Claim: GEO (Generative Engine Optimization) is not “SEO with a new name.”

SEO: optimizes for ranking and clicks.
GEO: optimizes for whether AI models recommend your brand on user questions — recall from training data, not page position.

FAQ schema and conversational headings alone miss the mechanism. Conflate the two and you underinvest in third-party association that models actually use.

Is anyone actually doing GEO, or is it just SEO rebranded?

Short answer: Real GEO work targets recommendation and recall in model outputs, not SERP position. Many vendors relabel classic SEO tactics as “GEO” without changing the mechanism — that is rebranding. Actual GEO programs measure whether assistants name your brand on buyer prompts, earn third-party problem–solution associations, and track LLM citations / recommendation strength — not only crawl and keyword rank.

What SEO Actually Optimizes For

Bottom line: SEO optimizes for ranking — the search engine orders pages, and you win traffic from the ranked list. The mechanism is: Google crawls your page, evaluates hundreds of signals (authority, relevance, structure, speed, etc.), and decides where to rank you relative to other pages.

The user then sees results, clicks, visits, and converts. The chain is: query → ranking → click → visit → conversion.

Every SEO tactic — keyword research, link building, technical optimization, content structure — exists to improve your position in that ranking system.

What GEO Actually Optimizes For

Bottom line: GEO optimizes for recommendation — being the brand an AI model names when a user asks a relevant question, often without any click.

The mechanism is fundamentally different. AI models don't crawl your page during the query. They recall patterns from training data — articles, forums, comparisons, reviews, transcripts — and have built an internal model of which brands match which problems, use cases, and buyer types.

When a user asks "what should I use to do X," the model doesn't run a search; it recalls. The chain is: query → recall → recommendation → trust → intent.

The user may never visit your website; they might act on the recommendation directly. Your website's ranking is irrelevant to this outcome. This is not a refinement of SEO — it's a different system, driven by a different mechanism, producing a different type of outcome.

Where People Get Confused

Bottom line: SEO and GEO share some inputs — good content, structured data, crawlable sites, external mentions — so people assume strong SEO implies strong GEO. That is only partially true for established brands; for most, especially newer ones, it is not.

Good content helps with both SEO and GEO. Structured data helps with both. Having a clear, crawlable website helps with both. Being mentioned in authoritative external sources helps with both.

Here's the specific thing SEO doesn't give you that GEO requires:

Third-party problem-solution association.

For AI models to recommend you, you need to be associated with a specific problem in sources that aren't yours. Your own website saying "we solve X problem" carries very little weight. An independent comparison article saying "for teams struggling with X problem, [your brand] is the most purpose-built solution" carries enormous weight.

SEO never required this distinction because your own content could rank on its own merit. GEO does require it because AI models discount self-description heavily.

The Practical Implications

Bottom line: If you build GEO from scratch, tactics differ from a classic SEO calendar: prioritize independent comparison coverage, aggregator listings, and conversational third-party context over keyword volume alone.

GEO priority list (high level):

Comparisons: "X vs Y" / "best tools for Z" from independent creators, analysts, or media — often higher leverage than more owned content.
Aggregators: Correct category descriptions on G2, Product Hunt, Capterra, newsletters — association density models rely on.
Conversational surfaces: Podcast transcripts, YouTube descriptions, forums (e.g. Reddit) — overweighted in many training mixes.
Specific takes: Opinionated category writing ("the mistake most B2B SaaS brands make…") beats generic "what is GEO" filler for quotability.

Not the classic SEO calendar — a different distribution strategy.

What Actually Stays the Same

Bottom line: Precise language, consistent messaging across surfaces, and genuine quality that earns independent talk still matter for SEO and GEO — but explaining it only on your own properties is no longer sufficient for GEO.

Still true for both:

Clear who / what in precise language (not vague aspiration).
Consistent messaging across public surfaces.
Quality that earns independent talk — not only owned campaigns.

The “do good work and explain it clearly” foundation does not change. What changes for GEO: clarity on owned properties alone is not enough — you still need third-party problem–solution association.

The Honest Summary

Bottom line: SEO is a ranking game; GEO is a recall game.

Ranking can be engineered with technical precision — you can test, measure, and iterate against a clear signal (your position in search results).

Recall is harder to engineer because it's built from the accumulated weight of how your brand is discussed across many sources over time. You can influence it, but you can't directly control it. You can't A/B test your way to being recommended by Claude.

What you can do is understand the mechanism — and start building accordingly. The brands that are well-represented in AI recommendations today started doing this two years ago, even if they didn't call it GEO. The brands that are doing it today will be the ones with strong AI presence in 2028.

The window is still open. But it's not going to stay open.

What About AEO (Answer Engine Optimization)?

Bottom line: AEO = GEO with the emphasis on answer engines (ChatGPT, Perplexity, Gemini) rather than text generation in general. The mechanism is the same — recall and recommendation from training data — so the fix is the same.

SEO → ranked list of pages.
GEO → AI model names and recommends your brand.
AEO → AI answer engine (ChatGPT, Perplexity) specifically names and recommends your brand.

If you are doing GEO correctly, you are doing AEO. The distinction matters only for vocabulary: "best practices for answer engine optimization" and "aeo vs seo" are rising search queries, so knowing the term helps. The audit output is identical.

SaaS go-to-market: See how recommendation-based visibility applies to your segment with our SaaS AI brand visibility audit — scored across ChatGPT and Gemini.

Curious where your brand currently stands in AI model recommendations? Run a free audit at askllm.io — we test ChatGPT 5 and Gemini against real buyer queries in your category.