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International Journal of Research in Management
Peer Reviewed Journal

Vol. 7, Issue 1, Part L (2025)

Analysis of search engine optimization tactics in the context of digital marketing for enhancing websites ranking and visibility in Generative AI and large language models

Author(s):

Nektarios S Makrydakis, Dimitris Spiliotopoulos and Afroditi Lymperi

Abstract:

Rise of generative Artificial Intelligence (AI) and Large Language Models (LLMs) has significantly transformed Search Engine Optimization (SEO) strategies and tactics. This study presents a quantitative analysis among digital professionals, assessing the effectiveness of on-page SEO, technical SEO, user engagement metrics and off-page SEO in optimizing a website for better ranking and visibility in AI and LLM-generated search results. Using statistical analysis, we evaluate the impact of traditional SEO tactics in new AI environment applications visibility. The results demonstrate that semantic keyword usage, content quality and structured data, remain critical for AI-driven search rankings. Findings also reveal a significant shift toward user engagement metrics, which AI models prioritize to assess content relevance and quality. Results offer actionable insights for digital marketers and webmasters seeking to optimize their websites for Generative AI and LLMs.

Pages: 1107-1113  |  93 Views  33 Downloads


International Journal of Research in Management
How to cite this article:
Nektarios S Makrydakis, Dimitris Spiliotopoulos and Afroditi Lymperi. Analysis of search engine optimization tactics in the context of digital marketing for enhancing websites ranking and visibility in Generative AI and large language models. Int. J. Res. Manage. 2025;7(1):1107-1113. DOI: 10.33545/26648792.2025.v7.i1l.386