A service evaluation system based on mobile internet service application

Abstract

This invention belongs to the field of mobile internet and relates to data analysis technology. It addresses the problem that existing service evaluation systems for internet service applications cannot monitor the actual service quality of these applications from a user perspective. Specifically, it provides a service evaluation system for mobile internet service applications, comprising a design perception module, a network perception module, and a feedback analysis module. These modules are sequentially connected and communicate with each other. The design perception module performs user experience perception analysis on the page design of mobile internet service applications: generating a perception period and acquiring error data (WD), consecutive click data (LD), and amplification data (FD) within the perception period. This invention performs user experience perception analysis on the page design of mobile internet service applications and obtains design coefficients by monitoring and analyzing user behavior within the perception period.

Description

Technical Field

[0001] This invention belongs to the field of mobile Internet and involves data analysis technology, specifically a service evaluation system based on mobile Internet service applications. Background Technology

[0002] The Internet is an important foundation for the development of all services, and the quality of services directly affects the development of WLAN and wired broadband services. However, the current network indicators cannot reflect the quality of services, the user's service experience cannot be quantitatively evaluated, and optimization work can only be carried out in segments and layers around network indicators. This highlights the imperfection of Internet service quality indicators and the lack of monitoring methods.

[0003] Furthermore, existing service evaluation systems for internet service applications can only monitor network status through parameters such as network latency and jitter when conducting service quality analysis. They cannot analyze the user's page and network perception, nor can they monitor the actual service quality of internet service applications from the user's perspective. This results in a mismatch between service evaluation results and user experience, making it difficult to provide targeted optimization directions for product optimization.

[0004] To address the aforementioned technical problems, this application proposes a solution. Summary of the Invention

[0005] The purpose of this invention is to provide a service evaluation system based on mobile internet service applications, which solves the problem that existing service evaluation systems for internet service applications cannot monitor the actual service quality of internet service applications from the perspective of user perception.

[0006] The technical problem to be solved by this invention is: how to provide a service evaluation system based on mobile Internet service applications that can monitor the actual service quality of Internet service applications from the perspective of user perception.

[0007] The objective of this invention can be achieved through the following technical solution: a service evaluation system based on mobile Internet service applications, comprising a design perception module, a network perception module, and a feedback analysis module, wherein the design perception module, the network perception module, and the feedback analysis module are sequentially connected in communication;

[0008] The design perception module is used to perform perception analysis on the user experience of the page design of mobile Internet service applications: generating a perception period, acquiring erroneous data WD, continuous data LD, and amplified data FD within the perception period, and obtaining the design coefficient SJ of the mobile Internet service application within the perception period by numerically calculating the erroneous data WD, continuous data LD, and amplified data FD; comparing the design coefficient SJ of the mobile Internet service application within the perception period with a preset design threshold SJmax, and determining whether the user experience of the page design of the mobile Internet service application within the perception period meets the requirements based on the comparison result;

[0009] The network perception module is used to perform perception analysis on the user experience of page loading of mobile Internet service applications and obtain the perception performance value and perception fluctuation value of the perception period. The perception performance value and perception fluctuation value are compared with the preset perception performance threshold and perception fluctuation threshold, respectively. The comparison results are used to determine whether the user experience of page loading of mobile Internet service applications within the perception period meets the requirements.

[0010] The feedback analysis module is used to analyze user feedback on mobile internet service applications.

[0011] In a preferred embodiment of the present invention, the process of acquiring error data WD includes: marking user operations of mobile internet service applications; marking the process of performing a return operation within L1 seconds of the user performing an operation of the mobile internet service application as an error process; and marking the number of error processes within the perception period as error data WD. The process of acquiring continuous data LD includes: marking the process of the user continuously performing the same operation of the mobile internet service application as a continuous process; if the interval between continuous processes is less than L2 seconds, the corresponding continuous process is marked as a continuous process; and marking the number of continuous processes within the perception period as continuous data LD. The process of acquiring magnified data FD includes: marking the operation of the user zooming in on a part of the mobile internet service application interface as a zoom-in process; and marking the number of zoom-in processes within the perception period as magnified data FD.

[0012] As a preferred embodiment of the present invention, the specific process of comparing the design coefficient SJ of the mobile Internet service application within the perception period with the preset design threshold SJmax includes: if the design coefficient SJ is less than the design threshold SJmax, it is determined that the user experience of the page design of the mobile Internet service application within the perception period meets the requirements; if the design coefficient SJ is greater than or equal to the design threshold SJmax, it is determined that the user experience of the page design of the mobile Internet service application within the perception period does not meet the requirements, and the design perception module sends a page optimization signal to the mobile terminal of the administrator.

[0013] As a preferred embodiment of the present invention, the process of obtaining the perceived performance value and perceived fluctuation value within the perception period includes: marking the page loading process of the mobile Internet service application within the perception period as the perception process; establishing a rectangular coordinate system with loading time as the X-axis and page loading completion as the Y-axis; setting several perception points in the perception process; marking the perception points in the rectangular coordinate system with the loading time of the perception points as the abscissa and the page loading completion as the ordinate; connecting the perception points from left to right to obtain a perception polyline; marking the perpendicular line between the rightmost perception polyline and the X-axis as the cutoff line; forming a closed figure with the perception polyline, the cutoff line, and the X-axis; marking the area value of the closed figure as the completion value; marking the ratio of the completion value to the abscissa of the rightmost perception point as the loading coefficient of the perception process; summing and averaging the loading coefficients of all perception processes within the perception period to obtain the perceived performance value; forming a loading set with the loading coefficients of all perception processes within the perception period; and calculating the variance of the loading set to obtain the perceived fluctuation value.

[0014] As a preferred embodiment of the present invention, the specific process of comparing the perceived performance value and the perceived fluctuation value with preset perceived performance thresholds and perceived fluctuation thresholds respectively includes: if the perceived performance value is greater than or equal to the perceived performance threshold and the perceived fluctuation value is less than the perceived fluctuation threshold, then it is determined that the user experience of page loading of the mobile Internet service application meets the requirements within the perception period; otherwise, it is determined that the user experience of page loading of the mobile Internet service application does not meet the requirements within the perception period, and the network perception module sends a network optimization signal to the administrator's mobile terminal.

[0015] In a preferred embodiment of the present invention, the specific process of the feedback analysis module analyzing user feedback on mobile internet service applications includes: acquiring complaint data TS and rating data PF within the perception period, where TS is the number of user complaints received within the perception period and PF is the average user feedback rating within the perception period; calculating the feedback coefficient FK of the mobile internet service application within the perception period by numerically calculating the complaint data TS and rating data PF; comparing the feedback coefficient FK with a preset feedback threshold FKmax: if the feedback coefficient FK is less than the feedback threshold FKmax, it is determined that the user feedback does not meet the requirements, and the feedback analysis module sends a service optimization signal to the administrator's mobile terminal; if the feedback coefficient FK is greater than or equal to the feedback threshold FKmax, it is determined that the user feedback meets the requirements.

[0016] The working method of this service evaluation system based on mobile internet service applications includes the following steps:

[0017] Step 1: Perform a perception analysis on the user experience of the page design of the mobile Internet service application: Generate a perception period, obtain the error data WD, continuous data LD, and magnification data FD within the perception period, and perform numerical calculations to obtain the design coefficient SJ. Use the design coefficient SJ to determine whether the user experience of the page design of the mobile Internet service application within the perception period meets the requirements.

[0018] Step 2: Perform perceptual analysis on the user experience of page loading for mobile internet service applications: Mark the page loading process of mobile internet service applications within the perception period as a perception process, obtain the perceptual coefficient of the perception process, sum and average the loading coefficients of all perception processes within the perception period to obtain the perceptual performance value, construct a loading set from the loading coefficients of all perception processes within the perception period, calculate the variance of the loading set to obtain the perceptual fluctuation value, and determine whether the user experience of page loading for mobile internet service applications within the perception period meets the requirements by using the perceptual performance value and the perceptual fluctuation value.

[0019] Step 3: Analyze user feedback on mobile internet service applications: Obtain complaint data TS and rating data PF within the perception period and perform numerical calculations to obtain the feedback coefficient FK. Use the feedback coefficient FK to determine whether the user feedback meets the requirements.

[0020] The present invention has the following beneficial effects:

[0021] 1. The design perception module can be used to perform perception analysis on the user experience of the page design of mobile Internet service applications. By monitoring and analyzing user operation behavior within the perception period, design coefficients are obtained. The user experience of the page design is then fed back through the design coefficients, the rationality of the page design is supervised from the perspective of user perception, and the page design is optimized when it is unreasonable.

[0022] 2. The network perception module can perform perception analysis on the user experience of page loading of mobile Internet service applications. By comprehensively analyzing the loading time and page loading index of the perception process, a perception coefficient is obtained. The user experience of page loading is then fed back through the perception coefficient, and the network status of Internet service applications is monitored from the perspective of user perception.

[0023] 3. The feedback analysis module can analyze user feedback on mobile internet service applications. By comprehensively calculating and analyzing complaint data and rating data, a feedback coefficient can be obtained. This coefficient can then be used to monitor the overall user experience and optimize the framework, structure, and scope layers of the software application when the user experience is poor. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0026] Figure 2 This is a flowchart of the method in Embodiment 2 of the present invention. Detailed Implementation

[0027] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0028] Example 1

[0029] like Figure 1 As shown, a service evaluation system based on mobile Internet service applications includes a design perception module, a network perception module, and a feedback analysis module, which are connected in sequence.

[0030] The design perception module is used to perform perception analysis on the user experience of mobile internet service applications' page design: It generates a perception cycle and acquires erroneous click data (WD), consecutive click data (LD), and magnification data (FD) within the perception cycle. The acquisition process for erroneous click data (WD) includes: marking user operations on the mobile internet service application; marking the process where the user performs a return operation within L1 seconds of executing an operation as an erroneous click process; and marking the number of erroneous click processes within the perception cycle as erroneous click data (WD). The acquisition process for consecutive click data (LD) includes: marking the process where the user continuously performs the same operation on the mobile internet service application as a consecutive process; if the interval between consecutive processes is less than L2 seconds (where L1 and L2 are constant values ​​set by administrators), then the corresponding consecutive process is marked as a consecutive click process; and marking the number of consecutive click processes within the perception cycle as consecutive click data (LD). The acquisition process for magnification data (FD) includes: marking the user's operation of zooming in on a part of the mobile internet service application interface as a zoom-in process; and marking the number of zoom-in processes within the perception cycle as magnification data (FD). The data is obtained using the formula SJ = α1*WD + α2*LD + α3*F. D obtains the design coefficient SJ of the mobile internet service application within the perception period. The design coefficient is a numerical value reflecting the quality of the user experience of the page design; the larger the design coefficient, the worse the user experience. α1, α2, and α3 are proportional coefficients, and α1 > α2 > α3 > 1. The design coefficient SJ of the mobile internet service application within the perception period is compared with a preset design threshold SJmax: if the design coefficient SJ is less than the design threshold SJmax, the user experience of the page design of the mobile internet service application within the perception period is deemed to meet the requirements; if the design coefficient SJ is greater than or equal to the design threshold SJmax, the user experience of the page design of the mobile internet service application within the perception period is deemed to not meet the requirements, and the design perception module sends a page optimization signal to the administrator's mobile terminal. The user experience of the page design of the mobile internet service application is perceptually analyzed. By monitoring and analyzing user operation behavior within the perception period, the design coefficient is obtained, thereby providing feedback on the user experience of the page design through the design coefficient. This allows for supervision of the rationality of the page design from the user's perception perspective, and page design optimization is performed when the page design is unreasonable.

[0031] The network perception module is used to perform perception analysis on the user experience of page loading for mobile internet service applications. It marks the page loading process of the mobile internet service application within the perception period as a perception process. A Cartesian coordinate system is established with loading time as the X-axis and page loading completion as the Y-axis. Several perception points are set within the perception process, and these points are marked in the Cartesian coordinate system with loading time as the x-axis and page loading completion as the y-axis. The perception points are connected sequentially from left to right to obtain a perception polyline. The perpendicular line from the rightmost perception polyline to the X-axis is marked as the cutoff line. The perception polyline, the cutoff line, and the X-axis form a closed figure. The area of ​​this closed figure is marked as the completion value. The ratio of the completion value to the x-axis of the rightmost perception point is marked as the loading coefficient of the perception process. The loading coefficients of all perception processes within the perception period are summed and averaged to obtain the perception performance value. The loading coefficients of all sensing processes constitute a loading set. Variance calculation is performed on the loading set to obtain the sensing fluctuation value. The sensing performance value and sensing fluctuation value are compared with preset sensing performance thresholds and sensing fluctuation thresholds, respectively. If the sensing performance value is greater than or equal to the sensing performance threshold and the sensing fluctuation value is less than the sensing fluctuation threshold, the user experience of page loading for the mobile internet service application within the sensing period is determined to meet the requirements. Otherwise, the user experience of page loading for the mobile internet service application within the sensing period is determined to not meet the requirements, and the network sensing module sends a network optimization signal to the administrator's mobile terminal. The user experience of page loading for the mobile internet service application is analyzed. A sensing coefficient is obtained by comprehensively analyzing the loading time of the sensing process and the page loading index. The user experience of page loading is then fed back through the sensing coefficient, allowing for monitoring of the network status of the internet service application from the user's perspective.

[0032] The feedback analysis module analyzes user feedback on mobile internet service applications: it acquires complaint data TS and rating data PF within the perception period. TS represents the number of user complaints received within the perception period, and PF represents the average user feedback ratings received during the perception period. The feedback coefficient FK of the mobile internet service application within the perception period is obtained using the formula FK = (β1*PF) / (β2*TS). The feedback coefficient is a numerical value reflecting the overall quality of the user experience; a higher feedback coefficient indicates a better overall user experience. β1 and β2 are proportionality coefficients, and β1 > β2 > 1. The feedback coefficient FK is compared with the preset feedback threshold FKmax. If the feedback coefficient FK is less than the feedback threshold FKmax, the user feedback is deemed unsatisfactory, and the feedback analysis module sends a service optimization signal to the administrator's mobile terminal. If the feedback coefficient FK is greater than or equal to the feedback threshold FKmax, the user feedback is deemed satisfactory. The system analyzes user feedback for mobile internet service applications, calculates and analyzes complaint data and rating data to obtain the feedback coefficient, and monitors the overall user experience through the feedback coefficient. When the user experience is poor, the framework, structure, and scope layers of the software application are optimized.

[0033] Example 2

[0034] like Figure 2 As shown, a service evaluation method based on mobile internet service applications includes the following steps:

[0035] Step 1: Perform a perception analysis on the user experience of the page design of the mobile Internet service application: Generate a perception period, obtain the error data WD, continuous data LD, and magnification data FD within the perception period, and perform numerical calculations to obtain the design coefficient SJ. Use the design coefficient SJ to determine whether the user experience of the page design of the mobile Internet service application within the perception period meets the requirements.

[0036] Step 2: Perform perceptual analysis on the user experience of page loading for mobile internet service applications: Mark the page loading process of mobile internet service applications within the perception period as a perception process, obtain the perceptual coefficient of the perception process, sum and average the loading coefficients of all perception processes within the perception period to obtain the perceptual performance value, construct a loading set from the loading coefficients of all perception processes within the perception period, calculate the variance of the loading set to obtain the perceptual fluctuation value, and determine whether the user experience of page loading for mobile internet service applications within the perception period meets the requirements by using the perceptual performance value and the perceptual fluctuation value.

[0037] Step 3: Analyze user feedback on mobile internet service applications: Obtain complaint data TS and rating data PF within the perception period and perform numerical calculations to obtain the feedback coefficient FK. Use the feedback coefficient FK to determine whether the user feedback meets the requirements.

[0038] In operation, this invention generates a perception cycle, acquires error data (WD), connection data (LD), and amplification data (FD) within the perception cycle, and performs numerical calculations to obtain a design coefficient (SJ). The design coefficient (SJ) is used to determine whether the user experience of the mobile internet service application's page design meets the requirements within the perception cycle. The page loading process of the mobile internet service application within the perception cycle is marked as a perception process, and the perception coefficient of each perception process is acquired. The average of the loading coefficients of all perception processes within the perception cycle is summed to obtain a perception performance value. A loading set is constructed from the loading coefficients of all perception processes within the perception cycle, and the variance of the loading set is calculated to obtain a perception fluctuation value. The perception performance value and the perception fluctuation value are used to determine whether the user experience of the mobile internet service application's page loading meets the requirements within the perception cycle. Finally, complaint data (TS) and rating data (PF) within the perception cycle are acquired and numerically calculated to obtain a feedback coefficient (FK). The feedback coefficient (FK) is used to determine whether user feedback meets the requirements.

[0039] The above description is merely an example and illustration of the structure of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the structure of the invention or exceed the scope defined in the claims, all of which should fall within the protection scope of the present invention.

[0040] The above formulas are all derived from software simulation using a large amount of data, and are selected to be close to the actual values. The coefficients in the formulas are set by those skilled in the art according to the actual situation; for example, the formula SJ=α1*WD+α2*LD+α3*FD; those skilled in the art collect multiple sets of sample data and set corresponding design coefficients for each set of sample data; substitute the set design coefficients and the collected sample data into the formulas, and any three formulas form a system of three linear equations; filter the calculated coefficients and take the average value to obtain the values ​​of α1, α2 and α3 as 3.48, 2.85 and 2.32 respectively;

[0041] The magnitude of the coefficient is a specific value obtained by quantifying each parameter to facilitate subsequent comparison. The magnitude of the coefficient depends on the amount of sample data and the design coefficient initially set by those skilled in the art for each set of sample data. As long as it does not affect the proportional relationship between the parameter and the quantified value, such as the design coefficient being proportional to the value of the connected data.

[0042] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0043] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A service evaluation system based on a mobile Internet service application, characterized by, It includes a design perception module, a network perception module, and a feedback analysis module, which are sequentially connected in communication. The design perception module is used to perform perception analysis on the user experience of the page design of mobile internet service applications: It generates a perception period, acquires erroneous data (WD), consecutive data (LD), and magnification data (FD) within the perception period, and obtains the design coefficient SJ of the mobile internet service application within the perception period using the formula SJ=α1*WD+α2*LD+α3*FD. The design coefficient is a numerical value reflecting the quality of the user experience of the page design; the larger the design coefficient, the worse the user experience. α1, α2, and α3 are proportional coefficients, and α1>α2>α3>1. The design coefficient SJ of the mobile internet service application within the perception period is compared with a preset design threshold SJmax, and the comparison result is used to determine whether the user experience of the page design of the mobile internet service application within the perception period meets the requirements. The process of acquiring erroneous data (WD) includes: marking user operations on mobile internet service applications; marking the process of returning within L1 seconds of a user performing an operation on a mobile internet service application as an erroneous process; and marking the number of erroneous processes within the perception period as erroneous data (WD). The process of acquiring continuous data (LD) includes: marking the process of a user continuously performing the same operation on a mobile internet service application as a continuous process; if the interval between continuous processes is less than L2 seconds, then the corresponding continuous process is marked as a continuous process; and marking the number of continuous processes within the perception period as continuous data (LD). The process of acquiring zoom data (FD) includes: marking the user's operation of zooming in on a part of the mobile internet service application interface as a zoom process; and marking the number of zoom processes within the perception period as zoom data (FD). The network perception module is used to perform perception analysis on the user experience of page loading of mobile Internet service applications and obtain the perception performance value and perception fluctuation value of the perception period. The perception performance value and perception fluctuation value are compared with preset perception performance thresholds and perception fluctuation thresholds, respectively. The comparison results are used to determine whether the user experience of page loading of mobile Internet service applications within the perception period meets the requirements. The process of obtaining the perception performance value and perception fluctuation value within the perception period includes: marking the page loading process of the mobile Internet service application within the perception period as the perception process; establishing a Cartesian coordinate system with loading time as the X-axis and page loading completion as the Y-axis; and setting several perception points during the perception process. The loading time of the sensing point is used as the x-axis, and the page loading completion rate of the sensing point is used as the y-axis. The sensing points are marked in a rectangular coordinate system. The sensing points are connected from left to right to obtain a sensing polyline. The perpendicular line between the rightmost sensing polyline and the X-axis is marked as the cutoff line. The sensing polyline, the cutoff line, and the X-axis form a closed figure. The area value of the closed figure is marked as the completion value. The ratio of the completion value to the x-axis of the rightmost sensing point is marked as the loading coefficient of the sensing process. The loading coefficients of all sensing processes within the sensing period are summed and averaged to obtain the sensing performance value. The loading coefficients of all sensing processes within the sensing period form a loading set. The variance of the loading set is calculated to obtain the sensing fluctuation value. The feedback analysis module is used to analyze user feedback on mobile internet service applications.

2. The service evaluation system based on the mobile Internet service application according to claim 1, characterized in that, The specific process of comparing the design coefficient SJ of the mobile internet service application within the perception period with the preset design threshold SJmax includes: if the design coefficient SJ is less than the design threshold SJmax, it is determined that the user experience of the page design of the mobile internet service application within the perception period meets the requirements; if the design coefficient SJ is greater than or equal to the design threshold SJmax, it is determined that the user experience of the page design of the mobile internet service application within the perception period does not meet the requirements, and the design perception module sends a page optimization signal to the administrator's mobile terminal.

3. The service evaluation system based on the mobile Internet service application according to claim 2, characterized in that, The specific process of comparing the perceived performance value and perceived fluctuation value with the preset perceived performance threshold and perceived fluctuation threshold respectively includes: if the perceived performance value is greater than or equal to the perceived performance threshold and the perceived fluctuation value is less than the perceived fluctuation threshold, then it is determined that the user experience of page loading of mobile Internet service applications meets the requirements within the perception period; otherwise, it is determined that the user experience of page loading of mobile Internet service applications does not meet the requirements within the perception period, and the network perception module sends a network optimization signal to the administrator's mobile terminal.

4. The service evaluation system based on the mobile Internet service application according to claim 3, characterized in that, The feedback analysis module analyzes user feedback for mobile internet service applications through the following process: It acquires complaint data TS and rating data PF within the perception period. TS represents the number of user complaints received during the perception period, and PF represents the average user feedback received during the perception period. It then calculates the feedback coefficient FK of the mobile internet service application within the perception period by performing numerical calculations on the TS and PF data. Finally, it compares the feedback coefficient FK with a preset feedback threshold FKmax. If the feedback coefficient FK is less than the feedback threshold FKmax, the user feedback is deemed unsatisfactory, and the feedback analysis module sends a service optimization signal to the administrator's mobile terminal. If the feedback coefficient FK is greater than or equal to the feedback threshold FKmax, the user feedback is deemed satisfactory.

5. A service evaluation system based on mobile internet service applications according to any one of claims 1-4, characterized in that, The working method of this service evaluation system based on mobile internet service applications includes the following steps: Step 1: Perform a perceptual analysis of the user experience of the mobile internet service application's page design: Generate a perception period, acquire erroneous click data (WD), consecutive click data (LD), and magnification data (FD) within the perception period, and perform numerical calculations to obtain the design coefficient SJ. The design coefficient SJ is used to determine whether the user experience of the mobile internet service application's page design meets the requirements within the perception period. The acquisition process of erroneous click data (WD) includes: marking user operations on the mobile internet service application; marking the process where the user performs a return operation within L1 seconds of executing an operation as an erroneous click process; and marking the number of erroneous click processes within the perception period as erroneous click data (WD). The acquisition process of consecutive click data (LD) includes: marking the process where the user continuously performs the same operation on the mobile internet service application as a continuous process; if the interval between continuous processes is less than L2 seconds, then the corresponding continuous process is marked as a consecutive click process; and marking the number of consecutive click processes within the perception period as consecutive click data (LD). The acquisition process of magnification data (FD) includes: marking the user's operation of zooming in on a part of the mobile internet service application interface as a zoom-in process; and marking the number of zoom-in processes within the perception period as magnification data (FD). Step Two: Perform Perceptual Analysis of Page Loading User Experience for Mobile Internet Service Applications: Mark the page loading process of the mobile internet service application within the perception period as a perception process, obtain the perception coefficient of the perception process, sum and average the loading coefficients of all perception processes within the perception period to obtain the perception performance value, construct a loading set from the loading coefficients of all perception processes within the perception period, calculate the variance of the loading set to obtain the perception fluctuation value, and determine whether the page loading user experience of the mobile internet service application within the perception period meets the requirements by using the perception performance value and the perception fluctuation value. The process of obtaining the perception performance value and perception fluctuation value within the perception period includes: marking the page loading process of the mobile internet service application within the perception period as a perception process, using loading time as the X-axis, and page loading as the Y-axis. A Cartesian coordinate system is established with the page loading completion rate as the Y-axis. Several sensing points are set during the sensing process. The loading time of the sensing points is used as the x-axis and the page loading completion rate of the sensing points is used as the y-axis to mark the sensing points in the Cartesian coordinate system. The sensing points are connected from left to right to obtain a sensing polyline. The perpendicular line between the rightmost sensing polyline and the X-axis is marked as the cutoff line. The sensing polyline, the cutoff line, and the X-axis form a closed figure. The area value of the closed figure is marked as the completion value. The ratio of the completion value to the x-axis of the rightmost sensing point is marked as the loading coefficient of the sensing process. The loading coefficients of all sensing processes within the sensing period are summed and averaged to obtain the sensing performance value. The loading coefficients of all sensing processes within the sensing period constitute the loading set. The variance of the loading set is calculated to obtain the sensing fluctuation value. Step 3: Analyze user feedback on mobile internet service applications: Obtain complaint data TS and rating data PF within the perception period and perform numerical calculations to obtain the feedback coefficient FK. Use the feedback coefficient FK to determine whether the user feedback meets the requirements.

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