A big data-based search engine optimization method and a readable storage medium

Abstract

The application relates to the technical field of search engine optimization, in particular to a search engine optimization method based on big data and a readable storage medium. The method comprises the following steps: determining innovative keywords through market and user demand analysis, positioning a project or a product, including AI and big data analysis, so as to improve the innovation and competitiveness of the product or service, collecting technical application effect data and establishing a continuous monitoring mechanism to track the effect of all steps, iteratively optimizing according to market changes and user feedback, and forming a closed loop. The application achieves the purpose of comprehensively improving the search engine optimization effect, and the specific performance is that the keyword ranking is improved, the traffic is increased, the user experience is improved, the mobile device adaptation optimization is optimized, and the strategy is continuously iteratively optimized.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of search engine optimization, and in particular to a search engine optimization method based on big data and a readable storage medium. BACKGROUND

[0002] Search engine optimization (SEO) is an important part of internet marketing. It improves the ranking of a website in search engines by optimizing the content and structure of the website, thereby attracting more traffic and potential customers. With the rapid development of internet technology, SEO has developed from simple keyword stuffing to a highly data-driven and intelligent process. Businesses and individual website managers increasingly rely on SEO to improve online visibility and brand influence, which not only helps to increase website traffic, but also improves user satisfaction and conversion rates. In existing SEO practices, common methods include keyword research and layout, content creation and optimization, link building, and user experience improvement. Specifically, keyword research is usually completed through manual analysis and tool assistance, determining target keywords and distributing them reasonably throughout the website; content creation relies on a professional editorial team to generate high-quality, original articles, while using title tags, lists, and other formats to optimize content structure; link building mainly builds internal and external links to enhance the authority and relevance of the website; and user experience is optimized through web design, interaction methods, and response time to improve user access experience. However, traditional SEO methods have some obvious shortcomings. For example, keyword research often lacks depth and breadth, making it difficult to fully cover potential related keywords; the content creation and optimization process is time-consuming and difficult to maintain long-term consistency and high quality; link building channels are limited, making it difficult to continuously obtain high-quality external links; and user experience optimization is often limited to superficial changes, failing to fundamentally improve user satisfaction and loyalty. These problems limit the maximization of SEO effectiveness, making it difficult for websites to stand out in fierce competition. Therefore, a more systematic and intelligent SEO method is needed to improve the search performance and user experience of websites. SUMMARY

[0003] The purpose of the present application is to overcome the above technical problems, and a search engine optimization method based on big data and a readable storage medium are provided

[0004] A big data-based search engine optimization method, comprising: S1: determining innovative keywords through market and user demand analysis, positioning the project or product; S2: based on the keywords determined in S1, creating high-quality content and optimizing to improve user appeal and search engine ranking; S3: by analyzing user behavior on products or content, collecting data, understanding user needs and preferences, providing basis for subsequent link strategy and data analysis; S4: according to the user behavior data collected in S3, formulating link strategy, enhancing the network visibility of content and user participation, and collecting link effect data; S5: integrating all data collected in S1 to S4, conducting in-depth analysis, identifying trends and problems, adjusting keywords, content, links and user experience strategy to improve overall effect; S6: based on the analysis results of S5, optimizing user experience on mobile devices, improving page loading speed, and ensuring good performance on mobile devices, while collecting optimized performance data; S7: exploring and applying the latest technologies, including AI and big data analysis, to improve the innovation and competitiveness of products or services, while collecting technology application effect data; S8: establishing a continuous monitoring mechanism to track the effect of all steps, iterating optimization according to market changes and user feedback, forming a closed loop. By adopting the above technical scheme, the method can comprehensively improve the effect of search engine optimization. Specifically, by analyzing market and user demand, determining innovative keywords, and positioning the project or product, the diversity and accuracy of keywords are ensured, and the ranking and traffic of the website in the search engine are improved. Based on the keywords determined in S1, high-quality content is created and optimized to improve user appeal and search engine ranking, which improves the appeal of the content and user experience, and enhances the user's dwell time and interaction frequency. By analyzing user behavior on products or content, collecting data, understanding user needs and preferences, and providing basis for subsequent link strategy and data analysis, the authority and credibility of the website are increased, and the trust of the search engine is further improved. According to the user behavior data collected in S3, link strategy is formulated, network visibility of content and user participation are enhanced, and link effect data is collected. Through in-depth mining of user behavior, the interaction design and content presentation of the website are optimized, and user satisfaction is significantly improved. Integrating all data collected in S1 to S4, conducting in-depth analysis, identifying trends and problems, adjusting keywords, content, links and user experience strategy to improve overall effect makes the SEO strategy more flexible and efficient, which can quickly adapt to market changes and user needs. Based on the analysis results of S5, the user experience on mobile devices is optimized, the page loading speed is improved, and the good performance on mobile devices is ensured, while the optimized performance data is collected to ensure the good performance of the website on various devices and improve the access experience of mobile users.Exploring and applying the latest technologies, including AI and big data analysis, to enhance the innovation and competitiveness of products or services, while collecting data on the effectiveness of technology applications introduces advanced technologies such as AI, improving the degree of automation and intelligence of optimization. Establishing a continuous monitoring mechanism to track the effectiveness of all steps and iterating optimization based on market changes and user feedback forms a closed loop, ensuring continuous improvement and optimization of the entire SEO strategy, forming a complete closed-loop system. Preferably, the determination of innovative keywords based on market and user demand analysis for project or product positioning includes the following steps: S11: semantic keyword analysis: using NLP tools, deeply analyze the semantic association of keywords, identify potential synonyms and related words, and build a comprehensive keyword library; S12: keyword trend prediction: use AI technology to predict keyword trends and dynamically adjust keyword strategies; S13: keyword layout optimization: reasonably distribute keywords in website meta tags, URLs, and content to ensure natural integration of keywords and avoid stacking; S14: keyword effect monitoring and adjustment: regularly evaluate the ranking and traffic of keywords and adjust keyword strategies based on the results to form a closed loop. By adopting the above technical solutions, the determination of innovative keywords based on market and user demand analysis for project or product positioning can effectively improve the coverage and accuracy of keywords and enhance the search visibility and traffic of the website. Specifically, semantic keyword analysis using NLP tools can identify more potential related words and build a more comprehensive keyword library; using AI technology to predict keyword trends and dynamically adjust keyword strategies ensures that keywords always meet market demand; reasonably distributing keywords in website meta tags, URLs, and content avoids excessive stacking and improves the natural integration of keywords; regularly evaluating the ranking and traffic of keywords and adjusting strategies based on data results in a timely manner forms an effective closed-loop management, thereby continuously improving SEO effectiveness. Preferably, the creation of high-quality content based on the keywords determined in S1 and optimization to improve user appeal and search engine ranking includes the following steps: S21: AI-assisted content creation: combine AI tools and professional editors to generate high-quality, original content to ensure the accuracy and appeal of the content; S22: content structure optimization: use title tags, lists, paragraphs, etc. to make the content structure clear and easy for search engines to understand, while improving user experience; S23: content personalization: use AI to analyze user preferences and optimize content form and style to provide personalized content; S24: content effect monitoring and optimization: evaluate the reading volume, sharing volume, and user feedback of the content and optimize content strategies based on the results to form a closed loop.By adopting the above technical solutions, the AI-assisted content creation can generate high-quality and original content, ensuring the accuracy and attractiveness of the content; the content structure optimization makes the content structure clearer, facilitating the understanding of search engines and improving user experience; the content personalization uses AI to analyze user preferences, optimizing content form and style to provide content that better meets user needs; and the content effect monitoring and optimization evaluates the reading volume, sharing volume and user feedback of the content, timely adjusts the content strategy, forms a closed loop, and ensures the effectiveness and continuous improvement of the content strategy. Preferably, the collecting data by analyzing user behavior on the product or content, understanding user needs and preferences, and providing basis for subsequent link strategy and data analysis includes the following steps: S31: internal link intelligent optimization: automatically identifying and optimizing internal link structure through algorithms to ensure clear link logic between internal pages; S32: external link quality improvement: using big data analysis to evaluate the quality and relevance of external links to ensure that the acquired links come from authoritative and relevant websites; S33: link building channel exploration: exploring new link building channels such as industry forums and social media to improve the authority of the website; S34: link effect monitoring and adjustment: monitoring the source and quality of links and adjusting link strategies based on the results to form a closed loop. By adopting the above technical solutions, the internal link structure rationality of the website can be significantly improved, ensuring clear link logic between internal pages and enhancing user navigation experience. At the same time, through big data analysis to evaluate the quality and relevance of external links, it is ensured that the acquired links come from authoritative and relevant websites, further improving the authority of the website. In addition, exploring new link building channels such as industry forums and social media helps to expand the influence and popularity of the website. Finally, by continuously monitoring the source and quality of links and adjusting link strategies based on the results, a closed loop management is formed to ensure the effectiveness and sustainability of the link strategy. Preferably, the developing link strategies based on the user behavior data collected in S3 to enhance the network visibility and user engagement of the content, while collecting link effect data includes the following steps: S41: personalized recommendation system: providing personalized content recommendations based on user historical behavior and preferences to increase user stickiness; S42: user behavior modeling: using big data to analyze user behavior patterns on the website to optimize website layout and content and improve user satisfaction; S43: AI predicts user behavior: using AI to predict user behavior to optimize user experience in advance; S44: user behavior monitoring and optimization: continuously monitoring user behavior and optimizing user experience strategies based on the results to form a closed loop. By adopting the above technical solutions, the personalized recommendation system can provide content recommendations that better meet user interests based on user historical behavior and preferences, thereby increasing user stickiness and dwell time. User behavior modeling uses big data to analyze user behavior patterns on the website to optimize website layout and content, improving user satisfaction and interaction experience.The AI prediction of user behavior can identify the possible behavior patterns of users in advance, optimize the user experience in time, and improve the user satisfaction and loyalty. The user behavior monitoring and optimization continuously monitor the user behavior data, constantly adjust and optimize the user experience strategy according to the analysis results, form a closed-loop optimization process, and ensure the continuous improvement and promotion of the user experience. Preferably, the integration of all data collected in S1 to S4 is performed for deep analysis to identify trends and problems, and the keywords, content, links and user experience strategy are adjusted to improve the overall effect, including the following steps: S51: real-time data analysis: using real-time data analysis tools to quickly respond to market changes and user needs, and adjusting the SEO strategy; S52: predictive analysis: using machine learning algorithms to predict future search trends and user behavior, and optimizing the website content and structure in advance; S53: strategy effect monitoring and iteration: regularly evaluating the effect of the SEO strategy, including keyword ranking, traffic, conversion rate and other indicators, and adjusting the strategy according to the results to form a closed loop. By using the above technical solution, real-time data analysis can quickly respond to market changes and user needs, adjust the SEO strategy in time, and improve the flexibility and adaptability of the strategy; predictive analysis uses machine learning algorithms to accurately predict future search trends and user behavior, and optimizes the website content and structure in advance to enhance the forward-looking nature of the strategy; strategy effect monitoring and iteration regularly evaluate the effect of the SEO strategy, including keyword ranking, traffic, conversion rate and other key indicators, and adjust the strategy according to the evaluation results to ensure the continuous optimization and effectiveness of the strategy. Preferably, based on the analysis results of S5, the user experience on mobile devices is optimized, the page loading speed is improved, and good performance on mobile devices is ensured, and the performance data after optimization is collected, including the following steps: S61: responsive design: ensuring consistent and excellent user experience on different devices; S62: page speed optimization: optimizing images, compressing code, using CDN, etc. to improve page loading speed; S63: mobile optimization effect monitoring and adjustment: monitoring the user experience and page loading speed on mobile devices, and optimizing the mobile strategy according to the results to form a closed loop. By using the above technical solution, responsive design ensures that the website can provide consistent and high-quality user experience on different devices, and page speed optimization significantly improves the page loading speed by optimizing images, compressing code and using CDN, etc., thereby improving the user's access satisfaction and retention rate. At the same time, the mobile optimization effect monitoring and adjustment mechanism can monitor the user experience and page loading speed on mobile devices in real time, optimize the mobile strategy in time according to the data feedback, form a closed-loop management, and further enhance the effect of mobile optimization.Preferably, the exploration and application of the latest technology, including AI and big data analysis, to improve the innovation and competitiveness of products or services, while collecting technical application effect data includes the following steps: S71: AI generates meta description: automatically generate attractive meta description using AI technology to improve click-through rate; S72: intelligent content update: based on real-time data analysis, automatically update content to ensure the timeliness and relevance of website content; S73: technical application effect monitoring and optimization: evaluate the application effect of AI and innovative technology, and adjust the technology strategy according to the results to form a closed loop. By adopting the above technical solutions, AI-generated meta description can significantly improve the click-through rate of web pages and attract more users to visit the website; intelligent content update ensures the timeliness and relevance of website content, improving user satisfaction and stickiness; the technical application effect monitoring and optimization mechanism allows continuous adjustment of technology strategies based on actual results, ensuring the continuous effectiveness and innovation of SEO optimization methods. Preferably, the establishment of a continuous monitoring mechanism to track the effects of all steps and iterative optimization according to market changes and user feedback to form a closed loop includes the following steps: S81: SEO effect monitoring: regularly evaluate the effectiveness of SEO strategies, including keyword ranking, traffic, conversion rate and other indicators; S82: strategy iterative optimization: continuously optimize SEO strategies based on monitoring results to ensure the innovation and effectiveness of the strategies; S83: overall strategy effect monitoring and iteration: comprehensively evaluate the overall effect of SEO strategies and make strategy iteration based on the results to form a closed loop. By adopting the above technical solutions, comprehensive monitoring and continuous optimization of SEO strategies can be achieved. Specifically, regularly evaluate the effectiveness of SEO strategies, including key indicators such as keyword ranking, traffic, conversion rate, etc., to ensure the effectiveness and innovation of the strategies; based on the monitoring results, continuously adjust and optimize the SEO strategies to keep them in the best state; at the same time, comprehensively evaluate the overall effect of SEO strategies and make strategy iteration based on actual conditions to form a closed loop management, thereby comprehensively improving the search engine performance of the website and user satisfaction. A readable storage medium stores a computer program, and the computer program is executed by a processor to perform any one of the search engine optimization methods based on big data.By adopting the above technical solutions, the readable storage medium can store and execute the big data-based search engine optimization method, which covers determining innovative keywords through market and user demand analysis, positioning projects or products, creating high-quality content based on the keywords determined in S1, and optimizing to improve user appeal and search engine ranking, collecting data by analyzing user behavior on products or content, understanding user needs and preferences, providing a basis for subsequent link strategy and data analysis, developing link strategies according to user behavior data collected in S3, enhancing content network visibility and user engagement, while collecting link effect data, integrating all data collected in S1 to S4, performing in-depth analysis, identifying trends and problems, adjusting keyword, content, link and user experience strategies to improve overall effectiveness, optimizing user experience on mobile devices based on the analysis results of S5, improving page loading speed to ensure good performance on mobile devices, while collecting optimized performance data, exploring and applying the latest technologies including AI and big data analysis to improve the innovation and competitiveness of products or services, while collecting technology application effect data and establishing a continuous monitoring mechanism to track the effectiveness of all steps, iterating and optimizing according to market changes and user feedback, forming a closed loop, etc., thereby comprehensively improving the search engine ranking and user experience of the website, ensuring the effectiveness and sustainability of the SEO strategy.

[0005] In summary, the present application includes at least one of the following beneficial technical effects: 1. By analyzing market and user demand, determining innovative keywords, and positioning projects or products, especially semantic keyword analysis, keyword trend prediction and keyword layout optimization, potential keywords can be more accurately captured and utilized, and keyword strategy can be dynamically adjusted to effectively improve website ranking and traffic in search engines. 2. Based on the keywords determined in S1, high-quality content is created and optimized to improve user appeal and search engine ranking, combining AI-assisted content creation, content structure optimization and content personalization, not only can generate high-quality, original content, but also can optimize content form and style according to user preferences, significantly improving content appeal and user satisfaction. 3. By analyzing user behavior on products or content, collecting data, understanding user needs and preferences, and providing a basis for subsequent link strategy and data analysis, through internal link intelligent optimization, external link quality improvement and link construction channel exploration, a more rich and authoritative link network can be built to enhance the authority and relevance of the website, further improving search engine ranking and user trust. BRIEF DESCRIPTION OF DRAWINGS

[0006] Figure 1 is a flowchart of a big data-based search engine optimization method in an embodiment of the present application.

[0007] Figure 2is a flow chart of a sub-step of step S1 in the embodiment of the present application.

[0008] Figure 3 is a flow chart of a sub-step of step S1 in the embodiment of the present application.

[0009] Figure 4 is a flow chart of a sub-step of step S1 in the embodiment of the present application.

[0010] Figure 5 is a flow chart of a sub-step of step S1 in the embodiment of the present application.

[0011] Figure 6 is a flow chart of a sub-step of step S1 in the embodiment of the present application.

[0012] Figure 7 is a flow chart of a sub-step of step S1 in the embodiment of the present application.

[0013] Figure 8 is a flow chart of a sub-step of step S1 in the embodiment of the present application.

[0014] Figure 9 is a flow chart of a sub-step of step S1 in the embodiment of the present application. DETAILED DESCRIPTION

[0015] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings, and the described embodiments are only possible technical implementations of the present application, not all possible implementations. Those skilled in the art can obtain other embodiments by combining the embodiments of the present application without creative labor, and these embodiments are also within the protection scope of the present application. The present inventors find that the existing search engine optimization method lacks systematicness and innovation, and cannot effectively improve the search performance and user experience of a website. Therefore, the present application mainly adopts the following search engine optimization method based on big data to achieve the effect of comprehensively improving the search performance and user experience of a website, and the present application will be described in further detail below. Embodiment 1 Figure 1The embodiments of the present application provide a search engine optimization method based on big data, which includes the following aspects: through market and user demand analysis, determine innovative keywords, and position projects or products (S1), based on the keywords determined in S1, create high-quality content, and optimize to improve user appeal and search engine ranking (S2), through analyzing user behavior on products or content, collect data, understand user needs and preferences, and provide basis for subsequent link strategy and data analysis (S3), according to the user behavior data collected in S3, develop link strategies, enhance the network visibility of content and user engagement, and collect link effect data (S4), integrate all data collected in S1 to S4, conduct in-depth analysis, identify trends and problems, and adjust keywords, content, links and user experience strategies to improve overall effectiveness (S5), based on the analysis results of S5, optimize user experience on mobile devices, improve page loading speed, and ensure good performance on mobile devices, and collect optimized performance data (S6), explore and apply the latest technologies, including AI and big data analysis, to improve the innovation and competitiveness of products or services, and collect technology application effect data (S7), establish a continuous monitoring mechanism to track the effects of all steps, and iteratively optimize according to market changes and user feedback to form a closed loop (S8). These aspects cooperate with each other to achieve the effect of comprehensively improving the search performance and user experience of the website. S1: Through market and user demand analysis, determine innovative keywords, and position projects or products Figure 2, Specifically, by market and user demand analysis, determine the innovation keywords, for the project or product positioning includes the following steps: S11: semantic keyword analysis: using NLP tools, such as NLTK, spaCy, etc., in-depth analysis of the semantic association of keywords, identify potential synonyms and related words, build a comprehensive keyword library. For example, for the keyword "holiday village" in the tourism industry, NLP tools can identify "hotel", "hotel", "inn" and other related words. S12: keyword trend prediction: use AI technology, such as Google Trends, TrendyTopic, etc., to predict the trend of keywords, dynamically adjust the keyword strategy. For example, if it is predicted that "family tour" will become a hot topic, the keyword strategy can be adjusted in advance to increase the frequency of use of related keywords. S13: keyword layout optimization: reasonably distribute keywords in the website's meta tags, URL, content, ensure that keywords are naturally integrated, avoid stacking. For example, you can reasonably embed keywords in article titles, first paragraphs, conclusions and other positions to improve keyword density while ensuring content fluency. S14: keyword effect monitoring and adjustment: regularly evaluate the ranking and traffic of keywords, adjust the keyword strategy according to the results, form a closed loop. For example, you can use SEMrush, Ahrefs and other tools to monitor the performance of keywords and adjust keywords that do not meet the standards in a timely manner. S2: Based on the keywords determined in S1, create high-quality content and optimize it to improve user appeal and search engine ranking Figure 3, Specifically, based on the keywords determined in S1, high-quality content is created and optimized to improve user appeal and search engine ranking, including the following steps: S21: AI-assisted content creation: Combine AI tools and professional editors to generate high-quality, original content that ensures accuracy and appeal. For example, AI writing tools such as GPT-3, Jasper, etc. can be used in combination with the experience of professional editors to generate high-quality articles about "family travel destination recommendations". S22: Content structure optimization: Use title tags, lists, paragraphs, etc. to make the content structure clear, easy for search engines to understand, and improve user experience. For example, you can use H1, H2, H3, etc. title tags to clearly present the "family travel destination recommendations" article in paragraphs, making it easier for readers to understand and search engines to crawl. S23: Content personalization: Use AI to analyze user preferences and optimize content form and style to provide personalized content. For example, you can push the latest content related to "family travel destination recommendations" according to the user's historical browsing records and interests, improving user stickiness. S24: Content effect monitoring and optimization: Evaluate the reading volume, sharing volume and user feedback of the content, and optimize the content strategy according to the results to form a closed loop. For example, you can use tools such as Google Analytics to analyze the performance of the "family travel destination recommendations" article, and adjust the content strategy according to user feedback and data. S3: By analyzing user behavior on products or content, collecting data, understanding user needs and preferences, and providing a basis for subsequent link strategies and data analysis Figure 4, Specifically, by analyzing user behavior on products or content, collecting data, understanding user needs and preferences, and providing basis for subsequent link strategy and data analysis, the steps include: S31: Internal link intelligent optimization: automatically identify and optimize internal link structure through algorithm, ensure the link logic between internal pages is clear. For example, tools such as Link Explorer can be used to analyze the internal link structure of the website, optimize the weight distribution of internal links, and ensure that the links between the "family travel destination recommendation" page and other related pages are more reasonable. S32: External link quality improvement: use big data analysis to evaluate the quality and relevance of external links, and ensure that the obtained links come from authoritative and relevant websites. For example, tools such as Moz Link Explorer, Ahrefs, etc. can be used to analyze the quality of external links, and preferentially select high PR value tourism websites for link exchange. S33: Link building channel exploration: explore new link building channels such as industry forums, social media, etc., to improve the authority of the website. For example, by participating in tourism forum discussions, publishing high-quality social media content, etc., more external links can be obtained. S34: Link effect monitoring and adjustment: monitor the source and quality of the link, and adjust the link strategy according to the result to form a closed loop. For example, tools such as SEMrush, Ahrefs, etc. can be used to regularly check the performance of external links and adjust low-quality links in a timely manner. S4: According to the user behavior data collected in S3, develop link strategies to enhance the network visibility and user engagement of the content, and collect link effect data Figure 5, specifically, according to the user behavior data collected in S3, formulate link strategy, enhance the network visibility and user participation of content, and collect link effect data including the following steps: S41: personalized recommendation system: based on user historical behavior and preference, provide personalized content recommendation, increase user stickiness. For example, Collaborative Filtering, Content-Based Filtering and other recommendation algorithms can be used, according to the user's historical browsing records and interest, push the latest content related to "family travel destination recommendation". S42: user behavior modeling: use big data to analyze user behavior patterns on the website, optimize website layout and content, and improve user satisfaction. For example, Google Analytics, Mixpanel and other tools can be used to analyze user click path, dwell time and bounce rate, and optimize the design and content layout of "family travel destination recommendation" page. S43: AI predicts user behavior: use AI to predict user behavior and optimize user experience in advance. For example, machine learning models such as Random Forest, XGBoost, etc. can be used to predict user behavior patterns and take corresponding optimization measures in advance, such as loading relevant recommended content in advance when the user browses the "family travel destination recommendation" page. S44: user behavior monitoring and optimization: continuously monitor user behavior and optimize user experience strategy according to the results to form a closed loop. For example, heat map tools such as Hotjar, Crazy Egg, etc. can be used to analyze user click hotspots and scrolling behavior, and optimize the user experience of "family travel destination recommendation" page according to the data. S5: integrate all data collected in S1 to S4, conduct in-depth analysis, identify trends and problems, and adjust keywords, content, links and user experience strategy to improve overall effect Figure 6, Specifically, integrate all data collected in S1-S4, conduct in-depth analysis, identify trends and problems, adjust keyword, content, link and user experience strategy to improve overall effect including the following steps: S51: Real-time data analysis: Use real-time data analysis tools to quickly respond to market changes and user needs and adjust SEO strategies. For example, you can use Google Data Studio, Tableau and other tools to monitor the data performance of the "Family Tour Destination Recommendation" page in real time and adjust the SEO strategy in a timely manner. S52: Predictive analysis: Use machine learning algorithms to predict future search trends and user behavior and optimize website content and structure in advance. For example, you can use ARIMA, LSTM and other time series prediction models to predict future search trends and user behavior and make preparations in advance, such as optimizing the content of the "Family Tour Destination Recommendation" page in advance before the peak season. S53: Strategy effect monitoring and iteration: Regularly evaluate the effectiveness of SEO strategies, including keyword ranking, traffic, conversion rate and other indicators, and adjust the strategy according to the results to form a closed loop. For example, you can use Google Search Console, SEMrush and other tools to regularly evaluate the effectiveness of SEO strategies and adjust keyword strategies and content strategies based on data. S6: Based on the analysis results of S5, optimize the user experience on mobile devices, improve page loading speed and ensure good performance on mobile devices, while collecting optimized performance data Figure 7Specifically, based on the analysis results from S5, we optimize the user experience on mobile devices, improve page loading speed, and ensure good performance on mobile devices. Collecting performance data after optimization includes the following steps: S61: Responsive Design: Ensure the website provides a consistent and excellent user experience across different devices. For example, you can use front-end frameworks such as Bootstrap and Foundation to implement responsive design, ensuring that the "Family Travel Destination Recommendations" page displays properly on mobile phones, tablets, and other devices. S62: Page Speed ​​Optimization: Optimize images, compress code, and utilize CDNs to improve page loading speed. For example, you can use tools such as ImageOptim and TinyPNG to optimize image size and format; use tools such as Webpack and Gulp to compress code; and use CDN services such as Cloudflare and Akamai to speed up the loading speed of the "Family Travel Destination Recommendations" page. S63: Mobile Optimization Results Monitoring and Adjustment: Monitor the user experience and page loading speed on mobile devices, and optimize the mobile strategy based on the results, forming a closed-loop system. For example, you can use tools such as Google PageSpeedInsights and GTmetrix to monitor page loading speed and user experience on mobile devices, and optimize the mobile strategy based on the data. S7: Explore and apply the latest technologies, including AI and big data analysis, to enhance the innovation and competitiveness of products or services, while collecting data on the effectiveness of technology applications for reference Figure 8 Specifically, exploring and applying the latest technologies, including AI and big data analysis, to enhance the innovation and competitiveness of products or services, while collecting data on the effectiveness of technology applications, including the following steps: S71: AI-generated meta descriptions: Using AI technology to automatically generate attractive meta descriptions and increase click-through rates. For example, you can use AI writing tools such as GPT-3 and Jasper to automatically generate meta descriptions that meet SEO standards, such as "Explore the best family travel destinations - Book now." S72: Intelligent content updates: Based on real-time data analysis, automatically update content to ensure the timeliness and relevance of website content. For example, you can use technologies such as RSS feeds and webhooks to obtain the latest content data in real time and automatically update the content of the "Family Travel Destination Recommendations" page. S73: Technology application effect monitoring and optimization: Evaluate the application effect of AI and innovative technologies, adjust technical strategies based on the results, and form a closed loop. For example, you can use tools such as Google Analytics and SEMrush to evaluate the effectiveness of AI-generated meta descriptions and intelligent content updates, and adjust technical strategies based on the data. S8: Establish a continuous monitoring mechanism to track the effectiveness of all steps, iterate and optimize based on market changes and user feedback, and form a closed-loop reference. Figure 9, specifically, establish a continuous monitoring mechanism to track the effectiveness of all steps, iterate and optimize based on market changes and user feedback, and form a closed loop including the following steps: S81: SEO effectiveness monitoring: regularly evaluate the effectiveness of SEO strategies, including keyword rankings, traffic, conversion rates, etc. For example, you can use Google Search Console, SEMrush, etc. to regularly evaluate the effectiveness of SEO strategies. S82: Strategy iteration and optimization: continuously optimize SEO strategies based on monitoring results to ensure the innovation and effectiveness of strategies. For example, you can adjust keyword strategies based on changes in keyword rankings; optimize content strategies based on changes in traffic. S83: Overall strategy effectiveness monitoring and iteration: evaluate the overall effectiveness of SEO strategies, and iterate strategies based on results to form a closed loop. For example, you can use KPI dashboards to evaluate the overall effectiveness of SEO strategies, and adjust overall strategies based on data. Embodiment 2 This embodiment is different from the above embodiments in that it highlights the importance of integrating all data collected in S1-S4 for in-depth analysis to identify trends and problems, and adjusting keyword, content, link and user experience strategies to improve overall effectiveness modules, especially the combination of real-time data analysis and predictive analysis to better respond to market changes and user needs. S51: Real-time data analysis and predictive analysis Specifically, real-time data analysis uses real-time data analysis tools to quickly respond to market changes and user needs, and adjust SEO strategies. For example, you can use Google Data Studio, Tableau, etc. to monitor the data performance of the "Family Tour Destination Recommendation" page in real time, and adjust SEO strategies in a timely manner. Predictive analysis uses machine learning algorithms to predict future search trends and user behavior, and optimizes website content and structure in advance. For example, you can use ARIMA, LSTM, etc. time series prediction model to predict future search trends and user behavior, and make preparations in advance, such as optimizing the content of the "Family Tour Destination Recommendation" page in advance before the peak season. Embodiment 3 This embodiment is different from the above embodiments in that it highlights the importance of developing link strategies based on user behavior data collected in S3 to enhance the network visibility and user engagement of content, while collecting link effectiveness data modules, especially the application of personalized recommendation system to improve user satisfaction and loyalty. S41: Personalized recommendation system Specifically, the personalized recommendation system provides personalized content recommendations based on user historical behavior and preferences to increase user stickiness. For example, you can use Collaborative Filtering, Content-Based Filtering, etc. recommendation algorithm, according to the user's historical browsing records and interests, push the latest content related to "Family Tour Destination Recommendation".The difference between this embodiment and the above embodiments is that it highlights the importance of optimizing the user experience on mobile devices, improving page load speed, ensuring good performance on mobile devices, and collecting performance data modules after optimization, especially the application of responsive design and page speed optimization to improve the user experience on mobile devices. S61: Responsive design and page speed optimization Specifically, responsive design ensures that the website provides consistent and excellent user experience on different devices. For example, you can use front-end frameworks such as Bootstrap, Foundation, etc. to implement responsive design and ensure that the "Family Tour Destination Recommendation" page can be displayed normally on different devices such as mobile phones and tablets. Page speed optimization optimizes images, compresses code, uses CDNs, etc. to improve page load speed. For example, you can use tools such as ImageOptim, TinyPNG, etc. to optimize image size and format; use tools such as Webpack, Gulp, etc. to compress code; use CDN services such as Cloudflare, Akamai, etc. to speed up the loading speed of the "Family Tour Destination Recommendation" page.

[0016] The present application also discloses a readable storage medium, which stores a computer program, and when the computer program is executed by a processor, it implements a search engine optimization method based on big data. By adopting the above technical solution, the readable storage medium can store and execute a search engine optimization method based on big data, covering the analysis of market and user needs, determining innovative keywords, positioning projects or products, creating high-quality content based on the keywords determined in S1, and optimizing to improve user appeal and search engine rankings, collecting data by analyzing user behavior on products or content, understanding user needs and preferences, providing a basis for subsequent link strategies and data analysis, formulating link strategies based on user behavior data collected in S3, enhancing the network visibility and user engagement of content, and collecting link effect data at the same time, integrating all data collected in S1 to S4, and conducting in-depth Analyze, identify trends and problems, adjust keywords, content, links and user experience strategies to improve the overall effect, optimize the user experience on mobile devices based on the analysis results of S5, improve page loading speed, ensure good performance on mobile devices, and collect optimized performance data, explore and apply the latest technologies, including AI and big data analysis, to enhance the innovation and competitiveness of products or services, and collect technology application effect data and establish a continuous monitoring mechanism to track the effects of all steps, iterate and optimize according to market changes and user feedback, form a closed loop and other aspects, so as to comprehensively improve the search engine ranking and user experience of the website, and ensure the effectiveness and sustainability of the SEO strategy. The above are all preferred embodiments of this application, and they do not limit the scope of protection of this application. Therefore, all equivalent changes made according to the structure, shape, and principle of this application should be covered within the scope of protection of this application.

Claims

1. A search engine optimization method based on big data, characterized in that: include: S1: Determine keywords and position the project or product through market and user demand analysis; S2: Create content based on the keywords identified in S1 and optimize it to increase user appeal and search engine rankings; S3: Analyze user behavior on products or content, collect data, understand user needs and preferences, and provide a basis for subsequent linking strategies and data analysis; S4: Based on the data collected in S3, develop a link strategy to enhance the content's online visibility and user engagement, while also collecting link effectiveness data; S5: Integrate all the data collected in S1 to S4, conduct in-depth analysis, identify trends and issues, and adjust keywords, content, links, and link strategies to improve overall effectiveness; S6: Based on the analysis results of S5, optimize the user experience on mobile devices, improve page loading speed, ensure good performance on mobile devices, and collect performance data after optimization; S7: Explore and apply the latest technologies, including AI and big data analytics, to enhance the innovation and competitiveness of products or services, while collecting data on the effectiveness of technology applications; S8: Establish a continuous monitoring mechanism to track the effectiveness of all steps, perform iterative optimization based on market changes and user feedback, and form a closed loop.

2. The search engine optimization method based on big data according to claim 1, characterized in that: The above mentioned steps include: determining innovative keywords through market and user demand analysis and positioning the project or product; S11: Semantic keyword analysis: Use NLP tools to deeply analyze the semantic associations of keywords, identify potential synonyms and related words, and build a comprehensive keyword library; S12: Keyword trend prediction: Use AI technology to predict keyword trends and dynamically adjust keyword strategies; S13: Keyword layout optimization: reasonably distribute keywords in the website's meta tags, URLs, and content to ensure that keywords are naturally integrated and avoid keyword stuffing; S14: Keyword effect monitoring and adjustment: Regularly evaluate the ranking and traffic of keywords, and adjust the keyword strategy based on the results to form a closed loop.

3. The search engine optimization method based on big data according to claim 1, characterized in that: Based on the keywords identified in S1, content is created and optimized to increase user appeal and search engine rankings The following steps are included: S21: AI-assisted content creation: combining AI tools and professional editors to generate content and ensure the accuracy and attractiveness of the content; S22: Content structure optimization: Use title tags, lists, and paragraphs to make the content structure clear, easier for search engines to understand, and improve user experience; S23: Content personalization: Using AI to analyze user preferences, optimize content format and style, and provide personalized content; S24: Content effectiveness monitoring and optimization: Evaluate the content’s reading volume, sharing volume, and user feedback, and optimize the content strategy based on the results to form a closed loop.

4. The search engine optimization method based on big data according to claim 1, characterized in that: The analysis of user behavior on products or content, collection of data, and understanding of user needs and preferences to provide a basis for subsequent linking strategies and data analysis includes the following steps: S31: Intelligent optimization of internal links: Automatically identify and optimize the internal link structure through algorithms to ensure clear link logic between internal pages of the website; S32: Improve the quality of external links: Use big data analysis to evaluate the quality and relevance of external links and ensure that the links obtained are from relevant websites; S33: Link building channel exploration: Explore new link building channels, industry forums, social media, and enhance the authority of the website; S34: Link effect monitoring and adjustment: Monitor the source and quality of links, adjust link strategies based on the results, and form a closed loop.

5. The search engine optimization method based on big data according to claim 1, characterized in that: The method of formulating a link strategy based on the user behavior data collected in S3, enhancing the network visibility and user engagement of the content, and collecting link effect data includes the following steps: S41: Personalized recommendation system: Based on user historical behavior and preferences, it provides personalized content recommendations to increase user stickiness; S42: User Behavior Modeling: Utilize big data to analyze user behavior patterns on the website, optimize website layout and content, and improve user satisfaction; S43: AI predicts user behavior: Use AI to predict user behavior and optimize user experience in advance; S44: User behavior monitoring and optimization: Continuously monitor user behavior and optimize the user experience based on the results to form a closed loop.

6. The search engine optimization method based on big data according to claim 1, characterized in that: The steps to integrate all the data collected in S1 to S4, conduct in-depth analysis, identify trends and issues, and adjust keywords, content, links, and user experience strategies to improve overall effectiveness include the following: S51: Real-time data analysis: Use real-time data analysis tools to quickly respond to market changes and user needs and adjust SEO strategies; S52: Predictive analysis: Use machine learning algorithms to predict future search trends and user behavior, and optimize website content and structure in advance; S53: Strategy effectiveness monitoring and iteration: Regularly evaluate the effectiveness of SEO strategies, including keyword rankings, traffic, and conversion rate indicators, and adjust strategies based on the results to form a closed loop.

7. The search engine optimization method based on big data according to claim 1, characterized in that: Optimizing the user experience on mobile devices, improving page loading speed, ensuring good performance on mobile devices, and collecting optimized performance data based on S5 analysis results includes the following steps: S61: Responsive design: Ensure that the website provides a consistent and excellent user experience on different devices; S62: Page speed optimization: optimize images, compress code, use CDN to increase page loading speed; S63: Mobile optimization effect monitoring and adjustment: Monitor the user experience and page loading speed on mobile devices, and optimize the mobile strategy based on the results to form a closed loop.

8. The search engine optimization method based on big data according to claim 1, characterized in that: The exploration and application of the latest technologies, including AI and big data analysis, to enhance the innovation and competitiveness of products or services, while collecting data on the effectiveness of technology application, includes the following steps: S71: AI-generated meta descriptions: Use AI technology to automatically generate meta descriptions to increase click-through rates; S72: Intelligent content update: Automatically update content based on real-time data analysis to ensure the timeliness and relevance of website content; S73: Monitoring and optimization of technology application effects: Evaluate the application effects of AI and innovative technologies, adjust technical strategies based on the results, and form a closed loop.

9. The search engine optimization method based on big data according to claim 1, characterized in that: The above mentioned mechanism is to establish a continuous monitoring mechanism to track the effects of all steps, and to iterate and optimize according to market changes and user feedback to form a closed loop. The following steps are included: S81: SEO effectiveness monitoring: Regularly evaluate the effectiveness of SEO strategies, including keyword rankings, traffic, and conversion rate indicators; S82: Strategy Iteration Optimization: Based on monitoring results, continuously optimize SEO strategies to ensure their innovation and effectiveness; S83: Overall strategy effectiveness monitoring and iteration: Comprehensively evaluate the overall effectiveness of the SEO strategy, iterate the strategy based on the results, and form a closed loop.

10. A readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the big data-based search engine optimization method according to any one of claims 1 to 9 is implemented.

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