Evaluating local SEO quality of municipal geoportals: a multi-method approach integrating automated, link, and AI-based analysis

Karol Król

doi:10.31648/aspal.11523

Published: 2025-12-30

Vol. 24 No. 4 (2025)

Evaluating local SEO quality of municipal geoportals: a multi-method approach integrating automated, link, and AI-based analysis

Karol Król

Acta Scientiarum Polonorum Administratio Locorum

Section: Articles

https://doi.org/10.31648/aspal.11523

Abstract

Motives: Research on search engine optimisation (SEO) usually focuses on commercial websites, with limited attention to public sector platforms like geoportals. The impact of SEO on their online visibility and Local SEO quality remains understudied, which presents a research gap worth exploring.
Aim: This study evaluates the SEO quality of selected municipal geoportals using Large Language Models (LLMs). It examines how well these portals are optimised for search engines and whether AI tools can effectively support SEO auditing.
Results: Audits of five geoportals using tools like ChatGPT, Copilot, Gemini, and Perplexity revealed low SEO support from public administrations, poor link building, and weak metadata. Referring domains and quality indicators were limited. Moreover, AI tools do not conduct real-time audits, which restricts their accuracy and usefulness for detailed SEO assessments.

Keywords:

Large Language Models, passive SEO, mechanical SEO audit, Local SEO, theoretical SEO audit, geoinformation

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Król, K. (2025). Evaluating local SEO quality of municipal geoportals: a multi-method approach integrating automated, link, and AI-based analysis. Acta Scientiarum Polonorum Administratio Locorum, 24(4), 605–622. https://doi.org/10.31648/aspal.11523

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