LLM optimization for teams who already do SEO well.
Your rankings are fine. The problem is that a language model now stands between your page and your buyer, and it is summarising you from sources you did not write. This is the work of fixing that.
Four shifts from SEO to LLM optimization.
Same site, different consumer.
Six levers for language models.
None of them are content volume.
Extractable claims
Short, specific, self-contained statements a model can lift without losing meaning.
Entity consistency
One name, one description, one set of facts across your site, schema, profiles and knowledge panels.
Retrievability
Key facts published as readable text, valid schema, no bot-blocking in robots.
Public documentation
Limits, integrations and setup steps outside the login wall — the most-cited source in technical answers.
Misinformation control
Stale third-party claims about you traced to source and corrected with citable pages.
Answer-level reporting
Mention share and citation share reported next to your existing search metrics.
Two metrics, two channels.
Strong rankings and weak LLM visibility is the most common pattern we see.
For SEO teams.
Partly. Crawlability, structure and authority carry over. Retrievability without JavaScript, entity consistency and quotable phrasing usually do not.
No. Every change we make — structured on-page copy, valid schema, published specifics — is neutral or positive for search.
Yes. We export by CSV so LLM metrics sit alongside your rank data rather than replacing it.
Usually SEO leads it with one developer for the technical layer. It rarely needs a new team.
Publishing real numbers — prices, limits, hours — in plain HTML. It is the most common blocking gap and the cheapest to fix.
Compare your rankings to your LLM visibility.
The free check shows both, and usually the gap is the story.