Information processing method and device, equipment and storage medium

Abstract

The embodiment of the invention relates to an information processing method and device, equipment and a storage medium. The method comprises the steps of displaying a satisfaction page of a target session in response to an information viewing operation; displaying satisfaction detail information of the target session in a satisfaction page, wherein the satisfaction detail information comprises at least one satisfaction level and factor information of a target influence factor corresponding to the satisfaction level; wherein the satisfaction detail information is obtained by performing data analysis on session data of the target session; the session data at least comprises performance data and abnormal data which are obtained in the life cycle of the target session and correspond to the target session; the factor information is used for representing the influence degree of the target influence factor on classification of the target session into the satisfaction level. In this way, the universality of user satisfaction measurement is improved, and more objective and accurate user satisfaction data reference is provided for related personnel more quickly and efficiently.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to an information processing method, apparatus, device and storage medium. Background Art

[0002] Consumer Satisfaction, also known as the user satisfaction index, is a subjective feeling and evaluation of the degree of match between the user's expectations of a product or service and the actual experience. User satisfaction is an important indicator for measuring the quality of a product or service.

[0003] At present, the measurement of user satisfaction is mainly through questionnaire surveys, active user feedback, feasibility testing, etc. to obtain indicators such as user feedback rate of products or services, retention rate of important paths, user participation, etc., in order to characterize the user satisfaction of the product or service. However, these indicators often require active user feedback and are highly dependent on user familiarity and cognition, lacking universality. Summary of the invention

[0004] In order to solve the above technical problems, the embodiments of the present disclosure provide an information processing method, apparatus, device and storage medium.

[0005] In a first aspect, an embodiment of the present disclosure provides an information processing method, the method comprising:

[0006] In response to the information viewing operation, displaying a satisfaction page of the target session;

[0007] The satisfaction details information of the target session is displayed in the satisfaction page, and the satisfaction details information includes at least one satisfaction level and factor information of a target influencing factor corresponding to the satisfaction level; wherein the satisfaction details information is obtained by performing data analysis on session data of the target session; the session data includes at least performance data and abnormal data corresponding to the target session obtained during the life cycle of the target session; the factor information is used to characterize the degree of influence of the target influencing factor on the classification of the target session into the satisfaction level.

[0008] In a second aspect, an embodiment of the present disclosure further provides an information processing device, the device comprising:

[0009] A page display module, for displaying a satisfaction page of a target session in response to an information viewing operation;

[0010] An information display module is used to display the satisfaction details information of the target session in the satisfaction page, the satisfaction details information including at least one satisfaction level and factor information of the target influencing factor corresponding to the satisfaction level; wherein the satisfaction details information is obtained by performing data analysis on the session data of the target session; the session data at least includes performance data and abnormal data corresponding to the target session obtained during the life cycle of the target session; the factor information is used to characterize the degree of influence of the target influencing factor on the classification of the target session into the satisfaction level.

[0011] In a third aspect, an embodiment of the present disclosure further provides an electronic device, the electronic device comprising:

[0012] processor;

[0013] A memory for storing executable instructions;

[0014] The processor is used to read executable instructions from the memory and execute the executable instructions to implement the information processing method described in any embodiment of the present disclosure.

[0015] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the processor implements the information processing method described in any embodiment of the present disclosure.

[0016] In a fifth aspect, an embodiment of the present disclosure further provides a computer program product, which is used to execute the information processing method described in any embodiment of the present disclosure.

[0017] The information processing method, apparatus, device and storage medium of the disclosed embodiments can display a satisfaction page of a target session in response to an information viewing operation; display satisfaction details information of the target session in the satisfaction page, the satisfaction details information including at least one satisfaction level and factor information of a target influencing factor corresponding to the satisfaction level; the satisfaction details information is obtained by performing data analysis on session data of the target session; the session data at least includes performance data and abnormal data corresponding to the target session obtained during the life cycle of the target session; the factor information is used to characterize the degree of influence of the target influencing factor on the classification of the target session into a satisfaction level; the performance data and abnormal data of the target session are obtained from the perspective of front-end monitoring, Based on this analysis, the satisfaction level of the user satisfaction of the target session and the factor information of its corresponding target influencing factor are obtained, which greatly reduces the need for users to actively feedback their experience information during the user satisfaction measurement process, and avoids the dependence of the obtained user satisfaction on the user's product familiarity and user cognition, thereby improving the versatility of user satisfaction measurement and providing developers with more objective and accurate user satisfaction data reference; in addition, the satisfaction-related information obtained from the analysis can be displayed through the satisfaction page, which improves the convenience and efficiency of developers in obtaining product user satisfaction-related information, and can provide effective guidance for product improvement through the displayed user satisfaction factor information, thereby improving product improvement efficiency.

[0018] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in the embodiments of the present disclosure are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and that components and elements are not necessarily drawn to scale.

[0020] Figure 1 A flowchart of an information processing method provided by an embodiment of the present disclosure;

[0021] Figure 2 A display schematic diagram of a satisfaction details page provided in an embodiment of the present disclosure;

[0022] Figure 3A schematic diagram of a flow chart of determining a satisfaction level of a single conversation in an information processing method provided in an embodiment of the present disclosure;

[0023] Figure 4 A schematic diagram of the structure of an information processing device provided by an embodiment of the present disclosure;

[0024] Figure 5 A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0025] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not intended to limit the scope of protection of the present disclosure.

[0026] It should be understood that the various steps described in the method embodiments of the present disclosure may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present disclosure is not limited in this respect.

[0027] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0028] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0029] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0030] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0031] The information processing method provided by the embodiments of the present disclosure can be applied to the scenario of measuring and / or displaying the user satisfaction of products or services, and can also be applied to the scenario of analyzing and displaying the network session process of products or services. The method can be executed by an information processing device, which can be implemented by software and / or hardware, and the device can be integrated in an electronic device with a display function and a certain computing function. The electronic device can include but is not limited to a smart phone, a tablet computer (Tablet Personal Computer, Tablet PC), a laptop computer, a desktop computer or a server.

[0032] Figure 1 FIG. 1 is a flow chart of an information processing method provided by an embodiment of the present disclosure. Figure 1 As shown, the information processing method may include the following steps:

[0033] S110 . In response to the information viewing operation, display a satisfaction page of the target session.

[0034] Among them, the information viewing operation is an interactive operation used to trigger the display of information, such as starting an application or web page with information display function, or triggering an interactive control with information display function in a related application or web page. The target session is a session in the web language to be viewed / analyzed, which is an uninterrupted sequence of requests and responses between the user and the server. For example, a web session can be a user visiting a certain web site, clicking multiple hyperlinks on this site, accessing multiple web resources on the server, and then closing the web site or the server not accepting any requests from the user within a predefined time limit. The whole process is called a session. The target session can be a single session or a collection of many single sessions. The satisfaction page is a page used to display relevant information about user satisfaction.

[0035] Specifically, the user can perform an information viewing operation in an application or a web page. In response to the information viewing operation, the electronic device displays a satisfaction page of a target session hit by the operation.

[0036] like Figure 2 As shown, the electronic device can display a satisfaction page 200 in response to the information viewing operation to display relevant information about the user satisfaction of the target session. A plurality of analysis objects (such as sessions) 210 of satisfaction can also be displayed in the satisfaction page 200. The user can select any session identifier that he wants to view in the analysis object 210, and the electronic device can redefine the target session in response to the selection operation, and refresh the satisfaction page 200 to display relevant information about the user satisfaction of the selected session identifier.

[0037] S120: Displaying satisfaction details information of the target session in a satisfaction page, where the satisfaction details information includes at least one satisfaction level and factor information of a target influencing factor corresponding to the satisfaction level.

[0038] Among them, the satisfaction details information is the detailed introduction information of the user satisfaction of the target session. The satisfaction details information may include the measurement indicators of user satisfaction and the indicator value of each measurement indicator, and the indicator value may reflect the user's satisfaction level on the corresponding measurement indicator dimension. In the embodiment of the present disclosure, the measurement indicator may be specifically reflected as a target influencing factor, and the indicator value may be specifically reflected as a satisfaction level to which the target influencing factor belongs and the factor information of the target influencing factor. That is, the satisfaction details information in the embodiment of the present disclosure includes at least one satisfaction level and the factor information of the target influencing factor corresponding to the satisfaction level.

[0039] Among them, the target influencing factor is a factor that affects user satisfaction during the target session, which can be used for attribution analysis and problem location. The target influencing factor can be a factor that has a positive impact on user satisfaction, such as a factor related to interactive performance with timely feedback; it can also be a factor that has a negative impact on user satisfaction, such as a factor that blocks signals that interrupt or hinder the normal operation process of the user for a long time; it can also be a neutral factor that may have a negative or positive impact, such as a factor related to the operation time of the interactive operation. The target influencing factor can be screened from a plurality of pre-set candidate influencing factors. The candidate influencing factors can be predetermined according to business conditions, questionnaires, or feasibility tests. The factor information is used to characterize the degree of influence of the target influencing factor on the classification of the target session into a satisfaction level, which can be the weight / proportion of the target influencing factor.

[0040] Among them, the satisfaction level is the result obtained by grading the user's satisfaction. Exemplarily, the satisfaction level may include a first-level satisfaction level, a second-level satisfaction level, and a third-level satisfaction level. The first-level satisfaction level characterizes that the process of the target session is satisfactory, which means that the user has a good experience and satisfaction in the process of using the product or service, and basically has no problems or troubles. The second-level satisfaction level characterizes that the process of the target session is tolerable, which means that although the user encounters some minor problems in the process of using the product or service, he can still accept and complete the task without obvious dissatisfaction. The third-level satisfaction level characterizes that the process of the target session is frustrating, which means that the user encounters major problems or troubles in the process of using the product or service, which makes the task unable to be completed, causing the user to have great dissatisfaction and unpleasant experience. This experience may include factors that affect the user experience, such as slow page response speed, untimely interactive feedback, and long waiting.

[0041] Specifically, the electronic device may obtain the specific contents of the satisfaction page before displaying the specific contents. For example, the electronic device may read the satisfaction details information corresponding to the target session from an internal or external storage medium. For another example, the electronic device may call a related functional interface with determined satisfaction details information to run a corresponding function to obtain the satisfaction details information of the target session. Then, the satisfaction details information is loaded and rendered for display according to the page layout of the satisfaction page.

[0042] See also Figure 2 , the electronic device may display satisfaction details in the lower right area 220 of the satisfaction page 200, which includes at least one satisfaction level 221 corresponding to the target session and factor information 223 of the target impact factor 222 corresponding to the satisfaction level. The factor information 223 may be represented by the percentage value of the target impact factor in the session data, or may be represented by a graphical display result of whether the percentage of the value of the target impact factor is abnormal. The specific display style may be set according to business requirements, and the embodiment of the present disclosure does not limit it.

[0043] It should be noted that Figure 2 The information of each factor and its display style are only exemplary and do not constitute any limitation to the embodiments of the present disclosure.

[0044] In the disclosed embodiment, the satisfaction details information can be obtained by analyzing the session data of the target session. The session data at least includes the performance data and abnormal data corresponding to the target session obtained during the life cycle of the target session. This is because in the process of using the product or service, the user mainly operates its functions through human-computer interaction with the front-end interactive interface provided by it. In the front-end interaction process, the factors that the user can perceive will affect the user satisfaction, which can be reflected by the performance data (such as page loading time, page response time, resource loading time, network request performance, etc.) and abnormal data (such as code running errors, resource loading errors, white screens, etc.) of the session process. In this way, the disclosed embodiment can obtain the performance data and abnormal data of the target session from the perspective of front-end monitoring, and automatically judge the user satisfaction of the target session by analyzing these session data, without the need for the user to actively feedback their satisfaction, and will not have a greater reliance on the user's product familiarity and cognitive level, so that more objective and accurate user satisfaction related data can be obtained more timely, and then the problems existing in the product or service and their improvement methods can be determined by analyzing them.

[0045] In some embodiments, see Figure 2, the satisfaction details information also includes category information of the influencing factor category 224. The influencing factor category is a category obtained by classifying each candidate influencing factor with similar characteristics. In the embodiment of the present disclosure, based on the analysis of performance data and abnormal data, each candidate influencing factor can be classified into four influencing factor categories: blocking signal category, interactive performance category, operation duration category, and operation waiting category. The satisfaction details information may include at least one of the four influencing factor categories based on the specific circumstances of the session data of the target session. In view of the fact that the influencing factor category is obtained by classifying the candidate influencing factors, the category information can be obtained by statistically summarizing the factor information of all target influencing factors contained in the influencing factor category. For example, when the factor information is the proportion of the target influencing factor, the proportion of each target influencing factor can be weighted and summed according to the weight of each target influencing factor to obtain the category information of the influencing factor category corresponding to these target influencing factors.

[0046] The above blocking signal category evaluates the emotional fluctuations caused by the user's failure to complete the expected behavior. Blocking signals are actually perceived by users. Since it is impossible to know whether the user actually perceives it, all abnormalities can be considered blocking signals. In the actual implementation process, meaningless blocking signals can be ignored to ensure the accuracy of the calculation. Candidate influencing factors under the blocking signal category may include but are not limited to white screen, code running errors, request errors, and resource errors. Continue to see Figure 2 When viewing the three-level satisfaction level and the category information as the percentage of blocking signal categories, it can help relevant personnel understand how many users have encountered blocking signals in these frustrated sessions. In addition, through each target influencing factor under the blocking signal category and its factor information, it can help relevant personnel understand the distribution of the subdivided categories of blocking signals encountered by users in frustrated sessions.

[0047] The interactive performance category evaluates the emotional fluctuations caused by the interaction between users and pages. Users expect the page to respond quickly after interaction and display the expected content as soon as possible. However, if the response time exceeds user expectations, or the page is stuck during the response process, resulting in unsmooth interaction, the user's mood will deteriorate. Candidate influencing factors under the interactive performance category may include but are not limited to factors of initialization loading performance (first content painting FCP / maximum content painting LCP / interactive time TTI / cumulative layout shift CLS), behavioral performance (Action.Duration) factors, page switching performance factors, and other custom performance indicators. Continue to see Figure 2 , when looking at the three-level satisfaction rating, the category information is the percentage of interactive performance categories, which can help stakeholders understand how many users experienced poor performance in these frustrating sessions ( Figure 2In addition, the target influencing factors and their factor information under the interactive performance category ( Figure 2 The light gray filled segments show the percentage of examples with very good performance, and the medium gray filled segments show the percentage of examples with performance that needs to be improved), which helps relevant personnel understand which performance indicator the user has poor performance on during frustrating sessions.

[0048] The operation time category evaluates the emotional fluctuations caused by the interactive operation that exceeds the expected time when the user starts to perform related tasks after the page is loaded. An interactive task operation has a basic operation time, also called the baseline time. If it exceeds the user's expected time, the user will feel frustrated and give up the task. These experience signals are generally related to the layout of the page and the usability design of the functions. For products with excellent layout and usability, the general user operation will not exceed the baseline time. Candidate influencing factors under the operation time category may include but are not limited to the excessively long interval between two element clicks, the excessively long overall task operation time, the increase in clicks unrelated to the main task, and the excessively long operation time unrelated to the main task. See more Figure 2 When viewing the three-level satisfaction level and the category information as the percentage of blocking signal categories, it can help relevant personnel understand how many users have encountered blocking signals in these frustrated sessions. In addition, through each target influencing factor under the blocking signal category and its factor information, it can help relevant personnel understand the distribution of the subdivided categories of blocking signals encountered by users in frustrated sessions.

[0049] The Operation Waiting category evaluates the emotional fluctuations caused by the long wait after the first screen rendering of the page is completed. It may be caused by interactive behavior or some asynchronous logic. Candidate influencing factors under the Operation Waiting category may include but are not limited to long request time, long resource loading time, and long task time. Figure 2 When viewing the three-level satisfaction rating and the category information is the proportion of the operation waiting category, it can help relevant personnel understand how many users have encountered long waits in these frustrating sessions. In addition, through the target influencing factors under the operation waiting category and their factor information, relevant personnel can understand the distribution of the subdivided categories of long waits encountered by users in frustrating sessions.

[0050] It should be noted that the session profile information corresponding to the triggered target influencing factor may also be displayed in a new page, or in a half-screen page or floating window that pops up in the satisfaction details page.

[0051] In some embodiments, after S120, the method further includes: in response to a triggering operation on any target influencing factor, displaying session profile information corresponding to the triggered target influencing factor; the session profile information includes a session identifier of at least one single session, or includes a session identifier of at least one single session and the impact result generated by the triggered target influencing factor in the single session.

[0052] Specifically, see Figure 2 , the user can trigger any displayed target influencing factor (such as request taking too long). In response to the trigger operation, the electronic device can display the session profile information 250 corresponding to the triggered target influencing factor in a certain area of ​​the satisfaction details page. The session profile information may include the session identifier of a single session in the session data that covers the triggered target influencing factor (such as the access address of the session, the name / code / number of the access address hyperlinked to the access address, etc.). Alternatively, the session profile information may include the session identifier of a single session and the impact result of the triggered target influencing factor in the single session (such as the number of users affected or the rate of users affected, etc.).

[0053] By triggering any target influencing factor under any influencing factor category, relevant personnel can conduct in-depth analysis of the problems or concerns encountered by users when using products / services, thereby locating the problems and making corresponding improvements and optimizations to product functions.

[0054] For example, users can trigger the "request error" factor under the blocking signal category to display which specific request errors occurred in the blocking signal and their corresponding impact results, so as to help relevant personnel locate the blocking signal with the greatest impact, thereby lowering the threshold for business troubleshooting.

[0055] For example, users can trigger the "resource loading time is too long" factor under the operation waiting category to display which specific resources take a long time to load during the long wait and their corresponding impact results, so as to help relevant personnel locate the long wait with the greatest impact, thereby lowering the threshold for business troubleshooting.

[0056] For example, users can trigger the "Single-page application switching performance" factor under the interactive performance category to display which pages have poor single-page application switching performance and their corresponding impact results, so as to help relevant personnel locate the most influential poor interactive performance indicators and the pages where they occur, thereby lowering the threshold for business troubleshooting.

[0057] In some embodiments, after displaying the session profile information corresponding to the triggered target influence factor in response to a trigger operation on any target influence factor, the method further includes: displaying a session details page of a single session corresponding to the triggered session identifier in response to a trigger operation on a session identifier, and displaying session data of multiple dimensions of the single session in the session details page.

[0058] Specifically, users can Figure 2 The trigger operation is performed by any session identifier in the session profile information 250 corresponding to the "request takes too long" factor shown. In response to the trigger operation, the electronic device can jump to the details page of the session data of the single session corresponding to the triggered session identifier (i.e., the session details page). In the session details page, detailed session data of various dimensions of the single session can be displayed, providing more detailed session data for relevant personnel.

[0059] In some embodiments, see Figure 2 The satisfaction page 200 also displays satisfaction profile information 230 and / or session profile information 240 of the target session.

[0060] The satisfaction profile information 230 is used to introduce the basic / overall information of the user satisfaction of the target session, which at least includes the session distribution information corresponding to each satisfaction level, such as the numerical display of the proportion / session number of multiple single sessions in the target session belonging to different satisfaction levels, and the graphical display of the bar chart / pie chart / curve, etc. In addition, the satisfaction profile information 230 may also include the number of sessions of the target session participating in the statistics, etc. This information can help relevant personnel evaluate the overall satisfaction of users with products or services. If the satisfaction of most single sessions is distributed in the first level of satisfaction level, it means that most users are satisfied with the experience of the product / service; if the satisfaction of most single sessions is distributed in the third level of satisfaction level, it means that most users are very dissatisfied with the experience of the product / service, and relevant personnel need to pay attention to and improve the specific factors that lead to user dissatisfaction.

[0061] The session profile information 240 is used to introduce the basic / overall information of the target session, which includes at least the statistical time period corresponding to the target session, the number of single sessions corresponding to the target session, the number of users participating in the session, the average session duration, the average session depth, and at least one of the session entry and session exit.

[0062] The changing trends of the number of sessions and users can help relevant personnel understand the growth of the user base and reflect the activity of the business. If the number of sessions and users continues to grow, it means that users' demand and interest in products and services are increasing. If the number of sessions and users decreases, it may mean that there are product problems or poor user experience leading to churn, etc., and improvements and optimizations are needed.

[0063] Average session duration is the average length of time that users stay in a session during the statistical time period. Its trend and distribution are used to reflect the user's product engagement. By observing the trend changes in session duration, you can understand the user's engagement with the product or service and the frequency of use. Longer session durations mean that users spend more time in the product and are more interested in the product or service. Shorter session durations may mean low user engagement and problems that need further research and improvement. These data can help understand user engagement, product experience, and content popularity, so as to formulate corresponding user growth strategies and product improvement strategies. Comprehensive analysis of session duration trends can help improve user engagement, increase user usage time, and improve user experience.

[0064] Average session depth is the average of the sum of page views and interactions in each single session, and is used to reflect user engagement. By observing the trend of session depth, you can understand the user's level of interaction and engagement with the product in a single session. If the session depth is large, it means that the user has more interactions when exploring and engaging with the product, and has a higher level of engagement. On the contrary, if the session depth is low, it may mean that the user has less interaction and exploration of the product. These data are important for evaluating user engagement, product experience, navigation design, and content optimization. By comprehensively analyzing the trend of session depth, corresponding product improvement strategies and navigation optimization strategies can be formulated to increase user engagement, improve user experience, and optimize product content.

[0065] Session entry and session exit represent the ways or functions for users to enter and leave a session, respectively, and are used to reflect the needs and interests of users. It can help understand the actions or processes that users usually take when using a product, and improve the product's functions and user interaction processes based on this information.

[0066] The information processing method provided by the above-mentioned embodiments of the present disclosure can display a satisfaction page of a target session in response to an information viewing operation; display satisfaction details information of the target session in the satisfaction page, the satisfaction details information including at least one satisfaction level and factor information of a target influencing factor corresponding to the satisfaction level; the satisfaction details information is obtained by performing data analysis on session data of the target session; the session data at least includes performance data and abnormal data corresponding to the target session obtained during the life cycle of the target session; the factor information is used to characterize the degree of influence of the target influencing factor on the classification of the target session into a satisfaction level; it is realized that the performance data and abnormal data of the target session are obtained from the perspective of front-end monitoring, and based on this The satisfaction level of the user satisfaction of the target session and the factor information of its corresponding target influencing factor are analyzed, which greatly reduces the need for users to actively feedback their experience information during the user satisfaction measurement process, and avoids the dependence of the obtained user satisfaction on the user's product familiarity and user cognition, thereby improving the versatility of user satisfaction measurement and providing developers with more objective and accurate user satisfaction data reference; in addition, the satisfaction-related information obtained from the analysis can be displayed through the satisfaction page, which improves the convenience and efficiency of developers in obtaining product user satisfaction-related information, and can provide effective guidance for product improvement through the displayed user satisfaction factor information, thereby improving product improvement efficiency.

[0067] Figure 3 1 is a flow chart of determining the satisfaction level of a single session in the information processing method provided by the embodiments of the present disclosure. If the target session is a single session, the single session satisfaction level determination process in these embodiments can be executed for the target session; if the target session includes multiple single sessions, the single session satisfaction level determination process in these embodiments can be executed for any single session. Figure 3 The process of determining the satisfaction level of a single session specifically includes the following steps:

[0068] S310: Determine multiple target influencing factors from multiple candidate influencing factors based on session data of a single session.

[0069] Specifically, according to the above description, multiple candidate impact factors can be pre-set for each business. After obtaining the session data of a single session, considering that a single session may not trigger all candidate impact factors. Therefore, the electronic device can analyze the session data of a single session to determine which candidate impact factors are covered in the session data, and determine these candidate impact factors as the target impact factors of the single session.

[0070] For example, as shown in the following table, the session data of a single session covers 9 target influencing factors, including initial loading performance, interactive behavior 1 performance, interactive behavior 2 performance, interactive behavior 3 performance, interactive behavior 4 performance, interactive behavior 5 performance, code running errors, long task time taking too long, and long request time taking too long.

[0071]

[0072] S320: Based on the level identifier and the factor weight of the satisfaction level corresponding to each target influencing factor, determine the total proportion of each target influencing factor corresponding to the level identifier.

[0073] Among them, the grade identifier is the identifier of the satisfaction grade to which the target influencing factor belongs, for example, it can be a grade name / abbreviation, grade code, etc. The satisfaction grade of the influencing factor is consistent with the satisfaction grade of the session. The satisfaction grade of the target influencing factor can be a preset default value, or it can be customized by relevant personnel based on the characteristics of the influencing factor. The factor weight is the weight value of the target influencing factor, which reflects the importance of the target influencing factor in the user satisfaction measurement. The factor weight can be a preset default value, or it can be a weight value customized by relevant personnel based on their business concerns. For example, a larger weight value can be set for a target influencing factor that is highly relevant to business concerns, while a smaller weight value can be set for a target influencing factor that is less relevant to business concerns.

[0074] Specifically, each target influencing factor should have a weight distinction. For example, for the two target influencing factors of code operation abnormality and white screen, the impact of white screen on user satisfaction will be significantly greater. Because once a white screen appears, the user experience will undoubtedly be very bad. In contrast, code operation abnormality may only slightly affect the user experience. Therefore, when allocating factor weights, it is necessary to make appropriate adjustments based on the importance and impact of different target influencing factors to more accurately evaluate the contribution of different influencing factors in user experience to the overall user satisfaction, so as to more truly reflect the impact of each influencing factor on the product / service experience. Similarly, each target influencing factor can also have a satisfaction level distinction. For example, for the target influencing factor of the blocking signal category, as long as it occurs, it will have a negative impact on the user experience, so it corresponds to the level identification of the three-level satisfaction level; and for the target influencing factor of the interactive performance category, it has the difference of the speed of interactive response. The faster the interactive response, the better the user experience, and vice versa, the worse the user experience, so this type of target influencing factor can correspond to the first-level identification, the second-level identification or the third-level identification according to its response speed. Through such a satisfaction level division, we can more accurately understand the impact of different target influencing factors on user emotions.

[0075] In specific implementation, the electronic device can obtain the level identification and factor weight of the satisfaction level of each target influencing factor, as shown in the table above. Then, the electronic device can use these data to calculate the total proportion of each target influencing factor corresponding to each level identification in all target influencing factors to represent the relative importance of each satisfaction level in a single session.

[0076] In some embodiments, S320 includes: determining the level weight corresponding to each level identifier based on the level identifier and factor weight corresponding to each target impact factor; and determining the total proportion of each target impact factor corresponding to the level identifier based on each level weight.

[0077] Specifically, the data in the above table is used as an example for explanation. The electronic device first accumulates the factor weights of each target influencing factor corresponding to each grade identifier, and obtains the total weight of each target influencing factor belonging to the corresponding satisfaction level as the grade weight corresponding to the corresponding grade identifier. For example, the grade weight of the first-level grade identifier (denoted as S) = 10 + 3 + 3 = 16; the grade weight of the second-level grade identifier (denoted as T) = 3 + 3 + 3 = 9; the grade weight of the third-level grade identifier (denoted as F) = 5 + 3 + 3 = 11.

[0078] Then, the electronic device calculates the proportion of the grade weight of each grade identifier relative to the sum of the grade weights of all grade identifiers as the total proportion of the corresponding grade identifier. For example, the total weight of all target influence factors (recorded as Total) = 16 + 9 + 11 = 36. Then, the total proportion of the first-level grade identifier = S / Total = 16 / 36*100% = 44%, indicating that 44% of the target influence factors in a single session belong to the first-level satisfaction level; the total proportion of the second-level grade identifier = T / Total = 9 / 36*100% = 25%, indicating that 25% of the target influence factors in a single session belong to the second-level satisfaction level; the total proportion of the third-level grade identifier = F / Total = 11 / 36*100% = 30.5%, indicating that 30.5% of the target influence factors in a single session belong to the third-level satisfaction level.

[0079] In other embodiments, S320 includes: determining the weight ratio of each target influence factor based on the factor weight corresponding to each target influence factor; and determining the sum of the weight ratios corresponding to each level identifier as the total ratio of the corresponding level identifier based on the level identifier corresponding to each target influence factor.

[0080] Specifically, the data in the above table is used as an example for explanation. The electronic device can first calculate the ratio of the factor weight of each target influencing factor to the sum of the factor weights of all level identifications as the weight ratio of the corresponding target influencing factor. For example, the total weight of all target influencing factors (denoted as Total) = 10+3+3+3+3+3+5+3+3=36. Then, the weight ratio of each target influencing factor = factor weight / Total*100%, and the result is shown in the last row of the above table. Then, the electronic device accumulates the weight ratios of each target influencing factor corresponding to each level identification, and obtains the total ratio of each target influencing factor belonging to the corresponding satisfaction level, as the total ratio corresponding to the corresponding level identification. For example, the total proportion of first-level grade identification = 27.78% + 8.33% + 8.33% = 44%, indicating that 44% of the target influence factors in a single session belong to the first-level satisfaction level; the total proportion of second-level grade identification = 8.33% + 8.33% + 8.33% = 25%, indicating that 25% of the target influence factors in a single session belong to the second-level satisfaction level; the total proportion of third-level grade identification = 13.89% + 8.33% + 8.33% = 30.5%, indicating that 30.5% of the target influence factors in a single session belong to the third-level satisfaction level.

[0081] In some embodiments, the process of the electronic device determining the factor weight of the target influence factor includes: in response to a first parameter setting operation on any target influence factor, determining the received parameter value as the factor weight of the target influence factor.

[0082] Specifically, in order to improve the flexibility of the satisfaction level determination process and make it applicable to different front-end scenarios, so as to more accurately evaluate user satisfaction and provide targeted improvement suggestions, the electronic device can provide an interactive interface for customizing the factor weights. In this way, the user can perform a parameter setting operation (i.e., a first parameter setting operation) of the factor weights through the interactive interface. The electronic device can receive the parameter value set by the user in response to the first parameter setting operation as the factor weight of the object of the first parameter setting operation (such as a certain target influencing factor).

[0083] In some embodiments, for each target impact factor included in the blocking signal category, whether it is a network disconnection, server error or other problem, it will interrupt or hinder the user's normal operation process, thereby bringing a bad experience to the user, so it can only correspond to the level identification of the third level of satisfaction level. Therefore, relevant personnel can pre-set the level identification of the target impact factor of this category to the third level identification through the configuration file or the interactive interface for customizing the level identification provided by the electronic device.

[0084] In other embodiments, for each target influencing factor included in the interactive performance category, the operation waiting category, and the operation duration category, the feedback results have different effects on user satisfaction in different numerical ranges. For example, for each target influencing factor in the interactive performance category, if the interactive response is fast, the user will feel satisfied; if the interactive response is general, the user may not have obvious emotions; and if the interactive response delay is serious, the user will feel frustrated. Therefore, different numerical ranges of interactive response speed can be set for it to determine its corresponding level identification as a first-level identification, a second-level identification, or a third-level identification. For another example, for the operation waiting category, a shorter operation waiting time will not make the user particularly happy; but a longer operation waiting time will make the user's mood worse. Therefore, different numerical ranges of operation waiting time can be set for it to determine its corresponding level identification as a second-level identification or a third-level identification. For another example, for the operation duration category, if the operation duration exceeds the normal duration, it means that there are problems with the usability and layout of the product, which makes it difficult for the user to complete the operation within the normal time and feel frustrated; if the operation duration is lower than the normal duration, it means that the product performance is excellent and the user is satisfied or exceeds expectations. Therefore, a numerical range of a normal duration may be set for it to determine its corresponding level identification as a primary identification, a secondary identification or a tertiary identification.

[0085] In specific implementation, based on the above description, the corresponding level identification can be automatically identified by setting the numerical range value thereof. The electronic device can provide an interactive interface for customizing the numerical range of each target influencing factor in the above categories. In this way, the user can perform a parameter setting operation (i.e., a second parameter setting operation) of the numerical range through the interactive interface. The electronic device can then receive the parameter value set by the user in response to the second parameter setting operation as the factor range value of the object of the second parameter setting operation (such as a target influencing factor under the above three influencing factor categories). Then, the electronic device can compare the actual parameter value (i.e., the target parameter value) of each target influencing factor in the session data of a single session with the factor range value set by it to determine which level identification the target parameter value is in the factor range value corresponding to, thereby determining the level identification corresponding to the target influencing factor.

[0086] It should be noted that the electronic device can also provide an interactive function for adding or deleting candidate influencing factors to further improve the flexibility of the satisfaction level determination process and its universality to different front-end scenarios.

[0087] S330: Determine a satisfaction level of a single session based on the total proportion corresponding to the level identifier and a preset level threshold.

[0088] The preset level threshold is a critical value of a preset satisfaction level, which can be used to measure the satisfaction level of a single session as a first-level satisfaction level, a second-level satisfaction level, or a third-level satisfaction level.

[0089] Specifically, the electronic device may compare the total proportion of each level identifier calculated above with the corresponding preset level threshold, and determine the satisfaction level of the single session according to the comparison result. For example, preset level thresholds of three satisfaction levels may be pre-set, and then each total proportion may be compared with the preset level threshold of the corresponding level to determine the satisfaction level of the single session.

[0090] In some embodiments, the preset level threshold includes a threshold corresponding to the first level satisfaction level (i.e., the first level threshold) and a threshold corresponding to the third level satisfaction level (i.e., the second level threshold). In this case, S330 includes: if the total proportion corresponding to the level identifier of the first level satisfaction level is greater than the first level threshold, then the single session is determined to be the first level satisfaction level; if the total proportion corresponding to the level identifier of the first level satisfaction level is less than or equal to the first level threshold, and the total proportion corresponding to the level identifier of the third level satisfaction level is less than or equal to the second level threshold, then the single session is determined to be the second level satisfaction level; if the total proportion corresponding to the level identifier of the third level satisfaction level is greater than the second level threshold, then the single session is determined to be the third level satisfaction level.

[0091] Specifically, the electronic device compares the total proportion corresponding to the level identifier of the first-level satisfaction level with the first-level threshold, or compares the total proportion corresponding to the level identifier of the third-level satisfaction level with the second-level threshold. If the total proportion corresponding to the level identifier of the first-level satisfaction level is greater than the first-level threshold, the single session is determined to be the first-level satisfaction level. If the total proportion corresponding to the level identifier of the first-level satisfaction level is less than or equal to the first-level threshold, and the total proportion corresponding to the level identifier of the third-level satisfaction level is less than or equal to the second-level threshold, the single session is determined to be the second-level satisfaction level. If the total proportion corresponding to the level identifier of the third-level satisfaction level is greater than the second-level threshold, the single session is determined to be the third-level satisfaction level.

[0092] Take the above table, the first level threshold is 50%, and the second level threshold is 30% as an example. The total proportion of the first level identification is 44%, which is less than the first level threshold; the total proportion of the third level identification is 30.5%, which is greater than the second level threshold. Therefore, the satisfaction level of a single session in this example is the third level satisfaction level "frustrated".

[0093] The method for determining the satisfaction level provided in the above-mentioned embodiments of the present disclosure can determine multiple target influencing factors from multiple candidate influencing factors for a single session in a target session based on session data; determine the total proportion of each target influencing factor corresponding to the level identifier based on the level identifier and the factor weight of the satisfaction level corresponding to each target influencing factor; determine the satisfaction level of a single session based on the total proportion corresponding to the level identifier and a preset level threshold; measure the real experience of the user from the perspective of a single session, and associate the front-end monitoring data with the actual experience and actual churn of the user, thereby realizing the monitoring and optimization guidance of the user experience.

[0094] The following is an embodiment of an information processing device provided by an embodiment of the present invention. The device and the information processing methods of the above-mentioned embodiments belong to the same inventive concept. For details not described in detail in the embodiment of the information processing device, reference can be made to the embodiments of the above-mentioned information processing methods.

[0095] Figure 4 FIG. 1 is a schematic diagram showing the structure of an information processing device provided by an embodiment of the present disclosure. Figure 4 As shown, the information processing device 400 may include:

[0096] A page display module 410, for displaying a satisfaction page of a target session in response to an information viewing operation;

[0097] The information display module 420 is used to display the satisfaction details information of the target session in the satisfaction page, and the satisfaction details information includes at least one satisfaction level and factor information of the target influencing factor corresponding to the satisfaction level; wherein the satisfaction details information is obtained by performing data analysis on the session data of the target session; the session data includes at least performance data and abnormal data corresponding to the target session obtained during the life cycle of the target session; the factor information is used to characterize the degree of influence of the target influencing factor on the classification of the target session into the satisfaction level.

[0098] The information processing device provided by the above-mentioned embodiments of the present disclosure can display a satisfaction page of a target session in response to an information viewing operation; display satisfaction details information of the target session in the satisfaction page, and the satisfaction details information includes at least one satisfaction level and factor information of a target influencing factor corresponding to the satisfaction level; the satisfaction details information is obtained by performing data analysis on session data of the target session; the session data at least includes performance data and abnormal data corresponding to the target session obtained during the life cycle of the target session; the factor information is used to characterize the degree of influence of the target influencing factor on the classification of the target session into a satisfaction level; it is realized that the performance data and abnormal data of the target session are obtained from the perspective of front-end monitoring, and based on this The satisfaction level of the user satisfaction of the target session and the factor information of its corresponding target influencing factor are analyzed, which greatly reduces the need for users to actively feedback their experience information during the user satisfaction measurement process, and avoids the dependence of the obtained user satisfaction on the user's product familiarity and user cognition, thereby improving the versatility of user satisfaction measurement and providing developers with more objective and accurate user satisfaction data reference; in addition, the satisfaction-related information obtained from the analysis can be displayed through the satisfaction page, which improves the convenience and efficiency of developers in obtaining product user satisfaction-related information, and can provide effective guidance for product improvement through the displayed user satisfaction factor information, thereby improving product improvement efficiency.

[0099] In some embodiments, the information processing device 400 further includes a session profile information display module, which is used to:

[0100] After displaying the satisfaction details information of the target session in the satisfaction page, in response to a triggering operation on any target influencing factor, the session profile information corresponding to the triggered target influencing factor is displayed; the session profile information includes a session identifier of at least one single session, or includes a session identifier of at least one single session and the impact result generated by the triggered target influencing factor in the single session.

[0101] In some embodiments, the information processing device 400 further includes a session details page display module, which is used to:

[0102] In response to a trigger operation on any target influencing factor, after displaying the session profile information corresponding to the triggered target influencing factor, in response to a trigger operation on a session identifier, display a session details page of a single session corresponding to the triggered session identifier, and display session data of multiple dimensions of the single session in the session details page.

[0103] In some embodiments, the information processing device 400 further includes:

[0104] A target influencing factor determination module is used to determine a plurality of target influencing factors from a plurality of candidate influencing factors for a single session in the target session based on session data before displaying the satisfaction details information of the target session in the satisfaction page;

[0105] A total proportion determination module, used to determine the total proportion of each target influencing factor corresponding to the grade identifier based on the grade identifier and factor weight of the satisfaction grade corresponding to each target influencing factor;

[0106] The satisfaction level determination module is used to determine the satisfaction level of a single session based on the total proportion corresponding to the level identifier and a preset level threshold.

[0107] In some embodiments, the total proportion determination module is specifically used to:

[0108] Based on the level identifier and factor weight corresponding to each target impact factor, determine the level weight corresponding to each level identifier;

[0109] Based on the weights of each level, determine the total proportion of each target impact factor corresponding to the level identification.

[0110] In some other embodiments, the total proportion determination module is specifically used to:

[0111] Based on the factor weight corresponding to each target impact factor, determine the weight ratio of each target impact factor;

[0112] Based on the level identification corresponding to each target impact factor, the sum of the weight proportions corresponding to each level identification is determined as the total proportion of the corresponding level identification.

[0113] In some embodiments, the satisfaction level determination module is specifically configured to:

[0114] If the total proportion corresponding to the level identifier of the first level satisfaction level is greater than the first level threshold, the single session is determined to be at the first level satisfaction level;

[0115] If the total proportion corresponding to the level identifier of the first level satisfaction level is less than or equal to the first level threshold, and the total proportion corresponding to the level identifier of the third level satisfaction level is less than or equal to the second level threshold, then the single session is determined to be at the second level satisfaction level;

[0116] If the total proportion corresponding to the level identifier of the third level of satisfaction level is greater than the second level threshold, it is determined that the single session is at the third level of satisfaction level.

[0117] In some embodiments, the information processing device 400 further includes a factor weight setting module, which is used to:

[0118] Before determining the total proportion of the target influence factors corresponding to each grade identifier based on the grade identifier and factor weight of the satisfaction grade corresponding to each target influence factor, in response to the first parameter setting operation on any target influence factor, the received parameter value is determined as the factor weight of the target influence factor.

[0119] In some embodiments, the information processing device 400 further includes a level identification determination module, which is used to:

[0120] Before determining the total proportion of each target influence factor corresponding to each level identifier based on the level identifier and the factor weight of the satisfaction level corresponding to each target influence factor, in response to a second parameter setting operation for any satisfaction level of the target influence factor, determining the received parameter value as the factor range value of the target influence factor;

[0121] Based on the target parameter value of the target influencing factor in the conversation data and the factor range value of each satisfaction level, the level identifier corresponding to the target influencing factor is determined.

[0122] In some embodiments, the satisfaction page also displays satisfaction profile information and / or session profile information of the target session;

[0123] The satisfaction profile information at least includes the session distribution information corresponding to each satisfaction level;

[0124] The session profile information includes at least one of the number of sessions, the number of users, the average session duration, the average session depth, the session entry, and the session exit corresponding to the target session.

[0125] In some embodiments, the satisfaction detail information also includes category information of the influencing factor category, and the category information is obtained based on the factor information of each target influencing factor contained in the influencing factor category; the influencing factor category includes at least one of the blocking signal category, the interactive performance category, the operation duration category and the operation waiting category.

[0126] The information processing device provided by the embodiment of the present invention can execute the information processing method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0127] It is worth noting that in the embodiment of the above-mentioned information processing device, the various modules included are only divided according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be realized; in addition, the specific names of the various functional modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this disclosure.

[0128] The present disclosure also provides an electronic device, which may include a processor and a memory, wherein the memory may be used to store executable instructions, wherein the processor may be used to read the executable instructions from the memory and execute the executable instructions to implement the information processing method in the above embodiment.

[0129] Figure 5 A schematic structural diagram of an electronic device provided by an embodiment of the present disclosure is shown.

[0130] like Figure 5 As shown, the electronic device 500 may include a processing device 501 (e.g., a central processing unit, a graphics processing unit, etc.), which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 502 or a program loaded from a storage device 508 into a random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the electronic device 500 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other via a bus 504. An input / output interface (I / O interface) 505 is also connected to the bus 504.

[0131] Typically, the following devices may be connected to the I / O interface 505: an input device 506 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 507 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 508 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 509. The communication device 509 may allow the electronic device 500 to communicate with other devices wirelessly or by wire to exchange data.

[0132] It should be noted that Figure 5 The electronic device 500 shown is only an example and should not limit the functions and scope of use of the embodiments of the present disclosure. Figure 5 The electronic device 500 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0133] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication device 509, or installed from the storage device 508, or installed from the ROM 502. When the computer program is executed by the processing device 501, the above-mentioned functions defined in the information processing method of any embodiment of the present disclosure are executed.

[0134] The embodiments of the present disclosure further provide a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the processor implements the information processing method in any embodiment of the present disclosure.

[0135] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0136] In some embodiments, the client and server may communicate using any currently known or future developed network protocol such as HTTP, and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), an internet (e.g., the Internet), and a peer-to-peer network (e.g., an ad hoc peer-to-peer network), as well as any currently known or future developed network.

[0137] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0138] The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device executes the information processing method described in any embodiment of the present disclosure.

[0139] In embodiments of the present disclosure, computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including but not limited to object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on a user's computer, partially on a user's computer, as a separate software package, partially on a user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0140] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the equipment, method and computer program product according to various embodiments of the present disclosure. In this regard, each box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0141] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0142] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0143] The above description is only a preferred embodiment of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present disclosure (but not limited to) by each other to form a technical solution.

[0144] In addition, although each operation is described in a specific order, this should not be understood as requiring these operations to be performed in the specific order shown or in a sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination mode.

[0145] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

Claims

1. An information processing method, characterized in that: include: In response to the information viewing operation, displaying a satisfaction page of the target session; The satisfaction details information of the target session is displayed in the satisfaction page, and the satisfaction details information includes at least one satisfaction level and factor information of a target influencing factor corresponding to the satisfaction level; wherein the satisfaction details information is obtained by performing data analysis on session data of the target session; the session data includes at least performance data and abnormal data corresponding to the target session obtained during the life cycle of the target session; the factor information is used to characterize the degree of influence of the target influencing factor on the classification of the target session into the satisfaction level.

2. The method according to claim 1, characterized in that: After displaying the satisfaction details information of the target session in the satisfaction page, the method further includes: In response to a triggering operation on any of the target influencing factors, the session profile information corresponding to the triggered target influencing factor is displayed; the session profile information includes a session identifier of at least one single session, or includes a session identifier of at least one single session and the impact result generated by the triggered target influencing factor in the single session.

3. The method according to claim 2, characterized in that After displaying the session brief information corresponding to the triggered target influence factor in response to the triggering operation on any of the target influence factors, the method further includes: In response to the triggering operation on the session identifier, a session details page of the single session corresponding to the triggered session identifier is displayed, and session data of multiple dimensions of the single session are displayed in the session details page.

4. The method according to claim 1, characterized in that: Before displaying the satisfaction details information of the target session in the satisfaction page, the method further includes: For a single session in the target session, determining a plurality of target influencing factors from a plurality of candidate influencing factors based on the session data; Based on the level identifier and the factor weight of the satisfaction level corresponding to each of the target influencing factors, determining the total proportion of each of the target influencing factors corresponding to the level identifier; The satisfaction level of the single session is determined based on the total proportion corresponding to the level identifier and a preset level threshold.

5. The method according to claim 4, characterized in that The determining, based on the level identifier and the factor weight of the satisfaction level corresponding to each target influencing factor, the total proportion of each target influencing factor corresponding to the level identifier includes: Determine the grade weight corresponding to each grade identifier based on the grade identifier and the factor weight corresponding to each target impact factor; Based on each of the grade weights, the total proportion of each of the target impact factors corresponding to the grade identifier is determined.

6. The method according to claim 4, characterized in that The determining, based on the level identifier and the factor weight of the satisfaction level corresponding to each target influencing factor, the total proportion of each target influencing factor corresponding to the level identifier includes: Determine the weight ratio of each target impact factor based on the factor weight corresponding to each target impact factor; Based on the level identifier corresponding to each of the target impact factors, the sum of the weight proportions corresponding to each of the level identifiers is determined as the total proportion of the corresponding level identifier.

7. The method according to claim 4, characterized in that The determining the satisfaction level of the single session based on the total proportion corresponding to the level identifier and a preset level threshold includes: If the total proportion corresponding to the level identifier of the first level satisfaction level is greater than the first level threshold, determining that the single session is at the first level satisfaction level; If the total proportion corresponding to the level identifier of the first level satisfaction level is less than or equal to the first level threshold, and the total proportion corresponding to the level identifier of the third level satisfaction level is less than or equal to the second level threshold, it is determined that the single session is at the second level satisfaction level; If the total proportion corresponding to the level identifier of the third level satisfaction level is greater than the second level threshold, it is determined that the single session is at the third level satisfaction level.

8. The method according to claim 4, characterized in that Before determining the total proportion of each target impact factor corresponding to each target impact factor based on the level identifier and the factor weight of the satisfaction level corresponding to each target impact factor, the method further includes: In response to a first parameter setting operation on any of the target impact factors, the received parameter value is determined as the factor weight of the target impact factor.

9. The method according to claim 4, characterized in that Before determining the total proportion of each target impact factor corresponding to each target impact factor based on the level identifier and the factor weight of the satisfaction level corresponding to each target impact factor, the method further includes: In response to a second parameter setting operation on any one of the satisfaction levels of the target impact factor, determining the received parameter value as a factor range value of the target impact factor; The level identifier corresponding to the target influence factor is determined based on the target parameter value of the target influence factor in the session data and the factor range value of each satisfaction level.

10. The method according to claim 1, characterized in that The satisfaction page also displays satisfaction profile information and / or session profile information of the target session; The satisfaction profile information at least includes session distribution information corresponding to each satisfaction level; The session profile information includes at least one of the number of sessions, the number of users, the average session duration, the average session depth, the session entry and the session exit corresponding to the target session.

11. The method according to claim 1, characterized in that: The satisfaction detail information also includes category information of the influencing factor category, and the category information is obtained based on the factor information of each target influencing factor contained in the influencing factor category; the influencing factor category includes at least one of a blocking signal category, an interactive performance category, an operation duration category and an operation waiting category.

12. An information processing device, characterized in that: include: A page display module, for displaying a satisfaction page of a target session in response to an information viewing operation; An information display module is used to display the satisfaction details information of the target session in the satisfaction page, the satisfaction details information including at least one satisfaction level and factor information of the target influencing factor corresponding to the satisfaction level; wherein the satisfaction details information is obtained by performing data analysis on the session data of the target session; the session data at least includes performance data and abnormal data corresponding to the target session obtained during the life cycle of the target session; the factor information is used to characterize the degree of influence of the target influencing factor on the classification of the target session into the satisfaction level.

13. An electronic device, characterized in that: include: processor; A memory for storing executable instructions; The processor is used to read the executable instructions from the memory and execute the executable instructions to implement the information processing method described in any one of claims 1 to 11.

14. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the processor implements the information processing method according to any one of claims 1 to 11.

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