CN107295050B - Front-end user behavior statistical method and device - Google Patents
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Abstract
The invention provides a front-end user behavior statistical method and a device, wherein a page click event of a page is monitored in the page running process by acquiring a preset embedded point rule for the page, and behavior data of a front-end user of the page is counted based on the embedded point rule after the page click event is monitored. In order to realize automatic point burying of the page, a point burying rule is firstly set for the page, and the point burying starting is triggered by a page clicking event when the page runs, so that the problem that the prior manual point burying has complex mistake and poor convenience is solved, the behavior of a front-end user of the page can be subjected to global statistics, and the statistical efficiency is high.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a front-end user behavior statistical method and device.
Background
Today, whether it is the operator of an e-commerce store or a personal captain, the rapid growth of the internet, if it is possible to keep track of some of the user's clicks during the residence of the page and to analyze them well, will provide the most immediate and efficient help in improving the user experience of the web page and attracting the user's clicks.
Usually, a click behavior of a user is recorded by performing a point burying operation on a page, and in a popular way, the point burying of the page is an operation of collecting data accessed and clicked by the user through a scripting language (JavaScript, JS for short). When a user opens a webpage and clicks, a JS code embedded in the webpage is executed, and the JS code returns collected data to a website server.
In the current point burying technology, a point is buried for a designated button manually, and the behavior of a user is counted based on the clicking operation of the designated button. In practical application, the page needs to be subjected to global statistics, and the manual point burying process is complicated, so that the problem of poor convenience exists.
Disclosure of Invention
The invention provides a front-end user behavior statistical method and device, which are used for solving the problems of complexity and poor convenience in a manual point burying process when a page is subjected to global statistics.
In order to achieve the above object, the present invention provides a front-end user behavior statistical method, which comprises:
acquiring a preset embedding point rule for a page;
monitoring a page click event of the page in the page operation process;
and after the page click event is monitored, counting behavior data of a user at the front end of the page based on the buried point rule.
In order to achieve the above object, the present invention provides a front-end user behavior statistics apparatus, including:
the acquisition module is used for acquiring a preset embedded point rule for the page;
the monitoring module is used for monitoring the page click event of the page in the page running process;
and the statistical module is used for counting the behavior data of the front-end user of the page based on the embedded point rule after the page click event is monitored.
According to the front-end user behavior statistical method and device provided by the invention, the page click event of the page is monitored in the page running process by acquiring the preset embedded point rule for the page, and after the page click event is monitored, the behavior data of the front-end user of the page is counted based on the embedded point rule. In order to realize automatic point burying of the page, a point burying rule is firstly set for the page, and the point burying starting is triggered by a page clicking event when the page runs, so that the problem that the prior manual point burying has complex mistake and poor convenience is solved, the behavior of a front-end user of the page can be subjected to global statistics, and the statistical efficiency is high.
Drawings
Fig. 1 is a schematic flow chart illustrating a front-end user behavior statistical method according to a first embodiment of the present invention;
FIG. 2 is a flowchart illustrating a front-end user behavior statistical method according to a second embodiment of the present invention;
fig. 3 is a schematic flow chart illustrating a front-end user behavior statistical method according to a third embodiment of the present invention;
fig. 4 is a schematic flow chart illustrating a front-end user behavior statistical method according to a fourth embodiment of the present invention;
fig. 5 is a schematic flow chart of a front-end user behavior statistical method according to a fifth embodiment of the present invention;
fig. 6 is a schematic structural diagram of a front-end user behavior statistics apparatus according to a sixth embodiment of the present invention;
fig. 7 is a schematic structural diagram of a front-end user behavior statistics apparatus according to a seventh embodiment of the present invention.
Detailed Description
The following describes in detail a front-end user behavior statistical method and apparatus provided by the embodiments of the present invention with reference to the accompanying drawings.
Example one
Fig. 1 is a schematic flow chart of a front-end user behavior statistical method according to a first embodiment of the present invention.
The front-end user behavior statistical method comprises the following steps:
s101, acquiring a preset embedded point rule for the page.
In this embodiment, a dot embedding rule is set for the page in advance, specifically, all the controls of the page are obtained, and the dot embedding rule is set for different controls according to statistical requirements. Optionally obtaining the type of each control, and setting the same embedded point rule for all the controls of the same type.
Wherein, the embedded point rule defines the embedded point object of the page, and a statistical strategy corresponding to the embedded point object is set.
During the operation of the page, the embedded point rule of the page needs to be acquired, and specifically, when the page is started, the embedded point rule is loaded into a service file of the page. The service file of the page is a service processing flow of the page.
S102, monitoring a page click event of the page in the page running process.
After a user opens a page, a service file of the page can be executed, namely a service processing flow of the page is started, and a page click event belonging to the page is monitored in the process of executing the processing flow. That is to say, when the front-end user clicks a page on a web page, a page click event can be triggered, and the service file corresponding to the page can monitor the page click event.
In this embodiment, a page is embedded, when the page is started, that is, when a service file of the page is loaded, a rule of embedding the point corresponding to the page is loaded at the same time, and accordingly, a function of embedding the point is started, and page click events of all controls under the page are monitored.
S103, after the page click event is monitored, behavior data of a user at the front end of the page are counted based on a buried point rule.
After a page click event is monitored, a target object corresponding to the page click event is determined, and further, after the target object is determined, whether the target object opens a buried point or not needs to be judged. In this embodiment, the object for opening the buried point is defined in the buried point rule, and the object for buried point may be a button label or other designated control such as a label.
In this embodiment, the embedded point rule defines the embedded point object and the statistical strategy corresponding to the embedded point object. Two alternatives for the buried object to open the buried point are as follows:
firstly, the embedded point object is opened to carry out embedded point recording when the page is loaded. Specifically, when a preset embedding rule is loaded, embedding is automatically started for all embedding objects such as button labels belonging to the page.
And secondly, judging whether each embedded point object under the page has a corresponding statistical strategy, if the statistical strategy of the embedded point object is not null, indicating that the embedded point is opened by the target object, and counting the behavior data of the front-end user based on the statistical strategy of the target object. And if the statistical strategy of the target object is null, the target object is not counted if the target object does not open the buried point.
When the buried point is judged to be opened by the target object, the buried point record can be performed on the target object, and optionally, the button, time and coordinate of the click event are recorded, wherein the coordinate of the click event is the position in the page and can also be called as the coordinate. Furthermore, a statistical strategy of the target object is obtained, the buried point record of the target object can be counted according to the statistical strategy, that is, information of a click position, a click event, a user ID, a module to which the control belongs and the like can be counted, so that behavior data of the front-end user can be obtained. For example, when the type of the control is a button type, that is, the corresponding HTML tag is (button/a/span), the position, the click time, the user ID, the module to which the control belongs, and the application to which the current operation belongs may be recorded, and if the page click event has a trigger background request, information such as a Uniform Resource Locator (URL) of the background request, time consumed by the background request, and whether the background request is successful or not is recorded. Further, after the information of the control is obtained, the control needs to be counted at a specific time, a counting strategy corresponding to the control is obtained according to the control and the control type of the control, and then the user behavior data of the control is counted according to the counting strategy. In the process of using the page, the user behavior of the front-end user can be supervised based on the embedded point rule, so that the behavior data of the front-end user when using the page can be obtained through statistics.
In the front-end user behavior statistical method provided by this embodiment, a page click event of a page is monitored in a page operation process by obtaining a preset embedded point rule for the page, and behavior data of a front-end user of the page is counted based on the embedded point rule after the page click event is monitored. In order to realize the automatic point burying of the page in the embodiment, a point burying rule is set for the page, the point burying is triggered by a page clicking event during the page operation, the problem that the prior point burying is mistaken and complicated and is poor in convenience is solved, the behavior of a page front-end user can be subjected to global statistics, and the statistical efficiency is high.
Example two
Fig. 2 is a schematic flow chart illustrating a front-end user behavior statistical method according to a second embodiment of the present invention. The front-end user behavior statistical method provided by this embodiment needs to be executed on the basis of modularizing the front end of the page. The front-end user behavior statistical method comprises the following steps:
s201, performing modularization processing on the page.
Under the rapid development of the internet, a page gradually becomes an internet application program, in order to adapt to intense market competition and meet the requirement of a user on diversification, JS codes embedded in a webpage are increasingly huge and complex, the page is also increasingly similar to a desktop program, and labor division cooperation, progress management, unit testing and the like are needed. In order to improve the development experience of the developer and provide good support for performance optimization, the developer can program the front end of the page based on modularization. The purpose of front-end modularization of the page can be achieved, the page can be cooperatively developed by multiple persons, the page research and development speed is increased, and the maintenance difficulty is reduced.
S202, a buried point rule is configured for the page corresponding module.
In order to realize global statistics of the page, a buried point rule is configured for a corresponding module of the page in advance. Specifically, all the controls, the control types, and the modules to which the controls belong of the page are obtained, and different modules can set different embedding rules, or one embedding rule can be globally set. Acquiring the control type needing embedding, setting a corresponding embedding rule for the control type, and attributing the embedding rule of the control type belonging to the same module to a file to form the embedding rule of the module.
S203, monitoring the click event belonging to the page in the operation process by executing the service file operation page.
When a front-end user tries to use a page, before the page is run, a service file of a module corresponding to the page needs to be acquired, wherein the service file is a service processing flow of the module corresponding to the page. And executing the service file, namely operating the service processing flow of the corresponding module of the page. In this embodiment, when executing the service file, the embedded point rule of the module corresponding to the page is loaded at the same time.
In the running process of the service file, based on the embedded object defined in the embedded rule, specifically, when the embedded point is opened by the page corresponding module, the click events of all controls under the module are monitored, and according to the embedded rule bound by the corresponding module, when the control corresponding to the click event is monitored to be the control of the embedded point, the behavior data of the page front-end user is acquired.
And S204, after the page click event is monitored, counting behavior data of a user at the front end of the page based on the buried point rule.
In the process of using the page, the user behavior of the front-end user can be supervised based on the embedded point rule, so that the behavior data of the front-end user when using the page can be obtained through statistics. For a specific process, reference may be made to the description of the related contents in the above second embodiment, which is not described herein again.
According to the front-end user behavior statistical method provided by the embodiment, the embedded point rule is configured for the corresponding module of the page on the basis of modularization of the page, when the service file of the page is executed, the corresponding embedded point rule is obtained, and the behavior data of the front-end user of the page is obtained based on the embedded point rule in the process of executing the service file, so that global automatic embedding of the page is realized, global statistics on the behavior of the front-end user of the page can be realized, and the statistical efficiency is high.
EXAMPLE III
Fig. 3 is a schematic flow chart of a front-end user behavior statistical method according to a third embodiment of the present invention. The front-end user behavior statistical method provided by this embodiment needs to be executed on the basis of modularizing the front end of the page.
The front-end user behavior statistical method comprises the following steps:
s301, determining a dependent file required by the operation of the corresponding module of the page according to the service file of the corresponding module of the page.
Currently, developers program the front end of a page modularly in order to facilitate optimization of the page. When a front-end user tries to use a page, before the page is run, a service file of a module corresponding to the page needs to be acquired, wherein the service file is a service processing flow of the module corresponding to the page.
In the page, generally, in the modularization process, a module corresponding to the page writes a dependent related code file according to defined dependence. After the business file of the module corresponding to the page is obtained, the business file is analyzed, and a dependent file required by the operation of the module corresponding to the page can be determined. The general page correspondence module includes three types of dependent files: HyperText Markup Language (HTML) dependent files, Cascading Style Sheets (CSS) dependent files, and JS dependent files.
S302, loading a dependency file and a buried point rule configured for a page corresponding module in advance.
In this embodiment, in order to implement a global point burying mechanism, a point burying rule is configured for the page corresponding module in advance, and a point burying object of the module is defined in the point burying rule. For example, the object of the buried point may be a button tag or other designated tag. While loading the dependent file, loading a buried point rule configured for the page object module in advance.
S303, executing the service file based on the embedded point rule to obtain behavior data of the front-end user of the page in a statistical manner.
And after the dependence file and the embedded point rule are loaded, executing the service file of the module corresponding to the page, namely, running the service processing flow of the module corresponding to the page. In this embodiment, since the embedded point rule corresponding to the module is loaded, in the running process of the service file, the behavior data of the user at the front end of the page can be obtained based on the embedded point object defined in the embedded point rule.
Specifically, when a front-end user uses a page, a control in the page can be clicked, the control can be monitored in this embodiment, and when it is monitored that the clicked control is a buried point object, a buried point record of the control can be obtained. Further, the embedded point rule further includes a statistical strategy of the embedded point object, after the embedded point record of the embedded point object is obtained, the statistical strategy of the embedded point object is obtained, if the statistical strategy of the embedded point object is empty, the embedded point record of the embedded point object is not counted, and if the statistical strategy is obtained, the embedded point record is counted according to the statistical strategy.
For example, when the type of the control is a button type, that is, the corresponding HTML tag is (button/a/span), the position, the click time, the user ID, the module to which the control belongs, and the application to which the current operation belongs may be recorded, and if the click event has a background request triggered, information such as a Uniform Resource Locator (URL), time consumption of the background request, and whether the background request is successful or not is recorded. Further, after the information of the control is obtained, the control needs to be counted at a specific time, a statistical strategy corresponding to the control is inquired and obtained from a background database according to the name of the module to which the control belongs and the control type of the control, and then the user behavior data of the control is counted according to the statistical strategy. In this embodiment, the statistical strategy is stored in a background database, so that real-time modification can be performed.
In the process of using the page, the user behavior of the front-end user can be supervised based on the embedded point rule, so that the behavior data of the front-end user when using the page can be obtained through statistics.
According to the front-end user behavior statistical method provided by the embodiment, the dependency file required by the operation of the corresponding module of the page is determined according to the service file of the corresponding module of the page, the dependency file and the embedded point rule configured for the corresponding module of the page in advance are loaded, the service file is executed based on the embedded point object defined in the embedded point rule, and the behavior data of the front-end user of the page is obtained. The embodiment provides a global point burying mechanism, a dependency file is loaded, a point burying rule of a module is written in, behaviors of front-end users can be counted based on the point burying rule, global statistics of the behaviors of the front-end users of the page can be achieved for global automatic point burying of the page, and the statistical efficiency is high.
Example four
Fig. 4 is a schematic flow chart of a front-end user behavior statistical method according to a fourth embodiment of the present invention. At present, RequireJS is a very small JavaScript module loading frame, and in this embodiment, the RequireJS frame is selected as a bottom-layer dependency implementation, and front-end modularization of a page is implemented on the basis. On the basis of the above embodiment, the process of loading the preset embedded point rule to the service file corresponding to the page includes:
s401, loading the business file of the page.
When a front-end user tries to use a page, before the operation, a service file of a module corresponding to the page needs to be called, wherein the service file is a service processing flow of the module corresponding to the page. In this embodiment, the service file of the corresponding module of the page is loaded based on the RequireJS frame, the service file is written in the JavaScript scripting language, and the JS is used as the JS file of the extension.
S402, analyzing the service file to obtain a dependent file required by the page operation.
And in the process of calling the service file, analyzing the service file to obtain the dependent file of the module. In the page modularization process, the dependency of the module can be defined, and a developer can write a related code file according to the dependency definition. The modules of a generic page include three types of dependent files: HTML dependent files, CSS dependent files, and JS dependent files.
In this embodiment, since RequireJS only supports dependency analysis of JS-dependent files, in order to implement analysis of HTML-dependent files and CSS-dependent files, a third-party plug-in needs to be inserted into the RequireJS frame, so that the RequireJS frame can support analysis of HTML-dependent files and CSS-dependent files.
And S403, packaging the service file.
After the required dependency file of the module corresponding to the page is analyzed, the dependency file of the module is loaded, and in practice, the service file of the module can be directly executed after the JS dependency file loading of the module is completed due to the Require JS frame. In this embodiment, the module needs to load the HTML dependent file and the CSS dependent file in addition to the JS dependent file.
In order to execute the service processing flow of the module after all the dependent files are loaded, in this embodiment, the service processing flow of the service file of the module is encapsulated based on the RequireJS framework, and the encapsulated service processing flow is not executed any more and is executed only after the encapsulation is released.
S404, loading a buried point rule of the dependent file and the page.
In order to implement a mechanism for global statistics on a page, in this embodiment, a dependent file of a module is loaded, and a buried point rule configured for the module in advance is loaded at the same time. The object of the buried point may be a button label or other designated label. Specifically, the burial point can be automatically opened for the objects of button labels (button/span/a) in all the Dom files belonging to the module, so that the burial point statistics can be carried out through all the button labels of the module.
S405, performing HTML template rendering and CSS rendering on the service file.
In this embodiment, after the dependent file is loaded, HTML template rendering and CSS rendering are performed on the service file of the module based on the dependent file.
S406, removing the encapsulation of the service file.
After the service file of the module is rendered, since the service file of the module is encapsulated before, the service processing flow of the service file needs to be decapsulated, so that the service file of the module can be executed.
After the encapsulation of the service file of the module is released, the service file is executed based on the RequireJS framework. In the process of executing the service file, because the embedded point rule of the module is loaded in the service file, the click behavior of the front-end user is recorded based on the embedded point object defined in the embedded point rule, so that the behavior data of the front-end user can be counted.
It should be noted here that the implementation of dependency using RequierJS as the bottom layer is a complete example here, and is not a condition for limiting the present invention. The front-end user statistical method can also be realized based on the underlying dependencies such as the SeaJS framework.
The front-end user behavior statistical method provided in this embodiment obtains behavior data of a page front-end user by loading a service file of a module corresponding to the page, parsing a dependent file of a service file obtaining module, encapsulating a service processing flow of the service file, loading the dependent file of the module and a embedding rule preset by the module, performing HTML template rendering and CSS rendering on the service file, removing encapsulation of the service file, and executing statistics of embedded objects defined in the embedding rule by the service file. The embodiment provides a global point burying mechanism, a dependent file is loaded, a point burying rule of a module is written in at the same time, behaviors of a front-end user can be counted based on a point burying object in the point burying rule, global statistics of the behaviors of the front-end user can be realized for global automatic point burying of a page, and the statistical efficiency is high.
EXAMPLE five
Fig. 5 is a schematic flow chart of a front-end user behavior statistical method according to a fifth embodiment of the present invention. On the basis of the above embodiment, the front-end user behavior statistical method includes the following steps:
s501, monitoring a page click event belonging to a page in the process of executing the service file.
After the business file is loaded and rendered, the business processing flow of the business file can be executed, and in the process of executing the processing flow, the business file monitors the page click event of the corresponding module of the affiliated page. That is to say, when a front-end user clicks a page on a web page, a page click event can be triggered, and a service file corresponding to a module to which the page click event belongs can monitor the page click event.
In this embodiment, a page is subjected to modular processing, then a module corresponding to the page is subjected to point burying, when the module is loaded, a point burying rule configured for the page is loaded at the same time, and page click events of all controls under the module are monitored under the condition that the module opens the point burying.
S502, determining a target object corresponding to the monitored page click event.
And when the business file of the page monitors a page click event, determining a target object corresponding to the page click event.
S503, judging whether the target object starts a buried point function or not.
In the above embodiment, when the service file loads the dependent file, the embedded point rule preset for the page is loaded at the same time. The embedded point rule defines the embedded point object of the page corresponding module, and is provided with a statistical strategy corresponding to the embedded point object. In this embodiment, the object for opening the buried point is defined in the code of the buried point rule, and the object for buried point may be a button label or other designated control such as a label. In this embodiment, the embedded point rule defines the embedded point object and the statistical strategy corresponding to the embedded point object. There are two alternative ways to open the buried point: firstly, the embedded point object is opened to carry out embedded point recording when the page is loaded. Specifically, when a preset embedding rule is loaded, embedding is automatically started for embedding objects such as button labels in all Dom files belonging to the page. And secondly, judging whether each buried point object has a corresponding statistical strategy, if the statistical strategy of the buried point object is not null, indicating that the target object starts a buried point function, and performing user behavior data statistics based on the buried point object. And if the statistical strategy of the target object is null, the target object is not counted if the statistical strategy of the target object indicates that the buried point function of the target object is not started.
If the target object is judged to start the embedded point function, S504 is executed; otherwise, return to execute S501.
S504, point burying recording is conducted on the clicking behaviors of the target object, and behavior data of the front-end user are counted according to the point burying recording and the statistical strategy of the target object.
When the buried point is judged to be opened by the target object, the buried point record can be performed on the target object, and optionally, the button, time and coordinate of the click event are recorded, wherein the coordinate of the click event is the position in the page and can also be called as the coordinate.
Furthermore, a statistical strategy of the target object is obtained, the buried point record of the target object can be counted according to the statistical strategy, that is, information of a click position, a click event, a user ID, a module to which the control belongs and the like can be counted, so that behavior data of the front-end user can be obtained.
And S505, while the click behavior of the target object is recorded in a buried point mode, acquiring a request event corresponding to the click behavior, and recording the service logic of the request event.
Further, each click behavior of the front-end user corresponds to one request event of the web page, and each request event has a certain service logic.
S506, judging whether the recorded times exceed a threshold value.
If the judgment result is negative, executing S507; otherwise, S508 is performed.
S507, judging whether a page refreshing event or a page closing event is monitored in the process of executing the service file.
If the judgment result is yes, executing S508; otherwise, returning to execute S501 to continue monitoring the page click event.
And S508, writing the behavior data of the front-end user and the recorded business logic into a log file.
In this embodiment, the behavior data and the service logic are locally stored at the front end, and when the number of records is N, the recorded behavior data and the recorded service logic may be written in a log file in batch for storage. That is, during the recording, the number of times of recording is compared with a preset threshold, and when the number of times of recording exceeds the threshold, the recorded behavior data and business logic are written in the log file in batches. In practical application, in order to relieve the pressure of local storage, when the number of times of recording exceeds a threshold value, the recorded behavior data and the service logic may be sent to the server in batch for storage, and after receiving the behavior data and the service logic, the server may write the behavior data and the service logic into a log file according to a set data format.
Further, in this embodiment, a page refresh event and a page close event of the page may also be monitored during the process of executing the service file, and when the page refresh event or the page close event is monitored, the recorded behavior data and the service logic are written into the log file. In order to avoid information loss, the recorded behavior data and the business logic are sent to a back-end server for storage. After receiving the behavior data and the service logic, the server can write the behavior data and the service logic into a log file according to a set data format.
Further, the log file containing the behavior data is analyzed, and based on the counted behavior data of the front-end user, the operation data of some webpages can be acquired. The operation data may include the number of independent visitors (UV for short), Page View volume or click volume (PV for short), module heat, project heat, request time consumption statistics, request success rate, statistics of designated buttons, partial module statistics of designated pages, click thermodynamic diagram of designated pages, and the like. Furthermore, the analysis result can be displayed to a web page developer, and the developer can use the operation data as reference data to provide reference for actual product operation and design troubleshooting errors and provide basis for front-end interactive design.
In the front-end user behavior statistical method provided in this embodiment, in the process of executing the service file of the page corresponding module, the page click event belonging to the page is monitored, a target object corresponding to the monitored page click event is determined, whether the target object is a buried object defined in the buried point rule is determined, when the target object starts a buried point function, a buried point record may be performed on the click behavior of the front-end user, and behavior data of the front-end user is counted according to the buried point record. The embodiment realizes the global statistics of the front-end user behavior of the webpage based on the embedded point rule loaded in the module, can acquire the global behavior data of the page, and is convenient for providing reference basis for the later maintenance or perfection of the page.
EXAMPLE six
Fig. 6 is a schematic structural diagram of a front-end user behavior statistics apparatus according to a sixth embodiment of the present invention. The front-end user behavior statistical device comprises: the device comprises an acquisition module 11, a monitoring module 12 and a statistic module 13.
The obtaining module 11 is configured to obtain a preset embedding rule for a page.
In this embodiment, a dot embedding rule is set for the page in advance, specifically, all the controls of the page are obtained, and the dot embedding rule is set for different controls according to statistical requirements. Optionally obtaining the type of each control, and setting the same embedded point rule for all the controls of the same type.
Wherein, the embedded point rule defines the embedded point object of the page, and a statistical strategy corresponding to the embedded point object is set.
During the operation of a page, the obtaining module 11 needs to obtain a buried point rule of the page, and specifically, when the page is started, the obtaining module 11 loads the buried point rule into a service file of the page. The service file of the page is a service processing flow of the page.
The monitoring module 12 is configured to monitor a page click event of a page in a page running process.
When a user opens a page, the service file of the page can be executed, that is, the service processing flow of the page is started, and in the process of executing the processing flow, the monitoring module 12 monitors the page click event belonging to the page. That is to say, when the front-end user clicks a page on a web page, a page click event can be triggered, and the service file corresponding to the page can monitor the page click event.
In this embodiment, a page is embedded, when the page is started, that is, when a service file of the page is loaded, a rule of embedding the corresponding page is loaded, and accordingly, a function of embedding the point is started, so that page click events of all controls under the page are all monitored by the monitoring module 12.
And the counting module 13 is used for counting behavior data of a user at the front end of the page based on the embedded point rule after the page click event is monitored.
After monitoring the page click event, the statistical module 13 determines a target object corresponding to the page click event, and further, after determining the target object, the statistical module 13 needs to determine whether the target object opens a buried point. In this embodiment, the object for opening the buried point is defined in the buried point rule, and the object for buried point may be a button label or other designated control such as a label.
In this embodiment, two optional ways of opening the buried point for the buried point object can be referred to the related descriptions in the above embodiments, and are not described herein again.
When the buried point of the target object is judged to be opened, the buried point of the target object can be recorded, and the statistical module 13 supervises the user behavior of the front-end user based on the statistical strategy corresponding to the target object, so that the behavior data of the front-end user when the front-end user uses the page can be obtained through statistics. For details, reference may be made to the related descriptions in the above embodiments, which are not described herein again.
The front-end user behavior statistical apparatus provided in this embodiment monitors a page click event of a page in a page operation process by obtaining a preset embedding rule for the page, and performs statistics on behavior data of a front-end user of the page based on the embedding rule after monitoring the page click event. In order to realize the automatic point burying of the page in the embodiment, a point burying rule is set for the page, the point burying is triggered by a page clicking event during the page operation, the problem that the prior point burying is mistaken and complicated and is poor in convenience is solved, the behavior of a page front-end user can be subjected to global statistics, and the statistical efficiency is high.
EXAMPLE seven
Fig. 7 is a schematic structural diagram of a front-end user behavior statistics apparatus according to a seventh embodiment of the present invention. The front-end user behavior statistical device comprises: the device comprises an acquisition module 11, a monitoring module 12 and a statistic module 13.
In this embodiment, an optional structure manner of the statistical module 13 includes: an acquisition unit 131, a judgment unit 132, a recording unit 133, and a writing unit 134.
The obtaining unit 131 is configured to determine a target object corresponding to the monitored page click event;
a determining unit 132, configured to determine whether the target object opens a buried point;
the recording unit 133 is configured to perform a buried point record on the click behavior of the target object when the determining unit determines that the buried point is opened by the target object, and count the behavior data of the front-end user according to the buried point record and the statistical policy of the target object.
Further, the recording unit 133 is further configured to determine a request event corresponding to the click behavior while performing a buried point recording on the click behavior of the target object, and record a service logic of the request event.
A writing unit 134, configured to write the behavior data and the service logic into a log file when the number of times of recording exceeds a threshold.
Further, the monitoring module 12 is further configured to monitor a page refresh event or a page close event during the page operation.
The writing unit 134 is further configured to write the behavior data and the service logic into a log file when the monitoring module 12 monitors the page refresh event or the page close event.
Optionally, the behavior data and the service logic are locally stored at the front end, in practical applications, in order to relieve the pressure of local storage, the recorded behavior data and the service logic may be sent to the server in batch for storage when the number of times of recording exceeds a threshold, and after receiving the behavior data and the service logic, the server may write the behavior data and the service logic into a log file according to a set data format.
Optionally, after a page refresh event or a page close event is monitored, to avoid information loss, the recorded behavior data and the service logic are sent to a server at the back end for storage. After receiving the behavior data and the service logic, the server can write the behavior data and the service logic into a log file according to a set data format.
In this embodiment, an optional structural manner of the obtaining module 11 includes: a modularization unit 111 and an acquisition unit 112.
The modularization unit 11 is configured to perform modularization processing on the page.
An obtaining unit 112, configured to load the embedded point rule into a service file of a module corresponding to the page when the page is started. And the service file is a service processing flow of the page.
An optional structure of the obtaining unit 112 includes: a loading sub-unit 1121, a parsing sub-unit 1122, an encapsulation sub-unit 1123, a rendering sub-unit 1124, and a decapsulation sub-unit 1125.
A parsing subunit 1122, configured to parse the service file to obtain the dependent file.
The parsing subunit 1122 is configured to parse the service file after the loading subunit 1121 loads the service file of the page corresponding module, so as to obtain a dependent file of the page corresponding module.
The module of the general page has three types of dependent files, namely an HTML dependent file, a CSS dependent file and a JS dependent file.
The loading subunit 1121 is specifically configured to load a service file of a page, and a rule of embedding points in the service file of the page is loaded. Further, the loading sub-unit 1121 is specifically configured to load a hypertext markup language HTML dependent file, a cascading style sheet CSS dependent file, and a JS dependent file.
And an encapsulating subunit 1123, configured to encapsulate the service file.
Before the loading subunit 1121 loads the dependency file and the embedded point rule configured in advance for the page corresponding module, the encapsulating subunit 1123 encapsulates the service processing flow of the service file.
And the decapsulating subunit 1125 is configured to decapsulate the service file.
Before the statistics module 13 executes the buried object defined by the service file based on the buried rule, and statistics is performed to obtain the behavior data of the front-end user of the page, the decapsulating subunit 1125 decapsulates the service file.
The rendering subunit 1124 is configured to perform HTML template rendering and CSS rendering on the service file.
Before the decapsulating subunit 1125 decapsulates the service file, the service file is HTML template rendered and CSS rendered using the dependent file.
Each functional module of the front-end user behavior statistical apparatus provided in this embodiment may be used to execute the flow of the front-end user behavior statistical method shown in fig. 1 to 5, and specific working principles thereof are not described again, for details, see description of method embodiments.
In this embodiment, based on the modularization of the page, a node burying rule is configured for a corresponding module of the page, when a service file of the page is executed, a corresponding node burying rule is obtained, and behavior data of a front-end user of the page is obtained based on the node burying rule in the process of executing the service file, so that global automatic node burying of the page is realized, global statistics on behaviors of the front-end user of the page can be performed, and the statistical efficiency is high.
Those of ordinary skill in the art will understand that: all or a portion of the steps of implementing the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium. When executed, the program performs steps comprising the method embodiments described above; and the aforementioned storage medium includes: various media that can store program codes, such as ROM, RAM, magnetic or optical disks.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (14)
1. A front-end user behavior statistical method is characterized by comprising the following steps:
acquiring a preset embedding point rule for a page;
monitoring a page click event of the page in the page operation process;
after the page click event is monitored, the behavior data of the front-end user of the page is counted based on the buried point rule,
after the page click event is monitored, the behavior data of the page front-end user is counted based on the buried point rule, and the method comprises the following steps:
determining a target object corresponding to the monitored page clicking event;
judging whether the target object opens the buried point or not, wherein the target object opening the buried point is defined in the buried point rule;
and if so, performing buried point recording on the clicking behavior of the target object, and counting the behavior data of the front-end user according to the buried point recording and the statistical strategy corresponding to the target object.
2. The front-end user behavior statistics method of claim 1, further comprising:
and while carrying out embedded point recording on the click behavior of the target object, determining a request event corresponding to the click behavior, and recording the service logic of the request event.
3. The front-end user behavior statistical method according to claim 2, after the statistics of the behavior data of the front-end user according to the statistical strategies corresponding to the buried point records and the target objects, further comprising:
and when the recorded times exceed a threshold value, writing the behavior data and the business logic into a log file.
4. The front-end user behavior statistical method according to claim 3, after the statistics of the behavior data of the front-end user according to the statistical strategies corresponding to the buried point records and the target objects, further comprising:
monitoring a page refreshing event or a page closing event in the process of running the page;
and when the page refreshing event or the page closing event is monitored, writing the behavior data and the service logic into a log file.
5. The front-end user behavior statistical method according to any one of claims 1 to 4, wherein the obtaining of the preset embedding rule for the page comprises:
performing modular processing on the page;
when the page is started, loading the embedded point rule into a service file of a module corresponding to the page;
and the service file is a service processing flow of the page.
6. The front-end user behavior statistical method according to claim 5, wherein the loading a preset embedded point rule into a service file of a module corresponding to the page when the page is started comprises:
loading the service file of the page;
analyzing the service file to obtain a dependent file required by the page operation;
packaging the service file;
loading the dependency file and the buried point rule;
performing hypertext markup language (HTML) template rendering and Cascading Style Sheet (CSS) rendering on the service file;
and releasing the encapsulation of the service file.
7. The front-end user behavior statistical method according to claim 6, wherein the monitoring of the page click event of the page in the page running process comprises:
and monitoring the click event belonging to the page in the operation process by executing the service file to operate the page.
8. A front-end user behavior statistics apparatus, comprising:
the acquisition module is used for acquiring a preset embedded point rule for the page;
the monitoring module is used for monitoring the page click event of the page in the page running process;
a statistic module for counting the behavior data of the front-end user of the page based on the buried point rule after monitoring the page click event,
the statistic module comprises:
the acquisition unit is used for determining a monitored target object corresponding to the page click event;
the judging unit is used for judging whether the target object opens the buried point or not, wherein the target object which opens the buried point is defined in the buried point rule;
and the recording unit is used for recording the embedded point of the click behavior of the target object when the judging unit judges that the embedded point of the target object is opened, and counting the behavior data of the front-end user according to the embedded point record and the statistical strategy of the target object.
9. The front-end user behavior statistics apparatus according to claim 8, wherein the recording unit is further configured to determine a request event corresponding to the click behavior while performing a point burying recording on the click behavior of the target object, and record a service logic of the request event.
10. The front-end user behavior statistics apparatus of claim 9, wherein the statistics module further comprises:
and the writing unit is used for writing the behavior data and the service logic into a log file when the recorded times exceed a threshold value.
11. The front-end user behavior statistics apparatus according to claim 10, wherein the monitoring module is further configured to monitor a page refresh event or a page close event during the running of the page;
the writing unit is further configured to write the behavior data and the service logic into a log file when the monitoring module monitors the page refresh event or the page close event.
12. The front-end user behavior statistics apparatus according to any one of claims 8-11, wherein the obtaining module comprises:
the modularization unit is used for carrying out modularization processing on the page;
the acquiring unit is used for loading the embedded point rule into a service file of a module corresponding to the page when the page is started;
and the service file is a service processing flow of the page.
13. The front-end user behavior statistics apparatus according to claim 12, wherein the obtaining unit comprises:
a loading subunit, configured to load a service file of the page, a dependency file required by the page during running, and the embedding rule;
the analysis subunit is used for analyzing the service file to acquire the dependent file;
the packaging subunit is used for packaging the service file;
the rendering subunit is used for performing hypertext markup language (HTML) template rendering and Cascading Style Sheet (CSS) rendering on the service file;
and the decapsulation subunit is used for decapsulating the service file.
14. The front-end user behavior statistics apparatus according to claim 13, wherein the monitoring module is specifically configured to execute the service file to run the page, and monitor the click event attached to the page during a running process.
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| PCT/CN2017/077244 WO2017167042A1 (en) | 2016-04-01 | 2017-03-20 | Statistical method and apparatus for behaviors of front-end users |
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| WO2017167042A1 (en) | 2017-10-05 |
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