CN-121998648-A - User experience measurement method and device

CN121998648ACN 121998648 ACN121998648 ACN 121998648ACN-121998648-A

Abstract

The embodiment of the application discloses a user experience measurement method and device, belongs to the technical field of user experience evaluation, and is used for solving the problem of low accuracy of user experience measurement. The method comprises the steps of obtaining monitoring data related to user experience, carrying out coding processing on the monitoring data to obtain a behavior trip map of a first line seat interacted with a user, wherein the monitoring data comprises one or more of user interview data, user observation data and operation log data, the behavior trip map comprises behavior contacts, screening experience indexes related to the user experience according to a pre-constructed candidate index base of user experience metrics, wherein the experience indexes comprise multiple dimensions and sub-features of the dimensions, carrying out mapping processing on the behavior contacts and the experience indexes to obtain a key index data set corresponding to the user, and carrying out layered weighted fusion processing on the key index data set through a user experience metric quantization model to obtain the experience metric score of the user.

Inventors

SONG XUE
TIAN RUNYU
XU HEXIAN
YANG XIAOBO
SUN LIN
WANG QINGXU
FU SHUANGHAI
HAN HAORAN

Assignees

中移在线服务有限公司
中国移动通信集团有限公司

Dates

Publication Date: 20260508
Application Date: 20251231

Claims (10)

1. A method of user experience measurement, the method comprising: Acquiring monitoring data related to user experience, and encoding the monitoring data to obtain a behavior trip map of a first-line seat interacted with a user, wherein the monitoring data comprises one or more of user interview data, user observation data and operation log data, and the behavior trip map comprises behavior contacts; Screening out experience indexes related to user experience according to a pre-constructed candidate index library of user experience metrics, wherein the experience indexes comprise a plurality of dimensions and sub-features of the dimensions; Mapping the behavior contact and the experience index to obtain a key index data set corresponding to the user; And carrying out layered weighted fusion processing on the key index data set through a user experience measurement quantization model to obtain the experience measurement score of the user, wherein the user experience measurement quantization model is used for scoring the dimensionality and the sub-features in the key index data set.
2. The method of claim 1, wherein the encoding the monitoring data to obtain a behavioral trip map of a first line agent interacting with the user comprises: Performing open coding processing on the monitoring data by using a root taking analysis method to obtain an initial conceptual tag, and determining the behavior contact of the first-line seat based on the initial conceptual tag; According to the similarity of each initial concept label, carrying out aggregation treatment on the initial concept labels, determining the aggregated initial concept labels, and carrying out spindle coding to obtain the behavior flow of the first-line seat; Determining the behavior phase of the first-line seat by selectively encoding the behavior flow; And generating the behavior trip map of the first-line seat according to the behavior contact, the behavior flow and the behavior stage.
3. The method of claim 1, wherein before screening out the experience metrics related to the user experience from the candidate metrics library of pre-constructed user experience metrics, further comprising: pre-acquiring authority data, extracting descriptive items related to the user experience measurement from the authority data, and performing semantic deduplication processing on the descriptive items to obtain semantic items subjected to semantic deduplication processing; layering the semantic items to obtain a layer of dimension of the authority data and two layers of sub-features corresponding to the layer of dimension; Constructing the alternative index library of the user experience metrics according to the one-layer dimension and the two-layer sub-feature of the authority data; The screening out experience indexes related to the user experience comprises the following steps: Determining a user behavior type based on the behavioral trip profile of the first-line agent; And screening the dimension related to the user experience and the sub-feature of the dimension from the alternative index library according to the user behavior type, and taking the dimension related to the user experience and the sub-feature of the dimension as the experience index.
4. The method of claim 1, wherein the mapping the behavior contact and the experience index to obtain the key index data set corresponding to the user comprises: acquiring the behavior contact points of the first-line seat in the behavior trip map; Performing matrix analysis on the behavior contact points and the sub-features of different dimensionalities in the experience index, and establishing a multidimensional corresponding relation between the behavior contact points and the sub-features, wherein the behavior contact points correspond to one or more sub-features; Based on the multidimensional corresponding relation, determining the similarity between the behavior contact and the corresponding sub-feature through a semantic analysis method; Determining the sub-features of all the behavior contact maps of the first-line seat and the dimensions corresponding to the sub-features according to the similarity; And generating the key index data set according to all the sub-features of the behavior contact map of the first-line seat and the dimensions corresponding to the sub-features.
5. The method according to claim 1, wherein the performing, by using a user experience metric quantization model, a hierarchical weighted fusion process on the key indicator dataset to obtain an experience metric score of the user includes: Determining the index function type of the sub-feature of the behavior contact in the key index data set according to the index value of the behavior contact in the key index data set and the index function type of the sub-feature of the behavior contact through the user experience measurement quantization model, wherein the index function type comprises a positive correlation index function and/or a negative correlation index function; determining a weight coefficient of each behavior contact under the corresponding sub-feature based on the importance degree of each behavior contact in the key index data set; Determining a datamation measurement formula corresponding to the sub-feature of each behavior contact and the datamation measurement formula corresponding to each dimension according to the positive correlation index function and/or the negative correlation index function and the weight coefficient; determining a score of the experience metric for the user on each of the sub-features according to the datamation metric formula for each of the sub-features; Based on a datamation measurement formula corresponding to each dimension, carrying out weighted fusion processing on the scores of the experience measurement of the sub-feature of each dimension to obtain the scores of the experience measurement of the user in the dimension corresponding to each sub-feature; The experience metric score for the user is determined based on the scores for the experience metrics in each dimension.
6. The method of claim 1, wherein after obtaining the experience metric score for the user, further comprising: dynamically monitoring a score of the experience metric of the user, and when the score of the experience metric of the user is greater than a preset threshold value, sending out a threshold value alarm; And generating and displaying an experience data report according to the threshold alarm.
7. A user experience measurement device, comprising: The system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring monitoring data related to user experience, and encoding the monitoring data to obtain a behavior trip map of a first-line seat interacted with a user, wherein the monitoring data comprises one or more of user interview data, user observation data and operation log data, and the behavior trip map comprises behavior contacts; The construction module is used for screening out experience indexes related to the user experience according to a pre-constructed alternative index library of the user experience measurement, wherein the experience indexes comprise a plurality of dimensions and sub-features of the dimensions; the mapping module is used for mapping the behavior contact and the experience index to obtain a key index data set corresponding to the user; And the scoring module is used for carrying out layered weighted fusion processing on the key index data set through a user experience measurement quantization model to obtain the experience measurement score of the user, and the user experience measurement quantization model is used for scoring the dimensionality and the sub-feature in the key index data set.
8. An electronic device comprising a processor and a memory electrically connected to the processor, the memory storing a computer program, the processor being configured to invoke and execute the computer program from the memory to implement a user experience metric method as claimed in claims 1-6.
9. A computer readable storage medium storing a computer program executable by a processor to implement a user experience metric method as claimed in claims 1-6.
10. A computer program product comprising a computer program which, when executed by a processor, implements a user experience metric method as claimed in claims 1 to 6.

Description

User experience measurement method and device Technical Field The present application relates to the field of user experience assessment technologies, and in particular, to a method and an apparatus for measuring user experience. Background The customer service system has complex service scene and multiple built-in functions, mainly uses personnel as seat personnel of each sub-center, and the quality of hotline service provided by the seat personnel for the user is positively correlated with the auxiliary capability provided by the customer service system, so that the customer service system has important significance for carrying out user experience measurement on the flow of key service scene of the customer service system. In the related art, the user experience measurement method generally adopts the embedded points of the page data to obtain the data, so that the experience data has single source and less dimension, and most of the user experience measurement method adopts a general index set, has thicker measurement granularity, cannot be applied to specific products and key business scenes related to the specific products, and has the problem of low accuracy of user experience measurement. Disclosure of Invention The embodiment of the application aims to provide a user experience measurement method and device, which are used for solving the problem of low accuracy of user experience measurement. In order to solve the technical problems, the embodiment of the application is realized as follows: In a first aspect, an embodiment of the present application provides a method for measuring user experience, where the method includes obtaining monitoring data related to user experience, encoding the monitoring data to obtain a behavioral trip map of a first line of agents interacting with a user, where the monitoring data includes one or more of user interview data, user observation data and operation log data, the behavioral trip map includes a behavioral contact, screening experience indexes related to the user experience according to a pre-constructed candidate index library of user experience measures, where the experience indexes include multiple dimensions and sub-features of the dimensions, mapping the behavioral contact and the experience indexes to obtain a key index data set corresponding to the user, and performing hierarchical weighted fusion processing on the key index data set through a user experience measure quantization model to obtain an experience measure score of the user, where the user experience measure quantization model is used to score the dimensions and the sub-features in the key index data set. In a second aspect, an embodiment of the present application provides a user experience measurement device, where the device includes an acquisition module configured to acquire monitoring data related to a user experience, and perform coding processing on the monitoring data to obtain a behavioral trip map of a line agent that interacts with the user, where the monitoring data includes one or more of user interview data, user observation data, and operation log data, the behavioral trip map includes a behavioral contact, a construction module configured to screen out an experience index related to the user experience according to a pre-constructed candidate index library of user experience metrics, where the experience index includes multiple dimensions and sub-features of the dimensions, a mapping module configured to map the behavioral contact and the experience index to obtain a key index data set corresponding to the user, and a scoring module configured to perform layered weighted fusion processing on the key index data set through a user experience metric quantization model to obtain an experience metric score of the user, where the user experience metric quantization model is used to score the dimensions and the sub-features in the key index data set. In a third aspect, an embodiment of the present application provides an electronic device, where the electronic device includes a processor, a memory, and a program or instruction stored on the memory and executable on the processor, where the program or instruction when executed by the processor implements a user experience metric method as described above. In a fourth aspect, embodiments of the present application provide a readable storage medium having stored thereon a program or instructions which, when executed by a processor, cause a user experience metric method as described above. In a fifth aspect, an embodiment of the present application provides a chip, where the chip includes a processor and a communication interface, where the communication interface is coupled to the processor, and the processor is configured to execute a program or instructions to implement a method for measuring a user experience as described above. In a sixth aspect, embodiments of the present application provide a computer program product comprising