Online activity promotion system based on user behavior analysis and data driving

Abstract

The invention discloses an online activity promotion system based on user behavior analysis and data driving. The system comprises a data acquisition module; a data storage module; the data preprocessing module is used for periodically collecting materials browsed by a single user based on material content keywords; the data analysis module is used for judging whether the pushing of the single material content area meets a second preset standard or not according to a browsing weight coefficient when the pushing of the single material content area is preliminarily judged to meet a first preset standard according to the browsing duration ratio of the material content area; when the browsing driving coefficient is smaller than a second preset driving coefficient, it is judged that pushing of the materials for the user does not conform to a third preset standard, and when the pushing of the materials for the user does not conform to the third preset standard, pushing of the materials for the user is initialized according to an equal proportion mode; and the data verification module is used for reducing the duration of a period for collecting the materials browsed by the user. The accurate popularization of the online activity materials is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of promotion, and in particular relates to an online activity promotion system based on user behavior analysis and data-driven. Background Art

[0002] User behavior analysis refers to the statistics, analysis and mining of basic data on website, APP or other Internet product visits, in order to discover the behavioral patterns, preferences and potential needs of users in the process of using the product, and use this as a basis for efficient information push and target marketing. However, the potential user behavior of users is generally real-time. How to accurately capture the real-time user consumption needs is the key to promoting online activities.

[0003] Chinese patent publication number: CN115239442A, discloses a method, system and storage medium for promoting Internet financial products, which involves Internet technology, and the method includes: constructing a financial delivery strategy under a real-time application program interface according to the financial characteristics under the delivery scenario; matching each financial delivery strategy with the user configuration data information in the application platform one by one, matching the corresponding financial delivery strategy for the customer to be delivered; pushing financial promotion information to the matched user according to the financial delivery strategy; calculating the relationship strength value of the financial promotion information to the first user based on the user behavior information; establishing an Internet financial product recommendation set according to the relationship strength value; and recommending Internet financial products to the first user using the Internet financial product recommendation set. However, the above-mentioned prior art cannot intelligently adjust and push in real time. Summary of the invention

[0004] To this end, the present invention provides a function for overcoming the lack of intelligent real-time adjustment of the push mode in the prior art.

[0005] To achieve the above objectives, the present invention provides an online activity promotion system based on user behavior analysis and data-driven, comprising:

[0006] A data collection module, which is used to obtain the historical browsing data of a single user within a preset period of time, wherein the historical browsing data includes the browsed materials, the duration of each material, the browsing duration of each material, and the search keywords;

[0007] A data storage module, which is connected to the data acquisition module and includes a first storage unit for storing pushed materials and a second storage unit for storing historical browsing data of users;

[0008] A data preprocessing module, which is connected to the data storage module, is used to periodically group the materials browsed by a single user according to the material content keywords to form a number of material content areas and sort the material content areas in descending order according to the browsing time ratio of each material content area;

[0009] a data analysis module, which is connected to the data acquisition module and the data preprocessing module respectively, and is used to preliminarily determine whether the push of a single material content area meets the first preset standard according to the browsing time ratio of the material content area, and determine whether the push of the single material content area meets the second preset standard according to the browsing weight coefficient when the first preset standard is met;

[0010] A data verification module is connected to the data analysis module. In response to a browsing drive coefficient being less than a second preset browsing drive coefficient, the module determines that the push of the material to the user does not meet a third preset standard and, when the third preset standard is not met, initializes the push of the material to the user in a proportional manner, or reduces the duration of the period for grouping the material browsed by the user.

[0011] Furthermore, in response to the browsing time ratio being less than a preset ratio threshold, the data analysis module preliminarily determines that the push of a single material content area does not meet a first preset standard, and stops pushing the material corresponding to the material content area.

[0012] Furthermore, the data analysis module determines whether the push of a single material content area meets a second preset standard according to the browsing weight coefficient, wherein:

[0013] If the browsing weight coefficient is less than the first preset weight coefficient, the data analysis module determines that the push of the material content area does not meet the second preset standard, and reduces the push amount of the material corresponding to the material content area according to the difference between the first preset weight coefficient and the browsing weight coefficient;

[0014] If the browsing weight coefficient is greater than or equal to the first preset weight coefficient and less than the second preset weight coefficient, the data analysis module determines that the push of the material content area does not meet the second preset standard, and verifies the push mode of the single material content area according to the search frequency of the associated search keyword within the preset time period;

[0015] If the browsing weight coefficient is greater than or equal to the second preset weight coefficient, the data analysis module determines that the push of the material content area meets the second preset standard, and increases the push amount of the material corresponding to the material content area according to the difference between the browsing weight coefficient and the second preset weight coefficient.

[0016] Furthermore, the browsing weight coefficient is an average value of the ratio of the browsing time of each material in a single material content area to the material time.

[0017] Furthermore, the data analysis module is provided with several push amount adjustment methods for increasing the push amount of the material, and each push amount adjustment method has a different increase range of the push amount of the material corresponding to a single material content area.

[0018] Furthermore, the data analysis module is provided with several push amount correction methods for reducing the push amount of the material under the first preset condition, and each push amount correction method has a different correction range for the push amount of the material corresponding to a single material content area; the first preset condition is that the data analysis module completes the adjustment of increasing the push amount of the material and after the adjustment, the average browsing time of the material in the material content area is less than the preset browsing time threshold.

[0019] Furthermore, the data analysis module verifies the push mode of a single material content area according to the search frequency of the associated search keyword within a preset period, wherein:

[0020] If the search frequency is less than the preset search frequency, the data analysis module does not adjust the push of the material content area;

[0021] If the search frequency is greater than or equal to the preset search frequency, the data analysis module performs associated search keyword screening on the pushed material stored in the first storage unit and then pushes the material content area.

[0022] Furthermore, the data verification module determines whether the push of the material to the user meets a third preset standard according to the browsing driving coefficient, wherein:

[0023] If the browsing driving coefficient is less than the first preset browsing driving coefficient, the data verification module determines that the push of the material for the user does not meet the third preset standard and initializes the push of the material for the user in the equal proportion manner;

[0024] If the browsing drive coefficient is greater than or equal to the first preset browsing drive coefficient and less than the second preset browsing drive coefficient, the data verification module determines that the push of the material for the user does not meet the third preset standard and reduces the duration of the period for grouping the materials browsed by the user according to the difference between the browsing drive coefficient and the first preset browsing drive coefficient;

[0025] If the browsing driving coefficient is greater than or equal to the second preset browsing driving coefficient, the data verification module determines that the push of the material to the user meets the third preset standard and continues to push according to the current push parameters.

[0026] Furthermore, the browsing driving coefficient is determined by browsing frequency, single browsing duration and browsing completeness ratio.

[0027] Furthermore, the reduction range of the duration of the aggregated period is negatively correlated with the browsing drive coefficient difference, wherein the browsing drive coefficient difference is the difference between the browsing drive coefficient and the first preset browsing drive coefficient.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] The present invention obtains the historical browsing data of a single user within a preset time period for subsequent data analysis and push strategy adjustment by setting a data acquisition module, collects and processes the pushed materials based on material content keywords and browsing time ratio by setting a data preprocessing module, preliminarily verifies the push mode based on the browsing time ratio of the material content area by the data analysis module, and adjusts the material push mode based on the browsing drive coefficient by the data verification module, thereby realizing the precise promotion of online activity materials.

[0030] Furthermore, the present invention preliminarily determines that the push of a single material content area does not meet the first preset standard in response to the browsing time ratio being less than a preset ratio threshold through the data analysis module, and stops pushing the material corresponding to the material content area, thereby improving the user's material browsing experience.

[0031] Furthermore, the present invention determines whether the push of the single material content area meets the preset push standard according to the browsing weight coefficient through the data analysis module, thereby improving the efficiency of material push.

[0032] Furthermore, the present invention realizes objective evaluation of browsing effect by setting browsing weight coefficient.

[0033] Furthermore, the present invention is provided with several push amount adjustment methods for increasing the push amount of the material through the data analysis module, and each push amount adjustment method has a different increase in the push amount of the material corresponding to a single material content area, thereby realizing precise control of the increase in the material push amount.

[0034] Furthermore, the present invention sets several push amount correction methods for reducing the push amount of the material under the first preset condition through the data analysis module, and each push amount correction method has a different correction range for the push amount of the material corresponding to a single material content area; the first preset condition is that the data analysis module completes the adjustment of increasing the push amount of the material and after the adjustment, the average browsing time of the material in the material content area is less than the preset browsing time threshold, thereby optimizing the deviation of the material push.

[0035] Furthermore, the present invention verifies the push mode of a single material content area according to the search frequency of the associated search keyword in a preset time period through the data analysis module, thereby realizing dynamic adjustment of the promotion mode.

[0036] Furthermore, the present invention achieves precise control of the reduction amplitude of the aggregated period length by setting a negative correlation between the reduction amplitude of the aggregated period length and the browsing drive coefficient difference, wherein the browsing drive coefficient difference is the difference between the browsing drive coefficient and the first preset browsing drive coefficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0038] Figure 1 A schematic diagram of the structure of an online activity promotion system based on user behavior analysis and data-driven provided by an embodiment of the present invention;

[0039] Figure 2 A schematic diagram of a flow chart for determining whether the push of a single material content area meets a preset standard provided by an embodiment of the present invention;

[0040] Figure 3 A schematic diagram of a process for verifying a push method for a single material content area provided by an embodiment of the present invention;

[0041] Figure 4 A schematic diagram of a flow chart for determining whether the push of material to the user meets a preset standard is provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0042] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0043] Those skilled in the art will appreciate that the system of the present invention may determine a single parameter by selecting the value with the highest proportion as the preset standard parameter based on data distribution, using weighted summation to take the obtained value as the preset standard parameter, substituting each historical data into a specific formula and taking the value obtained by using the formula as the preset standard parameter, or other selection methods, as long as the system of the present invention can clearly define different specific situations in a single determination process through the obtained values.

[0044] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention. Figure 1 , Figure 2 , Figure 3 as well as Figure 4 As shown, they are respectively a structural diagram of an online activity promotion system based on user behavior analysis and data-driven according to an embodiment of the present invention; a flowchart of an embodiment of the present invention for determining whether the push of a single material content area meets the preset standard; a flowchart of an embodiment of the present invention for verifying the push method of a single material content area; and a flowchart of an embodiment of the present invention for determining whether the push of the material for the user meets the preset standard.

[0045] Combination Figure 1 As shown, Embodiment 1 of the present invention provides an online activity promotion system based on user behavior analysis and data-driven, including:

[0046] A data collection module, which is used to obtain the historical browsing data of a single user within a preset period of time, wherein the historical browsing data includes the browsed materials, the duration of each material, the browsing duration of each material, and the search keywords;

[0047] A data storage module, which is connected to the data acquisition module and includes a first storage unit for storing pushed materials and a second storage unit for storing historical browsing data of users;

[0048] A data preprocessing module, which is connected to the data storage module, is used to periodically group the materials browsed by a single user according to the material content keywords to form a number of material content areas and sort the material content areas in descending order according to the browsing time ratio of each material content area;

[0049] a data analysis module, which is connected to the data acquisition module and the data preprocessing module respectively, and is used to preliminarily determine whether the push of a single material content area meets the first preset standard according to the browsing time ratio of the material content area, and determine whether the push of the single material content area meets the second preset standard according to the browsing weight coefficient when the first preset standard is met;

[0050] A data verification module is connected to the data analysis module. In response to a browsing drive coefficient being less than a second preset browsing drive coefficient, the module determines that the push of the material to the user does not meet a third preset standard and, when the third preset standard is not met, initializes the push of the material to the user in a proportional manner, or reduces the duration of the period for grouping the material browsed by the user.

[0051] Specifically, the user's historical browsing data has been collected with the user's permission.

[0052] In response to the browsing time ratio being less than the preset ratio threshold of 0.23, the data analysis module preliminarily determines that the push of a single material content area does not meet the first preset standard, and stops pushing the material corresponding to the material content area, wherein the browsing time ratio is the percentage of the browsing time of a single material content area to the browsing time of all material content areas. By judging the browsing time ratio, it is possible to judge whether the user is interested in a single material content area, and to perform subsequent push based on interest, which can help with subsequent precise promotion and further improve the user experience.

[0053] Specifically, combined Figure 2 As shown, the data analysis module determines whether the push of a single material content area meets the second preset standard according to the browsing weight coefficient, wherein:

[0054] If the browsing weight coefficient is less than the first preset weight coefficient, the data analysis module determines that the push of the material content area does not meet the second preset standard, and reduces the push amount of the material corresponding to the material content area according to the difference between the first preset weight coefficient and the browsing weight coefficient;

[0055] If the browsing weight coefficient is greater than or equal to the first preset weight coefficient and less than the second preset weight coefficient, the data analysis module determines that the push of the material content area does not meet the second preset standard, and verifies the push mode of the single material content area according to the search frequency of the associated search keyword within the preset time period of 40 minutes;

[0056] If the browsing weight coefficient is greater than or equal to the second preset weight coefficient, the data analysis module determines that the push of the material content area meets the second preset standard, and increases the push amount of the material corresponding to the material content area according to the difference between the browsing weight coefficient and the second preset weight coefficient.

[0057] By judging whether the browsing weight meets the second preset standard, it is possible to check whether the materials in the content area pushed under the condition that the user is interested in the material content area meet the user's needs, and make adaptive adjustments to improve the promotion accuracy.

[0058] Optionally, the first preset weight coefficient is set to 0.35, and the second preset weight coefficient is set to 0.46.

[0059] Specifically, the browsing weight coefficient is an average value of the ratio of the browsing time of each material in a single material content area to the material time.

[0060] Specifically, the data analysis module is provided with several push amount adjustment methods for increasing the push amount of the material, and each push amount adjustment method increases the push amount of the material corresponding to a single material content area by a different amount.

[0061] If the browsing weight difference is less than the first preset browsing weight difference of 0.148, the data analysis module uses the first preset material push amount adjustment coefficient of 1.08 to increase the push amount of the material, and if the increased push amount of the material is not an integer, it is rounded up;

[0062] If the browsing weight difference is greater than or equal to the first preset browsing weight difference and less than the second preset browsing weight difference of 0.345, the data analysis module uses the second preset material push amount adjustment coefficient of 1.12 to increase the push amount of the material, and if the increased push amount of the material is not an integer, it is rounded up;

[0063] If the browsing weight difference is greater than or equal to the second preset browsing weight difference, the data analysis module uses the third preset material push amount adjustment coefficient 1.31 to increase the push amount of the material, and if the increased push amount of the material is not an integer, it is rounded up;

[0064] The browsing weight difference is the difference between the browsing weight coefficient and the second preset weight coefficient. The first preset material push amount adjustment coefficient is less than the second preset material push amount adjustment coefficient. Specifically, the data analysis module is provided with several push amount correction methods for reducing the push amount of the material under the first preset condition, and each push amount correction method has a different correction range for the push amount of the material corresponding to a single material content area.

[0065] If the browsing time difference is less than the first preset browsing time difference of 1.42 minutes, the data analysis module uses the first correction coefficient 0.98 to correct the push amount of the material, and if the corrected push amount of the material is not an integer, it is rounded up;

[0066] If the browsing time evaluation value is greater than or equal to the first preset browsing time difference and less than the second preset browsing time difference of 3.23min, the data analysis module uses the second correction coefficient 0.97 to correct the push amount of the material, and if the corrected push amount of the material is not an integer, it is rounded up;

[0067] If the browsing time difference is greater than or equal to the second preset browsing time difference, the data analysis module uses a third correction coefficient of 0.96 to correct the push amount of the material, and if the corrected push amount of the material is not an integer, it is rounded up;

[0068] The first preset condition is that the data analysis module completes the adjustment of increasing the push amount of the material and the average browsing time of the material in the material content area after the adjustment is less than the preset browsing time threshold of 6 minutes;

[0069] The browsing time difference is the difference between the preset browsing time threshold and the average browsing time of the material in the material content area after the adjustment of the increase in the push amount of the completed material.

[0070] Among them, the first correction coefficient>the second correction coefficient>the third correction coefficient.

[0071] Specifically, combined Figure 3 As shown, the data analysis module verifies the push mode of a single material content area according to the search frequency of the associated search keyword within a preset time period, wherein:

[0072] If the search frequency is less than the preset search frequency, the data analysis module does not adjust the push of the material content area;

[0073] If the search frequency is greater than or equal to the preset search frequency, the data analysis module performs associated search keyword screening on the pushed material stored in the first storage unit and pushes the material content area;

[0074] Among them, the preset retrieval frequency can be set to 3 times / hour.

[0075] Specifically, the associated search keyword is the search term entered by the user. For example, if the user enters "Peking Opera" or "Mei Lanfang", the associated search keyword filter uses "Peking Opera" or "Mei Lanfang" to filter the pushed materials stored in the first storage unit and then push them to the material content area.

[0076] Specifically, combined Figure 4 As shown, the data verification module determines whether the push of the material for the user meets the third preset standard according to the browsing driving coefficient, wherein:

[0077] If the browsing driving coefficient is less than the first preset browsing driving coefficient, the data verification module determines that the push of the material for the user does not meet the third preset standard and initializes the push of the material for the user in the equal proportion manner;

[0078] If the browsing drive coefficient is greater than or equal to the first preset browsing drive coefficient and less than the second preset browsing drive coefficient, the data verification module determines that the push of the material for the user does not meet the third preset standard and reduces the duration of the period for grouping the materials browsed by the user according to the difference between the browsing drive coefficient and the first preset browsing drive coefficient;

[0079] If the browsing driving coefficient is greater than or equal to the second preset browsing driving coefficient, the data verification module determines that the push of the material to the user meets the third preset standard and continues to push according to the current push parameters.

[0080] The browsing drive coefficient can detect whether the materials that users are interested in have changed, and can update the material content area in real time to attract users or change the push method, thereby further realizing precise promotion.

[0081] It can be understood that initializing the push of the user's material in an equal proportion manner is to randomly push the material stored in the first storage unit to the user;

[0082] Among them, the first preset browsing driving coefficient is set to 0.723; the second preset browsing driving coefficient is set to 0.864.

[0083] Optionally, the browsing driving coefficient is determined by browsing frequency, single browsing duration and browsing completeness ratio.

[0084] Specifically, the browsing driving coefficient is calculated by the following formula:

[0085]

[0086] In the formula, A represents the browsing driving coefficient; F represents the browsing frequency of a single user within the preset time period of 50 minutes; F0 represents the preset user browsing frequency, and F0 can be taken as 4 times / 50 minutes; T represents the single browsing duration; T0 represents the preset single browsing duration, and T0 can be taken as 2 hours; C represents the number of complete browsing materials of a single user within the preset time period; C0 represents the number of browsing materials of a single user within the preset time period of 50 minutes, and C0 can be taken as 4; α represents the browsing frequency influence coefficient, which is set to α=0.25; β represents the browsing duration influence coefficient, which is set to β=0.47; η represents the browsing material quantity influence coefficient, which is set to η=0.28.

[0087] Optionally, the reduction range of the duration of the aggregated period is negatively correlated with a browsing drive coefficient difference, wherein the browsing drive coefficient difference is a difference between the browsing drive coefficient and the first preset browsing drive coefficient.

[0088] It can be understood that the greater the difference in browsing drive coefficients, the smaller the reduction in the duration of the aggregated period. The negative correlation can be a linear negative correlation or a nonlinear negative correlation, wherein the slope of the linear negative correlation is not limited.

[0089] Compared with the prior art, the present invention has the following beneficial effects:

[0090] The present invention obtains the historical browsing data of a single user within a preset time period for subsequent data analysis and push strategy adjustment by setting a data acquisition module, collects and processes the pushed materials based on material content keywords and browsing time ratio by setting a data preprocessing module, preliminarily verifies the push mode based on the browsing time ratio of the material content area by the data analysis module, and adjusts the material push mode based on the browsing drive coefficient by the data verification module, thereby realizing the precise promotion of online activity materials.

[0091] Furthermore, the present invention preliminarily determines that the push of a single material content area does not meet the first preset standard in response to the browsing time ratio being less than a preset ratio threshold through the data analysis module, and stops pushing the material corresponding to the material content area, thereby improving the user's material browsing experience.

[0092] Furthermore, the present invention determines whether the push of the single material content area meets the preset push standard according to the browsing weight coefficient through the data analysis module, thereby improving the efficiency of material push.

[0093] Furthermore, the present invention realizes objective evaluation of browsing effect by setting browsing weight coefficient.

[0094] Furthermore, the present invention is provided with several push amount adjustment methods for increasing the push amount of the material through the data analysis module, and each push amount adjustment method has a different increase in the push amount of the material corresponding to a single material content area, thereby realizing precise control of the increase in the material push amount.

[0095] Furthermore, the present invention sets several push amount correction methods for reducing the push amount of the material under the first preset condition through the data analysis module, and each push amount correction method has a different correction range for the push amount of the material corresponding to a single material content area; the first preset condition is that the data analysis module completes the adjustment of increasing the push amount of the material and after the adjustment, the average browsing time of the material in the material content area is less than the preset browsing time threshold, thereby optimizing the deviation of the material push.

[0096] Furthermore, the present invention verifies the push mode of a single material content area according to the search frequency of the associated search keyword in a preset time period through the data analysis module, thereby realizing dynamic adjustment of the promotion mode.

[0097] Furthermore, the present invention achieves precise control of the reduction amplitude of the aggregated period length by setting a negative correlation between the reduction amplitude of the aggregated period length and the browsing drive coefficient difference, wherein the browsing drive coefficient difference is the difference between the browsing drive coefficient and the first preset browsing drive coefficient.

[0098] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0099] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An online activity promotion system based on user behavior analysis and data-driven, characterized in that: include: A data collection module, which is used to obtain the historical browsing data of a single user within a preset period of time, wherein the historical browsing data includes the browsed materials, the duration of each material, the browsing duration of each material, and the search keywords; A data storage module, which is connected to the data acquisition module and includes a first storage unit for storing pushed materials and a second storage unit for storing historical browsing data of users; A data preprocessing module, which is connected to the data storage module, is used to periodically group the materials browsed by a single user according to the material content keywords to form a number of material content areas and sort the material content areas in descending order according to the browsing time ratio of each material content area; a data analysis module, which is connected to the data acquisition module and the data preprocessing module respectively, and is used to preliminarily determine whether the push of a single material content area meets the first preset standard according to the browsing time ratio of the material content area, and determine whether the push of the single material content area meets the second preset standard according to the browsing weight coefficient when the first preset standard is met; A data verification module is connected to the data analysis module. In response to a browsing drive coefficient being less than a second preset browsing drive coefficient, the module determines that the push of the material to the user does not meet a third preset standard and, when the third preset standard is not met, initializes the push of the material to the user in a proportional manner, or reduces the duration of the period for grouping the material browsed by the user.

2. The online activity promotion system based on user behavior analysis and data-driven according to claim 1 is characterized in that: In response to the browsing time ratio being less than a preset ratio threshold, the data analysis module preliminarily determines that the push of a single material content area does not meet a first preset standard, and stops pushing the material corresponding to the material content area.

3. The online activity promotion system based on user behavior analysis and data-driven according to claim 2 is characterized in that: The data analysis module determines whether the push of a single material content area meets the second preset standard according to the browsing weight coefficient, wherein: If the browsing weight coefficient is less than the first preset weight coefficient, the data analysis module determines that the push of the material content area does not meet the second preset standard, and reduces the push amount of the material corresponding to the material content area according to the difference between the first preset weight coefficient and the browsing weight coefficient; If the browsing weight coefficient is greater than or equal to the first preset weight coefficient and less than the second preset weight coefficient, the data analysis module determines that the push of the material content area does not meet the second preset standard, and verifies the push mode of the single material content area according to the search frequency of the associated search keyword within the preset time period; If the browsing weight coefficient is greater than or equal to the second preset weight coefficient, the data analysis module determines that the push of the material content area meets the second preset standard, and increases the push amount of the material corresponding to the material content area according to the difference between the browsing weight coefficient and the second preset weight coefficient.

4. The online activity promotion system based on user behavior analysis and data-driven according to claim 3 is characterized in that: The browsing weight coefficient is an average value of the ratio of the browsing time of each material in a single material content area to the material time.

5. The online activity promotion system based on user behavior analysis and data-driven according to claim 4 is characterized in that: The data analysis module is provided with several push amount adjustment methods for increasing the push amount of the material, and each push amount adjustment method has a different increase range of the push amount of the material corresponding to a single material content area.

6. The online activity promotion system based on user behavior analysis and data-driven according to claim 5 is characterized in that: The data analysis module is provided with several push amount correction methods for reducing the push amount of the material under the first preset condition, and each push amount correction method has a different correction range for the push amount of the material corresponding to a single material content area; the first preset condition is that the data analysis module completes the adjustment of increasing the push amount of the material and after the adjustment, the average browsing time of the material in the material content area is less than the preset browsing time threshold.

7. The online activity promotion system based on user behavior analysis and data-driven according to claim 6, characterized in that: The data analysis module verifies the push mode of a single material content area according to the search frequency of the associated search keyword within a preset period, wherein: If the search frequency is less than the preset search frequency, the data analysis module does not adjust the push of the material content area; If the search frequency is greater than or equal to the preset search frequency, the data analysis module performs associated search keyword screening on the pushed material stored in the first storage unit and then pushes the material content area.

8. The online activity promotion system based on user behavior analysis and data-driven according to any one of claims 1 to 7, characterized in that: The data verification module determines whether the push of the material to the user meets a third preset standard according to the browsing driving coefficient, wherein: If the browsing driving coefficient is less than the first preset browsing driving coefficient, the data verification module determines that the push of the material for the user does not meet the third preset standard and initializes the push of the material for the user in the equal proportion manner; If the browsing drive coefficient is greater than or equal to the first preset browsing drive coefficient and less than the second preset browsing drive coefficient, the data verification module determines that the push of the material for the user does not meet the third preset standard and reduces the duration of the period for grouping the materials browsed by the user according to the difference between the browsing drive coefficient and the first preset browsing drive coefficient; If the browsing driving coefficient is greater than or equal to the second preset browsing driving coefficient, the data verification module determines that the push of the material to the user meets the third preset standard and continues to push according to the current push parameters.

9. The online activity promotion system based on user behavior analysis and data-driven according to claim 8, characterized in that: The browsing driving coefficient is determined by browsing frequency, single browsing duration and browsing completeness ratio.

10. The online activity promotion system based on user behavior analysis and data-driven according to claim 9, characterized in that: The reduction range of the duration of the aggregated period is negatively correlated with the browsing drive coefficient difference, wherein the browsing drive coefficient difference is the difference between the browsing drive coefficient and the first preset browsing drive coefficient.

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