How to train the LLMs to promote your pages

Introduction to LLM SEO

"Training" the LLMs doesn’t mean retraining the model weights. It means shaping the information ecosystem so that when an LLM (via training data or live retrieval) looks for an answer, your brand is among the sources it finds, trusts, and cites. That’s the core of LLM SEO: making your content the kind of content AI systems select.

LLM SEO step 1 — How AI tools get information about you

AI tools get information about you in two main ways:

Training data

Models are trained on huge corpora of web text (e.g. Common Crawl, licensed data). Content that is widely linked, cited, and mentioned across the web is more likely to be in the model’s knowledge. So:

Backlinks and mentions still matter — they increase the chance your domain and key facts appear in the training set.
Consistent entity representation — Same company name, product names, and key claims in many places (your site, press, directories, forums) reinforce "who you are" in the model’s view.

Live retrieval (RAG)

When a user asks a question, many products (ChatGPT with search, Perplexity, Google AI Overviews) run retrieval-augmented generation:

Crawl & index — Content is crawled and often turned into embeddings.
Query — The user’s question is used to search this index (semantic and/or keyword).
Retrieval — Relevant passages or pages are pulled back.
Synthesis — The LLM generates an answer using those passages and may cite sources.

So for live visibility, your content must be retrievable (crawlable, well-structured, relevant to queries) and citable (clear, factual, with distinct claims the model can attribute to you). Conductor and similar guides stress that AI systems "retrieve and synthesize" from the open web; your job is to be in that retrieval set and easy to cite.

LLM SEO step 2 — Optimize your about-us page for artificial intelligence

Your About (and company/entity) pages are prime candidates for AI to understand who you are, what you do, and why you’re relevant. Optimize them for both humans and machines:

Clear, factual description — State your name, category, and value proposition in the first paragraph in a way that can be quoted or paraphrased (e.g. "X is a [category] company that …").
Structured facts — Use lists or short paragraphs for: what you do, who you serve, key differentiators, location, founding or key dates. This makes it easy for retrieval systems to pull a single, coherent "entity summary."
Schema — Implement Organization (and, if relevant, LocalBusiness or Product) schema so search and AI can parse your identity and attributes.
Consistency — Use the same company name, tagline, and key claims as on the rest of the site and, where possible, on external sites (Wikipedia, Crunchbase, LinkedIn, etc.). Inconsistency confuses both users and AI.

Treat the About page as the canonical source of truth for "who we are" so that when an LLM or RAG system looks for a summary of your company, it finds one clear, structured answer.

About page template (fill in the brackets)

Use this as a starting point; keep the first paragraph under 3–4 sentences so it can be quoted as a single chunk:

[Company name] is a [category, e.g. B2B SaaS / eCommerce brand / agency] that [core value proposition in one sentence]. We serve [primary audience, e.g. mid-size marketing teams / developers / small business owners]. [Founded in year; optional: location or "headquartered in X"]. [One key differentiator or proof point — e.g. "Used by over X companies" or "Trusted by brands like A, B, C."]**

Then add a short list or subheadings: What we do (2–3 bullets), Who we serve, Key differentiators, Contact or CTA. Keep the tone factual and consistent with how you’re described elsewhere (press, LinkedIn, directories).

Technical checklist for AI-friendly presence

Organization schema — On the About page (and/or homepage): name, url, logo, description, sameAs (social and profile URLs). Ensures search and AI can parse your identity.
One canonical "who we are" paragraph — A single, quotable block (the template above) that appears on the About page and, if useful, in the footer or meta description. Same wording everywhere you need a short summary.
robots.txt — Don’t block common AI crawlers on important pages. Many AI systems use crawlers similar to Googlebot; if you allow Google, you’re usually in good shape. If you use strict allowlists, add known AI crawler user agents (e.g. for OpenAI, Perplexity) for key URLs so your content can be retrieved.
Consistency — Company name, tagline, and one-sentence description match across the site, schema, and (where you control it) external profiles like LinkedIn or Crunchbase.

Results of how you can get promoted by AI

When your content is retrievable and citable, you can see:

Inclusion in AI answers — Your brand or product appears in the generated answer (e.g. as a recommendation or a source).
Citations and links — Many AI interfaces link back to your pages when they use your content.
Brand and direct traffic — Users who see you in an AI answer may search your brand or click through later; attribution can be indirect but the impact is real.

Because retrieval and ranking aren’t deterministic, the right way to measure is share of voice across a set of prompts: run the same (or similar) questions repeatedly, track how often you’re mentioned or cited, and improve content and structure based on gaps.

What to measure:

Which prompts to run — Use the 3 queries you wrote down in Module 1, plus 2–3 variations (rephrase the question, ask for "best" vs "top" vs "recommended"). Cover the intents that matter for your business (e.g. "what is X," "best X for Y," "how to do Z with X").
How often — Run your prompt set at least weekly when you’re actively optimizing; every 2–4 weeks for ongoing monitoring. AI responses can change as indexes and models update, so one-off checks aren’t enough.
What counts as "cited" — Note: (1) Named — your brand or product appears in the answer text. (2) Linked — your URL appears as a source or recommendation. (3) Quoted — a specific claim or sentence from your site is paraphrased or quoted. Any of these is a win; linked + named is the strongest. Track which prompts yield which level so you know where to improve.

Platforms like Obsurfable help you define those prompts, run checks against ChatGPT and other tools, and see where you’re already recommended and where you’re missing — so you can get promoted by AI in a repeatable way.

Google AI Overviews and SGE (Search Generative Experience)

Google AI Overviews (the generative summaries that appear in search) are part of Google’s move toward answer-first search. They synthesize information from the web and often cite multiple sources (commonly 3–8 per overview). Studies (e.g. Result First, Digital Applied) indicate that a large share of cited sources also rank in the top 10 organic results for the query — so strong SEO and strong, extractable content both matter.

To improve your chances of being cited in AI Overviews:

E-E-A-T — Demonstrate experience, expertise, authoritativeness, and trustworthiness (see Module 4).
Clear, comprehensive content — Answer the query and related sub-questions so your page is a natural source for the overview.
Structure and schema — Headings, lists, and structured data help Google’s systems parse and attribute content.

AI Overviews are one of the main places where "traditional" search and "generative" search meet: the same page can rank in blue links and be pulled into the overview. Optimising for both (as in Module 2) is the right strategy.

In the next module we focus on reputation: E-E-A-T and how external sources like Wikipedia, Quora, and Reddit influence what AI says about you.