What is LLM SEO?

LLM SEO is the practice of optimising your content so that large language models (the AI behind assistants like ChatGPT, Gemini, Claude and Perplexity) find, trust and quote your business when they answer a question, instead of only ranking your pages in a traditional list of search links.

It has its own name because the target has moved. When an assistant writes the answer, there is no page two and rarely more than two or three businesses named. Being the fourth-best result used to earn real traffic; inside a generated answer it earns you nothing. LLM SEO is the work of making sure you are one of the names that gets written down.

How is LLM SEO different from traditional SEO?

LLM SEO optimises your content to be quoted inside a generated answer; traditional SEO optimises it to rank as a link in a list. The foundations overlap heavily (both reward genuine quality, clean structure and real authority), but the target and the way you measure success are different.

Three differences matter in practice:

• ✓The result is a written answer, not a ranked list. You are competing to be one of a handful of sources the model cites, not to place tenth on a page nobody scrolls.
• ✓A mention is not a click. An assistant can recommend you and send no traffic at all, because the customer got what they needed in the chat. You measure presence in answers, not only sessions.
• ✓The sources are broader than your own site. Models assemble answers from your pages, yes, but also directories, roundups, review sites and industry press, so LLM SEO extends beyond your own content to what the wider web says about you.

LLM SEO is really a plain-English label for the same shift covered by the broader term generative engine optimisation: different words, same underlying change in how buyers find you.

How do you do LLM SEO?

You do LLM SEO by structuring pages so a model can lift a clean, correct answer from them, and by making your business easy to identify and corroborate. In short: answer the question first, name entities plainly, back claims with specifics, mark the page up so it is machine-readable, and then measure whether the assistants actually quote you.

• ✓Answer-first structure. Put a direct, self-contained answer in the opening line under each question heading, before any preamble. That opening block is what a model lifts.
• ✓Clear entities. State who you are, what you do and where you operate in plain terms, so the model can attribute the answer to a real business rather than an anonymous page.
• ✓Concrete, quotable claims. A specific number or named method you can stand behind beats a marketing generality every time. Vague sentences get skipped in favour of pages that state the fact cleanly.
• ✓Structured data. Machine-readable markup declares the author, the question and the answer explicitly, which raises the chance a model quotes you accurately rather than guessing.
• ✓Measure and adjust. Producing the content is the easy half now; the hard half is knowing whether it worked: which pages earn citations, which earn nothing, and what to change next.

The platforms differ in the detail. If ChatGPT is the assistant your buyers reach for first, the mechanics of getting quoted there are worth their own read: how to rank in ChatGPT.

What are the best LLM SEO tools?

There is no single best LLM SEO tool, and any list that crowns one is usually selling it. The useful ones fall into two camps: production tools that help you research and draft the content, and visibility trackers that tell you whether the assistants actually mention you and which sources their answers were built from.

Judge any tool on whether it does more than generate output:

• ✓Does it track the buying questions your customers really ask, across the assistants they really use, not a generic preset?
• ✓Does it show the sources behind each answer, so you know what to influence next, rather than only a mention count?
• ✓Does it connect what you publish to what happened (citations, enquiries), or does it stop at "content created"?

The visibility half of this (checking whether assistants name you and who they name instead) is a category of its own; if that is your immediate question, start with the deeper read on AI visibility tools. But keep the limit in view: a tool tells you where you stand, not what to do about it. Producing content is easy now; closing the loop (produce, measure, decide, adjust) is the part no tool does for you, and the part that actually moves results.

Is LLM SEO worth doing now?

Yes, and mostly because so few businesses are doing it deliberately. Search behaviour is shifting toward generated answers faster than most companies' content plans, and the businesses being named in answers today are building an advantage that compounds, because assistants keep returning to sources that have already proven reliable.

Set your expectations honestly, though. Like all SEO, this compounds over months, not weeks: structural fixes can show quickly, but the citations and authority that genuinely move the needle build over quarters. Anyone promising you AI citations in thirty days is selling something that does not exist. The upside is that the work overlaps heavily with good SEO, so very little of it is wasted even where generated answers have not taken over yet.

About the author

This guide is written from inside seodesk by the founder, who has 15+ years of senior e-commerce and frontend experience and has built and run multiple online businesses. The methods here are the ones used on platforms he owns, not repackaged theory.