Show up when the answer comes from AI, not a results page.

No. SEO optimizes for a position on a list of links; GEO optimizes for being retrieved and quoted inside a generated answer. The inputs overlap (crawlability, clear structure, credible content) but the weightings diverge: GEO leans far harder on self-contained passages, entity clarity, structured data, and AI-crawler access than on backlinks or keyword placement. Most companies need both, because buyers still use both.

AI Overviews draw mostly from pages already ranking well for the query, so conventional ranking is the entry ticket, but what gets quoted is the passage that answers the question directly and early. We restructure target pages so each section opens with a complete, standalone answer, add the supporting schema, and aim at the question variants that actually trigger an Overview rather than the head term.

Honestly, not much yet. llms.txt is a proposed standard for pointing AI systems at your best content, and no major engine has confirmed it as a retrieval or ranking input. We add one because it is cheap, harmless, and useful insurance if adoption arrives, but we won’t sell it as a lever. What verifiably moves AI visibility is crawler access, page structure, and entity clarity.

Referrals from ChatGPT, Perplexity, and Gemini arrive with identifiable referrers, so AI-driven sessions can be split out as their own channel in analytics rather than being lumped into direct traffic. We set that segmentation up at the start so there is a real before-and-after, then report sessions, pages entered, and conversions per engine. Bella Private Markets saw a 200–300% lift in AI-engine traffic measured this way.

ChatGPT, Perplexity, Google AI Overviews and Gemini, and Bing Copilot. They differ in ways that change the work: Perplexity cites heavily and visibly, so it rewards clearly sourced pages; AI Overviews lean on pages already ranking, so conventional SEO carries more weight there; ChatGPT blends live retrieval with training-era knowledge, so off-site entity presence matters more. We build the shared foundation, then tune per engine.

It depends which crawler. Training crawlers take your content to build models and send nothing back; answer-engine crawlers are how you get cited and referred. They use different user agents, so you can allow one and block the other: we’ve configured exactly that split at the CDN layer for a client, permitting answer bots while blocking training scrapers. Blocking everything makes you invisible in AI search.

They largely describe the same work at different scopes. AEO, answer engine optimization, is the older term for earning the direct answer, featured snippets included. GEO covers being retrieved and quoted by generative engines generally. AI Overview optimization is narrower still: Google’s Overviews alone. We treat them as one discipline, because the underlying work (reachable pages, self-contained answers, unambiguous entities) is shared. Anyone selling them as three products is selling packaging.

The same people you meet. This team has worked together fifteen to twenty years with settled areas of responsibility: you meet a decision-maker, not an account manager.

We come back with an actual opinion. No deck, no pitch, no follow-up gauntlet, and if we’re not a fit, we’ll tell you.