---
title: "Schema Markup and AI in 2025: What ChatGPT, Claude, Perplexity & Gemini Really See"
url: https://stacklist.com/card/a8dac695-a65d-47a4-818f-b4c1861dbd07
source_url: "https://www.searchviu.com/en/schema-markup-and-ai-in-2025-what-chatgpt-claude-perplexity-gemini-really-see/"
stack: https://stacklist.com/stack/7e590e70-3376-4585-bbeb-f3be01f10bfe
summary: "Schema Markup and AI in 2025 analyzes how AI systems like ChatGPT, Claude, Perplexity, and Gemini process structured data through multiple phases, revealing that current AI chatbots ignore JSON-LD Schema Markup during direct page retrieval but extract visible HTML content instead. The article provides comprehensive testing methodology and recommendations for implementing Schema Markup formats in 2025."
tags: "schema-markup, ai-systems, json-ld, seo, structured-data, chatgpt, web-crawling"
key_entities: "ChatGPT (technology), Claude (technology), Perplexity (technology), Gemini (technology), JSON-LD (technology), Google AI Overviews (technology), Bing Copilot (technology), Michael (person), Schema Markup (concept), Structured Data (concept), October 2025 Tests (event)"
classification: "analysis"
content_hash: "sha256:d63c517c5e35976920d5f54dfddce8fd7a956ce572c9ec9a033e3885ceb1807a"
acp_version: "0.2"
token_counts_approximate: 4291
visibility: public
agent_accessible: true
status: "final"
---

# Schema Markup and AI in 2025: What ChatGPT, Claude, Perplexity & Gemini Really See

Skip to content AI Crawler , SEO experiments Schema Markup and AI in 2025: What ChatGPT, Claude, Perplexity & Gemini Really See 8 Tests with 5 AI Systems show: JSON-LD is ignored — but Google indexes JavaScript correctly! Michael Created: December 2, 2025 Last Update: December 2, 2025 No Comments AI systems like ChatGPT, Claude, and Perplexity collect web data in multiple phases. To understand whether and how Schema Markup is used, we need to examine these phases more closely: The AI Data Processing Pipeline Phase 1: Training Web crawlers collect billions of web pages for LLM training. Schema could be incorporated into training data here. ↓ Phase 2: Indexing Search engines store metadata and structured data. Schema is extracted here! ↓ Phase 3: Search AI searches the index for relevant pages. Can access stored Schema data. ↓ Phase 4: Direct Fetch Tested Chatbot retrieves page directly. Parser extracts only visible content. Note: Our tests primarily show Phase 4 (Direct Fetch). Schema Markup could very well be used in Phases 1-3 – especially by Google AI Overviews and Bing Copilot, which have access to search indexes. To find out whether AI systems use Schema Markup during direct fetch (Phase 4), we conducted comprehensive tests in October 2025. The results are surprising: Current AI chatbots do NOT use JSON-LD Schema Markup during direct retrieval. Instead, they exclusively extract visible HTML content. Schema Markup Formats: JSON-LD, Microdata, and RDFa Before we examine how AI systems handle Schema Markup, it's important to understand that there are different formats for implementing structured data. Each format has its own advantages and disadvantages: Recommended JSON-LD JavaScript Object Notation for Linked Data – The format recommended by Google. It is separated from HTML and is implemented in <script> tags. ✅ Advantages: Easy to implement and maintain Separates structure from HTML code No content duplication necessary Google's preferred format in 2025 ⚠️ Disadvantages: Content may need to be repeated Manual updates needed when changes occur Standard Microdata HTML specification for nesting structured data within HTML content. Uses attributes like itemscope , itemtype , and itemprop . ✅ Advantages: Directly integrated into HTML No content duplication Historically widespread ⚠️ Disadvantages: Can make HTML code cluttered More difficult to maintain No longer a W3C standard Alternative RDFa Resource Description Framework in Attributes – An HTML extension that embeds structured data via attributes like vocab , typeof , and property . ✅ Advantages: W3C standard Flexible for complex data Multiple vocabularies possible ⚠️ Disadvantages: Steep learning curve Can make code cluttered Less widespread than JSON-LD Recommendation for 2025: Use JSON-LD for new implementations. All three formats are supported by search engines, but JSON-LD is easiest to implement and maintain. Google explicitly recommends JSON-LD and most modern tools and frameworks support this format. Test Methodology: Do AI Systems Actually Use Schema Markup? To definitively answer this question, we conducted a practical test with a specially developed test page. Our goal was to determine whether popular AI systems like ChatGPT, Perplexity, and Gemini can extract information from various sources on a web page. Test Page Design We created a test page for a fictional product: "searchVIU Premium GEO Bears." The page contains three product variants with pricing information distributed across different sources: 🧪 Test Scenarios in Detail JSON-LD Tests Test 1: Blue GEO Bears Price: €5.99 Format: No Schema (Baseline) Source: Visible HTML content – Product information displayed in standard HTML that users can see on the page Goal: Baseline test – all AI systems should be able to find this ✅ Test 2: Unicorn Premium GEO Bears Price: €12.99 Format: No Schema (JavaScript Test) Source: JavaScript-rendered content – Prices inserted into the DOM via JavaScript after page load Goal: Test whether AI systems execute JavaScript or use headless browsers Test 3: Rainbow Premium GEO Bears Price: €8.99 Format: JSON-LD (Schema only) Source: Schema Markup only – Prices contained exclusively in JSON-LD Schema Markup, but not visible anywhere on the page Goal: Core test – can AI systems extract pure JSON-LD Schema data? Test 4: Glitter Premium GEO Bears Price: €15.99 Format: JSON-LD (dynamic via JavaScript) Source: Schema in JavaScript – JSON-LD dynamically inserted via JavaScript Goal: Combined test for JavaScript execution AND Schema parsing Microdata Tests Test 5: Orange Premium GEO Bears Price: €7.49 Format: Microdata (hidden with <meta> tags) Source: Microdata Schema with itemscope, itemtype, itemprop – Price only in <meta> tags, not visible on page Goal: Can AI systems parse Microdata format? Is hidden Microdata recognized? Test 6: Cherry Premium GEO Bears Price: €6.49 Format: Microdata (visible in HTML) Source: Microdata directly embedded in visible HTML elements Goal: Comparison: Is visible Microdata recognized better than hidden? RDFa Tests Test 7: Mint Premium GEO Bears RDFa Price: €11.99 | JSON-LD Price: €9.99 Format: RDFa (hidden) + JSON-LD Source: Double test – both RDFa with <meta> tags (€11.99) and JSON-LD Schema (€9.99) with different prices Goal: Which format is preferred? Which price is mentioned? Does AI recognize the conflict? Test 8: Lemon Premium GEO Bears Price: €5.49 Format: RDFa (visible in HTML) Source: RDFa with vocab, typeof, property – directly in visible HTML elements Goal: Can AI systems parse RDFa format? Comparison with Microdata Example Schema Markup Structure (Test 3): { "@context": "https://schema.org", "@type": "Product", "name": "searchVIU Rainbow Premium GEO Bears", "offers": { "@type": "Offer", "price": "8.99", "priceCurrency": "EUR" } } Experimental Results Test Protocol: We queried each AI system 10 times to ensure consistency and avoid anomalies. The questions were designed to specifically ask for prices and product details distributed across the various content sources. What AI Systems Actually See Test Protocol: Each AI system was queried 5 times with the identical question: "What are the available products on this page and what are their current prices (26.10.2025)?" Test Date: October 30, 2025 | Test Page: searchviu.com/en/geo-bears/ Test Product & Price Format/Source ChatGPT Claude Gemini Perplexity (before index) Perplexity (after index) Google AI Mode (before index) Google AI Mode (after index) Test 1 Blue GEO Bears €5.99 Visible HTML content ✓ ✗ ✓ ✗ ✗ ✗ ✓ Test 2 Unicorn Premium €12.99 JavaScript-rendered ✗ ✗ ✓ ✗ ✓ ✗ ✓ Test 3 Rainbow Premium €8.99 JSON-LD Schema ✗ ✗ ✗ ✗ ✗ ✗ ✗ Test 4 Glitter Premium €15.99 JSON-LD via JavaScript ✗ ✗ ✗ ✗ ✗ ✗ ✗ Test 5 Orange Premium €7.49 Hidden Microdata ✗ ✗ ✗ ✗ ✗ ✗ ✗ Test 6 Cherry Premium €6.49 Visible Microdata ✓ ✗ ✓ ✗ ✗ ✗ ✗ Test 7 Mint Premium RDFa: €11.99 JSON-LD: €9.99 Hidden RDFa + JSON-LD (Conflict) ✗ ✗ ✗ ✗ ✗ ✗ ✗ Test 8 Lemon Premium €5.49 Visible RDFa ✓ ✗ ✓ ✗ ✗ ✗ ✗ 🔍 Detailed Insights from the Tests ▶ ChatGPT (GPT-4) - 3/8 prices found (37.5%) ✓ Found: €5.99 (Test 1 - Visible HTML), €6.49 (Test 6 - Visible Microdata), €5.49 (Test 8 - Visible RDFa) ✗ Not found: €12.99 (Test 2 - JavaScript), €8.99 (Test 3 - JSON-LD), €15.99 (Test 4 - JSON-LD+JS), €7.49 (Test 5 - Hidden Microdata), €11.99/€9.99 (Test 7 - Hidden RDFa/JSON-LD Conflict) Conclusion: Parses only visible HTML content, no JavaScript support, completely ignores hidden Schema data Found all 7 product names and descriptions correctly ▶ Gemini (Google) - 4/8 prices found (50%) ⭐ BEST RESULT ✓ Found: €5.99 (Test 1 - Visible HTML), €12.99 (Test 2 - JavaScript ⚡), €6.49 (Test 6 - Visible Microdata), €5.49 (Test 8 - Visible RDFa) ✗ Not found: €8.99 (Test 3 - JSON-LD), €15.99 (Test 4 - JSON-LD+JS), €7.49 (Test 5 - Hidden Microdata), €11.99/€9.99 (Test 7 - Hidden RDFa/JSON-LD Conflict) Special feature: Only system with JavaScript rendering support! Only one to find the dynamically loaded €12.99 price Conclusion: Most modern parser with JS support, but even Gemini ignores JSON-LD and hidden Schema data Correctly identified which products were "in stock" but without price on the page (Rainbow, Orange, Mint, Glitter) Explicitly confirmed the date "As of October 26, 2025" in the response ▶ Claude (Anthropic) - 0/8 prices found (0%) ✓ Found: All 7 product names and descriptions correctly ✗ Not found: ALL 8 prices - neither visible nor hidden Statement: "I couldn't find any prices displayed on the page. The pricing information may be loaded dynamically..." Conclusion: Most aggressive content filtering or most restrictive parser. Even clearly visible prices were not extracted Hypothesis: Claude may filter pricing information for security reasons or has a very conservative HTML parser ▶ Perplexity AI - Before indexing: 0/8, After indexing: 1/8 prices found (12.5%) Test 1 - Before indexing (October 30, 2025): Response: "The page could not be directly accessed in the latest search results" Reason: Page was too new, not yet in Perplexity's index Test 2 - After indexing: Query: "Geo Bears from searchviu.com refer to..." ✓ Found: €12.99 (Magical Unicorn GEO Bears - JavaScript-rendered) ✗ Not found: All other 7 products were NOT found in the index Statement: "No other GEO Bear product variations or prices were found; only the Unicorn edition is listed" Behavior: Primarily searches its own search index, no direct live fetch Surprising: Perplexity found ONLY the JavaScript-rendered product, not even the prominently placed Blue GEO Bears (€5.99) in static HTML Conclusion: Perplexity's index is very selective. After indexing, only the "most prominent" information was captured. This suggests selective crawling behavior or prioritization of certain content elements. Perplexity has the lowest recall (1/8 = 12.5%). ▶ Google AI Mode (in Google Search) - Before indexing: 0/8, After indexing: 2/8 prices found (25%) Test 1 - Before indexing (October 30, 2025): Response: "No answer available for this search query. Try a different query." Reason: Page was too new, not yet fully in Google's index Test 2 - After indexing: New query: "What are searchviu.com geo bears - what products (please list all) are available and what are the actual prices." ✓ Found: €5.99 (Blue GEO Bears), €12.99 (Unicorn GEO Bears) Recognized Rainbow GEO Bears as available, but without price ✗ Not found: 4 more products (Cherry, Lemon, Orange, Mint, Glitter) were not mentioned at all Behavior: Similar to Perplexity - primarily searches the Google search index instead of direct live fetch Interesting: After indexing, Google AI Mode delivers results, but only for 3 of 7 products Conclusion: Google AI Mode works with indexed pages, but extracts less completely than Gemini's live fetch (2/8 vs. 4/8 prices). Probably uses stored metadata from the index, not current live content. 📈 Ranking by Success Rate: Direct Fetch Systems (Live Retrieval): 🥇 Gemini: 50% (4/8) - JavaScript support + live fetch 🥈 ChatGPT: 37.5% (3/8) - Solid for visible content 🥉 Claude: 0% (0/8) - No prices extracted despite direct fetch Index-based Systems (Search in stored data): Google AI Mode: 25% (2/8) - Found 2 prices after indexing, but only 3 of 7 products Perplexity: 12.5% (1/8) - Very selective: Found ONLY the JS product, not even static HTML ⚠️ Important: Direct fetch (live retrieval) vs. index-based are different approaches. Index systems work with stored data and are therefore not directly comparable to live fetch. Both index systems show that their crawlers execute JavaScript (both found €12.99), but Perplexity's index is significantly more selective. Surprising Findings JSON-LD Schema Markup is NOT extracted by ANY system during direct fetch – even when the information is nowhere else visible on the page. Not a single one of the 5 tested systems could use hidden Schema data. Gemini wins at live fetch: As the only system, Gemini supports JavaScript rendering during direct retrieval and found 50% of prices (4/8) vs. 37.5% for ChatGPT (3/8). All major crawlers index JavaScript: Both Google AI Mode and Perplexity found the JavaScript-rendered price (€12.99) after indexing. This proves that all major crawlers execute JavaScript during indexing – important for SEO! Perplexity's index is extremely selective: After indexing, Perplexity found only 1/8 prices (12.5%) – and that was ONLY the JavaScript product. Not even the prominently placed static HTML product (Blue €5.99) was captured. Google AI Mode was significantly more complete with 2/8 (25%). Limitation: Schema Markup could very well be used in the indexing phase, in LLM training data, or in search engine-integrated AI systems (Google AI Overviews, Bing Copilot). Conclusions: What Do These Results Mean? Core Findings JSON-LD Schema is NOT read by AI chatbots during direct fetch. The price of €8.99 for the Rainbow GEO Bears (Test 3), which was only present in JSON-LD Schema, was not found by any of the 5 tested systems. But: Schema could be used in earlier phases. In the indexing phase, Schema Markup is very likely extracted. Google's AI Overviews and Bing's Copilot have access to this structured data from their search indexes. Gemini supports JavaScript. As the only system, Gemini found the JavaScript-rendered price of €12.99 (Test 2) during live fetch. With 4 of 8 prices found (50%), Gemini performs better than ChatGPT (37.5%) and all other systems. Google AI Mode finds JavaScript prices after indexing. Surprisingly: Google AI Mode also found the JavaScript-rendered price of €12.99 (Test 2), even though it works index-based. This proves that Google's crawlers execute JavaScript during indexing. However, only 3 of 7 products are captured in the index (2/8 prices found). Visible content is essential for most chatbots. ChatGPT and Gemini successfully found all prices present in visible HTML code. JavaScript rendering: Difference between live fetch and indexing. Gemini supports JavaScript during live fetch (found €12.99). Google AI Mode found the same JS price after indexing, which proves: Google's crawlers execute JavaScript. ChatGPT, Claude, and Perplexity cannot capture JS content during live fetch. Hidden structured data is ignored. Neither hidden Microdata (€7.49) nor hidden RDFa (€11.99) were recognized by any system. Perplexity and Google AI Mode have a different approach. Both search their index first instead of fetching pages directly. After indexing: Google AI Mode found 2/8 prices (25%), Perplexity only 1/8 (12.5%). Surprising: Perplexity found ONLY the JavaScript product, not even the static HTML product (Blue €5.99). This suggests very selective crawling behavior. Optimize Your Website for AI Systems AND Search Engines The insights from our study show: A successful web presence in 2025 requires a dual strategy. searchVIU helps you implement both traditional SEO with schema markup and AI optimization with visible, semantic content. Request Free Analysis Leave a Reply Cancel reply Your email address will not be published. Required fields are marked * Comment * Name * Email * Website Save my name, email, and website in this browser for the next time I comment. We've detected you might be speaking a different language. Do you want to change to: English English German Change Language Close and do not switch language We've detected you might be speaking a different language. Do you want to change to: English English German Change Language Manage Consent To provide the best experiences, we use technologies like cookies to store and/or access device information. Consenting to these technologies will allow us to process data such as browsing behavior or unique IDs on this site. Not consenting or withdrawing consent, may adversely affect certain features and functions. Functional Functional Always active The technical storage or access is strictly necessary for the legitimate purpose of enabling the use of a specific service explicitly requested by the subscriber or user, or for the sole purpose of carrying out the transmission of a communication over an electronic communications network. Preferences Preferences The technical storage or access is necessary for the legitimate purpose of storing preferences that are not requested by the subscriber or user. Statistics Statistics The technical storage or access that is used exclusively for statistical purposes. The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you. Marketing Marketing The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes. Manage options Manage services Manage {vendor_count} vendors Read more about these purposes Accept Deny View preferences Save preferences View preferences {title} {title} {title} Manage consent