> ## Documentation Index > Fetch the complete documentation index at: https://docs.asva-ai.com/llms.txt > Use this file to discover all available pages before exploring further. # AEO and GEO: Optimize Your Store for AI Discovery > Make your products discoverable and citable by AI assistants through structured data, entity consistency, and protocol signals that drive AI recommendations. Attribution tools tell you which AI sessions arrived. AEO and GEO determine whether AI assistants recommend you in the first place. If your products are not structured in a way that AI systems can read, parse, and cite with confidence, you will not appear in the responses that drive AI Commerce traffic — regardless of how well your checkout is configured. This page covers the practical tactics you need to implement to become a brand that AI systems recommend, cite, and transact with. ## What AEO and GEO mean for commerce **Answer Engine Optimization (AEO)** is the practice of making your product data, facts, and answers easy for AI systems and answer engines — ChatGPT, Gemini, Perplexity — to retrieve, understand, and cite. **Generative Engine Optimization (GEO)** is the practice of making your content discoverable and citable by generative AI through structured references, entity clarity, and protocol-ready feeds. The relationship between the two layers is straightforward: ``` AEO/GEO → AI recommends your products UCP / ACP → AI completes the purchase Asva Attribution → You see and measure what happened ``` UCP and ACP give AI assistants the plumbing to complete a transaction. AEO and GEO determine whether the AI recommends you at all. A brand that implements checkout protocols but ignores structured data and entity clarity will have the infrastructure to transact but not enough AI traffic to use it. ## AEO tactics ### Product JSON-LD schema Every product page must have `Product` and `Offer` structured data. This is the primary signal AI systems use to understand what you sell, at what price, and whether it is in stock. ```html theme={null} ``` Keep `availability` accurate in real time. AI systems that surface product recommendations — including Google AI Mode — will deprioritize or omit products marked as out of stock. A stale feed is a direct loss of AI Commerce traffic. ### Organization schema AI systems need to know who you are as an entity to cite you accurately and consistently. Add `Organization` schema to your site-wide `` or footer: ```html theme={null} ``` ### Entity consistency AI systems build knowledge graphs. When your brand name appears differently across pages and sources — "YourBrand", "Your Brand Inc", "yourbrand.com" — the AI's confidence in citing you drops, and so does the frequency of recommendations. Audit your brand entity across all touchpoints: * Same brand name on every page, in every schema reference * Legal entity name consistent with your company registry record * Physical address consistent with your Google Business Profile * Canonical URL used consistently in all schema markup ### Evidence blocks AI systems prefer to cite sources they can verify. Pages that include explicit references to authoritative third-party data are cited more often and with higher confidence. Add evidence blocks to your key landing and category pages: ```markdown theme={null} **Source:** [Seer Interactive study (2024)](https://seerinteractive.com/...) ChatGPT ecommerce conversion rate: 15.9% vs 1.76% Google organic ``` Link to the original source. AI systems evaluate link provenance, not just the claim. ## GEO tactics ### Product feed quality AI surfaces like Google AI Mode and Gemini Shopping use your product feed as their primary data source. Feed quality is the most direct GEO lever available to you. | Field | Why it matters | | -------------- | -------------------------------------------------------------------- | | `title` | Used verbatim in AI-generated responses | | `description` | Determines how the AI describes your product to the user | | `availability` | AI surfaces will not recommend unavailable products | | `price` | Must match your live storefront — discrepancies reduce trust signals | For full field requirements and formatting rules, see [Feed Specs and Formatting](/guides/feed-specs). ### UCP manifest Publishing `/.well-known/ucp` is a direct GEO signal. It tells AI agents that your store is agentic-commerce-ready and that they can initiate transactions on behalf of users. See [Publishing the .well-known Manifest](/ucp/well-known). ### FAQ schema AI systems heavily cite FAQ content when answering conversational queries. Add `FAQPage` schema to your key category and product pages: ```html theme={null} ``` Write FAQ questions the way users actually ask them in AI chat interfaces — conversational, specific, and intent-driven. ## Implementation checklist Use this checklist to audit your current state and track what remains to implement: * [ ] `Product` + `Offer` schema on every product page * [ ] `Organization` schema in site-wide `` or footer * [ ] `FAQPage` schema on key category and landing pages * [ ] `aggregateRating` populated with real review data where available * [ ] Brand name identical across all pages and schema references * [ ] Legal entity name matches company registry record * [ ] Address matches Google Business Profile * [ ] Canonical URL used consistently in all schema `url` fields * [ ] `/.well-known/ucp` manifest published and returning a valid response * [ ] Product feed quality score ≥ 80 (check via [Readiness Score](https://asva-ai.com/tools/readiness)) * [ ] Evidence blocks with links to authoritative sources on key pages * [ ] FAQ content written in conversational, query-style language * [ ] No conflicting brand name variants across pages or schema ## Audit your AEO/GEO gaps Run the Readiness Score to get a specific gap report for schema, entity, and feed quality: ```bash theme={null} curl -X POST https://asva-ai.com/api/audit \ -H "Authorization: Bearer $ASVA_API_KEY" \ -H "Content-Type: application/json" \ -d '{"domain": "yourstore.com", "checks": ["schema", "entity", "feed"]}' ``` Go to [asva-ai.com/tools/readiness](https://asva-ai.com/tools/readiness), enter your domain, and select the **AEO/GEO** audit type. The tool returns a score and a prioritised list of gaps to close. The Readiness Score checks schema validity, entity consistency, feed quality, and `/.well-known/ucp` availability in a single pass. Run it before and after implementing the checklist above to measure progress. ## Related * [Glossary: AEO, GEO, UCP, ACP](https://asva-ai.com/glossary) * [Feed Specs and Formatting](/guides/feed-specs) * [Publishing the .well-known Manifest](/ucp/well-known) * [Entity and Citation tool](https://asva-ai.com/tools/entity-check)