LLMO (AI Search Optimization) FAQ

Common questions about LLMO — what it is, how it differs from SEO, what it costs, and how long it takes.

What is LLMO?

LLMO (Large Language Model Optimization) is the practice of making a company, product or page more likely to be retrieved, cited and recommended inside answers generated by large language models such as ChatGPT, Gemini, Google AI Overviews and Perplexity. It is used interchangeably with AI SEO, GEO (Generative Engine Optimization) and AIO. The goal is inclusion in the generated answer itself, not a position on a search results page.

How is LLMO different from traditional SEO?

Traditional SEO aims to raise a page's rank on the search results page and drive clicks to the site. LLMO aims for the company's information to be referenced while the model composes its answer, so that the brand is named, compared and recommended in the answer text. Because assistants ground their answers in search results, SEO is a prerequisite for LLMO but not sufficient on its own: a top-ranked page that is not structured for extraction will not be quoted. Keyword selection also differs, since models decompose a user's question into short noun-phrase queries rather than searching the question verbatim.

How much does LLMO support cost in Japan?

Costs vary with scope. A one-off visibility audit typically runs in the low hundreds of thousands of yen, while ongoing engagements covering strategy, content and structural implementation, and monthly measurement generally start in the range of several hundred thousand yen per month. When comparing quotes, align them on two questions: how much of the implementation the vendor performs, and who runs the ongoing measurement.

How long does LLMO take to show results?

Technical changes such as structured data and page restructuring begin to take effect within a few weeks, once crawling and indexing catch up. Getting a brand named consistently inside AI answers usually takes three to six months, because it depends on accumulating content and third-party mentions. Model behaviour also shifts with each update, so plan for continuous monthly measurement rather than a one-time project.

How can I check whether AI search cites my company?

Manually, write a set of prompts a buyer would realistically use, run them against ChatGPT, Gemini and Perplexity, and record whether your brand appears, which competitors it is compared against, and which domains are cited as sources. For continuous tracking you need a system that runs a fixed prompt set on a schedule and aggregates mention rates and cited domains. In parallel, measure referral traffic from chatgpt.com, perplexity.ai and gemini.google.com in GA4 to capture actual visits.

What makes content likely to be cited by AI?

Content is cited when it is easy for a model to transcribe. In practice that means stating the conclusion immediately under each heading, structuring comparisons and procedures as tables or lists, attaching a source and a date to every figure, showing the author, operator and last-updated date, and — most importantly — publishing primary information that exists nowhere else. An article made entirely of general explanation gives a model no reason to cite it, because the model can already generate that text itself.

Who operates this site?

LLMO Navi is operated by Queue Inc. (Queue株式会社), a Japanese technology company running the LLMO business umoren.ai alongside ChatGPT advertising management services. The team works as LLM engineers across RAG, embeddings and answer generation, and publishes the findings and measured data from that practice here.