The AGORI Guides

AEO, GEO & AI visibility, explained for sellers.

Everything an online seller needs to understand the shift from search results to AI answers — in plain English, with no dashboard required. Written and maintained by the team at AGORI Labs.

What is AEO?

What is Answer Engine Optimization (AEO)?

AEO is the practice of making your products and brand citable inside AI-generated answers. When a buyer asks ChatGPT, Perplexity, or Gemini what to purchase, the engine responds with a short, synthesized recommendation — a shortlist, not a results page. AEO is the discipline of earning a place on that shortlist.

Traditional discovery had a forgiving structure: even ranking eighth on Google meant some traffic. AI answers have no eighth position. The engine names a handful of options with reasoning, and buyers act on them. This makes AI visibility a threshold game — you're in the answer or you're invisible — and it makes the machinery that decides inclusion worth understanding precisely.

AEO vs. GEO vs. SEO — what's the difference?

SEO optimizes for ranked links. AEO and GEO optimize for inclusion in generated answers. GEO is essentially the B2B-marketing name for the same goal AEO describes; you'll also see 'LLM SEO' and 'AI SEO.' The techniques overlap; the scoreboard is different.

SEO's currency is position — where your link ranks. AEO's currency is citation — whether the engine's answer names you, quotes your facts, and links your page as a source. Good SEO still helps AEO, but it's no longer sufficient: a page can rank well on Google and still be unparseable to an answer engine that needs explicit attributes, clean structure, and quotable facts. The practical rule: SEO makes you findable by people scrolling; AEO makes you quotable by machines answering.

How do AI engines choose which products to recommend?

Answer engines extract facts, then compose. They favor sources they can parse with confidence: machine-readable pages, complete structured data, explicit attributes, answer-format content, and corroborating third-party signals. Confidence in extraction is the hidden ranking factor of the answer era.

1. Machine readability

Fast, clean pages the crawler can fully parse. Scripts and clutter reduce extraction confidence — and low confidence means exclusion, not a lower rank.

2. Structural completeness

schema.org Product and Offer markup with price, availability, materials, and dimensions stated as data, not prose buried in a caption.

3. Answer-format content

Concise, factual blocks that map to real buyer questions: what it is, who it's for, how it compares, what it costs.

4. Earned corroboration

Consistent third-party mentions that let the engine trust its extraction. A claim confirmed in two places beats a superlative made in one.

Why do Etsy and Shopify listings underperform in AI search?

Marketplace pages are built to convert humans, which makes them hard for machines to read. Reviews widgets, upsell modules, scripts, and lazy-loaded galleries bury the facts AI needs; attributes live in images and free text; schema ships incomplete. Engines extract fragments and cite the seller who was easier to parse.

This isn't the marketplace's failure — it's a mismatch of eras. The fix isn't to make your human page worse; it's to give the machine its own perfect version. That's the architecture AGORI Beacon runs: your original page keeps converting humans, while a hosted, machine-optimized twin does the work of being read, cited, and recommended. See how the hosted layer works →

The complete AEO checklist for online sellers

Fourteen checks that take a catalog from invisible to citable. Items 1–8 you can do yourself; items 9–14 are the infrastructure layer Beacon automates.

Foundation (DIY): 1. Verify AI crawlers aren't blocked in robots.txt. 2. Submit your sitemap to Bing Webmaster Tools, not just Google. 3. Move every product fact out of images into text. 4. Rewrite titles descriptively: "organic cotton sleep mask," not "The Luna." 5. Add complete Product and Offer schema with live price. 6. Add Organization schema and a crawlable about page. 7. Write FAQ content in real question-and-answer format with FAQPage markup. 8. Publish llms.txt at your site root.

Infrastructure (what Beacon hosts): 9. A dedicated machine-readable page per product. 10. Buyer-intent coverage across discovery, comparison, and purchase questions. 11. Descriptive alt text and image metadata for visual-first surfaces. 12. Continuous price/stock sync. 13. First-party attribution capturing every AI referral. 14. Agent-operable catalog data (the AUX Protocol).

Work the DIY list this week; it's real progress and costs nothing. Then let Beacon stand up the infrastructure half free and compare how engines read you.

Agentic commerce: the next surface

Agentic commerce is shopping performed by AI agents on a buyer's behalf — researching, comparing, and increasingly transacting autonomously. Visibility gets you considered; operability lets the agent complete the job.

This is the horizon AGORI's AUX Protocol is built for: every Beacon-hosted storefront is agent-operable by default, so when agentic buying arrives in your category, you're already stocked on its shelf.

Glossary

AEO & AI visibility terms

AEO (Answer Engine Optimization)

Making content and products citable inside AI-generated answers on engines like ChatGPT, Perplexity, and Gemini.

GEO (Generative Engine Optimization)

Near-synonym of AEO, common in B2B marketing; optimizing for inclusion in generative AI responses.

AI visibility

How often and how favorably AI engines mention or recommend your brand or products across relevant prompts.

Citation

An AI answer naming or sourcing your brand, product, or page — the fundamental unit of AEO success.

Answer engine

An AI system that responds with synthesized answers rather than ranked links: ChatGPT, Perplexity, Gemini, Copilot.

Prompt corpus

A curated set of buyer questions used to measure and target AI visibility across discovery, comparison, and purchase intent.

Observed vs. Modeled

AGORI's labeling standard: Observed = events actually recorded; Modeled = projections. Never blended.

Beacon Score

AGORI's 0-100 measure of catalog discoverability, readability, and citability across ten weighted dimensions.

AI-readable storefront

A hosted, machine-optimized version of a product catalog: complete markup, answer-format content, no human-UI clutter.

Agentic commerce

Shopping performed by AI agents on a buyer's behalf; requires operable — not merely visible — catalogs.

AUX Protocol

AGORI's Adaptive UX protocol exposing prices, variants, stock, and policies for AI shopping agents to act on.

llms.txt

A root-level plain-text file giving AI crawlers a curated guide to a site's key content; published automatically on Beacon storefronts.

Reading about AEO is step zero.
Your score is step one.

Paste your store URL and see all ten Beacon Score dimensions for your real catalog — free.