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
Google Scholar
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Note : Google Scholar may take 15 to 20 days to display the article.
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 :
- Aggarwal, P., Murahari, V., Rajpurohit, T., Kalyan, A., Narasimhan, K., & Deshpande, A. (2023). GEO: Generative Engine Optimization. arXiv preprint arXiv:2311.09735. arXiv
- Shayegan, M. J., & Kouhzadi, M. (2020). An Analysis of the Impact of SEO on University Website Ranking. arXiv preprint arXiv:2009.12417. arXiv
- Aakash, V. (2024). AI-Powered SEO: Revolutionizing Digital Marketing. International Journal of Advance Research, Ideas and Innovations in Technology, 10(6). IJARIIT
- 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
- Gambella, C., Ghaddar, B., & Naoum-Sawaya, J. (2019). Optimization Problems for Machine Learning: A Survey. arXiv preprint arXiv:1901.05331. arXiv
- Roumeliotis, K. I., & Tselikas, N. D. (2023). A Machine Learning Python-based Search Engine Optimization Audit Software. arXiv preprint arXiv:2306.12345.ResearchGate
- 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
- Singh, S. (2021). BERT Algorithm used in Google Search. International Journal of Computer Applications, 183(20), 1-5. ResearchGate
- 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.
- 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
- 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
- Gupta, S., Agrawal, N., & Gupta, S. (2016). A Review on Search Engine Optimization: Basics. International Journal of Computer Applications, 975, 8887.ResearchGate
- 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.
- Aggarwal, P., Murahari, V., Rajpurohit, T., Kalyan, A., Narasimhan, K., & Deshpande, A. (2023). GEO: Generative Engine Optimization. arXiv preprint arXiv:2311.09735.
- Shayegan, M. J., & Kouhzadi, M. (2020). An Analysis of the Impact of SEO on University Website Ranking. arXiv preprint arXiv:2009.12417.arXiv
- 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
- Gambella, C., Ghaddar, B., & Naoum-Sawaya, J. (2019). Optimization Problems for Machine Learning: A Survey. arXiv preprint arXiv:1901.05331.arXiv
- Roumeliotis, K. I., & Tselikas, N. D. (2023). A Machine Learning Python-based Search Engine Optimization Audit Software. arXiv preprint arXiv:2306.12345.ResearchGate
- 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
- Singh, S. (2021). BERT Algorithm used in Google Search. International Journal of Computer Applications, 183(20), 1-5. ResearchGate
- 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.
- 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
- 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.