Short answer: SEO competes for a position in a list of links; GEO competes for a mention inside a written answer. GEO does not replace SEO. Most of the technical work carries over unchanged, because an engine has to fetch and read a page before it can use it. What does not carry over is measurement: there is no position in an answer, Search Console does not report whether you were named, and answers vary between runs, so GEO needs its own question set, its own metrics and its own cadence.

This guide is the programme-level comparison: which assumptions from an SEO programme still hold, which do not, and how to run both without doing the work twice. For the narrower page-level comparison, see AEO vs SEO; for what the four competing labels mean, see AI SEO vs GEO vs AEO vs LLMO.

What carries over unchanged from SEO to GEO

If you have a sound SEO programme, the foundation is already in place. Four pieces of it serve GEO without modification.

  • Crawlability. An engine cannot cite a page it cannot fetch. The difference is the list of agents: alongside Googlebot you now have OAI-SearchBot, PerplexityBot, Claude-SearchBot and others, plus the user-triggered agents that fetch a page because someone just asked about it. Our AI crawler access guide covers which to allow and how to test it.
  • Server-rendered content. Most AI crawlers do not execute JavaScript. Content that appears only after client-side rendering is an empty shell to them, so the rendering work you did for search matters more, not less.
  • Clean URLs and canonicals. Duplicate URLs split signals in both systems. On our own site a trailing-slash inconsistency left 46 pages indexed under two URLs each, splitting 1,980 impressions between the twins. Canonical and duplicate URLs covers the fix.
  • A clear, consistent entity. One name, one description and Organization markup with sameAs links to profiles that are really yours. Search engines use this to disambiguate; for an assistant it is part of deciding which brand a fact belongs to.

Third-party coverage also carries over, and arguably gains weight. A model needs the same fact from independent places before it will state it confidently, and a claim that exists only on your own domain is the weakest evidence you can offer.

GEO vs SEO: what is shared and what is notSEO onlyKeywords and volumePosition in a ranked listSearch Console dataGooglebot as the main agentShared foundationCrawler accessServer-rendered HTMLClean URLs and canonicalsOne consistent entityThird-party coverageGEO onlyFixed set of buyer questionsNamed, recommended, citedPer-engine resultsRun-to-run varianceSearch, training, user agents
Figure 1. The middle column is one project that serves both programmes; the outer columns need separate tooling and separate reports. Source: the comparison in this guide.

GEO vs SEO: where the two genuinely separate

SEOGEO
GoalA ranked position for a pageBeing named, recommended or cited in an answer
Unit that competesThe pageA passage inside the page, and the brand behind it
Input you trackKeywordsBuyer questions, usually full sentences
Primary metricsPosition, impressions, clicksMention rate, share of voice, citations counted from the answer text
StabilityBroadly stable between checksAnswers vary between runs even when nothing changed
Data sourceSearch Console and rank trackersOnly the answers you sample yourself
Crawler controlsGooglebot and the other search crawlersSeparate search, training and user-triggered agents per vendor

Position stops being the metric

There is no position ten in an answer. A brand is named, mentioned in passing, or absent, and separately it is cited or not. A brand can be recommended without any link to it, and your page can be cited as a source while the answer recommends a competitor, so those two results have to be recorded separately. The order in which brands happen to appear in one sampled answer is not stable enough to trend, which is why rank is the wrong metric for ChatGPT.

Variance changes how you read a change

A ranking moves for a reason, even if you cannot always see it. An answer can move for no reason at all: ask the same engine the same question twice and the brands it names, their order and the sources it cites can all differ. That changes the rules for reading a trend. A single run is an anecdote, a change counts only when it repeats in two consecutive runs, and each engine has to be reported on its own before any average. In our own benchmark one model named 3.5 providers per answer and another 2.1, so a blended figure describes neither. The methodology matters just as much: enabling web search once moved a site from 3% to 13% while the site did nothing, which is why runs on different methodology versions are never compared.

Search Console cannot see answers

Search data tells you about search. Over three months our own site received 45,793 impressions and 82 clicks in Search Console, and queries where we ranked in positions 4 to 10 produced 4,509 impressions and 2 clicks. Useful numbers for SEO decisions. None of them says whether any assistant named us when a buyer asked a question. That only comes from asking the questions yourself and storing the answers.

Crawler controls split by purpose

In SEO, blocking a crawler means leaving search. AI vendors separate jobs instead. Google documents Google-Extended as a usage control rather than a crawler: blocking it removes your content from grounded Gemini answers while Google Search inclusion and ranking are explicitly unaffected, according to Google's crawler documentation. OpenAI separates GPTBot, which gathers content that may be used for training, from OAI-SearchBot, which builds the index behind ChatGPT's search features. A single rule written with SEO habits often blocks both and removes the site from answers by accident.

Keywords are not the GEO input, but search data still helps

Running GEO off keyword volume is the most common way to measure the wrong thing. Buyers ask assistants in sentences that carry a situation, and a question with a budget or a constraint in it produces a different set of named brands than the bare category term.

Search data is still a good source of the sentences themselves. In our own Search Console export, 181 of 475 queries that produced impressions were full questions or phrases of seven words or more, carrying about 22% of impressions. Mine those for real buyer phrasing, remove anything that contains a brand name, and turn the rest into a fixed question set. Building a prompt set explains how.

One Search Console exportquery text · impressions · clicks · positionSEO READS THE NUMBERSImpressions, clicks, positionper queryUsed for: which pages to improveand which rankings movedAnswers: how you do in searchGEO READS ONLY THE WORDINGKeep full questions, 7+ wordsRemove any query with a brand nameFreeze the rest as a question setRun it on assistants, store answersThe export itself never shows whether an assistant named you; only the last step on the right does.
Figure 2. One Search Console export, two readings. SEO uses the numbers; GEO uses only the wording, and still has to run the questions to learn whether an assistant named you. Source: the operating model in this guide.

The reverse lesson holds too. Over the three months to mid-October 2026, 309 queries on our own site containing "best" or "top" produced 7,909 impressions and no clicks. Search demand for a phrase does not mean the phrase is worth chasing in either programme; it means people type it. Whether an assistant answers that question by naming anyone is something only an answer run can show.

How to run GEO and SEO without doing everything twice

  1. Keep one technical baseline. Access, rendering, canonicals, entity markup and dates are one project that serves both programmes. Add the AI agents to the crawl and rendering checks you already run rather than starting a parallel audit.
  2. Write pages once, for extraction. A heading that states the question and an answer in the first sentence under it serves a search snippet and an answer engine alike.
  3. Split measurement completely. Keywords and positions stay in your search tooling. Answers need a fixed question set, a competitor set, per-engine reporting and a methodology version on every run.
  4. Report them side by side, not merged. A blended "search plus AI" score hides which side moved. Show search metrics and answer metrics in separate sections with their own denominators.
  5. Set separate cadences. Search data arrives continuously. Answer runs cost quota, so a monthly cadence with alerts that need two consecutive runs is usually the honest default.
Running both programmes without doing the work twiceOne technical baselineAccess, rendering, canonicals,entity markup, datesWrite once for extractionQuestion as heading, answerin the first sentenceSearch measurementKeywords, positions, clicksContinuous dataAnswer measurementFixed questions, per engineMonthly runs, two-run alertsOne report, two sections, each with its own denominator
Figure 3. Shared work stays shared; only measurement forks, and the two halves meet again in a report that keeps them apart. Source: the operating model in this guide.

Common mistakes

  • Treating GEO as a rebrand of SEO. The foundation overlaps; the measurement does not. A programme that reports only search metrics cannot tell you whether you appear in answers.
  • Treating GEO as a replacement. If search crawlers cannot reach or render your pages, the AI agents usually cannot either.
  • Counting brand-named questions. Asking about your own brand by name guarantees a mention and measures nothing. In one of our own runs that inflated a score to 13% when the honest value was zero.
  • Counting everything the engine retrieved as a citation. Only sources marked in the answer text count; the retrieval pool overstated our own citation figures by two to four times.

Sources

  • Google Search Central, Google's common crawlers (Google-Extended).
  • OpenAI, crawler documentation (GPTBot, OAI-SearchBot, ChatGPT-User).
  • Perplexity, crawler guide (PerplexityBot, Perplexity-User).
  • Anthropic, how Anthropic crawls the web (ClaudeBot, Claude-SearchBot, Claude-User).
  • Our own Search Console exports for insightwonder.com (2026-09-09 and 2026-10-15), our Q3 2026 benchmark and our measurement incident records (first-party).