The discipline of optimizing for Large Language Models — making sure ChatGPT, Claude, Gemini, and Perplexity name your brand, recommend your products, and treat you as a trusted source.
When most people talk about "AI search," they mean retrieval — what an LLM grabs from the web at query time, like Perplexity or ChatGPT Browse. That's part of the picture. The other part is far bigger and far less understood: what the LLM already knows from its training data.
When you ask ChatGPT or Claude "what are the best D2C watch brands in India?" — the model doesn't always search the web. Often, it answers from its training. The brands it names are the ones whose information was prominent, well-structured, and frequently cited during the training period. Brands missing from that data simply don't exist in the model's worldview.
LLM SEO (also called LLMO — Large Language Model Optimization) is the discipline of becoming part of the training. It's about ensuring your brand, products, and expertise are present in the data sources LLMs learn from — and structured so they're confidently retrieved when needed.
| Discipline | Targets | Goal | Time Horizon |
|---|---|---|---|
| AEO | Featured snippets, AI Overviews, voice | Win the answer surface in Google | Short — weeks |
| GEO | Generative engines (Perplexity, ChatGPT Browse) | Get cited at retrieval time | Medium — 1–3 months |
| LLM SEO | Training data, model knowledge | Be known by the model itself | Long — 6–18 months |
All three work together. AEO is the fastest impact. GEO is the medium-term play. LLM SEO is the long-term moat — being part of the model itself means your brand surfaces even when no live retrieval happens, and remains in answers for the lifecycle of that model.
Large language models are trained on massive datasets — Common Crawl, Wikipedia, books, code repositories, news archives, academic papers, forum content like Reddit, and licensed datasets. From these sources, models learn:
Brands that appear strongly across these data sources during training become "known" to the model. Brands that don't, simply aren't part of the conversation when the model generates responses about your category.
Test how ChatGPT, Claude, Gemini, and Perplexity currently respond when asked about your brand, your category, and your competitors. Identify where you appear, where you're absent, and where competitors are dominant. This becomes the baseline.
Wikipedia is the single most-weighted training source for most major LLMs. Where appropriate (and notable enough to qualify), I work on Wikipedia article creation, expansion, citation strengthening, and Wikidata entity registration. This is high-effort, high-reward work — a strong Wikipedia presence often moves LLM visibility more than any other single intervention.
Strategic placements in publications LLMs trust — major news sites, industry trade publications, academic journals where applicable, expert roundups, and well-indexed knowledge bases. Each placement reinforces brand-category-solution associations the model learns from.
Reddit is one of the largest training data sources. Authentic, valuable participation in relevant subreddits — answering category questions, providing genuine expertise, never spamming — builds the kind of organic mentions that influence model knowledge.
Your own site, structured for LLM ingestion: clean HTML, comprehensive schema, consistent entity references, well-formed FAQ blocks, and content depth around your category's core questions. LLM crawlers (GPTBot, ClaudeBot, Google-Extended) read this content during training cycles.
When users ask LLMs comparison questions, the answers come from comparison content trained on. Strategic comparison content — both yours and through earned media — establishes your brand in the LLM's "consideration set" for your category.
Monthly sampling of brand mentions across major LLMs for target queries. Tracking trend over time. Identifying which interventions are working. Adapting strategy as new model versions roll out and new platforms emerge.
LLM SEO is a long-horizon investment. It works best for:
Send a WhatsApp message — let's discuss your brand's LLM presence.