# GEO vs SEO vs AEO: which should an ecommerce brand optimise for?

GEO, SEO and AEO overlap more than the acronyms suggest. A definitions table, a decision framework and a budget split for brands deciding where to invest.

By Rohin Aggarwal · 2026-06-28

Every budget meeting now has the acronym problem. Someone proposes a GEO line item, someone else says the SEO agency already covers it, and a third person asks whether AEO is the same thing spelt differently. Everyone is partially right, which is what makes the meeting long.

**Quick answer**

- **SEO** earns ranked links on a results page. **AEO** earns the quoted answer. **GEO** is the umbrella term for citation work across every AI engine; AEO is its tactical layer.
- Roughly two thirds of the underlying work is shared: crawlability, structured data, verified evidence, answer-shaped copy. Fund the shared layer first and every acronym benefits.
- Prioritise by demand source: organic-heavy brands defend SEO while adding citation work; comparison-heavy categories go GEO-first; new stores skip the SERP fight entirely.
- Our default split for an established store: **40% shared foundations, 35% classic SEO, 25% GEO/AEO-specific**, rebalanced quarterly against citation data.
- The most expensive mistake is running them as separate programmes with separate agencies. Same team, same pages, one roadmap.

The short answer: an ecommerce brand should not pick one. SEO, AEO and GEO describe overlapping work on the same pages, and the real decision is sequencing and budget weight, not allegiance to an acronym. The rest of this piece is the decision framework we use: what each term means, where they overlap, which to lead with given your situation, and how to split the spend.

## What do SEO, AEO and GEO actually mean?

Three acronyms, one buyer, three different moments of visibility. SEO gets you onto the results page. AEO gets you quoted when an engine answers a question directly. GEO covers citation earning across every generative surface, from ChatGPT to Google's AI Overviews, and is the term the research literature settled on.

| Acronym | Optimises for | Unit of success | Typical surface |
| --- | --- | --- | --- |
| SEO (search engine optimisation) | Ranking pages in an index | A ranked link, then a click | Google + Bing results pages |
| AEO (answer engine optimisation) | Being the source an answer quotes | A quoted answer with attribution | AI Overviews, featured snippets, chat answers |
| GEO (generative engine optimization) | Retrieval, trust + citation across AI engines | Citation rate across a prompt panel | ChatGPT, Perplexity, Gemini, Claude, Copilot |

_The working definitions. In practice AEO and GEO name the same discipline at different altitudes._

The GEO term has an academic pedigree (a 2023 Princeton-led paper coined it and measured a visibility lift of up to 40% from content-side changes). Its full definition, origin and mechanics are in [the generative engine optimization guide](/blog/what-is-generative-engine-optimization), which is the pillar this piece hangs off. If you take one framing from that guide: GEO is the strategy word, AEO is the playbook word.

- **+40%** — Max visibility lift from GEO content changes (Princeton/Georgia Tech/IIT Delhi/Allen Institute study)
- **14x** — Weight AI engines give verified vs unverified reviews (See reviews-as-evidence study)
- **88%** — of consumers consult reviews before purchase (BrightLocal Consumer Review Survey)

_What the research says moves citation rate._

## How much do SEO, AEO and GEO overlap?

More than the vendor pitches admit. All three depend on crawlable, server-rendered pages. All three reward structured data, because a schema block is legible to Googlebot and to a language model alike. All three punish thin content and fabricated evidence. A brand that ships honest Product and Review JSON-LD, real verified reviews, and plainly written answers has done most of the work for all three acronyms in one pass.

The divergences sit at the edges. Backlink acquisition still matters for classic rankings and matters far less for citations: in our [1,200-prompt study](/blog/which-ai-engine-cites-you-1200-prompt-study), domain authority was nearly uncorrelated with Perplexity citations while verified-review depth predicted citations on every engine. Prompt-panel tracking, llms.txt and product feeds are GEO-only work with no SEO equivalent. And Google AI Overviews are the literal overlap point: ranking gets you into the candidate set, but only a quotable passage gets you into the box, a distinction [the AI Overviews guide](/blog/how-to-appear-in-google-ai-overviews-sge) unpacks properly.

One number worth holding onto from that study: Perplexity cited a specific brand in 52% of shopping prompts while Copilot managed 18%. The channels are real, they are different sizes, and they reward different inputs. That asymmetry is why "just do SEO and the rest follows" stopped being true.

## Which should you prioritise? A decision framework

Sequencing depends on where your next customer actually comes from, not on which acronym is loudest on LinkedIn this quarter. Four situations cover most ecommerce brands we talk to.

**Which to lead with, by brand situation**
Q: Where does your next customer come from today?
- Organic search drives 40%+ of revenue: **Defend SEO, add citation work now** — Your organic base is exactly what AI Overviews cannibalise first. Keep the SEO programme running and layer schema depth plus verified-review evidence onto the pages that already rank, so the answer box quotes you instead of a competitor it found in your candidate set.
  - If Overviews already show on your money terms: Treat GEO as urgent. Optimise the exact ranking pages for quotability this quarter.
  - If they do not yet: A quarterly citation audit is enough. Keep compounding the SEO asset.
- Comparison-heavy category (electronics, appliances, supplements): **GEO first** — These are the categories where engines already name specific brands most often: home appliances and electronics hit 67% brand-citation on Perplexity in our panel. The citation slots for your category are being allocated now, and they are stickier than rankings.
- New store: no rankings, no domain authority: **Skip the queue** — Ten years of link building is not a plan. Answer-shaped PDPs, reviews collected from the first order, and full structured data give a new store a shot at citations long before it can rank. GEO is the cheaper open field.
- Paid social drives nearly everything: **Minimum viable everything** — Ship the shared layer and revisit quarterly. Buyers you acquire on TikTok still ask ChatGPT to sanity-check the product before checkout, and an engine with nothing to quote fills the gap with whatever it finds.

## How should you split the budget?

No public benchmark exists for this split yet, so treat the numbers below as our opinionated default rather than an industry figure. They come from watching which line items actually moved citation rate and organic revenue across the brands we audit, and they assume one team runs all of it.

| Brand situation | Shared foundations | Classic SEO | GEO/AEO-specific |
| --- | --- | --- | --- |
| Established, organic-heavy | 40% | 35% | 25% |
| Challenger in a comparison category | 40% | 20% | 40% |
| New store (first year) | 50% | 10% | 40% |

_Our default splits. Shared foundations: schema, reviews, UGC rights, server-rendering, site speed. GEO/AEO-specific: llms.txt, feeds, prompt-panel tracking, PDP answer restructuring._

The shared bucket is deliberately the biggest in every row, because it is the only spend that pays out three times. The GEO bucket buys the work with no SEO equivalent: the llms.txt, the product feed agents can read, the weekly prompt panel, and the PDP rewrites that put the answer in the first hundred words. The four levers behind that bucket, in priority order, are laid out in the [AEO 2026 playbook](/blog/answer-engine-optimisation-2026-playbook).

Rebalance quarterly, and rebalance on data. If the citation log shows you winning prompts in one engine and invisible in another, the next quarter's GEO hours go to the gap. If organic revenue starts eroding under answer boxes, shift weight from rank-chasing to quotability on the pages that still rank.

## What work counts for all three at once?

The double-counting list is the practical heart of this piece. Fund these before anything acronym-specific, because every one of them improves rankings, answer inclusion and citations simultaneously.

- **Product, Offer, Review and FAQPage JSON-LD** on every money page. The single highest-leverage shared input.
- **Verified reviews, server-rendered.** The first five reviews visible in the HTML, with authors and dates, not loaded behind JavaScript.
- **Rights-cleared UGC tagged to products.** Third-party evidence that engines and shoppers both trust.
- **Answer-shaped copy.** A plain first paragraph that says what the product is and who it is for, phrased the way buyers ask.
- **Fast, crawlable pages.** GPTBot and Googlebot fetch the same HTML; a page neither can read wins nothing anywhere.

A useful discipline: audit one PDP against [the 42-signal scorecard](/blog/the-42-signal-aeo-scorecard) before arguing about budget at all. The median page we see scores 18 of 42. When the shared layer is that unfinished, the SEO-versus-GEO debate is premature by definition.

## Where do teams burn the budget?

- **Hiring a separate GEO agency before the schema is done.** You pay strategy rates for work your existing team should ship in two sprints.
- **Optimising for one engine.** The engines disagree with each other; a ChatGPT-only programme is invisible to half the audience.
- **Treating GEO as a content stream.** Ten AI-flavoured blog posts a week move nothing. Citation rate responds to structural work on pages you already have.
- **Measuring nothing.** Without a prompt panel, the quarterly rebalance runs on vibes and the loudest voice in the meeting wins.
- **Faking the evidence.** Synthetic reviews and inflated AggregateRating counts earn demotion everywhere at once. The one mistake all three acronyms punish identically.

**In one line:** Do not pick an acronym. Fund the shared layer first, choose your growth lane by where demand actually comes from, and let a weekly citation log (not the meeting) decide the quarterly rebalance.

### References + further reading
- [GEO: Generative Engine Optimization (Aggarwal et al., 2023)](https://arxiv.org/abs/2311.09735) — The paper that coined GEO and quantified content-side visibility lift.
- [Google: AI features and your website](https://developers.google.com/search/docs/appearance/ai-features) — Google's own guidance on visibility in AI Overviews.
- [llms.txt: proposal + format spec](https://llmstxt.org/) — The GEO-only artefact with no SEO equivalent.
- [Idukki: What is Generative Engine Optimization?](/blog/what-is-generative-engine-optimization) — The pillar guide: definition, origin, inputs, measurement.
- [Idukki: Answer engine optimisation, the 2026 playbook](/blog/answer-engine-optimisation-2026-playbook) — The tactical four-lever programme referenced throughout.
- [Idukki: Which AI engine cites you (1,200-prompt study)](/blog/which-ai-engine-cites-you-1200-prompt-study) — Source of the per-engine citation rates used here.

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Canonical: https://idukki.io/blog/geo-vs-seo-vs-aeo-which-to-optimise-for
Tags: geo, seo, aeo, ai-search, strategy, budget-split