Real-time data analysis and adjustment method for Internet promotion

Abstract

The invention discloses a real-time data analysis and adjustment method for Internet promotion and propaganda, which is characterized in that key data such as click rate, conversion rate, user behavior and the like of a promotion activity are acquired in real time by utilizing a real-time data acquisition technology, so that an enterprise can quickly know the actual promotion effect, analysis is not needed after the activity is finished, and the promotion efficiency is improved. Real-time data feedback enables an enterprise to insight market changes in time, when market trends or user behaviors change, strategies can be rapidly adjusted, weak links and potential opportunities in popularization can be accurately recognized based on real-time data analysis, the enterprise can finely adjust the strategies, real-time data and visual reports according to the strategies, and powerful support is provided for decision making. A decision maker can quickly make accurate judgment, decision making efficiency and accuracy are improved, user feedback and data analysis results are brought into subsequent strategies through a closed-loop feedback mechanism, a continuous optimization cycle is formed, and then the popularization effect and market competitiveness are improved.

Description

Technical Field

[0001] The present invention relates to the field of Internet technology, and in particular to a real-time data analysis and adjustment method for Internet promotion and publicity. Background Art

[0002] With the rapid development of Internet technology, Internet promotion and publicity has become an important means of corporate marketing. At present, there are many ways of Internet promotion in the market, such as search engine advertising, social media advertising, content marketing, etc. However, these promotion methods often face many challenges in practical application.

[0003] The existing search engine promotion method refers to the method of using search engines, classified directories and other network tools with online information retrieval functions to promote websites. With the continuous development and popularization of search engine technology, the position of search engine promotion in network marketing is becoming increasingly important and is being paid attention to by more and more companies.

[0004] The above-mentioned technologies still have the following drawbacks: the data of promotional activities often need to be collected and analyzed after the activities are over, which makes it impossible for companies to understand the promotion effects in a timely manner and make rapid adjustments based on market changes. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a real-time data analysis and adjustment method for Internet promotion and publicity, which solves the problem that the data of promotion activities often need to be collected and analyzed after the activities are over, which makes it impossible for enterprises to understand the promotion effects in a timely manner and make rapid adjustments according to market changes.

[0006] The above technical objectives of the present invention are achieved through the following technical solutions:

[0007] A real-time data analysis and adjustment method for Internet promotion and publicity, comprising the following steps:

[0008] S1: Data collection: collect promotion activity data from multiple Internet channels in real time, including click-through rate, conversion rate, user behavior trajectory and comment information, etc., to ensure the real-time, accuracy and comprehensiveness of the data;

[0009] S2: Data preprocessing: cleaning, integrating and formatting the collected raw data to remove duplicate, erroneous or noisy data and improve data quality;

[0010] S3: Intelligent analysis, using machine learning algorithms and data analysis techniques to conduct in-depth mining and analysis of pre-processed data, identify key influencing factors, predict trends and evaluate promotion effects;

[0011] S4: Strategy adjustment: Based on the results of intelligent analysis, the promotion strategy is automatically or semi-automatically adjusted using preset adjustment rules or algorithms, including the geographical location, time period, target audience, and advertising content of advertising, so as to improve the pertinence and effectiveness of promotion activities;

[0012] S5: Visual report generation: Generate visual reports with data analysis results in the form of charts, trend lines, etc., intuitively display key indicators, trend analysis and strategic recommendations, and provide a scientific basis for decision-making;

[0013] S6: Closed-loop feedback and continuous optimization, integrating user feedback, forming a closed-loop optimization mechanism through continuous data analysis and strategy adjustment, constantly optimizing promotion strategies based on new data analysis and user feedback results, and iteratively updating analysis models and optimization algorithms to continuously improve promotion effects and the performance of optimization methods.

[0014] By adopting the above technical solutions, a systematic and dynamic Internet promotion and publicity data analysis and adjustment plan is provided, aiming to improve the pertinence and effectiveness of promotion activities and continuously optimize the promotion effect.

[0015] Preferably, in S1, the data collection is to obtain data from the advertising platform through an API interface, and to collect user behavior data from social media using web crawler technology.

[0016] By adopting the above technical solution and collecting data through API interface and web crawler technology, the efficiency and comprehensiveness of data collection are improved. The technical effect is that data from multiple Internet channels can be obtained in real time, providing a rich and accurate data basis for subsequent analysis.

[0017] Preferably, in S2, the data preprocessing includes data cleaning, data integration and data formatting, wherein data cleaning is used to remove duplicate, erroneous or noisy data, data integration is used to merge data from different sources, and data formatting is used to convert data into a format suitable for subsequent analysis and processing.

[0018] By adopting the above technical solutions, data quality is ensured through data cleaning, integration and formatting, which improves the accuracy and availability of data and provides reliable data support for subsequent intelligent analysis.

[0019] Preferably, in S3, the intelligent analysis uses machine learning algorithms such as random forests, neural networks or support vector machines, combined with data analysis techniques such as time series analysis and cluster analysis, to perform in-depth mining and analysis on the preprocessed data.

[0020] By adopting the above-mentioned technical solutions and using machine learning algorithms and data analysis technologies to conduct in-depth mining and analysis of data, it is possible to identify key influencing factors, predict trends and evaluate promotion effects, providing a scientific basis for strategy adjustments.

[0021] Preferably, in S4, the strategy adjustment is to flexibly adjust the geographical location, time period, target audience, advertising content, etc. of the advertising delivery according to user behavior, market trends and user feedback, and verify the adjustment effect through methods such as A / B testing.

[0022] By adopting the above technical solutions and flexibly adjusting promotion strategies according to user behavior, market trends and user feedback, we can quickly respond to market changes and improve the pertinence and effectiveness of promotion activities.

[0023] Preferably, in S5, the visualization report is presented in the form of charts, trend lines, heat maps, and interactive data exploration tools, so as to facilitate decision makers to quickly understand the promotion effect and make decisions.

[0024] By adopting the above technical solution, by presenting the data analysis results in the form of charts, trend lines, etc., it is easier for decision makers to understand, improves the readability and intuitiveness of the report, and helps decision makers make decisions quickly.

[0025] Preferably, in S6, the closed-loop feedback mechanism includes the collection, processing, integration and response of user feedback, ensuring that user feedback is effectively incorporated into subsequent data analysis and strategy adjustment to form a continuous optimization cycle.

[0026] By adopting the above-mentioned technical solutions and integrating user feedback, a continuous optimization cycle is formed, which can continuously optimize the promotion strategy according to user feedback and market changes and improve the promotion effect.

[0027] Preferably, the method also includes data security and privacy protection measures, using encryption technology, access control and data desensitization to ensure the security and privacy of user data during data collection, analysis, storage and transmission.

[0028] By adopting the above technical solutions and taking measures such as encryption technology, access control and data desensitization to protect user data security, the security and privacy of user data are enhanced, and user trust is improved.

[0029] In summary, the present invention mainly has the following beneficial effects:

[0030] By utilizing real-time data collection technology, key data such as click-through rate, conversion rate, user behavior, etc. of promotional activities can be instantly obtained, so that enterprises can quickly understand the effectiveness of promotion without having to analyze after the activity ends. Real-time data feedback allows enterprises to gain instant insight into market changes. When market trends or user behaviors change, strategies can be adjusted quickly to avoid waste of resources. Based on real-time data analysis, weak links and potential opportunities in promotion can be accurately identified. Enterprises can fine-tune strategies accordingly, such as optimizing the time, region and target audience of advertising to improve the effect. Real-time data and visual reports provide strong support for decision-making, enabling decision makers to make accurate judgments quickly and improve decision-making efficiency and accuracy. Through a closed-loop feedback mechanism, user feedback and data analysis results can be incorporated into subsequent strategies to form a continuous optimization cycle, allowing enterprises to continuously learn and improve promotion methods, thereby improving promotion effects and market competitiveness. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a system diagram of the present invention. DETAILED DESCRIPTION

[0032] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only 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.

[0033] refer to Figure 1 , a real-time data analysis and adjustment method for Internet promotion and publicity, comprising the following steps:

[0034] S1: Data collection: collect promotion activity data from multiple Internet channels in real time, including click-through rate, conversion rate, user behavior trajectory and comment information, etc., to ensure the real-time, accuracy and comprehensiveness of the data;

[0035] S2: Data preprocessing: cleaning, integrating and formatting the collected raw data to remove duplicate, erroneous or noisy data and improve data quality;

[0036] S3: Intelligent analysis, using machine learning algorithms and data analysis techniques to conduct in-depth mining and analysis of pre-processed data, identify key influencing factors, predict trends and evaluate promotion effects;

[0037] S4: Strategy adjustment: Based on the results of intelligent analysis, the promotion strategy is automatically or semi-automatically adjusted using preset adjustment rules or algorithms, including the geographical location, time period, target audience, and advertising content of advertising, so as to improve the pertinence and effectiveness of promotion activities;

[0038] S5: Visual report generation: Generate visual reports with data analysis results in the form of charts, trend lines, etc., intuitively display key indicators, trend analysis and strategic recommendations, and provide a scientific basis for decision-making;

[0039] S6: Closed-loop feedback and continuous optimization: Integrate user feedback, form a closed-loop optimization mechanism through continuous data analysis and strategy adjustment, continuously optimize promotion strategies based on new data analysis and user feedback results, and iteratively update analysis models and optimization algorithms to continuously improve promotion effects and the performance of optimization methods;

[0040] It also includes data security and privacy protection measures, using encryption technology, access control, data desensitization and other methods to ensure the security and privacy of user data during data collection, analysis, storage and transmission.

[0041] refer to Figure 1 In S1, the data collection is to obtain data from the advertising platform through the API interface, and use web crawler technology to collect user behavior data from social media. In S2, the data preprocessing includes data cleaning, data integration and data formatting, wherein data cleaning is used to remove duplicate, erroneous or noisy data, data integration is used to merge data from different sources, and data formatting is used to convert data into a format suitable for subsequent analysis and processing. In S3, the intelligent analysis uses machine learning algorithms such as random forests, neural networks or support vector machines, combined with data analysis techniques such as time series analysis and cluster analysis, to preprocess the data. The data is deeply mined and analyzed. In S4, the strategy adjustment is to flexibly adjust the geographical location, time period, target audience, advertising content, etc. of the advertising according to user behavior, market trends and user feedback, and verify the adjustment effect through methods such as A / B testing. In S5, the visualization report is presented in the form of charts, trend lines, heat maps and interactive data exploration tools, which is convenient for decision makers to quickly understand the promotion effect and make decisions. In S6, the closed-loop feedback mechanism includes the collection, processing, integration and response of user feedback, ensuring that user feedback is effectively incorporated into subsequent data analysis and strategy adjustment to form a continuous optimization cycle.

[0042] Working principle: Please refer to Figure 1As shown, when used, API interfaces, web crawlers and other technologies are used to collect data related to promotion activities from multiple Internet channels in real time. These data include user behavior data, advertising effect data and market trend data. The collected raw data is cleaned, duplicate, erroneous or invalid data is removed, and data from different sources and in different formats are integrated to form a unified and structured data set for subsequent analysis. Machine learning algorithms and data analysis techniques are used to deeply mine and analyze the pre-processed data, identify key influencing factors such as user preferences and market trends, evaluate the overall effect of promotion activities, predict future trends, and provide a scientific basis for strategy adjustments. Based on the results of intelligent data analysis, automatic or semi-automatic Automatically adjust the promotion strategy. The adjustment may include the geographical location, time period, target audience, advertising content, budget allocation, etc. of the advertisement. Verify the adjustment effect through A / B testing and other methods to ensure the effectiveness of the strategy. Generate visual reports with data analysis results in the form of charts, trend lines, etc., intuitively display key indicators, trend analysis and strategic recommendations, provide scientific basis for decision makers, help them quickly understand the promotion effect and make decisions, integrate user feedback, form a closed-loop optimization mechanism through continuous data analysis and strategy adjustment, continuously optimize the promotion strategy according to new data analysis and user feedback results, iteratively update the analysis model and optimization algorithm, and continuously improve the promotion effect and the performance of the optimization method through continuous optimization cycle.

[0043] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A real-time data analysis and adjustment method for Internet promotion and publicity, characterized in that: The following steps are involved: S1: Data collection: collect promotion activity data from multiple Internet channels in real time, including click-through rate, conversion rate, user behavior trajectory and comment information, etc., to ensure the real-time, accuracy and comprehensiveness of the data; S2: Data preprocessing: cleaning, integrating and formatting the collected raw data to remove duplicate, erroneous or noisy data and improve data quality; S3: Intelligent analysis, using machine learning algorithms and data analysis techniques to conduct in-depth mining and analysis of pre-processed data, identify key influencing factors, predict trends and evaluate promotion effects; S4: Strategy adjustment: Based on the results of intelligent analysis, the promotion strategy is automatically or semi-automatically adjusted using preset adjustment rules or algorithms, including the geographical location, time period, target audience, and advertising content of advertising, so as to improve the pertinence and effectiveness of the promotion activities; S5: Visual report generation: Generate visual reports with data analysis results in the form of charts, trend lines, etc., intuitively display key indicators, trend analysis and strategic recommendations, and provide a scientific basis for decision-making; S6: Closed-loop feedback and continuous optimization, integrating user feedback, forming a closed-loop optimization mechanism through continuous data analysis and strategy adjustment, constantly optimizing promotion strategies based on new data analysis and user feedback results, and iteratively updating analysis models and optimization algorithms to continuously improve promotion effects and the performance of optimization methods.

2. A real-time data analysis and adjustment method for Internet promotion and publicity according to claim 1, characterized in that: In S1, the data collection is to obtain data from the advertising platform through the API interface, and use web crawler technology to collect user behavior data from social media.

3. A real-time data analysis and adjustment method for Internet promotion and publicity according to claim 1, characterized in that: In S2, the data preprocessing includes data cleaning, data integration and data formatting, wherein data cleaning is used to remove duplicate, erroneous or noisy data, data integration is used to merge data from different sources, and data formatting is used to convert data into a format suitable for subsequent analysis and processing.

4. The real-time data analysis and adjustment method for Internet promotion and publicity according to claim 1, characterized in that: In S3, the intelligent analysis uses machine learning algorithms such as random forests, neural networks or support vector machines, combined with data analysis techniques such as time series analysis and cluster analysis, to conduct in-depth mining and analysis of the pre-processed data.

5. The real-time data analysis and adjustment method for Internet promotion and publicity according to claim 1, characterized in that: In S4, the strategy adjustment is to flexibly adjust the geographical location, time period, target audience, advertising content, etc. of the advertising delivery according to user behavior, market trends and user feedback, and verify the adjustment effect through methods such as A / B testing.

6. The real-time data analysis and adjustment method for Internet promotion and publicity according to claim 1, characterized in that: In S5, the visualization report is presented in the form of charts, trend lines, heat maps, and interactive data exploration tools, which helps decision makers quickly understand the promotion effect and make decisions.

7. The real-time data analysis and adjustment method for Internet promotion and publicity according to claim 1, characterized in that: In S6, the closed-loop feedback mechanism includes the collection, processing, integration and response of user feedback, ensuring that user feedback is effectively incorporated into subsequent data analysis and strategy adjustment to form a continuous optimization cycle.

8. The method according to any one of claims 1 to 7, characterized in that It also includes data security and privacy protection measures, using encryption technology, access control, data desensitization and other methods to ensure the security and privacy of user data during data collection, analysis, storage and transmission.

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