Information management promotion method and system, electronic equipment and storage medium

Abstract

The invention provides an information management promotion method and system, electronic equipment and a storage medium. The method comprises the following steps: constructing portrait information of a target user; processing static information and dynamic information in the portrait information of the target user to obtain a trigger word library of the target user; after the trigger word in the trigger word bank is monitored, carrying out combined analysis on the trigger word of the target user and the portrait information to obtain an analysis result; formulating a marketing strategy of the target user according to the analysis result; namely, the instant interest and demand of the user can be captured in time by analyzing the voice data and behavior of the user, so that the marketing content better conforms to the current preference of the user, and the marketing accuracy is greatly improved.

Description

Technical Field

[0001] The present invention belongs to the field of data processing technology, and more specifically, particularly relates to an information management and promotion method and system, electronic equipment, and storage medium. Background Art

[0002] With the advancement of technology, mobile banking applications are gradually exploring and introducing more advanced and accurate user profiling technologies in order to improve marketing effectiveness and user satisfaction.

[0003] At present, in traditional mobile banking applications, the formulation of marketing strategies mainly relies on two types of user portraits: static portraits and dynamic portraits. Static portraits usually include basic information such as the user's deposit status and financial attributes; while dynamic portraits focus on capturing user behavior data in the application, such as transaction records, browsing habits, etc.

[0004] However, although these existing user profiling technologies provide certain marketing guidance for applications, they still face many challenges in actual application. The most prominent problem is that these strategies often fail to accurately capture users' immediate needs and preferences. Since users' financial needs and behavior patterns may change rapidly over time and in different situations, traditional marketing strategies based on static and dynamic profiling often fail to respond to these changes in a timely manner, resulting in a large deviation between the push of marketing information and users' actual needs. This not only affects user satisfaction, but also reduces the actual effectiveness of marketing activities. Summary of the invention

[0005] In view of this, the purpose of the present invention is to provide an information management and promotion method and system, an electronic device, and a storage medium, which can be used to capture the user's immediate interests and needs in a timely manner by analyzing the user's voice data and behavior, so that the marketing content is more in line with the user's current preferences, thereby greatly improving the accuracy of marketing.

[0006] The first aspect of the present application discloses an information management promotion method, comprising:

[0007] Build profile information of target users;

[0008] Processing the static information and dynamic information in the portrait information of the target user to obtain a trigger word library of the target user;

[0009] After monitoring the trigger words in the trigger word library, combining the trigger words of the target user with the portrait information for analysis to obtain an analysis result;

[0010] A marketing strategy for the target users is formulated based on the analysis results.

[0011] Optionally, the building of the target user's portrait information includes:

[0012] Collect static data and dynamic data of the target user; wherein the static data includes at least one of the age, gender, occupation and income of the target user; and the dynamic data includes the behavior data of the target user in the target application;

[0013] Construct the profile information of the target user based on the static data and dynamic data of the target user.

[0014] Optionally, the processing of static information and dynamic information in the portrait information of the target user to obtain a trigger word library of the target user includes:

[0015] The target user's portrait information is trained using a machine learning model to obtain a behavior recognition model; wherein the behavior recognition model is used to identify the target user's behavior pattern and preference based on the target user's portrait information;

[0016] Based on the portrait information, the behavior pattern and the preference, a trigger word library of the target user is obtained.

[0017] Optionally, after obtaining the trigger word library of the target user based on the portrait information, the behavior pattern and the preference, the method further includes:

[0018] The target user's portrait information and trigger word library are updated regularly.

[0019] The second aspect of the present application discloses an information management promotion method, comprising:

[0020] The terminal monitors the voice data of the target user in real time; and after monitoring the trigger words in the trigger word library, sends the trigger words to the server;

[0021] The server combines the trigger word with the portrait information of the target user for analysis to obtain an analysis result; and customizes a marketing strategy for the target user based on the analysis result.

[0022] Optionally, also include:

[0023] The server sends the marketing strategy to the terminal;

[0024] The terminal displays the marketing strategy to the user.

[0025] Optionally, when the target user uses the target application, the real-time monitoring function of the terminal is allowed to be enabled; when the target user does not use the target application, the real-time monitoring function of the terminal is prohibited to be enabled.

[0026] The third aspect of the present application discloses an information management and promotion system, including:

[0027] Construction module, used to construct the target user's portrait information;

[0028] A word library module, used to process the static information and dynamic information in the portrait information of the target user to obtain a trigger word library of the target user;

[0029] An analysis module, configured to combine and analyze the trigger words of the target user with the portrait information after monitoring the trigger words in the trigger word library to obtain an analysis result;

[0030] The strategy module is used to formulate a marketing strategy for the target user according to the analysis result.

[0031] A fourth aspect of the present application discloses an electronic device, comprising:

[0032] one or more processors;

[0033] a storage device having one or more programs stored thereon;

[0034] When one or more programs are executed by one or more processors, the one or more processors implement the information management promotion method as described in any one of the first and second aspects of the present application.

[0035] In a fifth aspect, the present application discloses a storage medium on which a computer program is stored, wherein when the computer program is executed by a processor, the information management promotion method as described in any one of the first and second aspects of the present application is implemented.

[0036] It can be seen from the above technical scheme that the present invention provides an information management and promotion method, including: constructing portrait information of target users; processing static information and dynamic information in the portrait information of the target users to obtain a trigger vocabulary library of the target users; after monitoring the trigger words in the trigger vocabulary library, combining the trigger words of the target users with the portrait information for analysis to obtain analysis results; based on the analysis results, formulating a marketing strategy for the target users; that is, by analyzing the user's voice data and behavior, the user's immediate interests and needs can be captured in a timely manner, so that the marketing content is more in line with the user's current preferences, thereby greatly improving the accuracy of marketing. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0038] Figure 1 is a flow chart of an information management promotion method provided by an embodiment of the present invention;

[0039] Figure 2 is a flow chart of another information management promotion method provided by an embodiment of the present invention;

[0040] Figure 3 is a flow chart of another information management promotion method provided by an embodiment of the present invention;

[0041] Figure 4 is a schematic diagram of an information management and promotion system provided by an embodiment of the present invention;

[0042] Figure 5 It is a schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] In the present application, the term "comprise", "include" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, article or equipment including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or equipment. In the absence of more restrictions, the elements defined by the sentence "comprise one ..." do not exclude the existence of other identical elements in the process, method, article or equipment including the elements. In addition, the terms "first", "second", "third", "fourth", etc. (if present) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable in appropriate circumstances, so that the embodiments of the present application described here can be implemented in an order other than those illustrated or described here, for example.

[0045] An embodiment of the present application discloses an information management and promotion method, which is used to solve the problem that traditional marketing strategies based on static and dynamic portraits in the prior art often cannot respond to these changes in a timely manner, resulting in a large deviation between the push of marketing information and the actual needs of users; this not only affects the user experience satisfaction, but also reduces the actual effect of marketing activities.

[0046] Explanation of relevant terms:

[0047] User Profile is a comprehensive description of user characteristics, including basic information, behavioral habits, preference settings, transaction records, etc. In the field of financial technology, user profiles are often used to understand customer needs and behaviors in order to provide more personalized services.

[0048] Static Profile mainly refers to the fixed attributes of users, such as age, gender, occupation, income level, deposits, financial assets, etc. These attributes generally do not change frequently over time.

[0049] Dynamic Profile involves user behavior data, such as application usage patterns, transaction behavior, browsing history, etc. Dynamic Profile can better reflect the user's current needs and preferences.

[0050] Trigger words are keywords that can trigger specific actions or reactions in a certain context. In the present invention, trigger words are used to identify the user's possible interest in a certain type of product or service, such as "financial management" or "transfer".

[0051] Edge Intelligence refers to the technology that processes and analyzes data on the user's device (such as smartphones, tablets, etc.) rather than in the cloud. This approach helps to increase data processing speed and protect user privacy.

[0052] Voice recognition is a technology that converts human voice into text or instructions. In the present invention, voice recognition is used to capture trigger words in the user's oral expression in real time.

[0053] Machine Learning is a data analysis technology that enables computers to learn from data and make decisions or predictions. In the present invention, machine learning is used to analyze user data, build user portraits, and generate trigger words.

[0054] Personalized Marketing is a marketing strategy that aims to provide customized product or service information to specific users to improve marketing effectiveness. This strategy is usually based on the user's personal information and behavior data.

[0055] See also Figure 1 , information management promotion methods, including:

[0056] S101. Build profile information of target users.

[0057] In the key step of building the target user's portrait information, we are committed to comprehensively and deeply exploring and integrating the multi-dimensional information of the target user group, aiming to create a three-dimensional and detailed user portrait. This process is not limited to collecting relatively stable static information such as the user's age, gender, geographical distribution, professional identity and income level, but also covers a series of dynamic and changing information dimensions such as the user's consumption behavior habits, personal interests and hobbies, online active time periods and social interaction patterns.

[0058] Through the careful sorting and comprehensive analysis of this information, we can more accurately grasp the inherent needs and personalized preferences of target users, and provide strong data support and decision-making basis for subsequent market analysis, product positioning and the careful formulation of marketing strategies. Such a user portrait construction process undoubtedly lays a solid foundation for enterprises to seize the initiative and achieve precision marketing in the fierce market competition.

[0059] S102: Process the static information and dynamic information in the target user's portrait information to obtain a trigger word library of the target user.

[0060] It is necessary to conduct in-depth analysis and processing of the static and dynamic information of the target users. By using technical means such as data mining and text analysis, key words that can reflect user characteristics and behaviors can be extracted from this information, and then a trigger word library of the target users can be constructed; the words in these trigger word libraries will serve as an important basis for subsequent monitoring and analysis.

[0061] In order to build a trigger word library for target users, it is necessary to deeply analyze and finely process the static and dynamic information of target users. This process uses a series of advanced technical means such as data mining and text analysis to extract key words that can accurately describe user characteristics and behavior patterns from massive information.

[0062] Specifically, we first use data mining technology to quantitatively analyze users' static information (such as age, gender, region, occupation, income level, etc.) to identify the commonalities and differences between different user groups. Then, we use text analysis technology to deeply interpret users' dynamic information (such as consumption habits, hobbies, active time periods, social interaction content, etc.) to capture the user preferences and behavioral trends contained therein.

[0063] On this basis, we will carefully select key words that can fully reflect user characteristics and behaviors, and build a trigger word library for target users according to certain logical structures and classification standards. These carefully selected words not only cover the basic attributes and consumption preferences of users, but also deeply reveal the potential needs and psychological expectations of users, providing strong vocabulary support and semantic reference for subsequent monitoring, analysis and formulation of precision marketing strategies.

[0064] By building this trigger vocabulary, we can more keenly capture changes and trends in user behavior, providing strong support for companies to achieve accurate positioning and efficient marketing in a rapidly changing market environment.

[0065] S103: After monitoring the trigger words in the trigger word library, the trigger words of the target user are combined with the portrait information for analysis to obtain analysis results.

[0066] After listening to the key words in the trigger word library, you need to immediately combine these trigger words with the target user's profile information for analysis. This step aims to dig out the user's current or potential needs and interests by comparing the relevant features in the trigger words and profile information. Through comprehensive analysis, more accurate and targeted analysis results can be obtained, providing strong support for the formulation of subsequent marketing strategies.

[0067] Once the preset keywords or phrases (i.e. trigger words) in the trigger word library are detected, the process will be quickly initiated to combine these captured trigger words with the target user's profile information for in-depth analysis. The core of this process is to carefully compare the trigger words with various features in the profile, such as user preferences, behavioral habits, past interaction records, etc., in order to reveal the user's current needs or potential interests; after this comprehensive and detailed comprehensive analysis, an accurate and highly customized analysis result can be obtained, which will become an indispensable reference for the subsequent formulation of marketing strategies, ensuring that the strategy can accurately meet user needs and lay a solid foundation for the success of marketing activities.

[0068] S104. Develop marketing strategies for target users based on the analysis results.

[0069] Based on the analysis structure obtained in the above steps, you can start planning marketing strategies for target users. When formulating these strategies, you must fully consider the personalized needs and preferences of users, and closely combine them with the current market environment and competitive situation to ensure the effectiveness and pertinence of the strategies.

[0070] To provide target users with a more accurate and personalized marketing experience, a variety of marketing strategies and methods will be flexibly used. This may include attracting users' attention through high-quality content marketing, establishing closer interactive connections with users through social media platforms, or stimulating users' willingness to buy through coupons and promotions. The selection and implementation of each strategy will be closely centered on users' needs and preferences, striving to improve user satisfaction while also effectively enhancing users' brand loyalty.

[0071] Through this series of carefully planned marketing strategies, we hope to bring a more intimate and efficient marketing experience to target users, thereby standing out in the fierce market competition and achieving sustained business growth.

[0072] That is to say, combined with the trigger words and user portrait data captured in real time, the system uses algorithms to dynamically generate and push personalized marketing content to more accurately meet the user's immediate needs.

[0073] In this embodiment, portrait information of the target user is constructed; the static information and dynamic information in the portrait information of the target user are processed to obtain a trigger word library of the target user; after monitoring the trigger words in the trigger word library, the trigger words of the target user are combined with the portrait information for analysis to obtain an analysis result; based on the analysis result, a marketing strategy for the target user is formulated; that is, by analyzing the user's voice data and behavior, the user's immediate interests and needs can be captured in a timely manner, so that the marketing content is more in line with the user's current preferences, thereby greatly improving the accuracy of marketing.

[0074] Optionally, build target user profile information, including:

[0075] First, static data and dynamic data of the target user are collected; the static data includes at least one of the target user's age, gender, occupation and income; the dynamic data includes the target user's behavior data in the target application. Second, based on the target user's static data and dynamic data, the target user's portrait information is constructed.

[0076] That is to say, when building the target user's portrait information, it is necessary to first collect and analyze various types of target user data extensively and deeply. These data are mainly divided into two categories: static data and dynamic data.

[0077] Static data, as the basic framework of user portraits, mainly covers several core attributes of target users. This includes but is not limited to their age, which helps to understand the user's life cycle stage and possible consumption habits; gender, which is important for analyzing user interests, preferences and purchasing behaviors; occupation, which reflects the user's social status and economic ability, which in turn affects their consumption level and consumption areas; income, which is a key indicator to measure the user's purchasing power and consumption potential.

[0078] Dynamic data, like the dynamic colors in user portraits, captures the real-time behavior and interaction of target users in specific applications or platforms. These data are mainly derived from the user's behavior trajectory in the target application, such as browsing history, click behavior, purchase history, stay time, frequency of use, etc. Through in-depth analysis of these dynamic data, we can gain insight into user preference changes, points of interest, and potential needs, thereby providing users with more accurate and personalized services.

[0079] After collecting enough static and dynamic data, you can start to build the target user's profile information. In this process, we use advanced technologies such as data mining and machine learning to integrate, clean, analyze and model various types of data, and finally form a comprehensive, three-dimensional and insightful user profile. This profile can not only better understand the needs and behavior patterns of target users, but also provide strong support for formulating more accurate market strategies and improving user experience and satisfaction.

[0080] Optionally, the static information and dynamic information in the target user's portrait information are processed to obtain a trigger word library of the target user, including:

[0081] First, the target user's portrait information is trained using a machine learning model to obtain a behavior recognition model; the behavior recognition model is used to identify the target user's behavior patterns and preferences based on the target user's portrait information; secondly, based on the portrait information, behavior patterns and preferences, the target user's trigger vocabulary is obtained.

[0082] In other words, the target user's profile information is deeply mined and trained using advanced machine learning models to build an accurate behavior recognition model. The core function of this model is that it can carefully identify and analyze the user's behavior patterns and preferences based on the target user's profile information.

[0083] Specifically, the behavior recognition model will deeply analyze the user's static attributes (such as age, gender, occupation, etc.) and dynamic behaviors (such as consumption habits, online activity tracks, etc.), so as to accurately grasp the user's personalized characteristics. On this basis, the model can further predict and interpret the user's behavioral trends and preference changes that may be shown in the future.

[0084] In order to further improve the accuracy and efficiency of marketing, we carefully built a trigger word library for target users based on their profile information, behavior patterns and preferences. This trigger word library not only includes keywords and phrases that are closely related to user interests, but also fully considers the needs and reactions that users may have in specific situations.

[0085] By comprehensively using the behavior recognition model and trigger word library, we can more accurately capture the user's immediate needs and interests, and provide strong data support and decision-making basis for subsequent marketing activities. This not only helps to improve the relevance and attractiveness of marketing content, but also effectively reduces the interference of irrelevant information, bringing users a more pleasant and efficient interactive experience.

[0086] Optionally, after obtaining the trigger word library of the target user based on the portrait information, behavior patterns and preferences, it also includes:

[0087] Regularly update the target user's portrait information and trigger vocabulary.

[0088] That is to say, in order to ensure the timeliness and accuracy of the target user portrait, a regular update strategy is implemented to conduct a comprehensive review and update of the target user portrait information. This process not only covers the changes in the user's static attributes (such as age growth, career changes, etc.), but also deeply tracks the new trends and preference evolution of the user's dynamic behavior.

[0089] At the same time, based on the updated portrait information, the trigger word library of the target user is optimized and updated synchronously. This process includes re-evaluating the user's interest keywords and adding new words or phrases based on the user's latest behavior patterns and preferences. Through this mechanism, the trigger word library can always maintain a high degree of relevance to the user's current needs, providing strong support for precision marketing.

[0090] Regularly updating the target user's portrait information and trigger word library not only enhances the insight into user needs, but also improves the flexibility and responsiveness of marketing activities. This means that marketing strategies can be adjusted more quickly to better meet the changing needs of users, thereby deepening user relationships, improving user experience, and maximizing marketing effects.

[0091] The following is a detailed example of the process of building and updating the user profile information and trigger word library:

[0092] 1) Data collection. The first task is to conduct comprehensive data collection, which covers two core data types of users: static data and dynamic data. Static data mainly includes key information such as the user's age, gender, occupation, income, etc., which provide an overview of the user's basic background. Dynamic data focuses on various behaviors of users in mobile banking applications, such as the frequency of logging into the application, the specific transaction types performed, and the browsing history. These data reveal the user's behavior patterns and activity.

[0093] 2) Data preprocessing and feature engineering. Before the data was input into the model, meticulous data preprocessing and feature engineering were performed. In the data preprocessing stage, data cleaning (removing outliers and filling missing values), data conversion (encoding categorical data into numerical data), and data standardization (ensuring that all input features are on a similar scale) were performed to ensure data quality and consistency. In the feature engineering stage, key features were extracted from user data, such as transaction frequency, page type visited, etc., and these features were converted into a format that can be processed by the neural network to further enhance the model's predictive ability.

[0094] 3) Model training and triggering vocabulary generation.

[0095] The preprocessed data is input into a specially trained machine learning model. In particular, RNN (recurrent neural network) and its improved version LSTM (long short-term memory network) in deep learning are selected to process this data. RNN is good at processing sequence data due to its cyclic structure, which enables the neural network to "remember" previous information, which is particularly critical for analyzing the historical behavior of users. LSTM further enhances this memory ability by introducing structures such as forget gate, input gate, output gate and cell state, thereby more effectively solving the long-term dependency problem.

[0096] That is, entering the model training phase, the LSTM network is trained using a large amount of user data. During the training process, the network adjusts weights to minimize prediction errors. This optimization process usually relies on backpropagation algorithms and gradient descent methods. After training, the LSTM model can accurately predict the user's behavior patterns and preferences based on their historical behavior data. Subsequently, a personalized trigger word library is generated based on these prediction results. These trigger words are closely related to the user's preferences and needs, such as "financial management" and "transfer", providing strong support for subsequent precision marketing.

[0097] 4) Model optimization and triggering vocabulary update.

[0098] In order to improve the prediction accuracy and generalization ability of the model, we continue to optimize the model, including regularization processing (such as dropout) and cross-validation. At the same time, we also regularly update the trigger word library to ensure that it can reflect the latest changes in user needs in real time. This update process relies on the continuous collection of user data, which is achieved by retraining the model and generating new trigger words. Through such a mechanism, we can ensure the timeliness and accuracy of user portraits and trigger word libraries, and provide banks and financial institutions with more accurate and personalized marketing strategies.

[0099] To sum up, it is possible to mine valuable information from complex user data and generate trigger words that are closely related to users' actual needs, thereby providing users with a more accurate and personalized service experience.

[0100] It should be noted that real-time monitoring of user behavior, especially voice monitoring, will cause concerns about user privacy leaks.

[0101] Based on this, another embodiment of the present application provides an information management promotion method.

[0102] See also Figure 2 ,include:

[0103] S201, the terminal monitors the voice data of the target user in real time; and after monitoring the trigger words in the trigger word library, the terminal sends the trigger words to the server.

[0104] It should be noted that the user's portrait information can also be constructed before step S201. The portrait information can be constructed by the server or by the terminal. There is no specific limitation here. It depends on the actual situation and is within the protection scope of this application.

[0105] In other words, the terminal intelligent voice monitoring module can be set on the terminal.

[0106] Specifically, in order to provide users with a more intelligent and convenient service experience on their mobile devices, an end-to-end intelligent voice monitoring module is deployed. This module is highly intelligent and sensitive, but also pays great attention to user privacy protection.

[0107] Optionally, when the target user uses the target application, the real-time monitoring function of the terminal is allowed to be enabled; when the target user does not use the target application, the real-time monitoring function of the terminal is prohibited from being enabled.

[0108] Specifically, the voice monitoring module is only activated when the user is using the mobile banking application. This design is intended to minimize the impact on the user's device performance and ensure that the user will not be disturbed when using other applications or functions normally.

[0109] When the user enters the mobile banking application, the voice monitoring module begins to analyze the user's voice data in real time. But it is worth noting that this module does not blindly monitor and record all the user's conversations, but only focuses on preset trigger words. These trigger words are usually closely related to the user's financial service needs, such as "transfer" and "financial management". By focusing only on these specific trigger words, other irrelevant voice content can be effectively filtered out, thereby providing more accurate service responses while ensuring user privacy and security.

[0110] Once the voice monitoring module detects the preset trigger word, it will immediately transmit this key information back to the server. However, in the process, the module will never store or transmit the user's complete conversation content. This design not only protects the privacy rights of users, but also ensures the efficiency and security of data transmission.

[0111] In summary, by deploying an intelligent voice monitoring module on the user's mobile device, a more intelligent and personalized financial service experience can be provided without infringing on the user's privacy.

[0112] At the terminal device level, a strict privacy protection mechanism has been carefully constructed to ensure that the user's sensitive data is protected at the highest level. Specifically, all voice data processing is done on the local device, which means that the user's sensitive data will never be transmitted to an external server, thus effectively avoiding the risk of data leakage.

[0113] During the system design process, we strictly follow the principle of data minimization and only collect data that is absolutely necessary to achieve specific functions. This principle not only helps to reduce unnecessary data collection, but also further reduces the possibility of user privacy leakage.

[0114] In order to give users more control, the voice monitoring function is turned on and off, and the trigger word setting is customized. Users can choose to turn off the voice monitoring function or adjust the trigger word settings at any time according to their needs and preferences, thereby achieving full control over their personal data and privacy.

[0115] Through this series of carefully designed technology combinations, we have successfully achieved the precise provision of personalized services while protecting user privacy. These services are not only highly accurate and timely, but can also be dynamically adjusted according to the actual needs of users, thereby significantly improving user satisfaction.

[0116] For banks and financial institutions, the implementation of this plan will undoubtedly bring more effective marketing results. By deeply understanding the preferences and needs of users, they can provide them with financial products and services that better meet their needs, thereby enhancing user loyalty and stickiness, and laying a solid foundation for the long-term development of financial institutions.

[0117] S202. The server combines the trigger words with the target user's portrait information for analysis to obtain analysis results; and customizes the marketing strategy for the target user based on the analysis results.

[0118] After receiving the trigger word information accurately captured by the end intelligent module, the server will immediately initiate a series of sophisticated data processing processes to provide users with unprecedented personalized service experience.

[0119] Data integration and analysis phase: Once the trigger word information is received by the server, it will be quickly integrated with the detailed data set of the user portrait. The user portrait contains diversified information such as the user's age, gender, occupation, transaction history, browsing habits, etc., providing us with in-depth insights into user behavior and preferences. By cross-analyzing these trigger word information with the user portrait, the server can reveal the user's current needs and potential interests, providing strong support for the subsequent marketing strategy formulation.

[0120] Personalized customization of marketing strategies: Based on the results of in-depth data analysis, the system begins to formulate personalized marketing strategies. These strategies not only closely revolve around user needs and preferences, but also fully consider user behavior patterns and consumption habits. For example, the system may recommend financial products that match the user's investment style based on the user's financial status and transaction history; or provide personalized discount information and customized services based on the user's daily consumption habits. Such marketing strategies are not only closer to the actual needs of users, but can also significantly improve user satisfaction and loyalty.

[0121] Personalized marketing content push: Carefully planned and customized personalized marketing content will be pushed to users in real time through the convenient channel of mobile banking applications or other communication methods such as SMS and email. These push contents not only accurately reflect the interests and needs of users, but also have high timeliness and interactivity. Users can view these personalized information through their mobile phones anytime and anywhere, and respond or make decisions based on their actual situation.

[0122] In summary, through a series of processes such as data integration and analysis, formulation of personalized marketing strategies, and personalized marketing content push, we can provide users with an unprecedented personalized service experience. This process not only improves the intelligence and personalization of services, but also ensures the accuracy and effectiveness of marketing strategies.

[0123] Optionally, it may also include:

[0124] S203: The server sends the marketing strategy to the terminal.

[0125] S204: The terminal displays the marketing strategy to the user.

[0126] The server sends the carefully formulated marketing strategy to the user's terminal device. This step is the key link between back-end analysis and front-end display. After the marketing strategy successfully reaches the terminal, the mobile banking application or other related interfaces on the device will immediately start the intelligent display mechanism.

[0127] Specifically, after comprehensively analyzing the user's static profile, dynamic behavior data, and real-time trigger words, the server will use advanced algorithms to generate highly personalized marketing strategies. These strategies are designed to accurately match the user's current needs and potential interests, ensuring that each push is highly relevant and attractive. Once the strategy is formulated, the server will immediately package it and send it to the user's terminal device.

[0128] After receiving the marketing strategy, the user's terminal device quickly starts the display process. The mobile banking application will use its own interface layout and interactive design to present the marketing strategy to the user in an intuitive and easy-to-understand way. Whether it is product recommendations, preferential information or customized services, it will be clear to users at a glance through exquisite graphics, vivid animations or intuitive charts.

[0129] During the display process, the terminal device will also take into full account the user's personalized preferences. For example, according to the user's visual preferences and reading habits, the font size, color matching and layout method are adjusted to ensure the best display effect of the marketing strategy.

[0130] In addition to intelligent display, terminal devices also provide convenient interactive functions. Users can easily view the detailed information of marketing strategies through simple operations such as clicking, sliding or voice, and even directly make subsequent operations such as purchases or consultations. This convenient interactive method not only improves the user experience, but also further promotes the conversion effect of marketing strategies.

[0131] In summary, the process of the server sending the marketing strategy to the terminal and the terminal intelligently displaying it is the key link in realizing personalized marketing services. This process not only ensures the accurate push and effective display of the marketing strategy, but also provides users with a convenient and pleasant interactive experience.

[0132] It should be noted that by using data mining and analysis technology, users' preferences and needs can be deeply understood. According to preset standards, such as the user's age, income level and purchase history, relevant product or service information can be accurately pushed. Furthermore, by tracking the user's specific behavior on the website or application, such as click operations, browsing time and page access sequence, the user's interests and potential needs can be effectively inferred. However, traditional data mining and analysis methods have limitations and mainly rely on historical data, which may be difficult to accurately capture the user's immediate needs and interest changes. At the same time, online behavior tracking may touch the red line of privacy protection without the user's explicit authorization. In addition, marketing strategies based on fixed rules often lack the necessary flexibility and are difficult to respond quickly to dynamic changes in user needs, which leads to users often receiving a large amount of marketing information that is out of touch with their actual needs, thereby causing negative user experience.

[0133] In this embodiment, machine learning technology is used to deeply analyze the user's static and dynamic portrait data to build a personalized trigger word library. This method can keenly capture the user's immediate needs and interests, and significantly improve the relevance and timeliness of marketing content. More advanced is that end-to-end intelligent technology is deployed on the user's mobile device to realize the real-time voice monitoring function, but it is strictly limited to the range of preset trigger words, so as to improve the accuracy of marketing while respecting and protecting the user's privacy rights to the greatest extent. Combining the trigger words captured in real time with the user's portrait information, the system uses advanced algorithms to dynamically generate highly personalized marketing content. This innovative practice not only greatly improves the effectiveness of marketing activities, but also optimizes the user experience, effectively reduces the interference of irrelevant marketing information, and brings users a smoother and more pleasant interactive experience.

[0134] like Figure 3 As shown in the figure, the information management promotion method is illustrated by examples:

[0135] (1) Data collection: Collect static and dynamic data of users.

[0136] (2) Data preprocessing: Clean, convert, and standardize the collected data.

[0137] (3) User portrait construction: Use the machine learning algorithm to analyze user data and obtain user portrait information.

[0138] (4) Trigger word library generation: Generate a trigger word library based on user profile information.

[0139] (5) The terminal performs voice monitoring. The terminal monitors and recognizes specific trigger words.

[0140] A privacy protection mechanism is set up on the terminal to ensure that data is stored on the terminal device. Only the trigger word is sent to the server, and other data is not sent to the server. The terminal device may not store user voice data.

[0141] (6) Real-time analysis: Analyze the user's profile data and monitoring data (trigger words) after the holiday to obtain the analysis structure.

[0142] (7) Marketing content production: Generate personalized marketing strategies and content based on the analysis results.

[0143] That is, provide high-quality user interaction experience and optimize user experience.

[0144] The following scenario setting is used to illustrate the information management promotion method:

[0145] In the process of exploring how to provide personalized marketing content for users, a specific scenario was set, and a detailed user data model and marketing process were built based on this scenario. The following is an in-depth analysis of this scenario:

[0146] User data sample.

[0147] Static portrait data: These data reflect the user's basic information and background, such as age, gender, occupation, and income level. Taking the sample user "Zhang San" as an example, his static portrait data is: 35-year-old male, working in the IT industry, with an annual income of 300,000.

[0148] Dynamic behavior data: These data record the user's behavior patterns on the mobile banking application, such as login frequency, transaction type, and page browsing history. Zhang San's dynamic behavior data shows that he logs into the mobile banking at least three times a week, frequently browses the financial product page, and occasionally makes large transfers.

[0149] Model training process.

[0150] During the model training process, static and dynamic data are first preprocessed. Static data encoding: We convert static data such as age, gender, occupation, and annual income into corresponding digital codes so that the model can recognize and process them. For example, Zhang San's age of 35 is directly encoded as 35, male is encoded as 1, IT industry is assumed to be encoded as 5, and annual income of 300,000 is encoded as 300,000. Dynamic data processing: For dynamic data, we encode according to the frequency and type of user behavior. For example, Zhang San's login frequency is 3 times a week, the frequency of browsing the financial product page is high, which is encoded as 2, and large transfer behavior is occasionally encoded as 1.

[0151] Next, these encoded data are integrated into feature vectors, such as [35, 1, 5, 300000, 3, 2, 1], for model training.

[0152] The LSTM model is trained using a training set containing data from multiple similar users. The model is able to learn how to predict a user's possible needs and preferences from static and dynamic profiles of the user. For example, the model may output a user's interest score for products such as wealth management, insurance, and time deposits.

[0153] After the model training is completed, it is applied to actual user interaction scenarios to provide personalized marketing content. The following are the detailed steps of the usage process:

[0154] Real-time data capture: Generate a trigger word library for Zhang San, including keywords such as "financial management, insurance, time deposits", etc. When Zhang San uses mobile banking, if he mentions one of these keywords in his voice, such as "I want to learn more about time deposits", the subsequent process is triggered.

[0155] End-to-end intelligent voice monitoring: The end-to-end intelligent module of the mobile banking application monitors Zhang San’s voice in real time, and when it captures the trigger word "fixed deposit", it sends it as input to the server.

[0156] Combining trigger words with user profiles: After receiving the trigger words, the server combines them with Zhang San’s user profile and uses the previously trained LSTM model for analysis. This step aims to extract key information from user profiles and real-time data to predict user needs and preferences.

[0157] Personalized marketing content generation: Based on the analysis results of the model, the system will generate personalized marketing strategies. For example, for Zhang San, the system may push the latest preferential information and product details about fixed deposits. These suggestions are generated based on his personal preferences and immediate needs.

[0158] Finally, Zhang receives customized term deposit product recommendations on his mobile banking app that not only match his personal preferences but also help him better understand and utilize the services offered by the bank.

[0159] Through this specific example, we can clearly see how to combine static and dynamic user portraits with real-time data and use the LSTM model to provide users with personalized marketing content. This approach not only improves marketing accuracy and user satisfaction, but also provides banks and financial institutions with more effective marketing strategies.

[0160] In this embodiment, by real-time tracking and analyzing the user's voice data and behavior patterns, the user's immediate interests and needs can be quickly understood and captured. This feature can provide users with marketing content that is more in line with their current preferences, thereby significantly improving the accuracy and effectiveness of marketing. In terms of protecting user privacy, end-to-end intelligent technology is used. This technology ensures that all user data is processed and analyzed on the local device, and only when the key trigger words are identified, the necessary data is transmitted. This approach minimizes the potential threat to user privacy and effectively enhances the user's trust in the service. It has excellent dynamic content adaptability; by continuously analyzing the user's voice and behavior data in real time, the user portrait and trigger word library can be continuously updated. This dynamic adjustment ensures that the marketing strategy can keep up with the changes in user needs, so that the content always remains highly relevant and attractive. In terms of data processing efficiency, it also performs well. With the help of end-to-end intelligent technology, local data is quickly processed, which significantly reduces the data transmission time and the processing pressure on the server side. This enables the system to respond to user needs more quickly and provide users with a near real-time personalized service experience.

[0161] It should be noted that traditional marketing systems mainly rely on historical behavior data (such as past purchase records and page views) to formulate marketing strategies. This approach has obvious limitations because it cannot capture users' current needs and interest changes in a timely manner. At the same time, when processing user data, traditional marketing systems often need to collect and analyze a large amount of personal information, which often raises users' privacy concerns, especially without the user's explicit consent.

[0162] This embodiment, by introducing real-time user behavior analysis and end-to-end intelligent voice monitoring technology, accurately captures users' immediate needs and interests. This innovative approach enables us to provide users with more timely and accurate marketing responses, thereby significantly improving marketing effectiveness. At the same time, a more cautious data processing method is adopted, processing and storing only key trigger words instead of the entire conversation content, thereby ensuring marketing effectiveness while maximizing the protection of users' privacy rights.

[0163] When applying machine learning algorithms to personalized marketing content, a common problem is how to accurately process personalized and diverse user data to avoid inaccurate predictions caused by insufficient generalization capabilities.

[0164] This embodiment combines real-time behavior analysis and terminal intelligence technology to significantly improve the ability to identify users' immediate needs. This innovative approach enables us to provide users with more accurate personalized services to meet their diverse needs.

[0165] That is to say, this embodiment effectively makes up for the shortcomings of existing technologies in processing user behavior data and personalized marketing by introducing real-time behavior analysis and terminal intelligence technology. This application provides a more efficient, accurate and user privacy-respecting personalized marketing solution, bringing users a better marketing experience.

[0166] Yet another embodiment of the present application provides an information management and promotion system.

[0167] See also Figure 4 , information management and promotion system, including:

[0168] A construction module 101 is used to construct the profile information of the target user;

[0169] The word library module 102 is used to process the static information and dynamic information in the portrait information of the target user to obtain the trigger word library of the target user;

[0170] The analysis module 103 is used to combine and analyze the trigger words and the portrait information of the target user after monitoring the trigger words in the trigger word library to obtain the analysis result;

[0171] The strategy module 104 is used to formulate a marketing strategy for target users based on the analysis results.

[0172] For details of the specific working process and principle of each of the above modules, please refer to the information management promotion method provided in the above embodiment, which will not be described here one by one. It depends on the actual situation and is within the protection scope of this application.

[0173] In this embodiment, the construction module 101 constructs the portrait information of the target user; the vocabulary module 102 processes the static information and dynamic information in the portrait information of the target user to obtain the trigger vocabulary of the target user; after monitoring the trigger words in the trigger vocabulary, the analysis module 103 combines the trigger words of the target user with the portrait information for analysis to obtain the analysis results; the strategy module 104 formulates a marketing strategy for the target user based on the analysis results; that is, by analyzing the user's voice data and behavior, it is possible to capture the user's immediate interests and needs in a timely manner, so that the marketing content is more in line with the user's current preferences, thereby greatly improving the accuracy of marketing.

[0174] Another embodiment of the present application provides a storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the information management promotion method as described in any one of the above embodiments is implemented.

[0175] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0176] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0177] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0178] Another embodiment of the present invention provides an electronic device, such as Figure 5 As shown, including:

[0179] One or more processors 201.

[0180] The storage device 202 stores one or more programs.

[0181] When one or more programs are executed by one or more processors 201 , the one or more processors 201 implement the information management promotion method as described in any one of the above embodiments.

[0182] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a non-transitory computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart.

[0183] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

[0184] Although several specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Certain features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination.

[0185] The above description is only a preferred embodiment of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present disclosure (but not limited to) by each other to form a technical solution.

[0186] The features recorded in the various embodiments in this specification can be replaced or combined with each other, and the same and similar parts between the various embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system or system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiment. The system and system embodiments described above are only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative work.

[0187] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in the above description according to function. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0188] The above description of the disclosed embodiments enables one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An information management promotion method, characterized in that: include: Build profile information of target users; Processing the static information and dynamic information in the portrait information of the target user to obtain a trigger word library of the target user; After monitoring the trigger words in the trigger word library, combining the trigger words of the target user with the portrait information for analysis to obtain an analysis result; A marketing strategy for the target users is formulated based on the analysis results.

2. The information management promotion method according to claim 1, characterized in that: The constructing of the target user's portrait information includes: Collect static data and dynamic data of the target user; wherein the static data includes at least one of the age, gender, occupation and income of the target user; and the dynamic data includes the behavior data of the target user in the target application; Construct the profile information of the target user based on the static data and dynamic data of the target user.

3. The information management promotion method according to claim 1, characterized in that: The processing of the static information and the dynamic information in the portrait information of the target user to obtain the trigger word library of the target user includes: The target user's portrait information is trained using a machine learning model to obtain a behavior recognition model; wherein the behavior recognition model is used to identify the target user's behavior pattern and preference based on the target user's portrait information; Based on the portrait information, the behavior pattern and the preference, a trigger word library of the target user is obtained.

4. The information management promotion method according to claim 3, characterized in that: After obtaining the trigger word library of the target user based on the portrait information, the behavior pattern and the preference, the method further includes: The target user's portrait information and trigger word library are updated regularly.

5. An information management promotion method, characterized in that: include: The terminal monitors the target user's voice data in real time; After monitoring the trigger words in the trigger word library, the trigger words are sent to the server; The server combines the trigger word with the target user's portrait information for analysis to obtain an analysis result; And customize the marketing strategy for the target users according to the analysis results.

6. The information management promotion method according to claim 5, characterized in that: Also includes: The server sends the marketing strategy to the terminal; The terminal displays the marketing strategy to the user.

7. The information management promotion method according to claim 5, characterized in that: When the target user uses the target application, the real-time monitoring function of the terminal is allowed to be turned on; when the target user does not use the target application, the real-time monitoring function of the terminal is prohibited from being turned on.

8. An information management and promotion system, characterized in that: include: Construction module, used to construct the target user's portrait information; A word library module, used to process the static information and dynamic information in the portrait information of the target user to obtain a trigger word library of the target user; An analysis module, configured to combine and analyze the trigger words of the target user with the portrait information after monitoring the trigger words in the trigger word library to obtain an analysis result; The strategy module is used to formulate a marketing strategy for the target user according to the analysis result.

9. An electronic device, characterized in that: include: one or more processors; a storage device having one or more programs stored thereon; When one or more programs are executed by one or more processors, the one or more processors implement the information management promotion method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: A computer program is stored thereon, wherein when the computer program is executed by a processor, the information management and promotion method according to any one of claims 1 to 7 is implemented.

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