🤖 GEO & AI Search

The Complete Guide to GEO: How to Get Your Brand Into ChatGPT & Gemini Answers in 2025

FR
Farzin Rastgar
Founder, Top3Results
May 2025
18 min read
12,400 views

Something fundamental has shifted in how people search for information. In 2025, a significant and growing proportion of high-intent research begins not on Google, but inside ChatGPT, Gemini or Perplexity. These AI tools return one answer — not ten links. If your brand is not that answer, you receive zero visibility from that search. This guide explains exactly how to change that.

What is Generative Engine Optimization (GEO)?

Generative Engine Optimization (GEO) is the practice of optimising your brand's online presence to appear in the answers generated by AI language models — primarily ChatGPT (OpenAI), Gemini (Google), Perplexity AI, Claude (Anthropic) and Meta AI.

Unlike traditional SEO, which targets a position in a list of ranked links, GEO targets the conversational, synthesised answers that AI tools generate when users ask questions. When someone asks ChatGPT "What's the best CRM for small businesses?", the answer either mentions your brand or it doesn't. There is no page 2.

Why this matters now

A 2024 study found that 60% of users research products using AI tools before visiting any website. For B2B software, that figure is even higher. The brands that get cited in AI answers are capturing research intent that never reaches Google at all.

How AI Language Models Decide What to Cite

Understanding why an LLM cites one brand over another requires understanding two distinct systems that work together:

1. Pre-training Knowledge

Large language models are trained on enormous datasets of text from the web, books and other sources. During this training, they absorb factual associations — which companies exist in a space, what they do, what their reputation is. Brands that appeared frequently across high-quality sources during the training window have stronger entity representations in the model.

2. Retrieval-Augmented Generation (RAG)

More modern AI search tools — particularly Perplexity AI and the web-enabled versions of ChatGPT and Gemini — use RAG to pull current information from the web before generating their answer. This is where real-time GEO optimisation has the most leverage.

Key takeaways
Pre-training knowledge favours brands with high citation frequency across trusted web sources
RAG systems favour content that is authoritative, structured, recent and directly answers specific questions
Both systems can be influenced — through different tactics and different timelines

The 6 GEO Ranking Factors

Based on our testing across 200+ client accounts, these are the factors with the highest correlation to AI citations:

FactorImpact on GEOTimeline
Citation density across authoritative sources🔴 Very high3–6 months
Entity clarity and structured data🔴 Very high4–8 weeks
Content depth and direct Q&A matching🟠 High4–8 weeks
Domain authority and trust signals🟠 HighOngoing
Recency and content freshness🟡 Medium1–4 weeks
User intent alignment🟡 Medium4–8 weeks

The GEO Optimisation Process — Step by Step

Step 1: Run a GEO Baseline Audit

Before optimising, you need to know where you currently stand. Test your brand visibility by asking 30–50 queries related to your business across ChatGPT, Gemini and Perplexity. Document which queries trigger a brand mention, which mention competitors instead, and which sources are cited alongside your brand.

Step 2: Build Entity Authority

AI language models understand the world through entities — named things and the relationships between them. Your goal is to make your brand a clear, well-defined entity strongly associated with your target category.

  • Implement comprehensive Organization schema on your homepage and about page
  • Create consistent brand mentions across high-authority directories, Wikipedia and knowledge graph sources
  • Ensure your brand appears in industry databases — G2, Capterra, Clutch and vertical-specific listing sites
Organization schema example
{ "@context": "https://schema.org", "@type": "Organization", "name": "Top3Results", "url": "https://top3results.com", "description": "Elite SEO, GEO and AEO agency", "foundingDate": "2018", "sameAs": [ "https://linkedin.com/in/farzzin" ] }

Step 3: Create AI-Optimised Content

The content patterns that get cited in AI answers share several characteristics. Based on our analysis, cited content is: directly answering a specific question, clearly structured with headers and lists, authoritative in tone, comprehensive in scope, and unique in perspective — offering original data or frameworks that cannot be found elsewhere.

Step 4: Build Citation Infrastructure

AI models cite brands that appear repeatedly across trusted web sources. Priority citation sources include: industry publications, Reddit discussions in relevant subreddits, G2 and Trustpilot reviews, YouTube transcripts, podcast appearances and expert roundups.

Priority citation sources for GEO

Industry publications in your vertical · Reddit discussions · Quora answers · G2, Capterra & Trustpilot reviews · YouTube transcripts · Podcast appearances · Expert roundups · Wikipedia mentions (where appropriate)

Measuring GEO Success

GEO measurement requires a manual testing approach. The framework we use: Weekly AI Visibility Score (test 50 target queries across ChatGPT, Gemini and Perplexity), competitor displacement rate (track when you appear instead of competitors), platform coverage (which platforms cite you — they often differ significantly), and AI-referred traffic in Google Analytics 4.

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Farzin Rastgar
Founder, Top3Results

Farzin founded Top3Results with one obsession — rankings that generate real revenue. He has helped 200+ businesses reach the top 3 results across Google, AI search and the map pack. Follow his work on SEO, GEO and AEO strategy.

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