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GEO vs SEO vs AEO: a layered model

Neutral technical note. Industry naming still overlaps; this page uses a “layers, not replacements” working model.

One line each

  • SEO: Make pages discoverable and indexed, and earn meaningful clicks on results pages.
  • AEO: Make content easier to extract as direct-answer forms (snippets, FAQ, structured support).
  • GEO: Improve conditions for brands/content to be understood, compared, considered, and (accurately) recommended inside generative-engine synthesized answers.

Academically, “GEO” appears in an arXiv framework (src-004); practitioner wikis and Chinese practice pieces frame the goal as entering answers and being cited/mentioned (src-003, src-005). Commercial slogans are noisier—when shipping, define the variables you must explain.

Layer table

Layer Primary optimization object Common measures Failure looks like
SEO Crawl, index, relevance, authority, click paths Rank, impressions, clicks, conversion Demand exists but you miss visible results or CTR collapses
AEO Whether answer form is easy to extract and support Direct-answer presence, structured completeness Pages exist but assistants/snippets miss the point
GEO How generative systems understand, compare, consider, recommend Mention rate, shortlist rate, accurate recommendation, citations, same-conditions deltas Rank OK, but answers show absence/misstatement/no reason

In practice all three share foundations: clear entity definitions, verifiable facts, structured data, authoritative third-party corroboration. The difference is which KPI you explain to leadership. Merging “AI recommendation share” and “Google rank” into one number invites misjudgment.

Why SEO still matters

Generative systems still rely heavily on crawlable pages and authoritative sources. GEO Wiki and multiple practice pieces stress that GEO extends SEO rather than retiring it (src-003, src-006, src-007). Related answer: does-geo-still-need-seo.

Relation to “buy monitoring only”

Monitoring answers “are you in the answer now?” The layered model answers “which layer’s conditions are you improving?” If the goal is changing recommendation conditions, you still need fact alignment, approvable content/channel actions, and retest—see monitor-only-vs-optimization-loop and /en/facts/loop-find-govern-close-retest-operate/.

Naming collisions (put in your notes)

The same discussion may also use LLMO, AIO, AI SEO, and similar labels. Externally: fix “optimization object + success metric,” then apply a label. Internally: use stage gates Reach → Shortlist → Accurate & Recommended (/en/facts/stages-reach-shortlist-recommended/).

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