The Generation Logic

The quality of GeoSnap's analysis depends on the quality and coverage of the generated questions. The system employs a structured approach that simulates how real users interact with AIs.

GeoSnap does not use static keywords. The system generates complete conversational questions, formulated as a real user would pose them to ChatGPT, Gemini, or Perplexity. This approach reflects how people actually use AIs: with natural language questions, not search strings.

The Three Levels of Intent

Informational Intent

Questions oriented towards knowledge and education. The user wants to understand, learn, and delve deeper. Typical examples:

• "What is [your product category]?"

• "How does [your industry technology/approach] work?"

• "What are the benefits of [solution]?"

These questions measure if your brand is associated with authoritative content in your field.

Commercial Intent

Questions about evaluation, comparison, and selection. The user is considering different options. Typical examples:

• "What are the best [product/service] for [use case]?"

• "Comparison between [Solution A] and [Solution B]"

• "[Category]: which one to choose in 2025?"

These questions measure if your brand appears in AI recommendations when a user is deciding.

Transactional Intent

Questions with purchase, subscription, or direct action intent. Typical examples:

• "How much does [product/service] cost?"

• "How to buy/subscribe to [solution]?"

• "Alternatives to [competitor] with a lower price?"

These questions measure if your brand is present at the decision-making moment.

Coverage and Variety

GeoSnap generates hundreds of variants for each intent, varying formulation, angle, and specificity. This ensures that results do not depend on a single formulation but represent a statistically reliable picture.

Variety is important because LLMs are sensitive to formulation: the same question posed slightly differently can produce completely different answers. Covering many variants reduces noise and produces more robust data.

Updating the Questions

The questions are updated over time to reflect market evolution, changes in user language, and new trends in your sector. This ensures that the analysis remains relevant and accurate.