AEO vs GEO: How to Get Your Brand Cited in ChatGPT, Claude & Perplexity.
The architectural differences between Answer Engine Optimization and Generative Engine Optimization — and the exact steps to build presence in both.
AEO vs GEO: The Key Distinction.
Answer Engine Optimization (AEO) focuses on getting your brand cited in conversational AI responses — ChatGPT, Claude, Siri. Generative Engine Optimization (GEO) targets AI search surfaces that synthesize real-time web content — Perplexity, Google AI Overviews, Bing Copilot. Different systems. Different optimization strategies.
Most brands optimize for neither. They continue publishing blog posts for Google while their competitors quietly accumulate AI citation share.
How LLMs Decide Which Brands to Cite.
Large Language Models built on training data (GPT-4, Claude) cite brands that appear frequently in high-authority, trustworthy sources from their training corpus. Retrieval-augmented systems (Perplexity) cite brands that appear on pages the system can actually crawl and parse efficiently.
- Training data authority: guest posts in developer publications, Wikipedia mentions, Wikidata entity nodes
- Schema declaration: JSON-LD organization and product schemas that match the query context
- RAG readability: content structured so the first 150 words of each page answer the core question
- Entity consistency: same brand name, description, and facts across all public profiles
Building Your Entity Graph.
Your entity graph is the network of public records that AI systems query to understand who you are. Start with a Wikidata entry, then ensure consistency across Crunchbase, LinkedIn, Google Business Profile, and industry directories.
An AI platform we worked with grew from 4% to 42% citation share in 16 weeks by declaring a Wikidata entity node and restructuring their documentation for RAG ingestion.
RAG-Optimized Content Architecture.
Retrieval-Augmented Generation systems extract "chunks" from pages to answer queries. Each page should contain a self-contained summary in its opening paragraph — one that directly answers the most likely query that would bring someone to that page. Avoid burying the answer behind 400 words of context.
- Open every page with a 2-sentence direct answer to the most relevant query
- Use clear H2 headings that mirror how questions are actually phrased
- Include a structured FAQ section with 5-7 common questions
- End with a definitive conclusion that reinforces the key claim
Measuring Citation Share.
Track citation share by systematically prompting AI systems with your target queries weekly. Establish a baseline, then measure after each optimization sprint. A 40-query benchmark set, tested across 3 systems (GPT-4o, Claude, Perplexity) gives you 120 data points per month.
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