In this section, we’ve gathered answers to the most common questions about how brands are perceived in ChatGPT and Google AI, how large language models (LLMs) rank information, and how the GEO methodology works.
Language models do not browse the web in real time like a traditional search engine. They rely on accumulated data, trusted sources, and structured brand signals. How they describe your company depends on the quality and consistency of the information about it across the web. There are exceptions: newer implementations, such as paid versions of ChatGPT with browsing enabled or AI features built into Google Search, can integrate real-time results. However, the model’s core "knowledge" about a brand still comes from its training data.
Yes. You can simply ask ChatGPT about your company in natural language (for example, “What do you know about brand X?”). However, only a professional benchmark can show how often and in what context your brand appears in AI-generated responses, and how it compares to your competitors.
Usually because the models cannot detect consistent or trustworthy brand signals. This may result from incorrect or fragmented data, missing relationships between sources, weak site structure, or content that isn’t semantically clear enough for language models to interpret effectively.
No, but it changes what SEO means. SEO remains essential for indexing and quality content, while GEO (Generative Engine Optimization) determines whether and how your brand appears in AI-generated answers.
Not exactly. Gemini uses Google’s data, but processes it differently. It combines information from multiple sources to generate contextual responses rather than showing lists of links. This is why traditional SEO alone is not enough to build visibility inside AI answers.
Yes. You can upgrade from Starter to Pro or Full Suite anytime - we’ll retain and expand your existing visibility data.
Yes. We analyze brands in ChatGPT and Google AI across multiple languages and markets.
