LLM SEO · GEO · Answer Engine Optimization
LLM SEO: get your brand cited in AI answers
By Kristian Stig Henriksen · Dear Future
LLM SEO, also called Generative Engine Optimization (GEO) or Answer Engine Optimization (AEO), is the practice of making your brand visible inside the answers that ChatGPT, Gemini, Claude, Perplexity and Google AI Overviews give your customers. Ranking on Google is no longer enough. Increasingly, the first answer your buyer sees is written by an AI assistant, and if you aren't named or cited in it, you were never in the consideration set.
What LLM SEO actually measures
The Dear Future AI Visibility Engine runs a stratified prompt library against every major assistant, every day. From each answer we extract:
- Share of Voice in AI: your slice of the AI conversation vs the market, with a 95% Wilson confidence interval.
- Citations: which of your pages the assistant actually links to, and which competitor pages win when yours don't.
- Mentions & sentiment: whether your brand is named, in what order, and how it's framed.
- Whitespace: the prompts where competitors own the answer and you're invisible.
Why traditional SEO can't do this
Google keyword rankings tell you where your page sits in a list of blue links. AI Overviews and ChatGPT don't return a list, they return a synthesized answer, and only a handful of sources make it into that answer. LLM SEO measures who does. It also handles the messy statistics of AI output: models are non-deterministic, so a single query proves nothing. We aggregate weekly and only flag a change as real once the trend holds up across several weeks.
Answer Engine Optimization in practice
Each week, the Engine ranks the gaps in your AI visibility by win-likelihood times estimated impact, a prioritized to-do list, not a wall of data. You act on the highest-probability wins first, then prove the lift with control-group A/B tests against untouched prompts. That's what turns AEO from a buzzword into a measurable growth channel.
Frequently asked questions
What is LLM optimization?
LLM optimization is the same work as LLM SEO: making your brand visible inside the answers ChatGPT, Gemini and Google AI Overviews give your customers. You will also see it called GEO (generative engine optimization) and AEO (answer engine optimization). The work has two halves: measuring who gets named and cited today, then closing the gaps where competitors own the answer.
What is an LLM?
An LLM (large language model) is the language model behind ChatGPT, Gemini and Claude. It is trained on large amounts of text and predicts the next piece of text in its answer. For LLM SEO the maths is not the point. The point is that the model picks only a handful of sources for each answer, and you are either one of them or you are not mentioned at all.
What is the difference between LLM SEO and traditional SEO?
Classic SEO measures where your page sits in a list of blue links. LLM SEO measures whether you make it into the summarised answer the assistant writes instead of the list. The two are not alternatives: a page that cannot be crawled will be neither ranked nor cited, so LLM SEO is a layer on top of a healthy SEO foundation rather than a replacement for it.
Can you do LLM SEO yourself?
The content half you can do yourself. The hard part to do alone is the measurement: the models are non-deterministic, so a single answer proves nothing. You have to ask the same questions daily, aggregate over weeks, and only call a change real once the trend holds. Without that measurement you can write good content, but you cannot see whether it moved anything.
Keep reading
Share of Voice is one of four signals we track. See the full method on our Share of Voice in AI page, or start on the AI Visibility Engine overview.
See it on your brand
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- 1.Gartner (2024). Gartner Predicts Search Engine Volume Will Drop 25% by 2026, Due to AI Chatbots and Other Virtual Agents. Press release.
- 2.Reid, E. (2024). Generative AI in Search: Let Google do the searching for you. The Keyword, Google.
- 3.Aggarwal, P., Murahari, V., Rajpurohit, T., Kalyan, A., Narasimhan, K., & Deshpande, A. (2024). GEO: Generative Engine Optimization. KDD 2024. arXiv:2311.09735.
- 4.OpenAI (2023). Reproducible outputs with the seed parameter. OpenAI Cookbook.
- 5.Wilson, E. B. (1927). Probable Inference, the Law of Succession, and Statistical Inference. Journal of the American Statistical Association, 22(158), 209–212.