Multi-channel data fusion and intelligent marketing strategy generation system in digital marketing

Abstract

The invention belongs to the technical field of digital marketing, and particularly relates to a multi-channel data fusion and intelligent marketing strategy generation system in digital marketing. Comprising a data acquisition module, a data cleaning and fusion module, a user portrait modeling module, an intelligent marketing strategy generation module, a strategy execution and feedback module, a data security and privacy protection module and a system management and monitoring module. According to the system, the data acquisition module is arranged to be matched with the data cleaning and fusion module, data of all channels can be effectively integrated, the problem of data swelling is effectively avoided, cross-channel data collection is achieved, more comprehensive user information support is provided, meanwhile, a marketing strategy is generated through an intelligent algorithm, more personalized marketing can be achieved, and the marketing efficiency is improved. By monitoring the marketing effect in real time and performing automatic adjustment, the continuity and the high efficiency of the marketing activity are ensured, and by setting the system security and monitoring module, various sensitive data can be effectively encrypted, and the security and the compliance of user data are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of digital marketing, and specifically to a multi-channel data fusion and intelligent marketing strategy generation system in digital marketing. Background Art

[0002] With the development of Internet and big data technologies, digital marketing has become an important means for various industries to enhance market competitiveness. However, the complexity of digital marketing has also been increasing continuously. Especially in the context of multi-channel marketing, enterprises need to collect, analyze, and utilize user data on multiple platforms for decision-making. These data usually come from different channels (such as social media, e-commerce platforms, email marketing, search engines, etc.), and their forms are diverse, resulting in the phenomenon of data silos. Therefore, how to achieve cross-platform data fusion and automatically generate marketing strategies based on these data is an urgent problem to be solved in the current digital marketing field.

[0003] The existing technologies have the following defects or problems:

[0004] Although there are already some solutions to process data from some channels, most systems lack unified data fusion capabilities and cannot automatically generate personalized marketing strategies based on user portraits. Therefore, there is an urgent need for an innovative technical solution that can achieve data fusion and intelligent strategy generation in a multi-channel environment, thereby improving marketing effectiveness.

[0005] It should be noted that the above content belongs to the technical cognitive scope of the inventor and does not necessarily constitute the prior art. Summary of the Invention

[0006] Aiming at the deficiencies of the prior art, the present invention provides a multi-channel data fusion and intelligent marketing strategy generation system in digital marketing, which solves the existing problems.

[0007] To achieve the above object, the present invention provides the following technical solution: A multi-channel data fusion and intelligent marketing strategy generation system in digital marketing, comprising:

[0008] A data acquisition module, which is used to obtain various types of user data from each digital marketing channel, such as behavior data, transaction data, and social interaction data;

[0009] A data cleaning and fusion module, which is used to process the data by removing duplicate and invalid data and unifying the format, and at the same time adopts data fusion technology to ensure that user data from different channels can be effectively merged;

[0010] User Portrait Modeling Module, which constructs a detailed user portrait based on the data processed by the Data Cleaning and Fusion Module to understand the interests, behavior habits, and purchase preferences of each user;

[0011] Intelligent Marketing Strategy Generation Module, which combines the user portrait constructed by the User Portrait Modeling Module and generates personalized marketing strategies through machine learning and deep learning algorithms;

[0012] Strategy Execution and Feedback Module, which is used to push the generated marketing strategies to various marketing platforms and provide real-time feedback;

[0013] Data Security and Privacy Protection Module, which, based on the sensitivity of user data, takes encryption measures and privacy protection measures to ensure the security of user data;

[0014] System Management and Monitoring Module, which is used for the overall management, operation monitoring, fault troubleshooting, and performance optimization of the system.

[0015] In some embodiments, the Data Acquisition Module includes:

[0016] Data Access Interface, which accesses marketing platforms through API interfaces, SDKs, and data scraping tools. The marketing platforms include social media, e-commerce platforms, search engines, and email marketing platforms. These interfaces are responsible for pulling data regularly to support the integration of various types of data;

[0017] Multimedia Source Processing Module, which can process structured and unstructured data and ensure the compatibility and accuracy of data sources;

[0018] Data Scheduled Scraping and Synchronization Mechanism, which can achieve automated scraping, set scheduled tasks for data acquisition, ensure that data can be obtained in real-time and on-demand, and reduce data latency.

[0019] In some embodiments, the Data Cleaning and Fusion Module includes:

[0020] Data Duplication Removal and Filtering, which removes duplicate data through a rule engine and filters out invalid records, such as abnormal traffic and invalid user information;

[0021] Format Conversion and Standardization, which uniformly converts the formats of different data sources and standardizes all data for subsequent processing;

[0022] Data fusion and matching algorithm, which fuses data from different platforms through association rule algorithm, similarity calculation and data matching method, can judge the performance of the same user on different platforms and perform effective merging. The merging operation is carried out through the K-Means clustering algorithm, which can help find objects belonging to the same group in data from different sources. The specific formula is as follows:

[0023]

[0024] Among them, K is the number of clusters, Ci is the i-th cluster, Xj is the data point in the cluster, and μi is the center of the i-th cluster.

[0025] In some embodiments, the user portrait modeling module includes:

[0026] Behavior analysis engine, which extracts information on user interest tags and preference models by analyzing user behaviors on various platforms, such as browsing, clicking, purchasing, and interacting;

[0027] Demographic analysis module, which analyzes the background data of users by combining the basic information of users, such as age, gender, region, and occupation, to further enrich the dimensions of the portrait;

[0028] Prediction model, which predicts the possible future behaviors of users, such as purchase tendency and potential interests, in a decision tree manner based on historical behavior data and user characteristics;

[0029] Portrait update mechanism, the user portrait will be dynamically updated over time and with the addition of new data, and an incremental learning method is adopted to reconstruct the portrait regularly according to the new behaviors of users.

[0030] In some embodiments, the intelligent marketing strategy generation module includes:

[0031] Marketing goal setting module, which allows users to set marketing goals, such as increasing conversion rate, increasing exposure, and enhancing customer loyalty, and matches the goals with specific strategies;

[0032] Strategy generation engine, which automatically generates personalized marketing strategies based on user portraits, marketing goals, and historical data, using machine learning and deep learning models, including but not limited to personalized product recommendations, precise advertising placements, and targeted coupon distributions;

[0033] Multi-channel optimization module, which adjusts the content and presentation methods of marketing strategies according to the characteristics of different channels and the target audiences to ensure the maximum effect of the strategies on each platform;

[0034] A / B Testing and Strategy Adjustment: Verify the effectiveness of different marketing strategies through A / B testing and automatically optimize strategies based on feedback data, where the feedback data includes click-through rate, conversion rate, and ROI.

[0035] In some embodiments, the strategy execution and feedback module includes:

[0036] A strategy execution engine responsible for automatically pushing marketing strategies to various marketing platform forms and implementing the delivery. The marketing platforms include Facebook, Instagram, Google Ads, and email.

[0037] Feedback monitoring and data collection: Real-time tracking of the effectiveness of marketing strategies, including key metrics such as user clicks, user purchases, user browsing time, conversion rate, and ROI.

[0038] Feedback analysis and adaptive adjustment: Based on the data collected by the feedback monitoring and data collection, analyze the actual performance of each strategy and automatically adjust the strategy content through an adaptive algorithm to ensure the optimal structure.

[0039] In some embodiments, the data security and privacy protection module includes:

[0040] Data encryption and protection: All user data is encrypted during transmission and storage to ensure data security and privacy protection.

[0041] Privacy compliance mechanism: According to privacy protection regulations such as GDPR and CCPA, ensure that user data complies with legal requirements during collection, processing, and use. User data will be anonymized to prevent personal information leakage.

[0042] Access control and auditing: Set up an access control mechanism to ensure that only authorized users can access sensitive data, and audit and record all data access operations to ensure data transparency and compliance.

[0043] In some embodiments, the system management and monitoring module includes:

[0044] System health monitoring: Real-time monitoring of the system's operating status, and can promptly detect system failures, performance bottlenecks, and abnormal behaviors.

[0045] Log management and exception reporting: Record the system's operation logs and exception situations, and generate detailed reports to facilitate administrators in quickly locating problems.

[0046] Performance optimization module: Optimize the performance of each module based on system statistical data to improve the system's response speed and processing capacity.

[0047] Compared with the prior art, the present invention provides a multi-channel data fusion and intelligent marketing strategy generation system in digital marketing, which has the following beneficial effects:

[0048] This multi-channel data fusion and intelligent marketing strategy generation system in digital marketing can effectively integrate data from various channels by setting up a data collection module in cooperation with a data cleaning and fusion module, effectively avoid data duplication problems, collect data across channels, thereby providing more comprehensive user information support. At the same time, the marketing strategy is generated through intelligent algorithms, which can achieve more personalized and efficient marketing, improve the marketing effect. By real-time monitoring the marketing effect and making automated adjustments, the sustainability and efficiency of marketing activities are ensured. By setting up a system security and monitoring module, various sensitive data can be effectively encrypted to ensure the security and compliance of user data. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic flow chart of a multi-channel data fusion and intelligent marketing strategy generation system in digital marketing according to the present invention;

[0050] Figure 2 It is a schematic flow chart of the data collection module of the present invention;

[0051] Figure 3 It is a schematic flow chart of the data cleaning and fusion module of the present invention;

[0052] Figure 4 It is a schematic flow chart of the user portrait modeling module of the present invention;

[0053] Figure 5 It is a schematic flow chart of the intelligent marketing strategy generation module of the present invention;

[0054] Figure 6 It is a schematic flow chart of the strategy execution and feedback module of the present invention;

[0055] Figure 7 It is a schematic flow chart of the data security and privacy protection module of the present invention;

[0056] Figure 8 It is a schematic flow chart of the system security and monitoring module of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0057] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0058] It should be understood that the terms used in the specification of the present invention are merely for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0059] The terms "comprising" and "including" indicate the presence of the described features, wholes, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their combinations.

[0060] The term " / and / " refers to any combination and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0061] Please refer to Figure 1-8 , in this embodiment: A multi-channel data fusion and intelligent marketing strategy generation system in digital marketing, comprising:

[0062] A data acquisition module, which is used to obtain various types of user data from each digital marketing channel, such as behavioral data, transaction data, and social interaction data;

[0063] A data cleaning and fusion module, which is used to remove duplicate and invalid data from the data and unify the format, and at the same time adopts data fusion technology to ensure that user data from different channels can be effectively merged;

[0064] A user portrait modeling module, which constructs a detailed user portrait based on the data processed by the data cleaning and fusion module, and is used to understand the interests, behavioral habits, and purchase preferences of each user;

[0065] An intelligent marketing strategy generation module, which combines the user portrait constructed by the user portrait modeling module and generates personalized marketing strategies through machine learning and deep learning algorithms;

[0066] A strategy execution and feedback module, which is used to push the generated marketing strategies to each marketing platform and provide real-time feedback;

[0067] A data security and privacy protection module, which takes encryption means and privacy protection measures based on the sensitivity of user data to ensure the security of user data;

[0068] A system management and monitoring module, which is used for the global management, operation monitoring, fault troubleshooting, and performance optimization of the system.

[0069] What needs to be noted in the above modules is:

[0070] The data acquisition module includes:

[0071] A data access interface that accesses the marketing platform through API interfaces, SDKs, and data scraping tools. The marketing platform includes social media, e-commerce platforms, search engines, and email marketing platforms. These interfaces are responsible for pulling data regularly to support the integration of various types of data;

[0072] A multimedia source processing module that can process structured and unstructured data and ensure the compatibility and accuracy of data sources;

[0073] A data scheduling scraping and synchronization mechanism that can achieve automated scraping, set scheduled tasks for data acquisition, ensure that data can be obtained in real time and on demand, and reduce data latency;

[0074] The data cleaning and fusion module includes:

[0075] Data deduplication and filtering, which removes duplicate data through a rule engine and filters out invalid records, such as abnormal traffic and invalid user information;

[0076] Format conversion and standardization, which uniformly converts the formats of different data sources and standardizes all data for subsequent processing;

[0077] A data fusion and matching algorithm that fuses data from different platforms through association rule algorithms, similarity calculations, and data matching methods, can judge the performance of the same user on different platforms, and perform effective merging. The merging operation is carried out through the K-Means clustering algorithm, which can help find objects belonging to the same group in data from different sources. The specific formula is as follows:

[0078]

[0079] Among them, K is the number of clusters, Ci is the i-th cluster, Xj is the data point in the cluster, and μi is the center of the i-th cluster;

[0080] The user portrait modeling module includes:

[0081] A behavior analysis engine that extracts information on user interest tags and preference models by analyzing user behaviors on various platforms, such as browsing, clicking, purchasing, and interacting;

[0082] A demographic analysis module that analyzes the background data of users by combining basic user information, such as age, gender, region, and occupation, to further enrich the dimensions of the portrait;

[0083] A prediction model that, based on historical behavior data and user characteristics, uses decision trees to predict possible future user behaviors such as purchase propensity and potential interests;

[0084] A portrait update mechanism where the user portrait is dynamically updated over time and with the addition of new data. An incremental learning method is used to reconstruct the portrait regularly based on the user's new behaviors;

[0085] The intelligent marketing strategy generation module includes:

[0086] A marketing goal setting module that allows users to set marketing goals such as increasing conversion rates, increasing exposure, and enhancing customer loyalty, and matching the goals with specific strategies;

[0087] A strategy generation engine that, based on the user portrait, marketing goals, and historical data, uses machine learning and deep learning models to automatically generate personalized marketing strategies, including but not limited to personalized product recommendations, precise advertisement placements, and targeted coupon issuances;

[0088] A multi-channel optimization module that adjusts the content and presentation of marketing strategies according to the characteristics of different channels and the target audiences to ensure the maximum effectiveness of the strategies on each platform;

[0089] A / B testing and strategy adjustment that validates the effectiveness of different marketing strategies through A / B testing and automatically optimizes the strategies based on the feedback data, which includes click-through rates, conversion rates, and ROI;

[0090] The strategy execution and feedback module includes:

[0091] A strategy execution engine that is responsible for automatically pushing marketing strategies to various marketing platform forms and conducting real-time placements. The marketing platforms include Facebook, Instagram, Google Ads, and emails;

[0092] Feedback monitoring and data collection that real-time tracks the effectiveness of marketing strategies, including key metrics such as user clicks, user purchases, user browsing times, conversion rates, and ROI;

[0093] Feedback analysis and adaptive adjustment that, based on the data collected from feedback monitoring and data collection, analyzes the actual performance of each strategy and automatically adjusts the strategy content through an adaptive algorithm to ensure the optimal structure.

[0094] The data security and privacy protection module includes:

[0095] Data encryption and protection where all user data is encrypted during transmission and storage to ensure data security and privacy protection;

[0096] Privacy compliance mechanism. According to privacy protection regulations such as GDPR and CCPA, it ensures that user data complies with legal requirements during the collection, processing, and use processes. User data will be anonymized to prevent personal information leakage;

[0097] Access control and auditing. There is an access control mechanism set up to ensure that only authorized users can access sensitive data, and all data access operations are audited and recorded to ensure data transparency and compliance;

[0098] The system management and monitoring module includes:

[0099] System health monitoring. It monitors the operation status of the system in real time and can promptly detect system failures, performance bottlenecks, and abnormal behaviors;

[0100] Log management and exception reporting. It records the operation logs and exception situations of the system and generates detailed reports to facilitate administrators to quickly locate problems;

[0101] Performance optimization module. According to system statistical data, it optimizes the performance of each module to improve the system's response speed and processing capacity.

[0102] The working principle and usage process of the present invention: First, through the data access interface, it accesses the marketing platform through API interfaces, SDKs, and data scraping tools. Due to the set data timing scraping and synchronization mechanism, it can achieve automated timing scraping of various types of data. Subsequently, the multimedia source processing module processes structured and unstructured data, removes duplicate data through the rule engine, filters out invalid data during this process, then uniformly converts the formats of different data sources, fuses data from different platforms through the association rule algorithm, and merges them through the K-Means clustering algorithm;

[0103] By analyzing customer behaviors, extracting interest tag information, and completing the background data of basic information through the demographic analysis module, it predicts the possible future behaviors of users in a decision tree manner. Subsequently, a user portrait is generated. At the same time, there is a user portrait update mechanism, and the user portrait will be dynamically updated as events and new data are added. Through the intelligent marketing strategy generation module, marketing strategies are generated. Among them, based on the user portrait, marketing goals, and historical data, personalized marketing strategies are automatically generated using machine learning and deep learning models. At the same time, the effects of different marketing strategies are verified through A / B testing, and the strategies are automatically optimized according to the feedback data. The feedback data includes click-through rate, conversion rate, and ROI. The implementation of the marketing strategy is completed through the marketing execution and feedback module. Since data encryption is set in this application, it can effectively protect user information.

[0104] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, it is described relatively simply. For the relevant parts, reference can be made to the corresponding descriptions in the method embodiment.

[0105] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions recorded in the foregoing embodiments or perform equivalent replacements for some of the technical features. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A multi-channel data fusion and intelligent marketing strategy generation system in digital marketing, characterized by: include: A data collection module, which is used to obtain various types of user data from various digital marketing channels, such as behavioral data, transaction data, and social interaction data; Data cleaning and fusion module, which is used to remove duplicate and invalid data and unify the data format, and adopts data fusion technology to ensure that user data from different channels can be effectively merged; A user portrait modeling module, which constructs a detailed user portrait based on the data processed by the data cleaning and fusion module to understand the interests, behavior habits and purchase preferences of each user; An intelligent marketing strategy generation module, which combines the user portrait constructed by the user portrait modeling module to generate a personalized marketing strategy through machine learning and deep learning algorithms; A strategy execution and feedback module, which is used to push the generated marketing strategy to various marketing platforms and provide real-time feedback; Data security and privacy protection module, which takes encryption and privacy protection measures based on the sensitivity of user data to ensure the security of user data; The system management and monitoring module is used for global management, operation monitoring, troubleshooting and performance optimization of the system.

2. According to claim 1, a system for multi-channel data fusion and intelligent marketing strategy generation in digital marketing is characterized in that: The data acquisition module comprises: Data access interface, which accesses marketing platforms through API interfaces, SDKs, and data crawling tools. The marketing platforms include social media, e-commerce platforms, search engines, and email marketing platforms. These interfaces are responsible for pulling data at regular intervals to support the integration of various types of data; Multimedia source processing module, which can process structured and unstructured data and ensure the compatibility and accuracy of data sources; The data timing capture and synchronization mechanism can realize automatic capture and set timing tasks for data collection to ensure that data can be obtained in real time and on demand, reducing data delays.

3. The system for multi-channel data fusion and intelligent marketing strategy generation in digital marketing according to claim 1, characterized in that: The data cleaning and fusion module includes: Data deduplication and filtering: Use the rule engine to remove duplicate data and filter out invalid records, such as abnormal traffic and invalid user information; Format conversion and standardization: uniformly convert the formats of different data sources and standardize all data for subsequent processing; The data fusion and matching algorithm fuses data from different platforms through association rule algorithms, similarity calculations, and data matching methods. It can determine the performance of the same user on different platforms and merge them effectively. The merging operation is performed through the K-Means clustering algorithm, which can help find objects belonging to the same group in data from different sources. The specific formula is as follows: Among them, K is the number of clusters, Ci is the i-th cluster, Xj is the data point in the cluster, and μi is the center of the i-th cluster.

4. The system for multi-channel data fusion and intelligent marketing strategy generation in digital marketing according to claim 1, characterized in that: The user portrait modeling module includes: Behavior analysis engine, which extracts information about users’ interest tags and preference models by analyzing users’ behaviors on various platforms, such as browsing, clicking, purchasing, and interacting; The demographic analysis module combines the user's basic information, such as age, gender, region, and occupation, to analyze the user's background data and further enrich the dimensions of the portrait; Prediction model, based on historical behavior data and user characteristics, uses decision trees to predict users' possible future behaviors, such as purchase intentions and potential interests; Portrait update mechanism: User portraits will be dynamically updated over time and with the addition of new data. An incremental learning method is used to regularly reconstruct portraits based on new user behaviors.

5. According to claim 1, a system for multi-channel data fusion and intelligent marketing strategy generation in digital marketing, characterized in that: The intelligent marketing strategy generation module includes: The marketing goal setting module allows users to set marketing goals, such as improving conversion rates, increasing exposure, and improving customer loyalty, and match goals with specific strategies; The strategy generation engine uses machine learning and deep learning models to automatically generate personalized marketing strategies based on user profiles, marketing goals, and historical data, including but not limited to personalized product recommendations, targeted advertising, and targeted coupon distribution; The multi-channel optimization module adjusts the content and presentation of marketing strategies according to the characteristics of different channels and audience groups to ensure the maximum effect of the strategy on each platform; A / B testing and strategy adjustment: verify the effectiveness of different marketing strategies through A / B testing, and automatically optimize strategies based on feedback data, including click-through rate, conversion rate and ROI.

6. The system for multi-channel data fusion and intelligent marketing strategy generation in digital marketing according to claim 1, characterized in that: The strategy execution and feedback module includes: The strategy execution engine is responsible for automatically pushing marketing strategies to various marketing platforms and implementing them. The marketing platforms include Facebook, Instagram, Google ads and email; Feedback monitoring and data collection, real-time tracking of marketing strategy effects, including key indicators such as user clicks, user purchases, user browsing time, conversion rate, and ROI; Feedback analysis and adaptive adjustment, based on the data collected by the feedback monitoring and data collection, analyze the actual performance of each strategy, and automatically adjust the strategy content through adaptive algorithms to ensure the optimal structure.

7. The system for multi-channel data fusion and intelligent marketing strategy generation in digital marketing according to claim 1, characterized in that: The data security and privacy protection module includes: Data encryption and protection: All user data is encrypted during transmission and storage to ensure data security and privacy protection; Privacy compliance mechanism, according to privacy protection regulations such as GDPR and CCPA, ensures that user data complies with legal requirements during collection, processing and use. User data will be anonymized to prevent personal information leakage; Access control and auditing: An access control mechanism is set up to ensure that only authorized users access sensitive data, and all data access operations are audited and recorded to ensure data transparency and compliance.

8. The system for multi-channel data fusion and intelligent marketing strategy generation in digital marketing according to claim 1, characterized in that: The system management and monitoring module includes: System health monitoring: real-time monitoring of the system's operating status, and timely detection of system failures, performance bottlenecks, and abnormal behaviors; Log management and exception reporting: record system operation logs and exceptions, and generate detailed reports to help administrators quickly locate problems. The performance optimization module optimizes the performance of each module based on system statistical data to improve the system's response speed and processing capabilities.

Images