AI Search Visibility

Yes — different inputs, different ranking signals, different optimization tactics. Traditional SEO optimizes for Google's crawler and link graph. LLMO optimizes for how an AI model selects and synthesizes information at query time. Some overlap (schema, authority, content quality), but a lot of LLMO is brand-new: entity profiles, Wikipedia/Wikidata signals, retrieval-augmented generation (RAG) sources, and the way different LLMs weight different citation classes.

We run a structured query set across all major LLMs for your category — questions a Qatar buyer would actually ask — and capture every response. That gives you a baseline visibility map: where you're cited, where competitors are cited, where neither is, and which queries the LLMs refuse to answer. We re-run this weekly so you can see movement over time.

Faster than traditional SEO for two reasons: (1) LLMs ingest new authoritative signals quickly — sometimes weeks not months; (2) the field is so uncrowded that getting cited is achievable for most credible Qatar brands in the first 90 days. Full category leadership in AI search takes 6–12 months. The brands starting now will be unbeatable in their categories by 2027.

Fair question — there are plenty of LLMO snake-oil sellers. M&M's approach is measurable end-to-end: weekly mention-tracking against a fixed query set (so you can see actual progress), citation logging in third-party SEO tools (Ahrefs, SEMrush now track AI Overviews citations), and revenue attribution where AI-referred traffic shows up in your analytics. If we can't prove movement in 90 days, we'll tell you.