User promotion system based on big data

Abstract

The invention discloses a user promotion system based on big data, and relates to the technical field of big data promotion, in particular to a user promotion system based on big data, which comprises a user database, and the input end of the user database is electrically connected with a data analysis module. The input end of the data analysis module is electrically connected with user browsing data acquisition; the output end of the user database is electrically connected with a promotion module, and the input end of the user database is further connected with a data mining module; the input end of the data mining module is electrically connected with a user manager, and the input end of the data mining module is also connected with a promotion data feedback. According to the user promotion system based on the big data, browsing data of old users can be collected, new customers can be expanded, the system is divided into online promotion and offline promotion so as to increase the promotion coverage, and meanwhile, user data in the promotion process is collected so as to adjust the promotion direction in real time.

Description

Technical Field

[0001] The present invention relates to the technical field of big data promotion, and in particular to a user promotion system based on big data. Background Art

[0002] Big data is a collection of data with large capacity, multiple types, fast access speed and high application value as its main features. It was first applied in the IT industry and is currently developing rapidly into a new generation of information technology and service formats that collects, stores and analyzes huge amounts of data from scattered sources and in various formats, thereby discovering new knowledge, creating new value and improving new capabilities. Big data must adopt a distributed architecture to conduct distributed data mining on massive data, so it must rely on distributed processing, distributed databases and cloud storage, and virtualization technologies of cloud computing.

[0003] Big data refers to a collection of data that cannot be captured, managed, and processed by conventional software tools within a certain period of time. It is a massive, high-growth, and diversified information asset that requires a new processing model to have stronger decision-making, insight, and process optimization capabilities.

[0004] The strategic significance of big data technology lies not in mastering huge amounts of data information, but in professionally processing these meaningful data. In other words, if big data is compared to an industry, the key to profitability in this industry lies in improving the "processing capacity" of data and achieving "value-added" of data through "processing". Technically speaking, the relationship between big data and cloud computing is as inseparable as the front and back of a coin. Big data cannot be processed by a single computer, and a distributed architecture must be adopted. Its characteristic lies in the distributed data mining of the sea of ​​data. But it must rely on cloud computing distributed processing, distributed databases, cloud storage and virtualization technologies.

[0005] Through website link exchange, advertisement exchange, content cooperation, user resource cooperation and other methods, the purpose of mutual promotion can be achieved between websites with similar goals. The most commonly used resource cooperation method is the website link strategy, which utilizes the website traffic resource cooperation between partners to promote each other.

[0006] Each corporate website can have its own resources, which can be expressed as a certain amount of visits, registered user information, valuable content and functions, online advertising space, etc. The website resources can be used to cooperate with partners to achieve resource sharing and jointly expand the purpose of revenue. Among these forms of resource cooperation, link exchange is the simplest form of cooperation. According to surveys, it is also one of the effective ways to promote new websites. Link exchange, or reciprocal link exchange, is a simple form of cooperation between websites with certain complementary advantages, that is, placing the logo or website name of the other party's website on their own websites and setting up hyperlinks to the other party's website, so that users can find their own websites from the cooperative websites and achieve the purpose of mutual promotion. The role of link exchange is mainly manifested in several aspects: obtaining visits, increasing the impression of users when browsing, increasing advantages in search engine rankings, and increasing the credibility of visitors through the recommendation of cooperative websites. Link exchange also has a deeper meaning than whether it can achieve direct results. Generally speaking, each website tends to link to other websites with high value, so obtaining links from other websites means obtaining recognition from partners and similar websites in a field.

[0007] The existing patent (publication number: CN113360750A) discloses a promotion system and method based on big data analysis, which relates to the field of promotion technology, including: a data collection unit, which is used to collect behavioral big data generated by user terminals browsing web pages, and the behavioral big data includes: commented web page content data, self-comment data, liked comment data and clicked comment data; a data analysis unit: used to store the behavioral big data, and analyze the behavioral big data to obtain a user portrait that represents the user's behavioral habits; a promotion unit, which is used to obtain website content with a correlation degree of the user portrait reaching a specific threshold, and push the website content to the user terminal; ensure that the push result is more accurate, and push through big data analysis can improve the accuracy of push. However, the existing ones cannot meet people's usage needs well. Summary of the invention

[0008] In view of the deficiencies in the prior art, the present invention provides a user promotion system based on big data, which solves the problems xx and other problems raised in the above background technology.

[0009] To achieve the above objectives, the present invention is implemented through the following technical solutions: A user promotion system based on big data, including a user database, an input end of the user database is electrically connected to a data analysis module, and an input end of the data analysis module is electrically connected to a user browsing data collection;

[0010] The output end of the user database is electrically connected to a promotion module, and the input end of the user database is also connected to a data mining module;

[0011] The input end of the data mining module is electrically connected to the user management, and the input end of the data mining module is also connected to the promotion data feedback;

[0012] The output end of the data mining module is electrically connected in series with the input end of the promotion module.

[0013] Optionally, the user browsing data collection, data analysis module, user database and promotion module are electrically connected in series.

[0014] Optionally, the promotion module, promotion data feedback and data mining module are electrically connected in series, and the output end of the data mining module is electrically connected in series with the user database and the input end of the promotion module respectively.

[0015] Optionally, the user browsing data collection further includes a cache tool, a flow collector and a log file, and the cache tool, the flow collector and the log file are electrically connected in parallel;

[0016] The cache tool, the flow collector and the log file are all electrically connected in series with the input end of the data analysis module.

[0017] Optionally, the data parsing module further includes a rule configuration, a parser and a preprocessor, and the rule configuration, the parser and the preprocessor are electrically connected in parallel.

[0018] Optionally, the user database is composed of a single recording unit, a repeated recording unit, a data duplication judgment unit and a data backup unit;

[0019] The input end of the single recording unit is electrically connected in series with the data analysis module, the output end of the single recording unit is connected with the repeat recording unit, the output end of the repeat recording unit is connected with the data duplication judgment unit, and the single recording unit is electrically connected with the data backup unit;

[0020] The output end of the data backup unit is electrically connected in series with the input end of the data duplication determination unit.

[0021] Optionally, the single recording unit, the repeated recording unit, the data duplication judgment unit and the promotion module are electrically connected in series, and the data backup unit, the data duplication judgment unit and the promotion module are electrically connected in series.

[0022] Optionally, the data mining module is composed of a combination of data mining, user data tracking and machine learning, and the data mining, user data tracking and machine learning are electrically connected in parallel.

[0023] Optionally, the user management is a combination of authority management and task management.

[0024] Optionally, the promotion module includes a promotion user targeting unit and offline promotion and online promotion, wherein the promotion user targeting unit is electrically connected in series with the data mining module, and an output end of the promotion user targeting unit is respectively connected in series with input ends of the offline promotion and the online promotion;

[0025] The offline promotion includes physical advertising, store operation planning, marketing center advertising production, new user development and promotion group evaluation;

[0026] The online promotion includes mini-program advertising, APP advertising, user-side message sending, and online and offline feedback from old users.

[0027] The present invention provides a user promotion system based on big data, which has the following beneficial effects:

[0028] 1. This user promotion system based on big data uses cache tools to cache and record multiple operation data on the user side as backup files. At the same time, the traffic collector can collect and record the frequency of user browsing operations. It targets not only the browsing data of old customers, but also the browsing data of new users on online advertisements.

[0029] 2. The user promotion system based on big data constitutes an information recording module through the electrical coordination between a single recording unit, a repeated recording unit, a data duplication judgment unit and a data backup unit. The user can record and save the operation process within the system through the single recording unit and the repeated recording unit respectively, and then review and judge all recording units through the data duplication judgment unit to avoid duplication of data records, reduce the operation memory of the process, and rely on the data backup unit to back up the operation records.

[0030] 3. The user promotion system based on big data can independently control the client's voice, image, location, text fragments, network status, etc. through permission management, so as to achieve the collection of intelligent data from the client. The data source contains file information, input information, traffic statistics and database. The file information includes user browsed files and user's favorite files. Traffic data is collected for the types of browsed files and favorite files based on the content of specific fields of the files. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a schematic diagram of the overall flow of an embodiment of the user promotion system based on big data;

[0032] Figure 2 This is a schematic diagram of the internal flow of the user browsing data collection and data analysis module in the user promotion system based on big data;

[0033] Figure 3 This is a schematic diagram of the internal flow of the user database in the user promotion system based on big data;

[0034] Figure 4 This is a schematic diagram of the internal process of the data mining module in the user promotion system based on big data;

[0035] Figure 5 This is a schematic diagram of the internal process of user management in the user promotion system based on big data. DETAILED DESCRIPTION

[0036] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0037] In the description of the present invention, unless otherwise specified, "plurality" means two or more than two; the orientations or positional relationships indicated by the terms "upper", "lower", "left", "right", "inner", "outer", "front end", "rear end", "head", "tail", etc. are based on the orientations or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", "third", etc. are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0038] In the description of the present invention, it should be noted that, unless otherwise clearly specified and limited, the terms "connected" and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0039] See also Figures 1 to 5 , the present invention provides a technical solution: a user promotion system based on big data, including a user database, an input end of the user database is electrically connected to a data analysis module, and an input end of the data analysis module is electrically connected to a user browsing data collection;

[0040] The output end of the user database is electrically connected to a promotion module, and the input end of the user database is also connected to a data mining module;

[0041] The input end of the data mining module is electrically connected to the user management, and the input end of the data mining module is also connected to the promotion data feedback;

[0042] The output end of the data mining module and the input end of the promotion module are electrically connected in series.

[0043] In this embodiment, Figure 1 As shown, the user browsing data collection, data analysis module, user database and promotion module are electrically connected in series.

[0044] In this embodiment, Figure 1 As shown, the promotion module, the promotion data feedback and the data mining module are electrically connected in series, and the output end of the data mining module is electrically connected in series with the user database and the input end of the promotion module respectively.

[0045] In this embodiment, Figure 2 As shown, the user browsing data collection also includes a cache tool, a flow collector and a log file, and the cache tool, the flow collector and the log file are electrically connected in parallel;

[0046] The cache tool, traffic collector and log file are all electrically connected in series with the input end of the data analysis module; the cache tool is used to cache and record multiple operation data of the user end as backup files, and the traffic collector can collect and record the frequency of user browsing operations, which targets not only the browsing data of old customers, but also the browsing data of new users on online advertisements.

[0047] In this embodiment, Figure 2 As shown, the data parsing module also includes a rule configuration, a parser and a preprocessor, and the rule configuration, the parser and the preprocessor are electrically connected in parallel.

[0048] In this embodiment, Figure 3 As shown, the user database consists of a single recording unit, a repeated recording unit, a data duplication judgment unit and a data backup unit;

[0049] The input end of the single recording unit is electrically connected in series with the data analysis module, the output end of the single recording unit is connected with the repeated recording unit, the output end of the repeated recording unit is connected with the data duplication judgment unit, and the single recording unit is electrically connected with the data backup unit;

[0050] The output end of the data backup unit is electrically connected in series with the input end of the data duplication determination unit.

[0051] In this embodiment, Figure 3As shown, the single recording unit, the repeated recording unit, the data duplication judgment unit and the promotion module are electrically connected in series, and the data backup unit, the data duplication judgment unit and the promotion module are electrically connected in series; the information recording module is formed by the electrical coordination between the single recording unit, the repeated recording unit, the data duplication judgment unit and the data backup unit, and the user can record and save the operation process inside the system through the single recording unit and the repeated recording unit respectively, and then all the recording units can be reviewed and judged through the data duplication judgment unit to avoid duplication of data records, reduce the operation memory of the process, and rely on the data backup unit to back up the operation records.

[0052] In this embodiment, Figure 4 As shown, the data mining module is composed of data mining, user data tracking and machine learning, and data mining, user data tracking and machine learning are electrically connected in parallel.

[0053] In this embodiment, Figure 5 As shown, user management is composed of permission management and task management. Through permission management, the client's voice, image, location, text fragments, network status, etc. can be independently controlled, so as to achieve the collection of intelligent data from the client. The data source contains file information, input information, traffic statistics and database. File information includes user browsed files and user's favorite files. Traffic data is collected for the types of browsed files and favorite files according to the content of specific fields of the files.

[0054] In this embodiment, Figure 1 As shown, the promotion module includes a promotion user targeting unit and offline promotion and online promotion, wherein the promotion user targeting unit is electrically connected in series with the data mining module, and the output end of the promotion user targeting unit is respectively connected in series with the input ends of the offline promotion and the online promotion;

[0055] Offline promotion includes physical advertising, store operation planning, marketing center advertising production, new user development and promotion group evaluation;

[0056] Online promotion includes mini program advertising, APP advertising, user-side message sending and more.

[0057] The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. A user promotion system based on big data, including a user database, characterized in that: The input end of the user database is electrically connected to a data analysis module, and the input end of the data analysis module is electrically connected to a user browsing data collection device; The output end of the user database is electrically connected to a promotion module, and the input end of the user database is also connected to a data mining module; The input end of the data mining module is electrically connected to the user management, and the input end of the data mining module is also connected to the promotion data feedback; The output end of the data mining module is electrically connected in series with the input end of the promotion module.

2. The user promotion system based on big data according to claim 1, characterized in that: The user browsing data collection, data analysis module, user database and promotion module are electrically connected in series.

3. The user promotion system based on big data according to claim 1, characterized in that: The promotion module, promotion data feedback and data mining module are electrically connected in series, and the output end of the data mining module is electrically connected in series with the user database and the input end of the promotion module respectively.

4. The user promotion system based on big data according to claim 1, characterized in that: The user browsing data collection also includes a cache tool, a flow collector and a log file, and the cache tool, the flow collector and the log file are electrically connected in parallel; The cache tool, the flow collector and the log file are all electrically connected in series with the input end of the data analysis module.

5. The user promotion system based on big data according to claim 1, characterized in that: The data analysis module also includes a rule configuration, a parser and a preprocessor, and the rule configuration, the parser and the preprocessor are electrically connected in parallel.

6. The user promotion system based on big data according to claim 1, characterized in that: The user database is composed of a single recording unit, a repeated recording unit, a data duplication judgment unit and a data backup unit; The input end of the single recording unit is electrically connected in series with the data analysis module, the output end of the single recording unit is connected with the repeat recording unit, the output end of the repeat recording unit is connected with the data duplication judgment unit, and the single recording unit is electrically connected with the data backup unit; The output end of the data backup unit is electrically connected in series with the input end of the data duplication determination unit.

7. The user promotion system based on big data according to claim 6 is characterized by: The single recording unit, the repeated recording unit, the data duplication judgment unit and the promotion module are electrically connected in series, and the data backup unit, the data duplication judgment unit and the promotion module are electrically connected in series.

8. The user promotion system based on big data according to claim 1, characterized in that: The data mining module is composed of data mining, user data tracking and machine learning, and the data mining, user data tracking and machine learning are electrically connected in parallel.

9. The user promotion system based on big data according to claim 1, characterized in that: The user management is composed of authority management and task management.

10. The user promotion system based on big data according to claim 1, characterized in that: The promotion module includes a promotion user targeting unit and offline promotion and online promotion, wherein the promotion user targeting unit is electrically connected in series with the data mining module, and the output end of the promotion user targeting unit is respectively connected in series with the input ends of the offline promotion and the online promotion; The offline promotion includes physical advertising, store operation planning, marketing center advertising production, new user development and promotion group evaluation; The online promotion includes mini-program advertising, APP advertising, user-side message sending, and online and offline feedback from old users.

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