affairs task meets the timeliness standard, and the judgment is made in combination with the current time, timeliness standard, and water affairs task; the simulation judgment can also be made based on the existing simulation technology, that is, the simulation prediction is made according to the current actual situation to judge whether the completion of each water affairs task meets the timeliness standard;

[0068] Analyze each water affairs task in the water affairs task data through the timeliness judgment model to obtain the timeliness judgment value corresponding to each water affairs task;

[0069] Mark the timeliness evaluation result with a timeliness judgment value of 1 as qualified

[0070] The aging evaluation result with an aging judgment value of 0 is marked as unqualified aging evaluation.

[0071] In one embodiment, the method of setting the time efficiency coefficient corresponding to each type of water service task for each customer service according to the adjustment record includes:

[0072] Classify each water task in the water task data of each customer service to obtain classification data of each water task, that is, classify according to the corresponding water task type, and the specific classification standard of the platform shall prevail;

[0073] Get the adjustment record of each customer service, classify the adjustment record according to each water service classification data, obtain the adjustment record corresponding to each water service classification data, and mark it as a classification adjustment record; the classification adjustment record includes the original water service task quantity and adjustment quantity of the customer service in the water service classification. The adjustment quantity is negative if it is transferred away, and positive if it is increased due to adjustment. The specific value is the adjusted quantity;

[0074] According to the classification adjustment records, the corresponding classification timeliness value and adjustment timeliness value are identified in real time. The classification timeliness value is the original water affairs task quantity, and the adjustment timeliness value is the adjustment quantity.

[0075] According to the formula Calculate the time efficiency coefficient corresponding to each water service classification;

[0076] In the formula: μ is the timeliness coefficient; FZ is the classification timeliness value; TZ is the adjustment timeliness value; λ is the adjustment amplification value, which is greater than or equal to 1. If the management personnel does not set it, it will default to 1. It is set according to management needs to increase the proportion of adjusted water tasks and promote the improvement of customer service timeliness capabilities; BZ is the timeliness standard value, that is, the scheduled completion of water tasks set by the platform. It can be set according to the historical average value or directly set manually.

[0077] The monitoring module is used to monitor the service process of the customer service in real time and obtain the service monitoring data of the customer service for each water task; the monitoring is performed using the existing monitoring system and methods, and is generally performed based on the application of the customer service system.

[0078] The monitoring and analysis module is used to monitor and analyze each water task, obtain the evaluation data of each water task from the corresponding customers in real time, if there is no evaluation, the evaluation data is none, and the corresponding water task is evaluated according to the evaluation data to obtain an initial evaluation value; the evaluation value range adopts a percentage system, and the evaluation is performed according to the specific evaluation data, and the initial evaluation value corresponding to the absence of evaluation data is preset, generally defaulting to a qualified score or above; the customer evaluation system with a rating can be directly applied, or the evaluation data without a rating can be evaluated based on the existing rating system, as long as the corresponding rating criteria are set according to user needs;

[0079] When the initial evaluation value is not less than the threshold value X1, the initial adjustment coefficient is marked as 1; the threshold value X1 is determined according to the qualified standard recognized by the platform;

[0080] When the initial evaluation value is less than the threshold value X1, the service monitoring data corresponding to the water service task is obtained, and the service monitoring data is analyzed to obtain the corresponding initial adjustment coefficient. In this case, the initial adjustment coefficient is greater than or equal to 1; it is used to correct the initial evaluation value to avoid distortion of the evaluation of customer service personnel due to abnormally low scores of customers, because some customers tend to give extreme scores when they have opinions on a certain aspect of the service. If the normal score should be 50 points, it will be commented as 0 points, 1 point, etc.;

[0081] Identify the time efficiency coefficient, initial assessment value and initial adjustment coefficient corresponding to the water affairs task;

[0082] Calculate the corresponding task service value according to the formula PA = μ × η × CP;

[0083] Where: PA is the task service value; μ is the timeliness coefficient; η is the initial adjustment coefficient; CP is the initial evaluation value;

[0084] Generate a service evaluation curve based on the task service value corresponding to each water task of the customer; the horizontal axis is sorted according to the time sequence of completing the water tasks, and the vertical axis is the task service value;

[0085] Evaluate according to the service evaluation curve to obtain the customer service's comprehensive service score.

[0086] In one embodiment, a method for analyzing service monitoring data includes:

[0087] Set each service evaluation indicator and the corresponding weight coefficient of each service evaluation indicator, such as problem-solving ability, service attitude, professional ability and other service indicators, according to the actual requirements of the platform for customer service; set the corresponding reference characteristics for each evaluation segment according to each service evaluation indicator, and the evaluation segment is such as 0-10, 11-20, 21-30, or segmented from 0-20, which is set according to the needs of the platform; the reference characteristic is the characteristic data of the corresponding service evaluation indicator with the highest score in the segment, which can be set in combination with the evaluation standard of the initial evaluation value; no setting is required for the evaluation segment that is not less than the threshold X1;

[0088] Identify the evaluation segment corresponding to the initial evaluation value, mark it as a reference segment, and identify each reference feature corresponding to the reference segment;

[0089] Perform feature recognition on the service monitoring data according to each service evaluation indicator to obtain the monitoring feature corresponding to each service evaluation indicator, which refers to the feature data related to the service evaluation indicator;

[0090] Combine each monitoring feature with the corresponding reference feature to obtain a feature evaluation combination corresponding to each service evaluation indicator, and mark a corresponding weight coefficient for each feature evaluation combination;

[0091] A corresponding adjustment evaluation model is established based on a neural network such as a CNN network or a DNN network to analyze each feature evaluation combination, determine the reference feature that actually serves the benchmark segment for comparison, and determine whether it exceeds the service standard, and then output the corresponding initial adjustment coefficient according to the service comparison situation and the weight coefficient of each service evaluation indicator. If all do not exceed the corresponding reference feature, the initial adjustment coefficient is 1, and the initial adjustment coefficient is set comprehensively according to the degree of exceeding and the weight coefficient; a corresponding training set is established manually for training, and the training set includes input data and output data, and the input data is each feature evaluation combination; the output data is the initial adjustment coefficient, and the training set is set in combination with the initial evaluation value evaluation standard; the corresponding initial adjustment coefficient is obtained by analyzing the adjustment evaluation model after successful training.

[0092] In one embodiment, the method for evaluating according to the service evaluation curve includes:

[0093] Set an evaluation period, i.e., a periodic period set according to the platform's needs, such as weekly, monthly, etc.; divide the service evaluation curve into several curve segments according to the evaluation period, and mark the curve segments that have not been evaluated as unit segments; identify the variable interval corresponding to the unit segment, and mark the variable interval as [t1, t2]; the variable is represented by t;

[0094] Fit each unit segment to obtain the corresponding unit function, and mark the unit function as DY(t);

[0095] According to the formula Calculate the corresponding comprehensive service score;

[0096] Where: PB is the comprehensive service score.

[0097] The management module is used to manage according to the comprehensive service score of each customer service, and to set corresponding management measures for different comprehensive service score segments according to the management system of the platform, such as different reward and punishment measures, training, etc.; and then establish a management library;

[0098] Identify the comprehensive service score of each customer service, match the corresponding management measures from the management library according to the comprehensive service score, and manage the corresponding customer service according to the obtained management measures.

[0099] The above formulas are all calculated by removing dimensions and taking numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data.

[0100] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A water service customer service supervision system based on a cloud platform, characterized in that: It includes water affairs timeliness module, monitoring module, monitoring analysis module and management module; The water service timeliness module is used to supervise the water service tasks of each customer service, identify the water service task data of each customer service in real time, perform dynamic timeliness evaluation and adjustment on each water service task data, and set the timeliness coefficient corresponding to each water service task for each customer service according to the adjustment record; The monitoring module is used to monitor the service process of the customer service in real time and obtain the service monitoring data of each customer service for each water service task; The monitoring and analysis module is used to monitor and analyze each water task of each customer service, obtain the evaluation data of each water task by the corresponding customer in real time, evaluate the task service value of the corresponding water task according to the evaluation data and service monitoring data; generate a service evaluation curve according to the task service value corresponding to each water task of the customer; evaluate the customer service according to the service evaluation curve to obtain the comprehensive service score of the customer service; The management module is used to manage according to the comprehensive service score of each customer service and establish a management library, and the management library is used to store the management measures corresponding to each comprehensive service score; The comprehensive service score of each customer service is identified, corresponding management measures are matched from a management library according to the comprehensive service score, and the corresponding customer service is managed according to the management measures.

2. According to the water service customer service supervision system based on cloud platform in claim 1, it is characterized in that: The methods for dynamically evaluating and adjusting the timeliness of each water task data include: Step SA1: Obtain customer service task rules; set timeliness standards; Step SA2: Establishing a timeliness judgment model according to the timeliness standard, wherein the timeliness judgment model is used to evaluate the water service task data of each customer service to determine whether each water service task meets the timeliness standard; Step SA3: Analyze the water task data of each customer service through the timeliness judgment model to obtain the timeliness evaluation result corresponding to each water task, wherein the timeliness evaluation result includes a qualified timeliness evaluation and a failed timeliness evaluation; Mark each water affairs task with a timeliness assessment result of unqualified timeliness assessment as an adjustment task; Step SA4: reallocate each adjustment task according to the customer service task rules; Step SA5: loop from step SA3 to step SA4.

3. A water service customer service supervision system based on a cloud platform according to claim 2, characterized in that: The expression of the aging judgment model in step SA2 is: Where: s is the input data, the input data is the water task; the output data is the timeliness judgment value PX(s); Analyze each water affairs task in the water affairs task data through the timeliness judgment model to obtain the timeliness judgment value corresponding to each water affairs task; Mark the timeliness evaluation result with a timeliness judgment value of 1 as qualified The aging evaluation result with an aging judgment value of 0 is marked as unqualified aging evaluation.

4. According to the water service customer service supervision system based on cloud platform in claim 1, it is characterized in that: Methods for setting the time efficiency coefficients corresponding to various types of water service tasks for each customer service according to the adjustment records include: Classify each water affairs task in the water affairs task data of each customer service to obtain classification data of each water affairs task; Obtain the adjustment records of each customer service, classify the adjustment records according to each water service classification data, obtain the adjustment records corresponding to each water service classification data, and mark them as classification adjustment records; Identify the corresponding classification timeliness value and adjustment timeliness value in real time according to the classification adjustment record; According to the formula Calculate the time efficiency coefficient corresponding to each water service classification; In the formula: μ is the aging coefficient; FZ is the classification aging value; TZ is the adjusted aging value; λ is the adjustment amplification value, λ≥1; BZ is the aging standard value.

5. The water service customer service supervision system based on cloud platform according to claim 1 is characterized in that: Methods for evaluating the task service value of corresponding water tasks based on evaluation data and service monitoring data include: Evaluate the corresponding water affairs tasks according to the evaluation data to obtain the initial evaluation value; When the initial evaluation value is not less than the threshold value X1, the initial adjustment coefficient is marked as 1; When the initial evaluation value is less than the threshold value X1, the service monitoring data corresponding to the water task is obtained, and the service monitoring data is analyzed to obtain the initial adjustment coefficient corresponding to the water task; Identify the time efficiency coefficient, initial assessment value and initial adjustment coefficient corresponding to each water task; Calculate the corresponding task service value according to the formula PA = μ × η × CP; Where: PA is the task service value; μ is the timeliness coefficient; η is the initial adjustment coefficient; CP is the initial evaluation value.

6. A water service customer service supervision system based on a cloud platform according to claim 5, characterized in that: Methods for analyzing service monitoring data include: Set each service evaluation indicator and the corresponding weight coefficient of each service evaluation indicator, and set each evaluation segment according to the value range of the initial evaluation value and the threshold value X1; According to each service evaluation index, corresponding reference features are set for each evaluation segment; the evaluation segment corresponding to the initial evaluation value is identified, marked as a benchmark segment, and the reference features corresponding to the benchmark segment are identified; Perform feature recognition on the service monitoring data according to each service evaluation indicator to obtain the monitoring features corresponding to each service evaluation indicator; Combine each monitoring feature with the corresponding reference feature to obtain a feature evaluation combination corresponding to each service evaluation indicator, and mark a corresponding weight coefficient for each feature evaluation combination; An adjustment evaluation model is established, and each characteristic evaluation combination is analyzed through the adjustment evaluation model to obtain a corresponding initial adjustment coefficient.

7. The water service customer service supervision system based on cloud platform according to claim 1 is characterized in that: Methods for evaluation based on the service evaluation curve include: Setting an evaluation period, dividing the service evaluation curve into a plurality of curve segments according to the evaluation period, marking the curve segments that have not been evaluated as unit segments; identifying the variable interval corresponding to the unit segment, and marking the variable interval as [t1, t2]; Fitting each unit segment to obtain a corresponding unit function, and marking the unit function as DY(t); According to the formula Calculate the corresponding comprehensive service score; Where: PB is the comprehensive service score.

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