How AI reads this page
ChatGPT, Claude, Gemini and Perplexity don't look at colours, images or animations. They receive text, headings, links and structured data. Below is exactly what they read when they open “Prompt Simulation Logic”.
The AI receives 329 words in 5 sections, 0 links and 2 blocks of structured data.
Text
The page content in Markdown, without menus or graphics. It is the format closest to how a language model reads text.
# Prompt Simulation Logic > Geosnap doesn't just ask AI, "Do you know brand X?". It simulates the real behavior of a potential customer who uses AI to gather information, evaluate URL: https://geosnap.ai/en/doc/prompt-simulation-logic Language: English Version IT: https://geosnap.ai/doc/prompt-simulation-logic Publisher: Geosnap (Maind Group S.r.l.), https://geosnap.ai ## The Principle of Simulation Geosnap doesn't just ask AI, "Do you know brand X?". It simulates the real behavior of a potential customer who uses AI to gather information, evaluate options, and make purchasing decisions. This approach is crucial because the way a question is formulated deeply influences the AI's response. A direct query about the brand would produce an artificial result, not representative of the real user experience. ## How Prompts Are Constructed Geosnap prompts are designed to replicate the conversational queries a real user would pose to an AI assistant. The construction process follows these phases: - **Context Analysis**: From the website and country, Geosnap identifies the industry, offering, and market - **Question Mapping**: Variants of questions are generated for each level of intent - **Natural Formulation**: Every prompt is written in conversational language, as a user would pose it - **Diversification**: Questions are varied in formulation, specificity, and angle ## Why We Don't Use Keyword-Based Queries People don't speak with AIs like they would with Google. They don't type "best CRM small company price" but ask "What is the best CRM for a small business with a limited budget?". Geosnap replicates this conversational behavior because it is what produces realistic responses. ## Simulation Without Previous Context Every Geosnap inquiry is conducted without prior conversational context, simulating a user asking a question for the first time. This eliminates personalization bias and produces results that represent the average user experience. ## Volume and Statistical Significance AI responses are inherently variable: the same question asked twice can produce different answers. That's why Geosnap generates hundreds of questions and analyzes the aggregated patterns. High volume ensures statistical significance and reduces noise, producing reliable and actionable metrics.
Structured data
Schema.org data (JSON-LD) embedded in the page code. It tells the AI explicitly what the page is about and who published it.
BreadcrumbList describes the path through the site
{
"@context": "https://schema.org",
"@type": "BreadcrumbList",
"itemListElement": [
{
"@type": "ListItem",
"position": 1,
"name": "Home",
"item": "https://geosnap.ai/en/"
},
{
"@type": "ListItem",
"position": 2,
"name": "Documentation",
"item": "https://geosnap.ai/en/docs"
},
{
"@type": "ListItem",
"position": 3,
"name": "Prompt Simulation Logic",
"item": "https://geosnap.ai/en/doc/prompt-simulation-logic"
}
]
}
TechArticle describes the guide
{
"@context": "https://schema.org",
"@type": "TechArticle",
"headline": "Prompt Simulation Logic",
"url": "https://geosnap.ai/en/doc/prompt-simulation-logic",
"inLanguage": "en",
"publisher": {
"@id": "https://geosnap.ai/#organization"
},
"isPartOf": {
"@type": "WebPage",
"url": "https://geosnap.ai/en/docs"
},
"description": "Geosnap doesn't just ask AI, \"Do you know brand X?\". It simulates the real behavior of a potential customer who uses AI to gather information, evaluate"
}
Metadata
The information in the page header, which crawlers and engines read before the content.