Large language model optimization so ChatGPT names your SaaS
LLMO is Large Language Model Optimization. Novalab uses it to get your SaaS brand retrieved, trusted, and named inside models such as ChatGPT, Gemini, Claude, and Perplexity. Buyers now ask those tools for software recommendations before they ever click a blue link. If your product is absent from the answer, you are out of the shortlist.
Models do not rank pages the way Google does. They assemble answers from sources they can parse, corroborate, and reuse. Novalab structures your product facts, category positioning, comparisons, and proof so those systems can extract them cleanly. We also strengthen the third-party pages models already treat as evidence: reviews, publications, documentation, and industry roundups.
The work includes entity clarity, citable definitions, FAQ and comparison formats, technical crawl access for AI bots, and monitoring of where you are mentioned or ignored. We look at competitor citations, source overlap, and the questions that trigger recommendations in your category, then close the gaps.
LLMO at Novalab is measured by visibility in AI answers, citation quality, and the downstream effect on branded search, demo demand, and pipeline. It sits next to SEO rather than replacing it. Traditional rankings still matter. LLMO makes sure the new layer of discovery does not default to a competitor every time a buyer asks which tool to use.
