GEO vs SEO: what changes and what carries over

GEO and SEO aim at the same buyer

The same person is asking. They want to know which product to buy, first in a search box and now in a chat window. GEO (generative engine optimization) is the work of showing up correctly in the answer they get back; SEO is the work of ranking the page they might click.

That shared buyer is why the two disciplines share most of their foundation. Clear pages that answer real questions, fast to load, easy to read, published where your audience already looks: none of that became obsolete. What changed is the surface the answer appears on, and how few slots there are in it.

Where GEO and SEO actually differ

The difference is the surface and the unit of success: SEO competes for positions in a list of links, GEO competes for sentences inside one answer.

The variance row is the one teams underestimate. A ranking moves slowly and visibly. An answer is assembled at question time, so it flips between runs, which means GEO needs repeated measurement to separate a real change from a noisy day.

What SEO work carries over unchanged

Most of your existing SEO programme is already GEO work. The retrieval systems behind these answers read the same web your SEO fixes were aimed at.

• Technical access. If a crawler cannot fetch and render a page, no engine will cite it. The same crawlability work applies, and several tools now check which AI bots may read your site.
• Pages that answer a question completely. Answers get quoted when the passage stands on its own. Answer-first sections (the direct answer in the first 40 to 60 words, detail after) work for both scanners and readers.
• Clear structure. Headings that state the question, tables for comparisons, lists for steps. Engines extract passages; structure tells them where the extractable claim is.
• Entities and naming consistency. Your product name, category and pricing described the same way across your site, directories and profiles, so machines can tell what is true about you.
• Third-party proof. Reviews, comparisons, forum threads and documentation on other domains. SEO teams have always known these matter; in AI answers they often decide the outcome.

What GEO adds that SEO never had

Four things are genuinely new: you optimise for prompts instead of keywords, the result is unstable, the sources are chosen by the engine at answer time, and the work is invisible without collecting answers.

1. Prompt selection replaces keyword research. You decide which questions to run daily. A set of 15 to 25 buyer questions beats 200 keyword variations, because each prompt is asked repeatedly and costs an answer each time.
2. You plan for variance. One answer is an anecdote. Daily runs turn the same prompt into a sample you can average, which is why sample sizes and intervals matter more here than in rank tracking.
3. You influence sources you do not own. Engines cite review sites, Reddit threads and documentation written by other people. Updating your own page is necessary and often not sufficient.
4. Measurement starts from zero. No existing tool reports “position 3 for this prompt in ChatGPT”. You collect the answers yourself, or you buy a tool that does.

For the collection side of that last point (official APIs versus browser scraping) see API vs scraped answers.

Do you need a separate GEO team?

No. Give GEO to the people who already own content and SEO, and add one habit: read what the answers say every week and fix the page causing each problem.

The new part is a feedback loop, not a department. Someone runs the prompt set, scans which answers skip the brand, checks what the answers get wrong, and picks one page to update or one third-party profile to correct. In advisible that loop has a natural home: the overview shows where visibility moved, competitor gaps show which answers name a rival instead of you, and every original answer is in the archive so you can read the exact text you are trying to change.

When the work does justify a specialist hire is a budget question, not a methodology one. The trigger we would look for: more than about 40 tracked prompts across several markets, plus a reporting cadence clients depend on. Below that, one marketing generalist with a weekly slot will outperform a part-time GEO theorist with no data.