How well do structured data help with AI visibility? This is currently being discussed in the SEO industry. And not only there: Many agencies and specialists are currently developing strategies and measures for this new field of work. For example, Julio Guevara from the Interactive Media Group (IMG).
We spoke with him specifically about this, as Julio conducted his own study on the matter. The findings are clear.
What this means for GEO (Generative Engine Optimization) and how Julio and his team approach this new field of work — we discuss this in depth in our podcast. Here is the summary.


In the Podcast Interview: Julio C. Guevara
Julio Guevara leads the Organic Growth Team at Interactive Media Group (IMG). Julio originally comes from web development and combines UX, SEO, and data analytics.
Julio exemplifies a new generation of interdisciplinary marketing consultants. He views AI systems not only from an SEO perspective but approaches the field with an open mind.
IMG is also not a classic SEO agency — quite the opposite. The Hamburg-based management consultancy focuses on analyzing and optimizing the digital customer journey. Approximately 20 consultants work there. IMG’s clients include Nivea, o2, Deutsche Bahn, Eurowings, Lufthansa, and Audi.
This example also shows that the new field of AI optimization is being developed by agencies from very different directions.

Do JSON and similar formats help with AI visibility? These are the test results.
Julio’s team received an inquiry about whether structured data helps with AI visibility. The client operated a React-based online shop where all product information was delivered as JSON files. Julio and his team decided to find out — through tests.
Julio’s team conducted over 160 structured tests — from product and blog pages to organizational pages. The comparison was clearly designed: Variant A consisted only of structured data in JSON-LD format, while Variant B additionally contained the same information as visible HTML content. The goal was to determine whether ChatGPT and Gemini could extract information directly from JSON data and use it in responses. The results at a glance:
- Large language models exclusively read visible text, not code. None of the tested JSON-only pages were correctly read by ChatGPT or Gemini.
- ChatGPT hallucinated missing information. Where no data was available, the model invented plausible, but often incorrect, product details.
- Gemini refused to answer. Instead of guessing, the model transparently reported that it could not read JSON data.
- HTML content was reliably recognized. As soon as information was present in the visible text, both systems could reproduce it correctly.
A second series of tests with real brand setups confirmed the pattern. Only HTML-based pages were fully visible to AI systems, while client-side rendered JSON structures remained invisible.
For us, the significance of these results is clear: Anyone who delivers their product or brand information exclusively via JSON structures is practically invisible to AI systems. And anyone who trusts that ChatGPT will “somehow understand” it risks incorrect citations or distorted brand messages. Visibility arises where content is actually rendered and information is available in text form.
Further Topics from our Discussion
Further Topics in Our Discussion:
- How Julio and his team developed a five-stage GEO rollout for brands — from monitoring to community management.
- What “citable content” means and why AI systems prefer clear facts, figures, and also tables.
- Why structured data remains relevant for SEO, but plays no role in AI visibility — at least for now.
- Which tools and frameworks Julio uses to measure GEO performance and track brand perception in AI systems.
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More InformationThe Interview in the Video Podcast
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