ChatGPT Pro in practical testing

For a technical SEO audit of our own website, we had ChatGPT Pro conduct a complete analysis. While the AI identified real issues, it also generated numerous errors:

• Incorrect redirect analyses: ChatGPT reported missing HTTP > HTTPS redirects, even though they were correctly set up.
• Misinterpretations of canonical tags: Allegedly missing canonical tags were criticized, even though they were correctly implemented.
• Missing lazy loading? The tool claimed that certain images were not using lazy loading – when it had long been active.

Accuracy only improved when we provided additional data from Screaming Frog, Google Search Console, and Sistrix and explicitly pointed out the erroneous assumptions.

Conclusion: While ChatGPT Pro can provide initial insights, it is (still) not a reliable solution for automated technical SEO audits. The necessity for external datasets shows that solid SEO experience remains irreplaceable.

Another test involved creating a scalable URL structure for a regional page of a nationwide delivering retailer in Germany. The goal was to generate a dynamic structure following the pattern domain.com/bundesland/region/stadt for all cities with more than 5,000 inhabitants (about 3,000 cities).

• Expectations: The tool should generate a complete list of all relevant cities with state and region assignments as a URL structure and provide it as a CSV export.
• Result: ChatGPT Pro took about 30 minutes for the calculation and produced a meaningful structure in the preview.
• Limitations: The export of the data was denied as external geo-data was required for a complete output.
• Solution: After providing a structured list of cities and districts, it worked flawlessly.
• Bonus: ChatGPT Pro correctly recommended internal links to nearby cities, based on postal code data.

Conclusion: ChatGPT Pro effectively supports the creation of scalable URL structures – but only with manual adjustments. However, the automatic linking recommendation based on geographical proximity was a real plus.

For the integration of Google Reviews on an existing website, ChatGPT Pro should suggest an implementation to the Google Reviews API as a step-by-step guide.

• Requirement: We provided a code snippet of the previous implementation.
• Result: ChatGPT delivered a clearly structured, actionable step-by-step guide for the dynamic integration of the Google Reviews API.

Conclusion: Especially in clearly defined, structured task areas like API implementations, ChatGPT Pro shows its strengths. The provided instructions were understandable and easy to implement.

Another test field was the analysis of affiliate programs on various affiliate networks. We wanted to crawl five advertiser programs and summarize their details in a clear table. The URLs of the respective program descriptions were provided by us.

• Speed: ChatGPT Pro only needed two minutes for the task.
• Accuracy: The delivered data was correct and well-structured.

Conclusion: Especially for quick data analyses or extracting structured content from websites, ChatGPT Pro is well-suited – provided that the data is easily accessible.

The analysis of social media competitors is a central component of any data-driven marketing strategy. But how reliable is ChatGPT Pro in identifying successful content and target audiences? To find out, a detailed competitive analysis was conducted and applied to well-known websites. The data basis consisted of various GA4 exports, Google Search Console (GSC) data, and supplementary social media benchmarks. The goal was to gain informed insights into the current performance of content, the most relevant target audiences, and the best engagement strategies.

• Expectations: The AI-supported analysis was supposed to show which social media content performs best, which platforms achieve the highest interaction, and how target audiences differ in their usage behavior.
• Results: The data provided valuable insights into the engagement behavior of different user groups. It was particularly noticeable that interactive and practical content was particularly well received, while classic advertising messages showed lower interaction rates. The highest engagement rates were achieved on Instagram and Facebook, while other channels still showed untapped potential. Furthermore, the analysis clearly demonstrated that organic social traffic makes up only a limited share of the overall strategy, while paid strategies contribute specifically to increasing reach.
• Challenges: Despite the in-depth data analysis, it became apparent that some proposed topics and strategies did not align with the given framework conditions. While the AI could recognize patterns in the data, it could not always accurately assess the strategic relevance of certain topics and target audiences. This makes it clear that a purely data-based evaluation must always be supplemented by manual interpretation.

Conclusion: ChatGPT Pro can provide valuable support in social media analysis by structuring data, recognizing patterns, and delivering initial recommendations for action. However, to effectively utilize these insights for sustainable strategy optimization, manual evaluation and adjustment are essential. The best results arise from the intelligent combination of automated data analysis and human interpretation.