Can AI perform technical SEO analysis?

Modern artificial intelligence (AI) technologies are developing at a rapid pace, and one of their application areas is technical SEO analysis. The process involves optimizing websites for search engines by analyzing various technical aspects. 

In this article, we will explore the possibility of using AI, specifically ChatGPT, to perform technical SEO analysis based on data collected by the Screaming Frog crawler.

How the research was conducted

James Allen, in an article for “Search Engine Land,” uses GPT-4o to analyze data obtained through Screaming Frog. The updated version of GPT-4 responds faster to queries and processes more attached data, creates more types of media files, and supports online operation.

The author of the article aimed to determine how accurately and usefully AI can provide recommendations for the technical optimization of websites. The research used real data collected from various web pages.

Results

(Specific query and vague AI response)

1. General recommendations: AI is capable of providing general recommendations such as optimizing meta tags, fixing 404 errors, improving page load speed, etc. These tips can be useful for basic optimization, but they are often ineffective or misleading in more complex situations.

2. Accuracy and specificity: AI often provides overly general advice that does not always fit specific situations. For example, recommendations for fixing internal links may not always be relevant or detailed enough. Even when the author of the research provides a more detailed prompt, the instructions remain too vague. 

3. Error detection: AI performs well in detecting basic technical issues such as 404 errors, duplicate meta descriptions, missing H1 headers, etc. However, more complex problems, such as server misconfiguration or specific SEO settings, may be overlooked.

4. Content evaluation: AI can analyze content on pages and provide recommendations for improving keywords, optimizing texts for search engines. However, these suggestions are often general and require further verification by real specialists. Therefore, blindly following GPT-4o’s instructions is definitely not advisable.

J. Allen states that he would “rate AI’s performance as a D or E (satisfactory).” At the same time, he notes that most systems would not receive such a high rating for technical SEO from flat data tables. While there are prospects in this direction, the author of the article does not currently recommend using AI for this level of technical SEO analysis.

What AI lacks for successful technical SEO analysis

(The response to the query becomes clearer after the prompt)

1. Understanding the context. AI has a limited ability to understand the context of a specific business or audience. Sometimes this leads to irrelevant recommendations. That is why the system requires detailed explanations and clarifications.

2. Dynamic changes. SEO is a dynamic field where rules and recommendations are constantly changing. AI requires regular updates and training on new data to be effective. That is why the advice from AI is currently so vague.

3. The human brain. No matter how you look at it, it is indispensable. Despite the progress in AI development, real specialists remain essential for performing complex analytical tasks and making strategic decisions. For now.

Conclusions

According to the author of the article, AI has great potential in the field of technical SEO analysis. However, at this moment, the system cannot fully replace real specialists. The technology can be useful for identifying major issues and providing general recommendations, but for detailed and accurate analysis, human involvement is still needed. It is important to continue research and development of AI in this direction to make it a more effective and reliable tool in SEO.

You can find the content of the article by J. Allen at this link