Enhancement of Techniques in the Implementation of SEO


Authors : Dr. Vsrk. Sharma; Mohammad. Abdul Waris; Kapa Naveen; Nalamati Eswar Chandu

Volume/Issue : Volume 10 - 2025, Issue 4 - April


Google Scholar : https://tinyurl.com/3tze7kpz

Scribd : https://tinyurl.com/5n772jv5

DOI : https://doi.org/10.38124/ijisrt/25apr1049

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Abstract : In today's digital era, the swift development of technologies has dramatically transformed the way companies go about and implement SEO strategies. This research explores the changing role of new-age tools and big data analytics in shaping SEO methods across different digital platforms. From an intensive literature survey and case analysis, it ventures into the most vital building blocks and actionable processes to adopt for applying technology into SEO. Principal areas of consideration encompass processes such as data sourcing, preprocessing, and real-time analytics, but most specifically looking into personalized SEO campaigns and responsive decision-making considering user actions and search patterns. The research also elucidates key SEO factors like keyword intent modeling, user journey mapping, and measurement of performance using analytics tools such as Google Search Console and artificial intelligence-based analytics dashboards. These are revealed to be crucial in maximizing content visibility, enhancing technical SEO, and optimizing on-page and off-page tactics. Moreover, automation tools and AI-based optimization platforms for content allow real-time adjustments, backlink insights, and constant monitoring of performance. Aside from technical implementation, the study highlights the need to harmonize SEO practices with data privacy regulations and uphold ethical standards in web content and data processing. With SEO increasingly entwined with machine learning and big data, companies are urged to strike a balance between automation and transparency to establish trust and authority online. By integrating theoretical concepts with implementable strategies, this paper offers an assist guide for organizations on how to harness contemporary technological innovations in SEO, improve their online visibility, and maintain a competitive advantage in the fast-paced digital marketing space.

Keywords : SEO Technology, Big Data in SEO, AI Tools, Real-Time Search Optimization, Ethical SEO.

References :

  1. Aggarwal, P., Murahari, V., Rajpurohit, T., Kalyan, A., Narasimhan, K., & Deshpande, A. (2023). GEO: Generative Engine Optimization. arXiv preprint arXiv:2311.09735. arXiv
  2. Shayegan, M. J., & Kouhzadi, M. (2020). An Analysis of the Impact of SEO on University Website Ranking. arXiv preprint arXiv:2009.12417. arXiv
  3. Aakash, V. (2024). AI-Powered SEO: Revolutionizing Digital Marketing. International Journal of Advance Research, Ideas and Innovations in Technology, 10(6). IJARIIT
  4. Sun, S., Cao, Z., Zhu, H., & Zhao, J. (2019). A Survey of Optimization Methods from a Machine Learning Perspective. arXiv preprint arXiv:1906.06821. arXiv
  5. Gambella, C., Ghaddar, B., & Naoum-Sawaya, J. (2019). Optimization Problems for Machine Learning: A Survey. arXiv preprint arXiv:1901.05331. arXiv
  6. Roumeliotis, K. I., & Tselikas, N. D. (2023). A Machine Learning Python-based Search Engine Optimization Audit Software. arXiv preprint arXiv:2306.12345.ResearchGate
  7. Salminen, J., Corporán, J., Marttila, R., & Jansen, B. J. (2019). Using Machine Learning to Predict Ranking of Webpages in the Gift Industry: Factors for Search-Engine Optimization. Proceedings of the International Conference on Machine Learning.ResearchGate
  8. Singh, S. (2021). BERT Algorithm used in Google Search. International Journal of Computer Applications, 183(20), 1-5. ResearchGate
  9. Ms, V. (2023). Insights into Search Engine Optimization using Natural Language Processing and Machine Learning. International Journal of Advanced Computer Science and Applications, 14(2), 95-102.
  10. Bello, R.-W., & Noah, O. (2018). Conversion of Website Users to Customers-The Black Hat SEO Technique. International Journal of Computer Applications, 180(47), 1-5. ResearchGate
  11. Devi, S., Reddy, B. M., Ramadass, S., & Lakshmi, V. A. (2018). Performance Analysis and a Review on Search Engines with Its Optimization. International Journal of Engineering & Technology, 7(3.12), 507-511.ResearchGate
  12. Gupta, S., Agrawal, N., & Gupta, S. (2016). A Review on Search Engine Optimization: Basics. International Journal of Computer Applications, 975, 8887.ResearchGate
  13. Bardas, N., Mordo, T., Kurland, O., Tennenholtz, M., & Zur, G. (2025). White Hat Search Engine Optimization using Large Language Models. arXiv preprint arXiv:2502.07315.
  14. Aggarwal, P., Murahari, V., Rajpurohit, T., Kalyan, A., Narasimhan, K., & Deshpande, A. (2023). GEO: Generative Engine Optimization. arXiv preprint arXiv:2311.09735.
  15. Shayegan, M. J., & Kouhzadi, M. (2020). An Analysis of the Impact of SEO on University Website Ranking. arXiv preprint arXiv:2009.12417.arXiv
  16. Sun, S., Cao, Z., Zhu, H., & Zhao, J. (2019). A Survey of Optimization Methods from a Machine Learning Perspective. arXiv preprint arXiv:1906.06821.arXiv
  17. Gambella, C., Ghaddar, B., & Naoum-Sawaya, J. (2019). Optimization Problems for Machine Learning: A Survey. arXiv preprint arXiv:1901.05331.arXiv
  18. Roumeliotis, K. I., & Tselikas, N. D. (2023). A Machine Learning Python-based Search Engine Optimization Audit Software. arXiv preprint arXiv:2306.12345.ResearchGate
  19. Salminen, J., Corporán, J., Marttila, R., & Jansen, B. J. (2019). Using Machine Learning to Predict Ranking of Webpages in the Gift Industry: Factors for Search-Engine Optimization. Proceedings of the International Conference on Machine Learning.ResearchGate
  20. Singh, S. (2021). BERT Algorithm used in Google Search. International Journal of Computer Applications, 183(20), 1-5. ResearchGate
  1. Ms, V. (2023). Insights into Search Engine Optimization using Natural Language Processing and Machine Learning. International Journal of Advanced Computer Science and Applications, 14(2), 95-102.
  2. Bello, R.-W., & Noah, O. (2018). Conversion of Website Users to Customers-The Black Hat SEO Technique. International Journal of Computer Applications, 180(47), 1-5
  3. Kapanadze, G., & Bardavelidze, A. (2023). Development and Implementation of Search Engine Optimization Algorithm using Angular Framework. International Journal of Computer and Information Technology, 11(5). ijcit.com

In today's digital era, the swift development of technologies has dramatically transformed the way companies go about and implement SEO strategies. This research explores the changing role of new-age tools and big data analytics in shaping SEO methods across different digital platforms. From an intensive literature survey and case analysis, it ventures into the most vital building blocks and actionable processes to adopt for applying technology into SEO. Principal areas of consideration encompass processes such as data sourcing, preprocessing, and real-time analytics, but most specifically looking into personalized SEO campaigns and responsive decision-making considering user actions and search patterns. The research also elucidates key SEO factors like keyword intent modeling, user journey mapping, and measurement of performance using analytics tools such as Google Search Console and artificial intelligence-based analytics dashboards. These are revealed to be crucial in maximizing content visibility, enhancing technical SEO, and optimizing on-page and off-page tactics. Moreover, automation tools and AI-based optimization platforms for content allow real-time adjustments, backlink insights, and constant monitoring of performance. Aside from technical implementation, the study highlights the need to harmonize SEO practices with data privacy regulations and uphold ethical standards in web content and data processing. With SEO increasingly entwined with machine learning and big data, companies are urged to strike a balance between automation and transparency to establish trust and authority online. By integrating theoretical concepts with implementable strategies, this paper offers an assist guide for organizations on how to harness contemporary technological innovations in SEO, improve their online visibility, and maintain a competitive advantage in the fast-paced digital marketing space.

Keywords : SEO Technology, Big Data in SEO, AI Tools, Real-Time Search Optimization, Ethical SEO.

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