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GEO vs AEO: differences, evidence and measurement

GEO and AEO remain unstable terms. This decision map separates objectives, surfaces, levers, evidence and limits, then provides one protocol for Google, Perplexity and ChatGPT.

By
Naïm Ghezali
Publication date
Reading time
6 min read
Abstract editorial composition about data, AI and automation for the article “GEO vs AEO: differences, evidence and measurement”.

Short answer

SEO aims to make a page discoverable, indexable and visible in search engines. AEO is an industry term for making an answer clear and usable in an answer interface. GEO more broadly refers to optimizing the visibility of a source or entity in generated answers. These are not universal standard definitions. The practices overlap, but crawlers, interfaces and measurement differ across Google, Perplexity and ChatGPT. Start with SEO and reputation, then test each engine using dated prompts without promising a citation or recommendation.

GEO and AEO are not two standards to install

The market loves creating a new discipline whenever an interface changes. GEO, AEO, LLMO: labels multiply faster than evidence.

A company does not need to choose a label. It needs to choose a visibility surface, an audience, a question, an asset to improve and a way to measure it.

Academic fact. The research paper “GEO: Generative Engine Optimization”, submitted in November 2023 and revised June 28, 2024, proposes a black-box optimization framework and visibility metrics for generative engines. Its authors emphasize that observed effects vary across domains. This is research in a defined environment, not a platform standard or a commercial guarantee.

Seven Gold recommendation. Use GEO and AEO as working categories. For every recommendation, name the relevant product, the official source, the level of evidence and the measure.

Hypothesis to test. A clearer answer and a better-documented brand may improve some forms of generative visibility. The outcome may vary by question, language, account, mode and date.

Working definitions: SEO, AEO and GEO

TermWorking objectiveSurfaceMinimum evidence
SEOMake a page discoverable, indexable, relevant and useful.Traditional search results and features built on the index.Impressions, clicks, pages, queries and conversions.
AEOFormulate a direct, structured and verifiable answer to a question.Snippets, answer interfaces, assistants or conversational search.Observed answer, displayed source and test conditions.
GEOImprove the visibility of a source, expertise or entity in a generated answer.Named generative engines and assistants.A dated panel of mentions, citations, recommendations and downstream effects.

These definitions organize the work. No authority guarantees that every researcher, agency or platform will use them in the same way. AEO may be used broadly or restricted to direct answers. GEO may cover citations, mentions, recommendations or any form of visibility. The protocol should therefore define its own vocabulary.

What remains from traditional SEO

The three approaches share a foundation:

  • public pages accessible to authorized agents;
  • an understandable architecture and internal links;
  • a clear answer to genuine intent;
  • original, dated and maintained content;
  • an author, sources, method and limitations;
  • a coherent brand entity across the site and third-party sources;
  • measurement connected to a commercial objective.

In its official guide to optimizing for generative AI search, updated July 13, 2026, Google states that its SEO best practices remain relevant to AI Overviews and AI Mode. From Google Search’s perspective, optimizing these surfaces means optimizing the search experience.

That position concerns Google. It describes neither Perplexity’s crawling nor eligibility for ChatGPT Search. Copying guidance from one product to another without documentation is precisely the mistake a GEO strategy should avoid.

Three products, three sets of documentation that should not be mixed

Google relies on its index and ranking systems. Its 2026 guide says there is no special schema.org markup required for its AI features, no need to chunk content for AI and no impact from llms.txt on visibility or rankings in Google Search.

Google fact, not a universal rule. Another platform may document a different file or agent. The right question is always: which official documentation supports this action for the product being targeted?

The official Perplexity documentation, dated January 29, 2026 and checked August 15, 2026, distinguishes PerplexityBot, used to surface and link websites in search, from Perplexity-User, triggered by some user actions. It also publishes endpoints for its IP ranges.

Allowing a crawler meets an access condition. It does not guarantee that a page will be selected as a source. Measure mentions, citations and visits on a panel specific to Perplexity.

The official OpenAI crawler documentation, checked August 15, 2026, distinguishes OAI-SearchBot, used to surface websites in ChatGPT search features, from GPTBot, associated with model training. Their robots rules are independent. ChatGPT-User corresponds to certain user-requested actions and is not the agent that determines Search eligibility.

Again, allowing OAI-SearchBot does not promise a citation or recommendation. It removes an access obstacle for the relevant surface.

Structured data is not a GEO button

Google’s structured-data documentation, updated December 18, 2025, explains that structured data helps Google understand page content and may make it eligible for certain rich results. Marked-up properties should match what is visible.

Google’s AI guide adds that no special schema is needed for its generative features. Use:

  • Article for a genuine article with an author, dates, image and main page;
  • FAQPage only when the questions and answers are visible;
  • Organization or a suitable business type with real information;
  • other types only when the page genuinely represents that entity.

Never add a fictional rating, offer, person or date. Valid markup guarantees neither a rich result, an AI citation nor a ranking. And Google guidance does not prove that Perplexity or ChatGPT uses the same schema in the same way.

The same test across Google, Perplexity and ChatGPT

An ideal brief includes an identical test across products. But we publish no fabricated “result” here: no controlled, archived run was supplied for this batch. The protocol below is ready to execute.

  1. Set one question, language, country, intent and success criteria.
  2. Record the date, time, account, mode and every visible parameter.
  3. Use the exact prompt without rewriting it after seeing the answer.
  4. Archive the full answer, sources, links and displayed order.
  5. Code mention, citation, recommendation and accuracy separately.
  6. Repeat on the set schedule without deleting negative outcomes.
  7. Connect visits and opportunities where measurement permits.
FieldGooglePerplexityChatGPT
Date, language, account, modeTo recordTo recordTo record
Exact promptTo archiveTo archiveTo archive
Displayed source or URLTo observeTo observeTo observe
Mention / citation / recommendationTo codeTo codeTo code
Accuracy and caveatsTo reviewTo reviewTo review

The table is intentionally empty. Filling it with real observations is more valuable than listing alleged universal factors.

Which priority should you choose?

SituationPriorityWhy
Pages are not indexed or properly renderedTechnical SEODiscovery remains the bottleneck.
Impressions but no clicks for a useful intentSEO + direct answerThe message and fit need correction.
Recurring questions are poorly addressedAEO as an editorial disciplineA self-contained, precise and sourced answer helps the user.
The brand is absent from important AI panelsPlatform-specific GEO testAccess, content and reputation must be separated.
Citations create no visits or opportunitiesJourney and measurementVisibility is not the business bottleneck.

Before creating new content, ask whether it captures an intent, strengthens the entity, produces evidence, assists a sale or earns a legitimate citation. If the answer remains vague, improve pages that already have demand first.

A shared scorecard, with columns for each platform

  • Technical: access, statuses, robots, logs and rendering.
  • Search: impressions, clicks, queries and pages where available.
  • Answer: accuracy, mention, citation, recommendation and sources.
  • Reputation: credible third-party domains that connect the brand to the topic.
  • Audience: referring visits, branded searches and journeys.
  • Business: qualified leads, opportunities, revenue and contribution with attribution limits.
  • Execution: updated content, owner, evidence of completion and review date.

Citation rate should not become an end in itself. A low-value query may cite the brand frequently and change nothing in the pipeline. A rarely cited page may help decision-makers who are close to buying. The decision must combine visibility, intent, economics and capacity.

Prioritize foundations before trends

Do you keep hearing about GEO and AEO without knowing what to prioritize? Seven Gold can audit SEO fundamentals, citable content and a measurable panel of AI answers. Request an SEO and AI visibility audit.

What this changes in a growth system

An isolated lever rarely produces lasting results. Value comes from consistency between strategy, acquisition, conversion and measurement.

Frequently asked questions

Do GEO and AEO replace SEO?
No. Pages still need to be accessible, understandable, useful, connected and supported by a credible entity. Google also says its SEO best practices remain relevant to its generative search features. Other products have their own agents and rules; no label replaces platform-specific analysis.
Do you need special markup for GEO?
Google says no special schema.org markup is required for its generative AI features. Structured data remains useful when it precisely describes visible content and supports documented features. It guarantees neither a citation, recommendation nor rich result.
How do you measure a GEO or AEO strategy?
Build a stable prompt panel by intent, language and market, then run it separately on each product while recording date, mode, account, answer, sources, mention, citation and recommendation. Add crawl, referral traffic, leads and revenue where measurable. Results describe the panel, not a universal algorithm.

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