What is Generative Engine Optimization (GEO)?

Why GEO exists

A growing share of product research now starts as a conversation instead of a search. Someone asks an assistant "what's the best budget CRM for a two-person team?" and gets a synthesized answer naming two or three brands — often without ever seeing a results page. If your brand isn't in that answer, you weren't skipped; you were invisible.

Classic analytics makes this worse by hiding the traffic you DO get from AI. Visits from assistant apps frequently arrive with no referrer and land in the "Direct" bucket, so most teams underestimate how much AI already sends them — why AI traffic shows up as Direct covers that in full.

What GEO actually consists of

In practice GEO has two levers, and they are not equally heavy:

• On-site readiness — the signals you control directly and can verify: can AI systems crawl you (robots.txt not blocking AI bots), do you answer questions directly near the top of the page, do you carry structured data (Organization, FAQ schema), are your claims sourced and dated. This is necessary hygiene — cheap to fix, and fully in your control.
• Off-site evidence — the third-party sources already appearing in answers for your market: are you present in the sources AI actually reads for your category — review sites, comparison articles, community threads (Reddit, forums), industry lists. Assistants synthesize from what they trust; if the pages they trust never mention you, on-site work is not addressing where that answer's evidence comes from.

Any tool or agency promising a guaranteed top-3 placement in AI answers is overselling — answers vary run to run, differ by engine, and depend on sources you don't control. What you CAN do is measure where you stand, fix the on-site gaps, and systematically earn presence in the sources that engines cite for your category.

How you measure GEO

You measure GEO the way your customers experience it: ask the engines real questions and record who they name. A useful measurement loop looks like this:

• Track the exact questions your buyers ask ("best X for Y"), across multiple engines — one engine is an anecdote, seven is a signal.
• Record whether each answer mentions you, cites your URL, or names a competitor instead — and your position within the answer.
• Audit your site's technical readiness once, fix what's red, then re-check the same questions and watch the mention count move.
• Separately, measure the visits and revenue AI assistants already send you, so the effort connects to money rather than vanity mentions.

That loop — measure, fix, re-check, prove — is exactly what Promvia automates. But the loop matters more than the tool: even doing it manually once a month beats not knowing.

Where to start this week

• Check your robots.txt: many sites block a search crawler by accident (often via a CDN's bot protection) and never find out. OAI-SearchBot, Claude-SearchBot and PerplexityBot are the search crawlers behind those assistants' answers; Googlebot is the ordinary Google Search crawler, and AI Overviews runs on the Search eligibility it establishes rather than on a separate per-answer fetch. GPTBot and ClaudeBot are training crawlers, and blocking those is a separate choice that costs you nothing here.
• Pick the five questions that should name you, ask them in ChatGPT and Perplexity, and write down who gets named. That's your baseline.
• Put a direct, quotable answer in the first paragraph of your most important page — engines lift concise answers, not marketing prose.
• Find the two or three sources engines cited in those answers, and ask honestly: could your brand plausibly be mentioned there? That's your off-site to-do list.

Frequently asked questions