User Experience Data Processing Method and Electronic Device

Abstract

Embodiments of the present application disclose a user experience data processing method and an electronic device. The method includes: obtaining analysis objects generated in a target information system, including multiple first analysis objects and multiple second analysis objects; determining a positive influence value on user experience generated by the target information system according to the multiple first analysis objects; determining a negative influence value on user experience generated by the target information system according to the user experience obstacle problem categories corresponding to the multiple second analysis objects, where the user experience obstacle problem categories are determined after clustering according to corresponding solution schemes and problem handlers; determining whether it is necessary to improve the user experience of the target information system according to the positive influence value and the negative influence value, and if so, providing the corresponding solution scheme to the problem handler. Through the embodiments of the present application, it is possible to more effectively measure the experience brought by the information system to users and achieve operability.

Description

Technical Field

[0001] This application relates to the technical field of user experience measurement, and particularly to a method for processing user experience data and an electronic device. Background Art

[0002] For the developers or operators of information systems, in order to better retain customers, the past general focus has been on what products can be delivered to users or what services can be provided. For example, for an e-commerce information service system, the usual focus is on what goods consumers can purchase through the system. For a mobile payment system, the usual focus is on what specific payment services can be provided to merchants or consumers, and so on.

[0003] However, with the reduction of market dividends, the focus of system developers or operators is shifting from "delivering products" to "delivering experiences", that is, the focus is changing to: what kind of experiences can be created for users. For example, in an e-commerce information service system, it may be more concerned about whether there are obstacles during the order placement process, whether a certain coupon can be used normally, whether there are logistics delays or package damages during the fulfillment process, and so on.

[0004] In the prior art, user experience information is mainly obtained through methods such as questionnaires. For example, a certain number of users are randomly selected each month, and questionnaires are sent to them to ask whether they have encountered certain obstacles during the use of the system, and so on. However, this method has at least the following problems: First, it is mainly from the perspective of managers, obtaining macroscopic characterization indicators related to user experience, which is not operable, that is, the executor cannot know exactly what operational actions should be taken to improve the user experience. And because only a part of users are selected for research, it is not comprehensive and objective enough.

[0005] Therefore, how to more effectively measure the experience brought by an information system to users has become a technical problem that needs to be solved by those skilled in the art. Summary of the Invention

[0006] This application provides a method for processing user experience data and an electronic device, which can more effectively measure the experience brought by an information system to users and achieve operability.

[0007] This application provides the following solutions:

[0008] A method for processing user experience data, including:

[0009] Obtaining analysis objects generated in a target information system, where the analysis objects include multiple first analysis objects representing no user experience obstacle problems and multiple second analysis objects representing user experience obstacle problems;

[0010] Determine the positive impact value of the target information system on the user experience according to the multiple first analysis objects;

[0011] Determine the negative impact value of the target information system on the user experience according to the user experience obstacle problem categories corresponding to the multiple second analysis objects; the user experience obstacle problem categories are determined after clustering according to the corresponding solutions and problem handlers;

[0012] Determine whether it is necessary to improve the user experience of the target information system according to the positive impact value and the negative impact value. If so, provide the corresponding solution to the problem handler.

[0013] Among them, obtaining the analysis objects generated in the target information system includes:

[0014] Obtain the quasi-real-time analysis objects generated in the target information system during the target historical time period.

[0015] Among them, obtaining the analysis objects generated in the target information system includes:

[0016] Obtain the analysis objects generated in real time in the target information system during the target statistical period;

[0017] The method further includes:

[0018] When new analysis objects are generated during the target statistical period, re-determine the positive impact value and / or the negative impact value.

[0019] Among them, the target information system includes a commodity object information system, and the analysis object includes order data;

[0020] Among them, obtaining the analysis objects generated in the target information system includes:

[0021] Determine the new orders generated in the target information system during the target statistical period, and / or the historical orders with user positive reviews, and / or the historical orders with on-time fulfillment as the first analysis objects representing no user experience obstacle problems.

[0022] Among them, obtaining the analysis objects generated in the target information system includes:

[0023] Obtain multiple second analysis objects corresponding to various user experience obstacle problems generated by the target information system at multiple links of the data link.

[0024] Among them, obtaining the analysis objects generated in the target information system includes:

[0025] Determine multiple second analysis objects corresponding to multiple user experience obstacle problems based on the user negative feedback generated within the target statistical period, the status of the operation node, and / or the behaviors of users towards the analysis object.

[0026] Among them, the categories of user experience obstacle problems have corresponding weights; the weights represent the severity of the impact of the categories of user experience obstacle problems on the user experience.

[0027] Determining the negative impact value of the target information system on the user experience according to the categories of user experience obstacle problems respectively corresponding to the multiple second analysis objects includes:

[0028] According to the number of second analysis objects under various categories of user experience obstacle problems and the weights of the categories of user experience obstacle problems, respectively determine the negative impact value components corresponding to each category of user experience obstacle problems, and determine the negative impact value of the target information system on the user experience according to each negative impact value component.

[0029] Among them, it also includes:

[0030] Respectively obtain the severity information of the impact of the categories of user experience obstacle problems on the user experience in the user perception dimension and in the user behavior dimension, and determine the weights corresponding to the categories of user experience obstacle problems according to the severity information in the two dimensions.

[0031] Among them, obtaining the severity information of the impact of the categories of user experience obstacle problems on the user experience in the user perception dimension and in the user behavior dimension includes:

[0032] According to the common information and difference information existing in the perception dimension and / or behavior dimension of multiple different user groups, determine the severity information of the impact of the categories of user experience obstacle problems on the user experience in the user perception dimension and in the user behavior dimension respectively.

[0033] Among them, the weights corresponding to the categories of user experience obstacle problems are determined in advance, or are dynamically updated during the process of quantifying the impact of the target information system on the user experience.

[0034] Among them, determining whether it is necessary to improve the user experience of the target information system according to the positive impact value and the negative impact value includes:

[0035] Determine the user experience impact index obtained by the target information system according to the positive impact value and the negative impact value;

[0036] By comparing the user experience impact index with the target threshold, determine whether it is necessary to improve the user experience of the target information system.

[0037] Further included are:

[0038] The user experience impact index is disassembled from the target dimension to obtain user experience impact indices corresponding to multiple sub-items, so as to determine whether it is necessary to improve the user experience according to the user experience impact indices corresponding to the sub-items, and the problem handler performs the operation actions corresponding to the solution on the sub-items.

[0039] Among them, the target dimension includes: the application module dimension in the target information system, and the user experience impact index component is used to represent the user experience impact indices corresponding to multiple different application modules.

[0040] Among them, the target dimension includes: the link dimension included in the processing link of the analysis object, and the user experience impact index component is used to represent the user experience impact indices corresponding to multiple different links.

[0041] Among them, the target dimension includes: the problem handler dimension of the analysis object, and the user experience impact index component is used to express the user experience impact indices of multiple different problem handlers for performance appraisal of the problem handlers.

[0042] Among them, the target information system includes a commodity object information service system;

[0043] The target dimension includes: the commodity object category dimension or the commodity object dimension, and the user experience impact index component is used to represent the user experience impact indices corresponding to multiple different commodity object categories or different commodity objects.

[0044] Further included are:

[0045] The user experience impact index is disassembled at multiple different granularities under the same sub-item for positioning the target object with specific user experience obstacle problems, so that the responsible person preferentially performs the operation actions on the target object.

[0046] Further included are:

[0047] If the target object repeatedly has user experience obstacle problems in a certain problem category, warning information about the target object is provided.

[0048] Among them, providing the corresponding solution to the problem handler includes:

[0049] Provide the information of the solution and the corresponding problem handler to the associated work order system, so that the work order system can generate a task work order based on the solution and the information of the problem handler, and the problem handler can perform the operation actions corresponding to the solution according to the task work order.

[0050] Among them, the analysis object is determined according to the final goal to be achieved in the target information system.

[0051] Among them, the target information system includes a commodity object information service system, and the analysis object includes a transaction order; or,

[0052] The target information system includes a logistics service system, and the analysis object includes a logistics order; or,

[0053] The target information system includes a mobile payment system, and the analysis object includes records of income and expenditure operation behaviors; or,

[0054] The target information system includes a customer service system, and the analysis object includes customer service session records.

[0055] A user experience data processing device includes:

[0056] An analysis object acquisition unit, configured to acquire analysis objects generated in a target information system, where the analysis objects include multiple first analysis objects representing no user experience obstacle problems and multiple second analysis objects representing user experience obstacle problems;

[0057] A positive influence value determination unit, configured to determine a positive influence value generated by the target information system on user experience according to the multiple first analysis objects;

[0058] A negative influence value determination unit, configured to determine a negative influence value generated by the target information system on user experience according to the user experience obstacle problem categories corresponding to the multiple second analysis objects; the user experience obstacle problem categories are determined after clustering according to the corresponding solutions and problem handlers;

[0059] A solution providing unit, configured to determine whether it is necessary to improve the user experience of the target information system according to the positive influence value and the negative influence value, and if so, provide a corresponding solution to the problem handler.

[0060] A computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the method described in any one of the foregoing are implemented.

[0061] An electronic device includes:

[0062] One or more processors; and

[0063] A memory associated with the one or more processors, the memory being configured to store program instructions that, when read and executed by the one or more processors, perform the steps of the method according to any one of the foregoing.

[0064] According to the specific embodiments provided in the present application, the present application discloses the following technical effects:

[0065] Through the embodiments of the present application, the analysis objects generated in the target information system can be used as data sources. By counting multiple first analysis objects representing no user experience obstacle problems and multiple second analysis objects corresponding to user experience obstacle problems, the positive influence value and negative influence value of the target information system on user experience can be determined. Furthermore, based on the positive influence value and negative influence value, it can be determined whether the user experience of the target information system needs to be improved. Among them, when determining the negative influence value, the multiple second analysis objects can be classified into corresponding problem categories according to the problem categories to which the user experience obstacle problems belong. Then, based on information such as the number of second analysis objects under various problem categories, the negative influence value of the target information system on user experience can be determined. Moreover, in the embodiments of the present application, the specific problem categories are determined after clustering according to the solution and the corresponding problem handling party (for example, the responsible person). In this way, the specific problem categories are corresponding to the solution and the problem solving party. Therefore, in the case where it is determined that the user experience of the target information system needs to be improved, the problem handling party that needs to perform operation actions and the solution under each problem category can be identified, and the problem handling party can perform operation actions according to the corresponding solution, thereby improving the user experience. That is to say, in the embodiments of the present application, the specifically measured user experience result is operable. In this way, not only can the quality of the user experience in the target information system be measured, but also when the user experience needs to be improved, it can be known which problem handling party or parties need to perform what operation actions, so as to make a quick and accurate response, thus achieving timely loss prevention.

[0066] Second, in the embodiments of the present application, the analysis objects generated in the target information system (such as orders, user behavior records, etc.) are used as data sources, so that the obtained user experience impact index can be more objective. When obtaining the analysis objects, especially the second analysis objects with user experience obstacle problems, various links, various modules, etc. can be covered as much as possible. Therefore, the data can be made more comprehensive, rather than making one-sided judgments using sampling surveys. In addition, the specific data sources obtained can also be obtained in real time. In this way, as the analysis objects are generated, the user experience impact index can be updated in real time. Therefore, the user experience impact index can also have the characteristic of real-time, and can reflect more real-time problems such as poor user experience in the system, without the need to be gradually reflected in a long statistical cycle. Furthermore, since real-time generated data can be used to measure the user experience situation in the embodiments of the present application, the generation of each analysis object will cause a change in the positive impact value or the negative impact value, thereby changing the user experience impact index. Therefore, the user experience impact index also has the characteristic of sensitivity. And after the responsible person executes the operation action, the execution effect of the operation action can be determined in time through the updated user experience impact index.

[0067] Third, in order to determine the negative impact value, multiple problem categories can be clustered, and weight calculations can be performed for each problem category. In the embodiments of the present application, a measurement method that combines the user perception dimension and the user behavior dimension is used for the weight calculation, so as to obtain a more accurate weight calculation result. And in practical applications, the specific problem clustering and weight calculation processes can also be carried out in real time, that is, as more new data (such as new repurchase behavior data, etc.) is generated in the system, more problem categories can be clustered, or the weights of the problem categories can be updated, etc., so as to achieve adaptive dynamic weighting.

[0068] Fourth, since the analysis objects used in the embodiments of the present application can be small-granularity data units such as orders and user behavior records, the holographic decomposition of the user experience impact index can also be realized, that is, the user experience impact index can be decomposed into experience index components on multiple sub-items in any dimension to reflect the quality of the user experience on multiple shares, etc. For example, it can be specifically decomposed in dimensions such as application modules, each link on the data link, and responsible persons. In the commodity object information system, it can also be decomposed in dimensions such as commodity object categories and commodity objects, so as to determine the user experience situation obtained by each specific category or specific commodity object, etc. Under the same sub-item, further down-drilling of multiple granularities can be carried out to locate the target object with specific user experience obstacle problems, and then the responsible person preferentially executes the operation action on the target object.

[0069] Furthermore, it is also possible to track the user experience impact index, which intuitively reflects the improvement of the operation actions on the user experience. If the user experience impact index fluctuates, or certain objects frequently encounter certain problems in certain problem categories, etc., warnings can also be issued so that the corresponding managers or responsible persons can intervene in a timely manner, etc.

[0070] Of course, it is not necessary for any product implementing this application to achieve all the above-mentioned advantages simultaneously. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for use in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0072] Figure 1 is a schematic diagram of the system architecture provided by the embodiment of the present application;

[0073] Figure 2 is a flowchart of the method provided by the embodiment of the present application;

[0074] Figure 3 is a schematic diagram of the index calculation method provided by the embodiment of the present application;

[0075] Figure 4 is a schematic diagram of the device provided by the embodiment of the present application;

[0076] Figure 5 is a schematic diagram of the electronic device provided by the embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0077] The following will clearly and completely describe the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art belong to the scope of protection of the present application.

[0078] In the embodiments of the present application, a full-process digitalization system for customer experience can be constructed through big data, and a long-term mechanism conducive to the continuous improvement of customer experience can be established within an organization such as an information system, effectively implementing the experience into actions. Specifically, data related to the ultimate goal to be achieved in the information system can be used as the analysis object. For example, for a product object information system (also known as an e-commerce information system, etc.), the ultimate goal to be achieved is the transaction of the product object, and the data related to the transaction is the transaction order. Therefore, the transaction order in the system can be used as the analysis object to measure the impact value of the specific product object information service system on the user experience (in the embodiments of the present application, it can be called the "Rui Si value"). Since this impact value is obtained through data analysis, it can more objectively reflect the experience of users during the process of using the specific information system. Moreover, in the specific implementation, a comprehensive acquisition of the specific analysis object can be carried out instead of sampling, etc. Therefore, more accurate and comprehensive conclusions can be drawn. Furthermore, this analysis object can be obtained in real time, and even every time an analysis object is generated, the impact value can be updated. Therefore, real-time performance can be reflected, enabling changes in the user experience, etc. to be reflected more promptly through the impact value rather than slowly through a long period. Additionally, since the specific analysis object can specifically be data at the minimum unit such as an order or a user behavior, after performing an operation action on this analysis object (for example, modifying the coupon rule of a certain product object), the specific impact value can change to reflect the effect of this operation action on improving the user experience. Therefore, it has the characteristic of sensitivity.

[0079] Among them, specifically when calculating the impact value, the positive impact value and negative impact value of the target information system on the user experience can be determined based on the analysis objects generated within the specific target statistical period. Then, by subtracting the negative impact value from the positive impact value and other methods, the overall impact value of the target information system on the user experience can be determined. The level of this overall impact value represents the popularity of the target information system in terms of user experience. It can also be compared with a pre-set threshold and other methods to judge whether it is necessary to improve the user experience. If necessary, improvement can be made by performing operation actions, and so on.

[0080] Among them, in order to calculate the positive influence value and the negative influence value, when obtaining the analysis object, it may include multiple first analysis objects representing no user experience obstacles generated in the information system, and multiple second analysis objects representing user experience obstacle problems. Among them, regarding the first analysis object, it may be the full amount of analysis objects generated within the target statistical period. For example, when taking one day as the statistical period, it may be newly generated transaction orders on the same day, etc. Regarding the second analysis object, it can be comprehensively obtained from multiple channels. Specifically, various user experience obstacle problems generated at multiple links of a specific data link can be obtained, etc.

[0081] Specifically, after obtaining the first analysis object and the second analysis object, the positive influence value can be determined according to information such as the cumulative quantity of the first analysis object within the target statistical period. Regarding the negative influence value, since there are various specific user experience obstacle problems, the degrees of influence of different types of problems on the user experience may be different. For example, in the commodity object information system, the problem that coupons cannot be used and the problem that orders cannot be placed normally may have different degrees of severity on the user experience, etc. Therefore, in specific implementation, the specific user experience obstacle problems can also be classified. In an optional manner, different problem categories can also correspond to different weights. In this way, the negative influence value generated by the target information system on the user experience can be determined according to the quantity of the second analysis object under various problem categories and the weight of the problem category. Through this method, the actual situation of the user experience can be reflected more accurately.

[0082] Among them, regarding the classification of problem categories, in the embodiments of this application, a solution-based clustering scheme for user experience obstacle problems is adopted. That is to say, the embodiments of this application adopt a "starting from the end" clustering method. When clustering, the solutions corresponding to the problem categories after clustering are considered. Such solutions can correspond to specific responsible persons (that is, front-line executors, rather than managers), so that user experience obstacle problems with the same solutions can be clustered into the same problem category. In this way, during the process of calculating the specific user experience impact index, the negative impact value components corresponding to multiple problem categories can be determined respectively; if the overall user experience impact index calculated finally is relatively low, then based on the negative impact value components corresponding to each problem category, it can be determined which type of problems need to be improved and what specific solutions can be used to solve them. Even the information such as specific negative impact values can be provided to the corresponding responsible persons, enabling them to know what operational actions to perform to improve the overall user experience impact index. That is to say, through this method, the index specifically used to measure the user experience situation is operable. That is, when the user experience is relatively poor, it can be determined which responsible person or persons need to perform what operational actions to improve the user experience. That is to say, it enables the "voice" of users to reflect whether the work done by specific front-line staff is correct. If not, it can be timely known where the problem lies and how to improve the user experience by performing what operational actions.

[0083] In addition, under the way of clustering problems through the above method, if problems can be solved by the same or similar operational actions, the severity of the impact on the user experience is usually similar. Therefore, the same weight can be used to express such severity. That is to say, through this method, the weight measurement of each problem category can be more objective.

[0084] From the perspective of the system architecture, referring to Figure 1 , the embodiments of this application can provide a customer experience full-process digitalization system. This system can collect analysis objects from the target information system based on big data for a more comprehensive, objective, timely, and sensitive measurement of user reputation and the like obtained from the target information system. And by clustering user experience obstacle problems in the solution dimension, the obtained user experience impact index has the characteristic of being operable. For example, specific information such as the user experience impact index can be provided to the responsible persons who can solve specific user experience obstacle problems, enabling the specific responsible persons to know what operational actions to perform to improve the user experience.

[0085] For example, the target information system may be a commodity object information system. In this case, order data can be used as the analysis object. New orders generated within the target period, historical orders with positive user feedback, historical orders with on-time performance, etc. can be used as the first analysis objects representing no user experience obstacle problems; orders with negative user feedback, orders that stay at a certain operation node for a relatively long time, orders that users repeatedly check the status within a short period of time, etc. can be used as the second analysis objects representing user experience obstacle problems. In addition, various possible user experience obstacle problems can be pre-clustered, and user experience obstacle problems corresponding to the same solution and problem handler can be clustered into the same problem category. In this way, the user experience of the target information system can be measured based on information such as the number of the aforementioned first analysis objects and the second analysis objects under each category. When it is found that the user experience needs to be improved, corresponding solutions can be provided to specific problem handlers according to the clustering of problem categories.

[0086] The following provides a detailed introduction to the specific implementation solutions provided in the embodiments of the present application.

[0087] First, the embodiments of the present application provide a method for processing user experience data. Refer to Figure 2 , and the method may specifically include:

[0088] S201: Obtain analysis objects generated in the target information system, where the analysis objects include multiple first analysis objects representing no user experience obstacle problems and multiple second analysis objects representing user experience obstacle problems.

[0089] In the embodiments of the present application, there can be various specific target information systems. For example, it may include a commodity object information system, or a logistics service system, a mobile payment system, a customer service system, etc. The specific analysis object can be determined according to the ultimate goal to be achieved in the target information system. For example, in a commodity object information system, the ultimate goal is to complete a transaction. Therefore, the specific analysis object can be a transaction order. At this time, multiple orders generated in the target information system within the target statistical period can be obtained, including newly generated orders, or orders with user experience obstacle problems, etc. In a logistics service system, the ultimate goal is to deliver a specific package to the designated receiving address. Therefore, the analysis object can be a logistics order; in a mobile payment system, the ultimate goal is to complete a specific collection or payment operation. Therefore, the analysis object can be a record of revenue and expenditure operation behaviors; in a customer service system, the ultimate goal is to complete a specific call or instant messaging session, etc. Therefore, the analysis object can be a customer service session record, etc.

[0090] In specific implementation, the user experience problems of the target information system can be measured according to a certain statistical period. For example, it can be one day as a period, and so on. Among them, the specific analysis object can be the data that is generated in real time within the target statistical period in the target information system. For example, in the case of taking one day as the statistical period, it can be the analysis object that is generated in real time by the target information system on the statistical day. In the case of obtaining the analysis object in this way, each time an analysis object is obtained, it can trigger an update of the user experience impact index, so as to reflect the real-time characteristic of the user experience impact index.

[0091] Alternatively, in the case of insufficient system performance, etc., a quasi-real-time processing method can also be adopted. At this time, the analysis objects generated within the historical time period can be used as the data source to measure the user experience impact index of the information system. Among them, the historical time period here can also be a time period that is relatively close to the current time and has a short time length. For example, the T+1 method can be adopted, and the analysis objects generated on the previous day can be used as the data source, and so on. It should be noted here that even if the T+1 method is used for data source collection, compared with the user research method in the prior art, the real-time nature of the data can be improved to a large extent (in the user research method, usually a cycle of one month or even longer is required).

[0092] Regarding the specific analysis object, for the first analysis object, it can be the full amount of newly generated analysis objects within the target statistical period. For example, in the commodity object information service system, all the newly generated orders within one day, and so on. Of course, in the case of real-time acquisition, the first analysis object can be obtained as new orders are generated, and so on.

[0093] In addition, if the specific information system is a product object information system, then in addition to taking the new orders newly generated within the target statistical period as the first analysis object, the historical orders that received positive user reviews and fulfilled the contract on time within the target statistical period can also be determined as such first analysis objects, and so on. That is to say, not only the newly generated orders can represent the absence of user experience obstacle problems, but also the historical orders that received positive user reviews and fulfilled the contract on time can represent the absence of user experience obstacle problems. In this way, the positive impact value of the target information system on user experience within the target statistical period can be jointly determined by combining the newly generated orders, as well as the historical orders that obtained positive user review information and / or fulfilled the contract on time. Among them, the positive user review information can be determined based on the evaluation information submitted by users, etc., and the on-time contract fulfillment information can be determined based on the changes in the specific order status. For example, within the current target statistical period, if a certain order has completed the contract fulfillment, it can be judged whether the contract fulfillment was completed on the agreed time. If so, it can be determined as an order that fulfilled the contract on time, and so on. That is to say, the specific order may not be newly generated within the current statistical period, but received a positive user review within the current statistical period, or completed the contract fulfillment on time. For example, a certain order may have been generated the day before yesterday and received a positive user review today, or completed the contract fulfillment on time today, and so on.

[0094] For the second analysis object, since it has specific user experience obstacle problems, it belongs to a more important data source when determining the system user experience impact index. Therefore, in specific implementation, it is possible to discover as comprehensively as possible the user experience obstacle problems generated during the target statistical period, as well as the corresponding second analysis objects. For example, specifically, various user experience obstacle problems generated by the target information system at multiple links in the data link, as well as the corresponding second analysis objects, can be obtained. For example, in a product object information system, the transaction order link includes links such as product selection before sales, participation in activities, order placement and payment, the logistics link during sales, and links such as product quality, after-sales service, and consultation and suggestions after sales, and so on. In order to more accurately reflect the actual situation of user experience, it is possible to discover as comprehensively as possible the various user experience obstacle problems that may occur in each link.

[0095] Among them, there are various ways to specifically discover the second analysis object. For example, in one way, based on the user feedback generated within the target statistical period, the multiple user experience obstacle problems and the corresponding multiple second analysis objects can be determined. The user feedback can include various active interactions initiated by users for specific analysis objects (such as orders), including complaints, feedback, refunds, industrial and commercial reports, product evaluations, public opinions in relevant media, and so on. That is to say, if users encounter some experience obstacle problems, they may actively give feedback. Therefore, based on the received user feedback, some analysis objects with user experience obstacle problems can be discovered.

[0096] Or, in some cases, even if users encounter obstacles, they may choose to remain silent, that is, not actively give feedback (after statistics, the actual proportion of this situation is very high in many systems). Therefore, in another way, it is also possible to judge whether the corresponding users have experience obstacles for the analysis object based on the status of multiple analysis objects at multiple operation nodes. That is to say, if users encounter experience obstacles and do not actively give feedback, however, it may be reflected from the data status at specific operation nodes. For example, an order remains in the pending shipment state for a long time, and so on. Therefore, it is also possible to discover the possible user experience obstacles encountered by users and the corresponding analysis objects (such as orders) by judging the data status at such operation nodes.

[0097] Furthermore, in some other cases, users encounter experience obstacles and do not give active feedback, and from the data status at the operation nodes, no user experience obstacle problems are found. However, it may be reflected from the behavior of users. That is, it is also possible to judge whether the corresponding users have experience obstacles for the analysis object based on the user behavior generated by users for the analysis object. For example, if a user repeatedly views an order within a short period of time, it may be because the user has experience obstacles for this order, resulting in an increase in the user's effort level, longer time consumption, and so on.

[0098] In short, through various ways, it is possible to discover as comprehensively as possible the user experience obstacle problems generated within the same target statistical period and the corresponding analysis objects. In this way, multiple analysis objects with user experience obstacle problems can be obtained. Based on this, the negative impact value of the target information system on the user experience can be determined.

[0099] S202: Determine the positive impact value of the target information system on the user experience according to the first analysis object.

[0100] After obtaining the specific first analysis object and the second analysis object, the positive influence value and the negative influence value of the target information system on the user experience can be calculated respectively according to the obtained analysis objects. Specifically, for the positive influence value, it can be directly determined according to information such as the number of the first analysis objects. In the real-time calculation mode, as the first analysis objects are continuously generated within the same statistical period, the specific positive influence value can also change accordingly.

[0101] S203: Determine the negative influence value of the target information system on the user experience according to the user experience obstacle problem categories respectively corresponding to the multiple second analysis objects; the user experience obstacle problem categories are determined after clustering according to the corresponding solution and problem handling party.

[0102] For the negative influence value, first, the multiple second analysis objects can be classified into the corresponding problem categories according to the problem categories to which the user experience obstacle problems belong. Among them, the problem categories can be determined in advance or dynamically determined through an independent module. That is, before determining the user experience influence index of the specific target information system, multiple main problem categories can be determined in advance. In this way, for the second analysis objects generated during the target statistical period, they can first be classified into specific problem categories respectively. For example, in the real-time calculation mode, the second analysis objects can also be gradually discovered as the user's active feedback, or the judgment of the data status on specific link nodes, the judgment of user behavior, etc. are carried out. Each second analysis object with a user experience obstacle problem can be classified into one of the problem categories. In this way, as the second analysis objects are generated, the second analysis objects under each problem category gradually increase, and the negative influence value of the target information system on the user experience will also change.

[0103] In specific implementation, regarding the negative influence value, the negative influence components corresponding to multiple different problem categories can be calculated, and then the overall negative influence value can be obtained after addition processing. For example, in specific implementation, the negative influence components corresponding to multiple different problem categories can be determined according to the number of the second analysis objects under each problem category. That is, according to the difference in the number of the second analysis objects under each problem category, it can be determined that the negative influence of each problem category on the user experience in the current target information system is different, and this difference can be reflected by their respective corresponding negative influence components.

[0104] Among them, there are various ways to classify problem categories. For example, specifically, a large amount of user voice data related to user experience obstacles can be collected (specifically, it can be obtained from various channels such as service records in the customer service system related to the target information system. The so-called voice data is the description of the problems encountered by users). Then, based on the application of big data intelligent AI technology, through methods such as algorithm recognition, the user voice data is clustered into multiple problems. After that, the specific problems are further clustered to obtain multiple main problem categories.

[0105] In the process of clustering problems into main problems, in the traditional way, there are various ways. For example, clustering by department into commodity problems, logistics problems, etc.; or clustering according to the links included in the data processing link into order placement problems, logistics problems, and so on. However, this clustering method has a relatively coarse clustering granularity and is not conducive to the actual improvement of problems. In addition, in this clustering method, it is difficult to determine the weights of each problem category. For example, it is difficult to determine whether the impact of commodity problems on user experience is more serious or the impact of logistics problems on user experience is more serious.

[0106] Therefore, in the embodiments of this application, a solution for clustering user experience obstacle problems based on solutions and corresponding problem handlers is adopted. That is to say, user experience obstacle problems corresponding to the same solution can be clustered into the same problem category. For example, if two user experience obstacle problems can be solved by performing the same operation action, they can be clustered into the same problem category. In other words, the embodiments of this application adopt a "beginning with the end in mind" clustering method. When clustering, the solution corresponding to the problem category after clustering is considered, and this solution can correspond to the problem handler (specifically, it can be the person responsible, that is, the front-line executor, rather than the manager). In this way, in the process of calculating the specific user experience situation, the negative impact value components corresponding to multiple problem categories can be determined. If the overall user experience impact index is relatively low, then according to the negative impact value components corresponding to each problem category, it can be determined which type of problems need to be improved and what specific solutions can be used to solve them. Even the information such as the specific negative impact value can be provided to the corresponding problem handler so that they know what operation actions to perform to improve the overall user experience.

[0107] It should be noted here that for different target information systems, due to different specific user experience obstacle problems, the specific problem category clustering results can also be different. However, they can all be clustered according to specific solutions and corresponding problem handlers. For example, in an e-commerce information system, specific problem categories may include: experience obstacles caused by unclear expression, unobtained customer benefits, increased consumer effort due to imperfect product processes, time impact on users due to performance negligence, obstacles in payment / order placement, impact on the normal use of goods due to product quality problems, and so on. Each problem category may include multiple different user experience obstacle problems, but all can be solved with the same solution. For example, for the problem of "experience obstacles caused by unclear expression", it can be solved by the person responsible for the front-end page content design by modifying the product description copywriting, etc. For the problem of "obstacles in payment / order placement", it can be solved by the person responsible for the link design by optimizing the data link, and so on. Another example is that in a logistics information service system, the specifically clustered problem categories may include delivery timeliness problems, distribution timeliness problems, end interaction problems, packaging problems, cargo integrity problems, service quality problems, and so on. Each specific problem category is clustered from the perspective of the solution.

[0108] In addition, since there are various specific user experience obstacle problems, the degrees to which different types of problems affect the user experience may be different. For example, in a commodity object information system, the problem of unable to use coupons and the problem of unable to place an order normally may have different degrees of severity in affecting the user experience, and so on. Therefore, in the specific implementation, weights can also be assigned to specific problem categories, and through this weight, the severity of the specific problem category in affecting the user experience can be reflected. In this way, according to the number of the second analysis objects under each problem category and the weight of the problem category, the negative impact value of the target information system on the user experience can be determined. For example, multiplying the number of specific second analysis objects under each problem category by the weight can obtain the negative impact value component corresponding to this problem category. After that, adding the negative impact value components corresponding to multiple problem categories can obtain the overall negative impact value, and so on. Through this method, the actual impact degree of various user experience obstacles specifically generated in the current statistical period on the user experience can be more accurately reflected.

[0109] Among them, when specifically calculating the weights, there can be multiple methods. For example, one method is to determine the severity of the impact of specific problem categories on the user experience from the perspective of user perception through methods such as questionnaires. For example, multiple users can be asked whether encountering a certain problem category will affect their repurchase, and so on. By synthesizing the results of multiple user questionnaires, the severity of the impact of each problem category on the user experience can be statistically obtained.

[0110] However, the inventors of the present application also found during the implementation of the present application that in actual applications, the user's perception may be inconsistent with their actual behavior. For example, when conducting a questionnaire survey on a certain user, they believe that a certain problem category has a very serious impact on their user experience. However, when actually encountering this type of problem, after the problem is solved, the user still makes a repurchase; or, when conducting a questionnaire survey on a certain user, they believe that a certain problem category has an insignificant impact on their user experience. However, when actually encountering this type of problem, even after the problem is solved, the user does not make a repurchase, and so on.

[0111] Therefore, in the preferred embodiment of the present application, the severity information of the impact of each problem category on the user experience can be obtained separately in the user perception dimension and the user behavior dimension, and by fusing the results obtained in the two dimensions, the weight corresponding to each problem category can be determined. That is to say, by combining the information of user perception and user behavior, each problem category is calculated.

[0112] Among them, in the user perception dimension, it can be determined through various methods. For example, it can include factor analysis, principal component analysis, entropy method, and so on. In addition, it can also be determined and quantified through methods such as questionnaires, or questionnaires can be sent to experts to ask them how serious the impact is when they encounter user experience obstacle problems of certain categories. In this way, through a large number of questionnaire results, specific problem categories can generate corresponding values. After that, different problem categories can also be sorted, normalized, etc. according to the specific values, so as to obtain the weight components of each problem category in the user perception dimension.

[0113] In the dimension of user behavior, it can be carried out through big data analysis. Specifically, first, based on the data attributes in a specific information system, the behavior indicators to be specifically evaluated can be selected. For example, in an e-commerce information system, the repurchase rate of users can be used as a behavior indicator. That is to say, for users in the e-commerce information system, assuming that they have encountered a certain user experience obstacle problem before, when judging the severity of the impact of this problem on the user experience, it can be reflected by whether the users make repeat purchases later, and so on. After selecting the behavior indicators, the historical behavior records of multiple users in the information system can be used to determine the weights of specific problem categories in the dimension of user behavior. For example, after obtaining a large number of historical behavior records, multiple users who have encountered user experience obstacle problems and those who have not can be identified. For the former, they can also be divided into multiple groups according to the problem categories of the user experience obstacle problems they have encountered. For example, assuming there are a total of 20 problem categories, the users who have encountered user experience obstacle problems can be divided into 20 groups, corresponding to each problem category respectively. In addition, the users who have not encountered user experience obstacle problems can form a separate group. In this way, based on each user group respectively, it can be judged whether specific users have behaviors such as "repeat purchase". By comparing the repurchase rates between different user groups, the weight components of each user category in the dimension of user behavior can be determined. For example, for the first user group, the corresponding problem category is "poor product quality". Through statistics, the repurchase rate of users who have encountered this problem is 30%; for the second user group, the corresponding problem category is "coupons cannot be used", and the repurchase rate of users who have encountered this problem is 40%; for the user group that has not encountered user experience obstacle problems, the repurchase rate is 50%, and so on. Through the above data, it can be determined that the problem category of "poor product quality" has a more serious impact on the user experience, and so on.

[0114] In addition, in the specific implementation, when specifically calculating the weights, the commonalities and differences of different users in the perception dimension and / or behavior dimension can also be considered to determine the severity information of the impact of each problem category on the user experience in the user perception dimension and in the user behavior dimension respectively. For example, for the same problem category, it may have a relatively small impact on young people and a relatively large impact on older people, and so on. Therefore, when calculating the weights, the differences or commonalities between different groups of people can be fully considered. For example, each user group can cover multiple user groups, and the dimensions for dividing user groups can also be diverse, so as to obtain more statistically significant weights.

[0115] After determining the weight components of specific problem categories in the user perception dimension and the user behavior dimension respectively, the weight components of the two parts can be fused to determine the weight corresponding to the specific problem category. For example, the weight components of the two parts can be averaged, and the average value can be used as the final weight, and so on.

[0116] It should be noted here that the specific weight measurement can be pre-completed. That is, in the specific implementation, before measuring the user experience impact index of a specific target information system, multiple main problem categories can be clustered first according to the historical user experience obstacle problems in the target user information system, etc. (clustered according to the solution and the corresponding responsible person). In addition, the historical behavior records of multiple users in the target information system can also be used to determine the weights of each problem category respectively based on the two dimensions of user perception and user behavior. Then, according to the multiple main problem categories obtained specifically and their respective corresponding weights, the negative impact value generated by the specific target information system on the user experience is calculated. This calculation process, as described above, can be carried out in real time or in the T+1 manner, and so on.

[0117] Or, in another way, the specific problem categories and weights can also be generated in real time and dynamically changed. For example, specifically, there can be a system or module specifically for clustering problem categories and measuring weights. This system or module can automatically cluster problem categories and measure weights according to the historical user experience obstacle problems and the user experience obstacle problems generated in real time in the system. For example, with the emergence of specific new user experience obstacle problems, new problem categories may be clustered, and the weights corresponding to the new problem categories are determined based on the two levels of user perception and user behavior, and so on. In this way, the dynamic generation and dynamic weighting of specific problem categories are realized, and the accuracy of the user experience impact index is further improved.

[0118] S204: According to the positive impact value and the negative impact value, determine whether it is necessary to improve the user experience of the target information system. If so, provide the corresponding solution to the problem handling party.

[0119] After determining the positive impact value and the negative impact value, it can be judged whether it is necessary to improve the user experience of the target information system accordingly. For example, in one way, the user experience impact index obtained by the target information system can be determined according to the positive impact value and the negative impact value. Then, it can be judged whether it is necessary to improve the user experience of the target information system by comparing the user experience impact index with the target threshold. For example, if the user experience impact index is lower than a certain threshold, it is determined that the user experience needs to be improved, and so on.

[0120] Among them, there can be various ways to specifically determine the user experience impact index based on the positive impact value and the negative impact value. For example, in one way, as Figure 3 shown, the positive impact value can be subtracted from the negative impact value, and the resulting result can be determined as the user experience impact index, and so on. For example:

[0121]

[0122] Among them, are respectively functions for calculating the positive impact value and the negative impact value, is the positive impact factor, is the negative impact factor. For the latter, it mainly includes the user's active feedback situation described above, the user experience obstacle problems found according to the data status on the relevant data link nodes, the user experience obstacle problems reflected by the user's behavior, and so on.

[0123] Among them, in the real-time calculation method, since both the first analysis object and the second analysis object can be generated in real time, and for each newly generated analysis object, the positive impact value and / or the negative impact value can be re-determined, and then the user experience impact index can be updated. That is to say, in practical applications, the specific user experience impact index may be a continuously changing value, and the high or low of the value can reflect the quality of the user experience.

[0124] After determining the user experience impact index through the above method, it reflects the user experience situation of the entire target information system. In practical applications, the user experience impact index can also be disassembled from the target dimension to obtain user experience impact index components corresponding to multiple sub-items. And, since the embodiments of the present application use orders, one-time behavior records, etc. as the unit as the analysis object, it is also possible to achieve holographic disassembly in any dimension.

[0125] For example, specific target dimensions may include: the application module dimension in the target information system. At this time, the multiple user experience impact index components specifically broken down can be used to express the user experience impact indexes corresponding to multiple different application modules. That is to say, when determining the overall user experience impact index before, the analysis objects obtained may be respectively related to different application modules. For example, in the current statistical period, a first analysis object set and multiple second analysis object sets are respectively obtained, corresponding to different problem categories; when specifically disassembling by application module, each analysis object set can be split according to the application module, and then, according to the analysis object sets corresponding to the same application module, the user experience impact index component of this application module can be determined. For example, assuming there are 20 problem categories in total, the overall analysis object set can be 21 (one is a set composed of the first analysis objects without user experience obstacles); there are 5 main application modules in the target information system, then the above 21 analysis object sets can be split into 5 subsets respectively, and each application module can correspond to 21 analysis object subsets. After that, the positive impact value and the negative impact value can be calculated by using information such as the number of analysis objects and weights in these 21 subsets, and then the user experience impact index component corresponding to this application module can be determined. Information such as the user experience impact index components corresponding to each application module can be provided to users such as the supervisors of the application modules, so that they can determine what kind of user experience the application modules they are responsible for can provide to users.

[0126] Or, the target dimension includes: the link dimension included in the processing link of the analysis object. At this time, the multiple user experience impact index components specifically broken down can be used to express the user experience impact indexes corresponding to multiple different links. For example, in a certain target information system, the links in the specific data link include: placing an order, shipping, delivery, after-sales, and other different links. Similarly, the user experience impact indexes corresponding to each link can be disassembled.

[0127] In addition, the target dimension can also include: the problem-solving party dimension of the analysis object. The user experience impact index component is used to express the user experience impact indexes of multiple different problem-solving parties, so as to be used for performance appraisal of the problem-solving parties. For example, in an e-commerce information system, a specific order may be responsible by a certain or several responsible persons, including the responsible person for configuring coupon information, the responsible person for ensuring the quality of commodity objects, and so on. Therefore, when specifically disassembling by the responsible person dimension, the multiple analysis object sets obtained in the current statistical period can be disassembled into multiple subsets corresponding to each responsible person respectively. Similarly, the user experience impact index component corresponding to this responsible person can be calculated according to the multiple analysis object sets corresponding to the same responsible person.

[0128] It should be noted that, in the way of disassembling in this problem-solving dimension, the component of the user experience impact index corresponding to the specific responsible person can also be used for the performance appraisal of the responsible person. That is to say, in the embodiments of the present application, in addition to being able to measure the user experience impact index of the specific target information system, the user experience impact index can also be disassembled according to the dimension of the responsible person, and the component of the user experience impact index corresponding to the specific responsible person can also be provided to the specific responsible person. In this way, the responsible person can see the feedback of their personal work in the hearts of users. In other words, whether the work of the specific responsible person is done well depends not only on information such as sales volume, but can be judged according to the user experience that their work can bring to users. For example, in the traditional way, in the e-commerce information system, the responsible person may be appraised based on indicators such as sales volume or transaction amount. However, in this traditional appraisal mechanism, there may be situations where the long-term user experience is damaged in order to pursue high short-term sales volume or transaction amount. Therefore, using the method provided in the embodiments of the present application to conduct performance appraisal on the responsible person can be more conducive to ensuring the user experience of the system and the long-term healthy development of the business entity.

[0129] In addition, specifically in the commodity object information system, the specific target dimension may further include: the commodity object category dimension or the commodity object dimension, and the user experience impact index component is used to express the user experience impact index corresponding to multiple different commodity object categories or different commodity objects. That is to say, multiple user experience impact index components can be disassembled according to the commodity object category, so that each commodity object category can correspond to its own user experience impact index, which is used to represent the quality of the experience brought by the specific category to users. It is even possible to disassemble according to the commodity object dimension, so that each commodity object can have its own user experience impact index, and so on.

[0130] In summary, in the embodiments of the present application, the dimensions to be disassembled can be configured according to the actual application requirements of specific users, etc., so that user experience impact indexes of multiple specific sub-items can be obtained. In addition, during the disassembly process, it is also possible to drill down step by step from the largest to the smallest granularity. In this way, the target objects with specific user experience obstacle problems (such as commodity objects, or commodity categories, deliverymen, etc.) can be located, so that the responsible person can preferentially perform the operation actions on the target objects. In addition, through this method, the user experience can also be traced, making the execution of operation actions more well-founded. For example, for a logistics information system, it can first be disassembled into the user experience impact index component corresponding to the "delivery" module and the user experience impact index component corresponding to the "warehouse" module according to the application module dimension. Among them, for the "delivery" module, it is also possible to drill down in turn to the granularities of large regions, provinces, cities, locations, deliverymen, etc., so as to know the user experience brought to users by the "delivery" module in each large region, the user experience brought to users by the "delivery" module in each province, etc. In this way, if the user experience impact index corresponding to the "delivery" module is relatively low, the specific problems in which large region, which province, city, location, or even deliveryman can be gradually determined, etc.

[0131] After determining the specific user experience impact index, it can be determined whether there are problems with poor user experience in the current information system (or a specific application module, link, etc.) based on this user experience impact index. For example, if a certain user experience impact index is lower than a certain threshold, it proves that the user experience in this system is poor and some operation actions need to be executed to improve the user experience. Among them, the operation actions can specifically be actions for solving specific user experience obstacle problems. For example, if a problem category is "coupons cannot be used" and the corresponding solution is "reconfigure the coupon usage rules", then the corresponding operation action can be the action of reconfiguring the coupon usage rules, etc.

[0132] In the embodiments of the present application, since the user experience obstacle problems are pre-classified according to the solutions and problem solvers, when it is determined that the information system needs to improve the user experience, the corresponding solutions can be directly provided to the specific problem handlers. In this way, the problem handlers can directly execute the corresponding operation actions according to the specific solutions, and the user experience can be improved.

[0133] In addition, since the specific user experience impact index is obtained by calculating the positive impact value and the negative impact value, and the negative impact value can be determined according to the negative impact value components corresponding to multiple problem categories, therefore, while determining the specific user experience impact index, the negative impact value components corresponding to each problem category can also be obtained. If it is necessary to improve the user experience, the target problem categories that need to be focused on can also be determined according to information such as the negative impact value components corresponding to each problem category. For example, if the negative impact value component corresponding to a certain problem category is relatively high, it can be determined as the problem that needs to be solved first. Furthermore, since the problem categories in the embodiments of the present application are generated by clustering based on the solution and the problem solver, therefore, they can have a corresponding relationship with the specific solution and the problem solver. In this way, when it is found that a certain user experience obstacle problem needs to be solved first, the corresponding solution can be provided to the problem solver corresponding to this key problem, and the operation actions corresponding to the specific solution can be executed by the problem solution to improve the user experience.

[0134] For example, in a certain logistics information service system, the user experience impact index of the overall system calculated at a certain moment is α. Among them, the specific problem categories include delivery timeliness problems, distribution timeliness problems, end - interaction problems, packaging problems, cargo integrity problems, service quality problems, and so on. Specifically, when displaying the user experience indicators of the information service system, the values of the negative impact components corresponding to each problem category can also be displayed, so that personnel such as system managers can know the severity of the impact of each problem category on the user experience. For example, assuming that the negative impact value component of the "cargo integrity" problem is relatively high, it proves that its impact on the user experience is the most serious. Therefore, it can be regarded as the problem that needs to be improved first.

[0135] To facilitate the execution of specific operation actions, the corresponding relationships between specific problem categories, solutions, and problem solvers can also be pre-saved. Additionally, it can be integrated with message systems, work order systems, etc. In this way, when a certain type of problem needs to be solved, it can be notified to the specific responsible person. Or, a work order can be directly generated based on the specific solution and pushed to the specific problem solver for execution. For example, if the solution corresponding to a certain problem category is to modify the description copy of the product object name, a corresponding work order can be generated and sent to the person responsible for the product object title copy for modification to complete the operation action, and so on. Of course, other problem categories can also be handled in a similar manner by the corresponding responsible persons to execute the corresponding operation actions, and so on. Additionally, after the specific operation action is executed, since the negative impact value components of various problems can be calculated in real-time or near real-time, the tracking of the negative impact value of specific problem categories or the tracking of the user experience impact index can be realized, achieving a closed-loop solution to user experience obstacle problems. For example, according to the change situation of the user experience impact index after the specific operation action is executed, a curve of the change of the user experience impact index can be drawn, and it can also be compared with the curve corresponding to the target value, enabling managers and other personnel to know the improvement effect of the specific user experience, and so on.

[0136] Among them, since the specific user experience impact index can be disassembled according to multiple dimensions, it is also possible to judge whether it is necessary to improve the user experience of a certain link, module, product object category, product object, etc. based on the disassembled user experience impact index components, and so on. In this way, the specific problem solver can be more targeted when executing operation actions. For example, if the user experience of a certain product object is relatively poor, the user experience obstacle problems of the product object in one or several categories can be improved, and so on. Additionally, through the aforementioned method of tracking the improvement effect, it can be judged whether the user experience of the product object has been effectively improved. If it has not been effectively improved, the product object can also be taken off the shelf, and so on.

[0137] Furthermore, in specific implementation, an early warning mechanism can also be provided. For example, for an e-commerce information system, if the negative impact value of a certain product object or category in a certain category is relatively high, or the user experience obstacle problems in a certain problem category are relatively concentrated (for example, the same product object is complained about for more than 3 times regarding shipping errors within 24 hours, etc.), then an early warning can be issued for the product object or category to remind the management personnel to pay attention to the product object or category. Additionally, the specific problem category, details, etc. can also be prompted, and so on.

[0138] Alternatively, warnings can also be issued in terms of event dimensions. For example, if it is found at a certain moment that there is a public opinion risk in a certain information system, a warning can be issued. Moreover, if there is a relatively large fluctuation in the user experience impact index of an information system, a warning can also be issued to remind responsible persons such as managers to pay attention to the specific changes in the user experience impact index, and so on.

[0139] In summary, the analysis objects generated in the target information system can be used as the data source. By statistically analyzing multiple first analysis objects representing no user experience obstacle problems and multiple second analysis objects corresponding to user experience obstacle problems, the positive impact value and negative impact value of the target information system on the user experience can be determined. Then, based on the positive impact value and negative impact value, it can be judged whether the user experience of the target information system needs to be improved. Among them, when determining the negative impact value, the multiple second analysis objects can be first classified into the corresponding problem categories according to the problem categories to which the user experience obstacle problems belong. Then, based on information such as the number of second analysis objects in various problem categories, the negative impact value of the target information system on the user experience can be determined. And in the embodiments of the present application, the specific problem categories are determined after clustering according to the solution and the corresponding problem handler (for example, the responsible person). In this way, the specific problem categories are corresponding to the solution and the problem solver. Therefore, when it is determined that the target information system needs to improve the user experience, the problem handlers and solutions that need to perform operation actions in each problem category can be clarified, and the problem handler can perform operation actions according to the corresponding solution, so that the user experience can be improved. That is to say, in the embodiments of the present application, the specifically measured user experience result is operable. In this way, not only can the quality of the user experience in the target information system be measured, but also when the user experience needs to be improved, it can be known which problem handler or handlers need to perform what operation actions in order to make a quick and accurate response, so as to achieve timely loss prevention.

[0140] Second, in the embodiments of the present application, the analysis objects generated in the target information system (such as orders, user behavior records, etc.) are used as data sources, so that the obtained user experience impact index can be more objective. When obtaining the analysis objects, especially the second analysis objects with user experience obstacle problems, various links, various modules, etc. can be covered as much as possible. Therefore, the data can be made more comprehensive, rather than using sampling surveys for one-sided judgments. In addition, the specific data sources obtained can also be obtained in real time. In this way, as the analysis objects are generated, the user experience impact index can be updated in real time. Therefore, the user experience impact index can also have the characteristic of real-time, and can reflect more real-time problems such as poor user experience in the system, rather than gradually being reflected in a long statistical cycle. Furthermore, since the embodiments of the present application can use the data generated in real time to measure the user experience situation, the generation of each analysis object will cause a change in the positive impact value or negative impact value, and then change the user experience impact index. Therefore, the user experience impact index also has the characteristic of sensitivity. And after the responsible person executes the operation action, the execution effect of the operation action can be determined in time through the updated user experience impact index.

[0141] Third, in order to determine the negative impact value, multiple problem categories can be clustered, and weight calculations can be performed for each problem category. When performing weight calculations, the embodiments of the present application adopt a calculation method that combines the user perception level and the user behavior level, so as to obtain more accurate weight calculation results. And in practical applications, the specific problem clustering and weight calculation processes can also be performed in real time, that is, as more new data (such as new repurchase behavior data, etc.) are generated in the system, more problem categories can be clustered, or the weights of the problem categories can be updated, etc., so as to achieve adaptive dynamic weighting.

[0142] Fourth, since the analysis objects used in the embodiments of the present application can be small-granularity data units such as orders and user behavior records, the holographic decomposition of the user experience impact index can also be realized, that is, the user experience impact index can be decomposed into experience index components on multiple sub-items in any dimension to reflect the quality of the user experience on multiple shares, etc. For example, it can be specifically decomposed in dimensions such as application modules, each link on the data link, and responsible persons. In the commodity object information system, it can also be decomposed in dimensions such as commodity object categories and commodity objects, so as to determine the user experience situation obtained by each specific category or specific commodity object, etc. Under the same sub-item, further down-drilling of multiple granularities can be performed to locate the target object with specific user experience obstacle problems, and then the responsible person preferentially executes the operation action on the target object.

[0143] Furthermore, it is also possible to track the user experience impact index, which can intuitively reflect the improvement of the operation actions on the user experience. If the user experience impact index fluctuates, or certain objects frequently encounter certain problems in certain problem categories, etc., warnings can also be issued so that the corresponding managers or responsible persons can intervene in a timely manner, etc.

[0144] It should be noted that the embodiments of the present application may involve the use of user data. In actual applications, user-specific personal data can be used in the solutions described herein within the scope permitted by applicable laws and regulations (for example, with the user's explicit consent and actual notification to the user, etc.) and in compliance with the applicable laws and regulations of the country where it is located.

[0145] Corresponding to the foregoing method embodiments, the embodiments of the present application also provide a user experience data processing device. Refer to Figure 4 and this device may include:

[0146] An analysis object acquisition unit 401, configured to acquire analysis objects generated in a target information system, where the analysis objects include multiple first analysis objects representing problems without user experience obstacles and multiple second analysis objects representing problems with user experience obstacles;

[0147] A positive impact value determination unit 402, configured to determine a positive impact value of the target information system on the user experience according to the multiple first analysis objects;

[0148] A negative impact value determination unit 403, configured to determine a negative impact value of the target information system on the user experience according to the user experience obstacle problem categories corresponding to the multiple second analysis objects; the user experience obstacle problem categories are determined after clustering according to the corresponding solution and problem handling party;

[0149] A solution providing unit 404, configured to determine whether it is necessary to improve the user experience of the target information system according to the positive impact value and the negative impact value, and if so, provide a corresponding solution to the problem handling party.

[0150] Specifically, the analysis object acquisition unit may specifically be configured to: acquire quasi-real-time analysis objects generated in the target information system during a target historical time period.

[0151] Alternatively, the analysis object acquisition unit may specifically be configured to:

[0152] acquire real-time analysis objects generated in the target information system during a target statistical cycle;

[0153] The device may also include:

[0154] A real-time update unit, configured to re-determine the positive influence value and / or negative influence value when new analysis objects are generated within the target statistical period.

[0155] Wherein, the target information system includes a commodity object information system, and the analysis objects include order data;

[0156] At this time, the analysis object acquisition unit may specifically be configured to: determine new orders generated in the target information system within the target statistical period, and / or historical orders with positive user reviews, and / or historical orders with on-time performance fulfillment as the first analysis objects representing no user experience obstacle problems.

[0157] When acquiring the second analysis object, the analysis object acquisition unit may specifically be configured to:

[0158] Acquire second analysis objects corresponding to various user experience obstacle problems generated at multiple links of the data link of the target information system.

[0159] In addition, the analysis object acquisition unit may specifically be configured to:

[0160] Determine multiple second analysis objects corresponding to various user experience obstacle problems according to the negative feedback situation of users generated within the target statistical period, the status of operation nodes, and / or the behaviors of users towards the analysis objects.

[0161] Specifically, each category of user experience obstacle problems has a weight; the weight represents the severity of the impact of the category of user experience obstacle problems on user experience;

[0162] The negative influence value determination unit may specifically be configured to:

[0163] Determine the negative influence value component corresponding to each category of user experience obstacle problems respectively according to the number of second analysis objects under various categories of user experience obstacle problems and the weight of the category of user experience obstacle problems, and determine the negative influence value generated by the target information system on user experience according to each negative influence value component.

[0164] In addition, the device may further include:

[0165] A weight determination unit, configured to respectively obtain the severity information of the impact of the category of user experience obstacle problems on user experience in the user perception dimension and the user behavior dimension, and determine the weight corresponding to the category of user experience obstacle problems according to the severity information in the two dimensions.

[0166] Wherein, the weight determination unit may specifically be configured to:

[0167] Based on the common information and differential information existing in multiple different user groups in the perception dimension and / or behavior dimension, determine the severity information of the impact of the user experience obstacle problem category on the user experience in the user perception dimension and in the user behavior dimension respectively.

[0168] Among them, the weight corresponding to the user experience obstacle problem category is determined in advance, or is dynamically updated during the process of quantifying the impact of the target information system on the user experience.

[0169] Specifically, the solution providing unit can specifically be used for:

[0170] Determine the user experience impact index obtained by the target information system according to the positive impact value and the negative impact value;

[0171] By comparing the user experience impact index with the target threshold, determine whether it is necessary to improve the user experience of the target information system.

[0172] In addition, the device may further include:

[0173] A first index decomposition unit, configured to decompose the user experience impact index from the target dimension to obtain the user experience impact indexes corresponding to multiple sub-items, so as to determine whether it is necessary to improve the user experience according to the user experience impact indexes corresponding to the sub-items, and the problem handling party executes the operation actions corresponding to the solution for the sub-items.

[0174] Among them, the target dimension includes: the application module dimension in the target information system, and the user experience impact index component is used to represent the user experience impact indexes corresponding to multiple different application modules.

[0175] Or, the target dimension includes: the link dimension included in the processing link of the analysis object, and the user experience impact index component is used to represent the user experience impact indexes corresponding to multiple different links.

[0176] Or, the target dimension includes: the problem handling party dimension of the analysis object, and the user experience impact index component is used to express the user experience impact indexes of multiple different problem handling parties, so as to perform performance appraisal on the problem handling party.

[0177] Among them, the target information system includes a commodity object information service system;

[0178] The target dimension includes: the commodity object category dimension or the commodity object dimension, and the user experience impact index component is used to represent the user experience impact indexes corresponding to multiple different commodity object categories or different commodity objects.

[0179] Furthermore, the device may further include:

[0180] A second index decomposition unit, configured to decompose the user experience impact index at multiple different granularities under the same sub-item, so as to locate a target object with specific user experience obstacle problems, so that the responsible person preferentially executes the operation action on the target object.

[0181] Furthermore, the device may further include:

[0182] An early warning unit, configured to provide early warning information about the target object if the target object has user experience obstacle problems in a certain problem category multiple times.

[0183] Specifically, the solution providing unit may specifically be configured to:

[0184] Provide the solution and the information of the corresponding problem handler to the associated work order system, so that the work order system generates a task work order according to the solution and the information of the problem handler, and the problem handler executes the operation action corresponding to the solution according to the task work order.

[0185] Wherein, the analysis object is determined according to the final goal to be achieved in the target information system.

[0186] Specifically, the target information system includes a commodity object information service system, and the analysis object includes a transaction order; or,

[0187] The target information system includes a logistics service system, and the analysis object includes a logistics order; or,

[0188] The target information system includes a mobile payment system, and the analysis object includes a record of income and expenditure operation behaviors; or,

[0189] The target information system includes a customer service system, and the analysis object includes a customer service session record.

[0190] In addition, an embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the method described in any one of the foregoing method embodiments are implemented.

[0191] And an electronic device, including:

[0192] One or more processors; and

[0193] A memory associated with the one or more processors, the memory being configured to store program instructions that, when read and executed by the one or more processors, perform the steps of the method described in any one of the foregoing method embodiments.

[0194] Wherein, Figure 5 An exemplary architecture of an electronic device is shown, which may specifically include a processor 510, a video display adapter 511, a disk drive 512, an input / output interface 513, a network interface 514, and a memory 520. The above-mentioned processor 510, video display adapter 511, disk drive 512, input / output interface 513, network interface 514, and the memory 520 can be communicatively connected through a communication bus 530.

[0195] Wherein, the processor 510 can be implemented in the form of a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, etc., and is used to execute relevant programs to implement the technical solution provided by the present application.

[0196] The memory 520 can be implemented in the form of a ROM (Read Only Memory), a RAM (Random Access Memory), a static storage device, a dynamic storage device, etc. The memory 520 can store an operating system 521 for controlling the operation of the electronic device 500, and a basic input / output system (BIOS) for controlling the low-level operations of the electronic device 500. In addition, a web browser 523, a data storage management system 524, a user experience data processing system 525, etc. can also be stored. The above-mentioned user experience data processing system 525 can be the application program that specifically implements the operations of the foregoing steps in the embodiments of the present application. In short, when implementing the technical solution provided by the present application through software or firmware, the relevant program code is stored in the memory 520 and is called and executed by the processor 510.

[0197] The input / output interface 513 is used to connect to an input / output module to implement information input and output. The input / output module can be configured as a component in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. The input device can include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device can include a display, a speaker, a vibrator, an indicator light, etc.

[0198] The network interface 514 is used to connect to a communication module (not shown in the figure) to enable communication and interaction between this device and other devices. The communication module can achieve communication through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0199] The bus 530 includes a path for transmitting information between various components of the device (such as the processor 510, video display adapter 511, disk drive 512, input / output interface 513, network interface 514, and memory 520).

[0200] It should be noted that although the above device only shows the processor 510, video display adapter 511, disk drive 512, input / output interface 513, network interface 514, memory 520, bus 530, etc., in the specific implementation process, the device may also include other components necessary for normal operation. In addition, those skilled in the art can understand that the above device may also only include the components necessary to implement the solution of this application, and does not necessarily include all the components shown in the figure.

[0201] From the description of the above embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus a necessary general hardware platform. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0202] Each embodiment in this specification is described in a progressive manner. For the same or similar parts between the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiments, since they are basically similar to the method embodiments, the description is relatively simple. For the relevant parts, reference can be made to the partial description of the method embodiments. The systems and system embodiments described above are only illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative work.

[0203] The above has introduced in detail the user experience data processing method and electronic device provided by the present application. Specific examples are used in this article to elaborate on the principle and implementation manner of the present application. The description of the above embodiments is only used to help understand the method and its core idea of the present application; at the same time, for those of ordinary skill in the art, according to the idea of the present application, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation to the present application.

Claims

1. A method for processing user experience data, characterized in that, Including: Based on the data related to the goals to be achieved in the target information system, obtain the analysis objects generated in real time in the target information system, so as to determine and update the impact value used to measure the impact of the target information system on the user experience according to the analysis objects; the analysis objects include multiple first analysis objects representing no user experience obstacle problems and multiple second analysis objects representing user experience obstacle problems; wherein, the second analysis objects are obtained from multiple channels to cover multiple links in the data link or multiple application modules in the target information system; Determine the positive impact value of the target information system on the user experience according to the multiple first analysis objects; According to the user experience obstacle problem categories corresponding to the multiple second analysis objects respectively, determine the negative impact value components corresponding to the multiple problem categories, and determine the negative impact value of the target information system on the user experience according to the multiple negative impact value components; the user experience obstacle problem categories are determined after clustering according to the corresponding solutions and operation action responsible persons, so as to cluster the user experience obstacle problems corresponding to the same solution and operation action responsible person into the same problem category; Determine the user experience impact index obtained by the target information system according to the positive impact value and the negative impact value, disassemble the user experience impact index from the target dimension to obtain the user experience impact indexes corresponding to multiple sub-items, and disassemble the user experience impact index at multiple different granularities under the same sub-item, so as to determine whether it is necessary to improve the user experience of the target information system. If so, determine the problem category that needs to be improved according to the negative impact value component, locate the target object with specific user experience obstacle problems, and provide the corresponding solution to the operation action responsible person corresponding to the problem category.

2. The method according to claim 1, wherein: The obtaining of the analysis objects generated in the target information system includes: Obtain the analysis objects generated in real time in the target information system within the target statistical period; The method further includes: When new analysis objects are generated within the target statistical period, re-determine the positive impact value and / or the negative impact value.

3. The method according to claim 1, wherein: The obtaining of the analysis objects generated in real time in the target information system includes: Obtain the second analysis objects corresponding to multiple user experience obstacle problems generated in real time by the target information system at multiple links in the data link.

4. The method according to claim 1, wherein: The obtaining of the analysis objects generated in the target information system includes: Determine multiple second analysis objects corresponding to multiple user experience obstacle problems according to the user negative feedback situation generated within the target statistical period, the status of the operation node, and / or the behavior of the user towards the analysis object.

5. The method according to claim 1, wherein: The user experience obstacle problem categories correspond to weights; the weights represent the severity of the impact of the user experience obstacle problem categories on the user experience; Determining the negative impact value of the target information system on user experience includes: Determining the negative impact value component corresponding to each user experience obstacle problem category respectively according to the number of the second analysis objects under various user experience obstacle problem categories and the weight of the user experience obstacle problem category, and determining the negative impact value of the target information system on user experience according to each negative impact value component.

6. The method according to claim 5, wherein It further includes: Obtaining the severity information of the influence of the user experience obstacle problem category on user experience in the user perception dimension and the user behavior dimension respectively, and determining the weight corresponding to the user experience obstacle problem category according to the severity information in the two dimensions.

7. The method according to claim 6, wherein Obtaining the severity information of the influence of the user experience obstacle problem category on user experience in the user perception dimension and the user behavior dimension includes: Determining the severity information of the influence of the user experience obstacle problem category on user experience in the user perception dimension and the user behavior dimension respectively according to the common information and difference information existing in the perception dimension and / or behavior dimension of multiple different user groups.

8. The method according to claim 1, wherein The target dimension includes: the application module dimension in the target information system, and the user experience impact index component is used to represent the user experience impact indexes corresponding to multiple different application modules; or The target dimension includes: the link dimension included in the processing link of the analysis object, and the user experience impact index component is used to represent the user experience impact indexes corresponding to multiple different links; or The target dimension includes: the problem handling party dimension of the analysis object, and the user experience impact index component is used to express the user experience impact indexes of multiple different problem handling parties for performance appraisal of the problem handling party; or The target information system includes a commodity object information service system; the target dimension includes: the commodity object category dimension or the commodity object dimension, and the user experience impact index component is used to represent the user experience impact indexes corresponding to multiple different commodity object categories or different commodity objects.

9. The method according to any one of claims 1 to 7, wherein Providing the corresponding solution to the operation action responsible person corresponding to the problem category includes: Providing the solution and the information of the corresponding operation action responsible person to the associated work order system, so that the work order system generates a task work order according to the solution and the information of the operation action responsible person, and the operation action responsible person executes the operation action corresponding to the solution according to the task work order.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 9.

11. An electronic device, characterized in that, It includes: One or more processors; And A memory associated with the one or more processors, the memory is used to store program instructions, and when the program instructions are read and executed by the one or more processors, the steps of the method according to any one of claims 1 to 9 are executed.

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