What is GEO, and why are your buyers asking ChatGPT about you?

What happens when a buyer asks ChatGPT about you?

Try it now, before reading further. Ask ChatGPT or Gemini, in English and then in Arabic: who are the reliable providers of what you sell, in your city? Then ask what it knows about your company by name.

Three outcomes are possible. You are recommended, a competitor is recommended instead, or the assistant has nothing useful to say about you. Most Saudi B2B companies land in the third bucket, and increasingly that is where deals are quietly lost — because this is no longer a niche behaviour. OpenAI's own stated figure, from October 2025, is 800 million people using ChatGPT every week.

Generative engine optimization, or GEO, is the work of making sure those answers describe you accurately and cite you when you deserve it. Here is how it actually works, minus the mysticism this field attracts.

How AI assistants decide what to say

Two mechanisms, and the difference matters for what you should do.

Training knowledge. What the model absorbed about your company before its cutoff date. If your company is young, small, or thinly documented, the model may know almost nothing — or repeat something outdated. You influence this slowly, by existing verifiably in the places models learn from.

Live retrieval. For current questions, assistants search the web and read pages before answering, citing what they used. This is where you have real, near-term leverage, because it behaves much more like search: crawlable pages, direct answers, evidence worth quoting.

The overlap with SEO is not a coincidence. An assistant deciding what to cite is asking roughly what Google asks: is this page clear, is it credible, does it answer the question? Which is why GEO is not a replacement for search work — it is what search work earns when the content is good enough to quote.

What makes a page quotable

Assistants quote pages that make their job easy. In practice:

• A direct answer near the top. A page that takes four hundred words to get to the point gets skimmed past. State the answer, then justify it.
• Claims with numbers, dates and names. "Delivered a bilingual site in eleven weeks for a Dammam logistics company" is quotable. "Fast delivery and happy clients" is not.
• Questions phrased the way buyers ask them. Assistants match questions to pages that visibly answer that question. Headings that ask and answer real buyer questions outperform clever ones.
• Structured data. Schema markup telling machines what your organization is, what you offer and where you operate. Invisible to readers, load-bearing for machines.
• Consistency across the web. If your site, your LinkedIn, your Google profile and a directory all describe you differently, the model hedges or stays silent. Same name, same claims, everywhere.

The Arabic asymmetry, again — and stronger

We have written about the Arabic content gap in search. In AI answers the effect is amplified.

Ask an assistant a commercial question in Arabic and it draws on a far thinner pool of Arabic sources — Arabic is roughly 0.6 percent of the world's web content — so a single genuinely good Arabic page can dominate answers in a way that is nearly impossible in English. Ask the same question in English about the Saudi market and the assistant often falls back on global sources with no local knowledge at all, which is why its recommendations can be strangely disconnected from who actually operates here.

Both failure modes are opportunities. A Saudi company that publishes substantive Arabic answers, and English answers with real local evidence, is competing against almost nobody for the citation.

What GEO is not

The field is young and attracts nonsense, so it is worth naming some.

• It is not a trick. There is no tag that makes assistants recommend you. Anyone selling one is selling the 2026 version of the meta-keywords tag.
• It is not precisely measurable yet. You can test what assistants say about you and your category — in both languages, monthly, recorded — and you can watch referral traffic from assistant browsers grow. What you cannot get is anything like the impression data search gives you. Anyone quoting exact "AI visibility scores" is measuring their own dashboard, not the market.
• It is not separate from your website. The site is the source of truth assistants read. GEO on top of a thin, slow, evidence-free site fixes nothing.

Where to start, in order

• Run the audit above: ten questions a real buyer would ask, in Arabic and English, across ChatGPT, Gemini and Perplexity. Record the answers and the citations. This is your baseline.
• Fix what they got wrong that you control: outdated descriptions, inconsistent claims, missing basics on your own site and profiles.
• Publish direct answers to the questions where you were absent — starting in Arabic, where a good page travels furthest.
• Add organization and service schema so machines can read what you are without inferring it.
• Re-run the same audit quarterly. The models update; your evidence should compound.

Common questions

Is GEO going to replace SEO?

No — they share a foundation. Assistants retrieve from the same web Google crawls, and largely reward the same qualities. What changes is the bar: pages now need to be worth quoting, not just worth ranking. Do the work once, earn both.

How do we know if it is working?

Three honest signals: the monthly answer audit trends in your favour; assistant referral visits appear in your analytics; and prospects start saying "I asked ChatGPT about you." That last one is already common in Saudi B2B, and it is the point.

Can we block AI crawlers instead?

You can, and for a B2B company it is almost always the wrong call. Blocking means the assistant answers the buyer's question using everyone except you. Publishers with content businesses have a real dilemma; a company that wants to be found does not.

Does this matter if our buyers are traditional?

The committee is rarely uniform. The owner may not use AI assistants; the engineer preparing the shortlist memo very likely does. You are optimizing for whoever does the research, not whoever signs.

What should we do about being misdescribed by an AI?

First fix the sources: assistants usually repeat something that exists somewhere — an old directory entry, a stale page of yours. Correct the source, publish the accurate version prominently, and the answers follow over weeks to months. Complaining to the model vendor is rarely the fast path.

Sources

OpenAI weekly user figure as stated by Sam Altman at DevDay, 6 October 2025, as reported by TechCrunch. W3Techs, content-language survey, August 2026. Observations on retrieval and citation behaviour based on our own recorded monthly audits across ChatGPT, Gemini and Perplexity in Arabic and English.