Google ranks pages. AI ranks answers. You need both.
Search is splitting in two. Google still drives traffic, but more and more people ask AI for answers instead: ChatGPT, Perplexity, Claude, Gemini. These engines give responses that look authoritative, recommend specific solutions and shape decisions before a buyer ever lands on a website. If your brand isn't showing up in those answers, you're invisible to a meaningful share of your audience.
Mooning's LLMO and SEO work optimises for both worlds, with a sharp focus on what AI engines cite and what Google still ranks. The strategies overlap (clean technical SEO, citable content, structured data) but the signals each system weights are different. We know what to ship for both.
How AI engines decide what to cite
AI engines don't browse the web the way people do. They retrieve, weight and synthesise, pulling from sources they have decided are worth quoting. That decision rests on patterns: structured data that machines can parse without ambiguity, factual statements that survive being lifted out of context, named entities that match how the engine has organised its knowledge, and authority signals that say a source can be trusted.
Most pages weren't written with any of that in mind. They were written for human readers, on the assumption that Google would parse the rest. That assumption is breaking. Mooning builds content and infrastructure that holds up to both human reading and machine extraction, without compromising either.
LLMO starts with the pages you already have
For brands that want to appear in AI answers consistently, the first wins come from rewriting how existing pages present information, not from publishing more of them. We restructure key pages around the patterns AI engines reliably cite: short factual statements, schema-marked entities, question-and-answer blocks that mirror real query intent, and llms.txt summaries that hand crawlers the version of your story you want quoted.
The work is meticulous and unglamorous. It moves the needle quickly because it removes the friction that stops AI from citing you in the first place.
Rank in Google and get cited by AI
Traditional SEO doesn't go away. Google still drives the largest share of organic traffic, and AI Overviews increasingly pull from pages that already rank in classic search. The right LLMO strategy strengthens classic SEO; the wrong one trades it away.
Mooning's process keeps both intact. On-page work meets Google's E-E-A-T signals while feeding AI engines the structured facts they need. Technical SEO (Core Web Vitals, indexation, crawl budget) runs in parallel with AI-specific optimisation. You don't pick one or the other, because a page that ranks well in Google is also more likely to be pulled into an AI Overview.
Content worth citing
AI engines cite content that earns the citation: clear claims, supporting evidence, named experts, real data and structured Q&A blocks. Generic SEO copy doesn't survive the cut. We commission and produce content with citation in mind, the kind that ends up in answers because it's the source worth quoting.
We work across formats: pillar guides, Q&A libraries, expert quotes, original research and case studies. Each piece has a job: rank in classic search, get cited in AI answers, and earn links from real publications, which help with both.
The technical layer behind AI search visibility
Most of LLMO is invisible to the casual visitor: JSON-LD schema, Open Graph metadata, llms.txt files, canonical and hreflang tags, and crawl directives for both Google and the new wave of AI crawlers (GPTBot, ClaudeBot, PerplexityBot, Google-Extended, Applebot-Extended). Each of these signals tells a machine what your page is, who it's for and why it should be quoted.
Mooning ships this layer as part of every engagement. Once it's in place, the whole site becomes legible to the systems shaping how buyers find you. That's the foundation, and every other part of the LLMO work depends on it. An LLMO and SEO engagement covers:
- AI citation audit
- Schema and structured-data implementation
- llms.txt and AI-citable content
- Traditional technical and on-page SEO
- Citation tracking across AI surfaces