CN110597702A - User behavior analysis system, method and medium - Google Patents
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Abstract
The invention discloses a user behavior analysis system which comprises a timely statistics module, a key index statistics module, a trend analysis module, an access distribution analysis module and a page analysis module, wherein the timely statistics module acquires page access data of a user in real time; the key index counting module counts the page access times and the number of functional users according to the core indexes according to the page access data; the trend analysis module analyzes the use trend of the user according to the page access data and generates a corresponding trend graph; the access distribution analysis module analyzes the degree of dependence of the user on the application program; and the page analysis module ranks the heat of page access by setting a query index and combining the trend graph and the dependence of the user on the application program, and deduces the requirement and preference of the user. By acquiring data of a user access page, the demand, the use habit and the preference of the user are analyzed, the auxiliary market operation is facilitated, the propaganda effect and the activity promotion effect are evaluated, and the commercial purpose is better realized.
Description
Technical Field
The invention relates to the technical field of software, in particular to a user behavior analysis system, a method and a medium.
Background
In order to help internet enterprises know the degree of the customer's reaction to enterprise products, a user behavior access amount statistical strategy is presented. At present, user behavior access amount statistics is mainly performed by means of a third-party platform, for example, centesimal statistics, but the third-party platform is used, conclusion data, which is not basic data, are acquired from the third party, and reference value is not high, so that internet enterprises cannot directly and effectively acquire pain points of pages.
Disclosure of Invention
In view of the defects in the prior art, embodiments of the present invention provide a user behavior analysis system, method, and medium, which are helpful for assisting market operations by acquiring data of a user access page to analyze the user's needs and preferences.
In a first aspect, an embodiment of the present invention provides a user behavior analysis system, including: the system comprises a timely counting module, a key index counting module, a trend analysis module, an access distribution analysis module and a page analysis module, wherein the timely counting module is used for acquiring page access data of a user in real time and obtaining the change condition of the access data according to the page access data;
the key index counting module is used for counting the page access times and the number of functional users according to the page access data and the core indexes;
the trend analysis module is used for analyzing the use trend of the user according to the page access data and the set time and the core index and generating a corresponding trend graph;
the access distribution analysis module is used for acquiring the total time length of accessing and using the application program by the user and analyzing the degree of dependence of the user on the application program according to the distribution of the number of the reuse-removing users in each time length interval;
the page analysis module is used for sequencing the heat of page access by setting a query index and combining the trend graph and the dependence of the user on the application program, finding out the page with the highest heat and deducing the requirement and preference of the user.
Optionally, the system further includes a transaction analysis module, which is configured to obtain transaction statistics of the user, and analyze the health distribution of the transaction according to the transaction statistics.
Optionally, the access distribution analysis module includes a cartesian thermodynamic diagram generation unit for generating a corresponding cartesian thermodynamic diagram according to the total duration, the total number of people and the total number of times that the user accesses and uses the application program.
Optionally, the page analysis module further includes a page statistics unit, and the page statistics unit is configured to perform classification statistics on page access data according to the query index.
Optionally, the page analysis module further includes a sorting unit, and the sorting unit is configured to sort the page access data of the classification statistics by combining the trend graph and the user's dependency on the application program to the heat of accessing the page.
Optionally, the page analysis module further includes a user behavior analysis unit, and the user behavior analysis unit is configured to analyze and judge the requirement and preference of the user according to the number of page visitors, the visiting duration, and the visiting times of the user.
In a second aspect, a method for analyzing user behavior provided in an embodiment of the present invention includes:
acquiring page access data of a user in real time, and obtaining the change condition of the access data according to the page access data;
counting the page access times and the number of functional users according to the core indexes according to the page access data;
analyzing the use trend of the user according to the page access data and the set time and the core index, and generating a corresponding trend graph;
acquiring the total duration of accessing and using the application program by the user, and analyzing the dependence degree of the user on the application program according to the distribution of the number of reuse-removing users in each duration interval;
and sequencing the heat of page access by setting a query index and combining the trend graph and the dependence of the user on the application program, finding out the page with the highest heat, and deducing the requirement and preference of the user.
Optionally, the method further comprises: and acquiring transaction statistics of the user, and analyzing the health distribution condition of the transaction according to the transaction statistics.
Optionally, the specific method for determining the demand and preference of the user by setting the query index, ranking the popularity of the visited pages in combination with the trend graph and the dependency of the user on the application program, finding the page with the highest popularity, and inferring the demand and preference of the user includes: performing classified statistics on page access data according to the query indexes;
sorting the page access data of the classification statistics by combining the trend graph and the dependence of the user on the application program;
and analyzing and judging the requirements and the preferences of the user according to the number of the page visitors, the visiting time and the visiting times of the user.
In a third aspect, the present invention also provides a computer-readable storage medium, in which a computer program is stored, the computer program including program instructions, which, when executed by a processor, cause the processor to execute the method steps described in the above embodiments.
The invention has the beneficial effects that:
according to the user behavior analysis system, the user behavior analysis method and the user behavior analysis medium, the requirement, the use habit and the preference of the user are analyzed by acquiring the data of the page accessed by the user, the auxiliary market operation is facilitated, whether the expected target is achieved or not is judged, the promotion effect and the activity promotion effect are facilitated to be evaluated, the commercial purpose is better achieved, products can be adjusted and optimized according to the requirement, the use habit and the preference of the user, the user experience is improved, and the user viscosity and the page depth are enhanced. And (4) mining preference distribution of the user according to user requirements and preferences, depicting different dimensionality requirements, and promoting final conversion.
Drawings
In order to more clearly illustrate the detailed description of the invention or the technical solutions in the prior art, the drawings that are needed in the detailed description of the invention or the prior art will be briefly described below. Throughout the drawings, like elements or portions are generally identified by like reference numerals. In the drawings, elements or portions are not necessarily drawn to scale.
Fig. 1 is a block diagram illustrating a user behavior analysis system according to a first embodiment of the present invention;
fig. 2 is a flowchart illustrating a user behavior analysis method according to a second embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It is also to be understood that the terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. As used in the specification of the present invention and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.
It should be further understood that the term "and/or" as used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.
As used in this specification and the appended claims, the term "if" may be interpreted contextually as "when", "upon" or "in response to a determination" or "in response to a detection". Similarly, the phrase "if it is determined" or "if a [ described condition or event ] is detected" may be interpreted contextually to mean "upon determining" or "in response to determining" or "upon detecting [ described condition or event ]" or "in response to detecting [ described condition or event ]".
It is to be noted that, unless otherwise specified, technical or scientific terms used herein shall have the ordinary meaning as understood by those skilled in the art to which the invention pertains.
Referring to fig. 1, a user behavior analysis system according to a first embodiment of the present invention includes: a timely statistic module, a key index statistic module, a trend analysis module, an access distribution analysis module and a page analysis module,
the timely counting module is used for acquiring page access data of a user in real time and obtaining the change condition of the access data according to the page access data;
the key index counting module is used for counting the page access times and the number of functional users according to the page access data and the core indexes;
the trend analysis module is used for analyzing the use trend of the user according to the page access data and the set time and the core index and generating a corresponding trend graph;
the access distribution analysis module is used for acquiring the total time length of accessing and using the application program by the user and analyzing the degree of dependence of the user on the application program according to the distribution of the number of the reuse-removing users in each time length interval;
the page analysis module is used for sequencing the heat of page access by setting a query index and combining the trend graph and the dependence of the user on the application program, finding out the page with the highest heat and deducing the requirement and preference of the user.
In the user behavior analysis system of this embodiment, the timely statistics module obtains the user access data in real time, obtains the page access times of the granularity of looking over about one hour and one minute, and timely grasps the change condition of the real-time page access data. The page access data includes: counting the number of users on the same day, the number of page accesses, the total number of people accessed on the same day, the total number of accesses, the number of newly added users on yesterday, the starting time of an application program, user persistence information, page access detail information and the like according to the hour granularity.
The key index counting module counts page access times and number of functional users according to the page access data and core indexes, wherein the core indexes comprise: the number of times of function use, the number of people used, the number of page visits, the average stay time, the stay time of family, the number of active people in 7 days, the number of active people in 30 days, the cumulative number of people used, the cumulative number of times of use, the cumulative number of shared people, the cumulative number of times of sharing, and the like.
And the trend analysis module analyzes the use trend of the user according to the page access data and the set time and the core index to generate a corresponding trend graph. For example: a request to view the 30-day usage of functions is obtained, the 30-day usage of functions is collected and a function usage trend graph is generated using this data. Y-axis of function usage number trend graph: number, X-axis: the date. Such as: acquiring a viewing request of the average residence time trend, extracting an average residence time variation trend graph from the time of the user using the application program, wherein the Y axis of the average residence time variation trend graph is as follows: duration (in milliseconds), X-axis: the date.
And the access distribution analysis module acquires the total time length of the user for accessing and using the application program, and analyzes the degree of dependence of the user on the application program according to the distribution of the number of the reuse-removing users in each time length interval. The stickiness of the user to the application can be analyzed by accessing a distribution analysis module. The access distribution analysis module further comprises a Cartesian thermodynamic diagram generation unit, and the Cartesian thermodynamic diagram generation unit is used for generating corresponding Cartesian thermodynamic diagrams according to the total time, the total number of people and the total times of the users accessing and using the application program. The access depth distribution situation of the user can be visually analyzed through the Cartesian thermodynamic diagram. Such as: according to the set 30 days, collecting the number of people in each page access depth interval to generate a Cartesian thermodynamic diagram, wherein the Y axis of the Cartesian thermodynamic diagram is as follows: depth of access, X-axis: date, interval value: the number of accesses. Collecting the number of times of each page access depth interval according to the set 30 days to generate a Cartesian thermodynamic diagram, wherein the Y axis of the Cartesian thermodynamic diagram is as follows: depth of access, X-axis: date, interval value: the number of visitors. According to the set 30 days, collecting the number of people in each page access time interval to generate a Cartesian thermodynamic diagram, wherein the Y axis of the Cartesian thermodynamic diagram is as follows: depth of access, X-axis: date, interval value: the number of visitors.
And the page analysis module ranks the heat of page access by setting a query index and combining the trend graph and the dependence of the user on the application program, finds out a page with the highest heat and deduces the requirement and preference of the user. The page analysis module comprises a page statistical unit, and the page statistical unit is used for carrying out classification statistics on page access data according to the query indexes; the page analysis module also comprises a sorting unit, and the sorting unit is used for sorting the page access data of the classification statistics by combining the trend graph and the dependency degree of the user on the application program to the heat degree of the access page; the system also comprises a user behavior analysis unit, wherein the user behavior analysis unit is used for analyzing and judging the requirements and the preferences of the user according to the number of the page access people of the user, the access time and the access times. The query indexes comprise: number of visitors, number of visits, number of entrance pages, and per-person dwell time. And analyzing the heat of the user accessing the page according to the indexes in combination with the obtained trend graph and the dependency degree, sequencing according to the heat, finding the page with the highest heat, and deducing the requirement and preference of the user. For example: the method comprises the steps of counting page visit number, entrance page number and per-person stay time data of users in a certain time period, displaying the data in a table after counting, analyzing the heat of a page by combining a generated page visit number trend graph, a generated page per-person stay time trend graph, a generated entrance page visit number trend graph and a generated dependence degree of the users on an application program, and analyzing and judging the demands and the preferences of the users according to the page visit number, the visit time and the visit number of the users.
According to the user behavior analysis system provided by the embodiment, the requirement, the use habit and the preference of the user are analyzed by acquiring the data of the user access page, the auxiliary market operation is facilitated, whether the expected target is achieved or not is judged, the promotion effect of the publicity effect and the activity promotion effect are evaluated, the business purpose is better achieved, the product can be adjusted and optimized according to the requirement, the use habit and the preference of the user, the user experience is improved, and the user viscosity and the page depth are enhanced. And (4) mining preference distribution of the user according to user requirements and preferences, depicting different dimensionality requirements, and promoting final conversion.
In this embodiment, the user behavior analysis system further includes a transaction analysis module, where the transaction analysis module is configured to obtain transaction statistics of the user, and analyze a health distribution condition of the transaction according to the transaction statistics. The transaction analysis module counts the transaction amount of the user, for example: and (3) counting the transaction condition with high accumulated error rate in the last 1 hour, the transaction condition with average consumed time in the last 1 hour and the transaction condition with high accumulated error frequency in the last 1 hour according to the transaction statistics, and analyzing the first ten transaction conditions in the 3 conditions to obtain the transaction health distribution condition. For example: according to the statistical total amount of the transactions in the near 1 hour, the high quality rate (within 1 second), the yield (within 1-3 seconds), the pause rate (within 3-5 seconds) and the deadlock rate (more than 5 seconds) of the transactions are counted. The transaction analysis module also comprises a graph generation unit which is used for generating corresponding graphs for different types of transaction conditions according to the counted transaction conditions, so that the graphs are convenient to check.
In the first embodiment described above, a user behavior analysis system is provided, and correspondingly, the present application also provides a user behavior analysis method. Please refer to fig. 2, which is a flowchart illustrating a user behavior analysis method according to a second embodiment of the present invention. Since the method embodiment is basically similar to the device embodiment, the description is simple, and the relevant points can be referred to the partial description of the device embodiment. The method embodiments described below are merely illustrative.
Referring to fig. 2, a user behavior analysis method according to a second embodiment of the present invention is applicable to the user behavior analysis system according to the above embodiment, and the method includes the following steps:
and S1, acquiring the page access data of the user in real time, and acquiring the change condition of the access data according to the page access data.
Specifically, the page access times of the granularity of about one hour and one minute are obtained and checked, and the real-time page access data change condition is mastered in time. The page access data includes: counting the number of users on the same day, the number of page accesses, the total number of people accessed on the same day, the total number of accesses, the number of newly added users on yesterday, the starting time of an application program, user persistence information, page access detail information and the like according to the hour granularity.
And S2, counting the page access times and the number of functional users according to the core indexes according to the page access data.
Specifically, the page access times and the number of functional users are counted according to the page access data and core indexes, wherein the core indexes comprise: the number of times of function use, the number of people used, the number of page visits, the average stay time, the stay time of family, the number of active people in 7 days, the number of active people in 30 days, the cumulative number of people used, the cumulative number of times of use, the cumulative number of shared people, the cumulative number of times of sharing, and the like.
And S3, analyzing the user use trend according to the set time and the core index according to the page access data, and generating a corresponding trend graph.
Specifically, a request to view the number of function usages for 30 days is acquired, the number of function usages for 30 days is collected, and a function usage trend graph is generated using the data. Y-axis of function usage number trend graph: number, X-axis: the date. Such as: acquiring a viewing request of the average residence time trend, extracting an average residence time variation trend graph from the time of the user using the application program, wherein the Y axis of the average residence time variation trend graph is as follows: duration (in milliseconds), X-axis: the date.
And S4, acquiring the total duration of the user accessing and using the application program, and analyzing the dependence degree of the user on the application program according to the distribution of the reuse removal user number of each duration interval.
And S5, generating a corresponding Cartesian thermodynamic diagram according to the total time, the total number of people and the total times of accessing and using the application program by the user. The access depth distribution situation of the user can be visually analyzed through the Cartesian thermodynamic diagram.
Specifically, according to the set 30 days, the number of people in each page access depth interval is collected to generate a Cartesian thermodynamic diagram, wherein the Y axis of the Cartesian thermodynamic diagram is as follows: depth of access, X-axis: date, interval value: the number of accesses. Collecting the number of times of each page access depth interval according to the set 30 days to generate a Cartesian thermodynamic diagram, wherein the Y axis of the Cartesian thermodynamic diagram is as follows: depth of access, X-axis: date, interval value: the number of visitors. According to the set 30 days, collecting the number of people in each page access time interval to generate a Cartesian thermodynamic diagram, wherein the Y axis of the Cartesian thermodynamic diagram is as follows: depth of access, X-axis: date, interval value: the number of visitors.
And S6, sequencing the heat of page access by setting a query index and combining the trend graph and the dependence of the user on the application program, finding out the page with the highest heat, and deducing the requirement and preference of the user.
Specifically, page access data are classified and counted according to the query indexes; sorting the page access data of the classification statistics by combining the trend graph and the dependence of the user on the application program; and analyzing the requirements and the preferences of the user according to the number of the page visiting persons, the visiting time and the visiting times of the user. For example: the method comprises the steps of counting page visit number, entrance page number and per-person stay time data of users in a certain time period, displaying the data in a table after counting, analyzing the heat of a page by combining a generated page visit number trend graph, a generated page per-person stay time trend graph, a generated entrance page visit number trend graph and a generated dependence degree of the users on an application program, and analyzing and judging the demands and the preferences of the users according to the page visit number, the visit time and the visit number of the users.
And S7, acquiring the transaction statistic of the user, and analyzing the health distribution condition of the transaction according to the transaction statistic.
Specifically, the transaction condition with a high cumulative error rate in the last 1 hour, the transaction condition with a long average time consumption in the last 1 hour and the transaction condition with a large number of cumulative error times in the last 1 hour are counted according to the transaction statistics, and then the first ten transaction conditions are respectively taken from the 3 conditions for analysis to obtain the transaction health distribution condition. For example: according to the statistical total amount of the transactions in the near 1 hour, the high quality rate (within 1 second), the yield (within 1-3 seconds), the pause rate (within 3-5 seconds) and the deadlock rate (more than 5 seconds) of the transactions are counted. And generating a corresponding graph according to the health distribution condition of the transaction.
According to the user behavior analysis method provided by the embodiment, the requirement, the use habit and the preference of the user are analyzed by acquiring the data of the page accessed by the user, so that the auxiliary market operation is facilitated, whether the expected target is achieved or not is judged, the promotion effect and the activity promotion effect are evaluated, the commercial purpose is better achieved, the product can be adjusted and optimized according to the requirement, the use habit and the preference of the user, the user experience is improved, and the user viscosity and the page depth are enhanced. And (4) mining preference distribution of the user according to user requirements and preferences, depicting different dimensionality requirements, and promoting final conversion.
A third embodiment of the present invention provides a computer-readable storage medium, which stores a computer program comprising program instructions that, when executed by a processor, cause the processor to perform the method described in the second embodiment above.
The computer readable storage medium may be an internal storage unit of the terminal described in the foregoing embodiment, for example, a hard disk or a memory of the terminal. The computer readable storage medium may also be an external storage device of the terminal, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the terminal. Further, the computer-readable storage medium may also include both an internal storage unit and an external storage device of the terminal. The computer-readable storage medium is used for storing the computer program and other programs and data required by the terminal. The computer readable storage medium may also be used to temporarily store data that has been output or is to be output.
Those of ordinary skill in the art will appreciate that the elements and algorithm steps of the examples described in connection with the embodiments disclosed herein may be embodied in electronic hardware, computer software, or combinations of both, and that the components and steps of the examples have been described in a functional general in the foregoing description for the purpose of illustrating clearly the interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the implementation. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working processes of the terminal and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed terminal and method can be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may also be an electric, mechanical or other form of connection.
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; such modifications and substitutions do not depart from the spirit and scope of the present invention, and they should be construed as being included in the following claims and description.
Claims (10)
1. A user behavior analysis system, comprising: a timely statistic module, a key index statistic module, a trend analysis module, an access distribution analysis module and a page analysis module,
the timely counting module is used for acquiring page access data of a user in real time and obtaining the change condition of the access data according to the page access data;
the key index counting module is used for counting the page access times and the number of functional users according to the page access data and the core indexes;
the trend analysis module is used for analyzing the use trend of the user according to the page access data and the set time and the core index and generating a corresponding trend graph;
the access distribution analysis module is used for acquiring the total time length of accessing and using the application program by the user and analyzing the degree of dependence of the user on the application program according to the distribution of the number of the reuse-removing users in each time length interval;
the page analysis module is used for sequencing the heat of page access by setting a query index and combining the trend graph and the dependence of the user on the application program, finding out the page with the highest heat and deducing the requirement and preference of the user.
2. The user behavior analysis system of claim 1, further comprising a transaction analysis module to obtain transaction statistics of the user and to analyze the health profile of the transaction based on the transaction statistics.
3. The user behavior analysis system of claim 1, wherein the access distribution analysis module comprises a cartesian thermodynamic diagram generation unit for generating respective cartesian thermodynamic diagrams according to a total duration, a total number of people, and a total number of times users access and use an application.
4. The user behavior analysis system according to any one of claims 1 to 3, wherein the page analysis module further comprises a page statistics unit for performing a classification statistics on page access data according to the query index.
5. The user behavior analysis system of claim 4, the page analysis module further comprising a ranking unit to rank the page visit data of the classification statistics in combination with a trend graph and the user's dependencies on the application to rank the heat of visiting pages.
6. The user behavior analysis system according to claim 5, wherein the page analysis module further comprises a user behavior analysis unit for analyzing and judging the needs and preferences of the user according to the number of page visitors, the visiting duration, and the visiting times of the user.
7. A user behavior analysis method is characterized by comprising the following steps:
acquiring page access data of a user in real time, and obtaining the change condition of the access data according to the page access data;
counting the page access times and the number of functional users according to the core indexes according to the page access data;
analyzing the use trend of the user according to the page access data and the set time and the core index, and generating a corresponding trend graph;
acquiring the total duration of accessing and using the application program by the user, and analyzing the dependence degree of the user on the application program according to the distribution of the number of reuse-removing users in each duration interval;
and sequencing the heat of page access by setting a query index and combining the trend graph and the dependence of the user on the application program, finding out the page with the highest heat, and deducing the requirement and preference of the user.
8. The user behavior analysis method of claim 7, the method further comprising: and acquiring transaction statistics of the user, and analyzing the health distribution condition of the transaction according to the transaction statistics.
9. The method of claim 7, wherein the specific method of determining the user's needs and preferences by setting query metrics, ranking the popularity of pages visited by combining the trend graph and the user's dependency on applications, finding the page with the highest popularity, and then inferring the user's needs and preferences comprises: performing classified statistics on page access data according to the query indexes;
sorting the page access data of the classification statistics by combining the trend graph and the dependence of the user on the application program;
and analyzing and judging the requirements and the preferences of the user according to the number of the page visitors, the visiting time and the visiting times of the user.
10. A computer-readable storage medium, characterized in that the computer storage medium stores a computer program comprising program instructions that, when executed by a processor, cause the processor to perform the method according to any of claims 7-9.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111768274A (en) * | 2020-06-24 | 2020-10-13 | 中国地质大学（武汉） | Data classification storage system based on artificial intelligence |
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