To optimize for AI answers, you need to understand, at a practical level, how LLMs decide what to surface.
Generative engines combine two types of knowledge: parametric memory (information encoded during training) and real-time retrieval, known as RAG, Retrieval-Augmented Generation.
ChatGPT processes approximately 60% of requests using parametric memory and 40% via real-time search integration.
Perplexity is primarily retrieval-based.
Google AI Overviews retrieves in real time and synthesizes a 3-5 sentence answer with citations.
Four signals matter most for GEO visibility:
Structured clarity: LLMs prefer content that makes its meaning unambiguous, direct answers in the first 200 words, clear question-based headings, FAQ sections. LLMs are 28-40% more likely to cite content with clear formatting: hierarchical headings, bullet points, numbered lists, and tables.
Statistical specificity: A Princeton research found that adding specific, sourced statistics to content increases its probability of being cited by AI by 37%. Vague claims like "many brands are adopting AI" carry no value for an LLM. Precise formulations, with data and attribution, do.
Entity recognition: AI models think in entities, brands, products, people, categories. The more consistently your brand is mentioned, described and associated with specific concepts across the web, the more clearly a model understands who you are and what you offer.
Third-party authority: AI platforms trust third-party sources more than brand-owned content. Reviews, press coverage, forum discussions and editorial mentions on platforms LLMs actively index are often more powerful GEO signals than your own website.
On the technical side - Content with proper schema markup shows 30-40% higher visibility in AI-generated answers. FAQ schema, specifically, is the single highest-impact and easiest-to-implement starting point for most ecommerce brands.
