How GeoSnap Works

GeoSnap operates in four main phases, each designed to simulate how a potential customer interacts with AI to make decisions.

Phase 1 — Brand Contextualization

When you enter your website and select your country, GeoSnap analyzes the context of your business: industry, offering, target market, and positioning. This information serves as the basis for generating relevant and realistic questions.

Phase 2 — Question Generation

GeoSnap automatically generates hundreds of structured prompts, organized into three types of search intent:

Informational intent — Questions a user might ask to learn about a topic. Example: "How does a project management software work?" These questions measure whether your brand is associated with educational content in your field.

Commercial intent — Questions evaluating and comparing solutions. Example: "What are the best CRMs for small businesses?" Here, it measures whether your brand appears in recommendations and comparisons generated by AI.

Transactional intent — Questions intending to purchase or take immediate action. Example: "How much does [product category] cost and where can I buy it?" These questions check if your brand is mentioned at the decision-making moment.

The division by intent is crucial because LLMs respond differently based on the type of question. A brand can be highly visible for informational questions but completely absent for transactional ones.

Phase 3 — Querying AI Engines

Each question is sent to major AI engines: ChatGPT (OpenAI), Gemini (Google), and Perplexity. GeoSnap simulates the behavior of a real user asking conversational questions to AI, gathering comprehensive responses including cited sources.

Phase 4 — Analysis and Data Delivery

The responses are analyzed and transformed into actionable metrics:

• AI Rating: the frequency and position with which your brand appears in responses

• Sentiment: the analysis of tone and perception associated with your brand

• Competitors: the mapping of all brands mentioned in your category

• Sources: the list of web sources that AI cites as reference

• Insights: correlations and patterns that emerge from the data

• Actions: concrete recommendations to enhance your visibility

The Value of Multi-Intent Simulation

The strength of GeoSnap lies in its broad and structured coverage. Analyzing a single prompt would give specific data, but not representative. By generating hundreds of questions on different intents, GeoSnap builds a reliable statistical map of your presence in the AI ecosystem.

This approach reveals patterns invisible with manual analysis: you might discover that your brand is recommended for educational questions but ignored in purchasing moments, or that a competitor dominates on a specific AI engine but is absent on another.