# AI Buyer Score: The Shopping Agent Checklist > How an AI shopping agent evaluates your Shopify store. The 9 recommendability criteria and how to go from 'not recommended' to 'recommended'. - Canonical HTML: https://verityscore.io/en/kb/ai-buyer-score/ - Markdown alternate: https://verityscore.io/en/kb/ai-buyer-score.md - Language: en - Content type: kb - Published: 2026-02-21 - Updated: 2026-04-19 - Tags: ai-buyer, ai-agents, recommendation, checklist - Audit zone: AI Buyer ## What is the AI Buyer Score? The AI Buyer Score simulates an autonomous shopping agent's decision (OpenAI Operator, Google Shopping AI, Perplexity Shopping) when facing your Shopify store. The verdict is binary: **recommended** or **not recommended**. No gray area, exactly like a real shopping agent that must decide "yes" or "no". ## Why it matters for AI Shopping agents don't look for the "best design." They look for the **product with the clearest and most verifiable signals**. Stores with 99.9% attribute completeness (Golden Record) have 3-4x more AI visibility ([eFulfillment, 2026](https://www.efulfillmentservice.com/2026/01/the-complete-product-data-optimization-guide-for-googles-ai-shopping-2026/)). 96% of AI Overview citations come from sources with strong E-E-A-T signals ([Wellows, 2026](https://wellows.com/blog/google-ai-overviews-ranking-factors/)). The foundational research in the field, the Princeton GEO paper (KDD 2024), confirms that content enriched with authoritative citations gains up to +115% AI visibility, and +41% when it includes verifiable statistics ([Princeton, 2024](https://arxiv.org/abs/2311.09735)). A store with average design but perfect data will be recommended before a stunning store with incomplete data. ## The 9 Decision Criteria
The 9 AI Buyer Score decision criteria: price, reviews, shipping, returns, availability, brand, specs, coherence, and crawlability - with importance level (blocking or high)
Figure 1 - The 9 criteria evaluated by an AI shopping agent before recommending a store
### 1. Clear, structured price The agent looks for `schema.org/Offer` with `price`, `priceCurrency`, and `availability` ([Schema.org Offer spec](https://schema.org/Offer)). Without this, it can't compare your product with competitors. ### 2. Credible, accessible reviews The agent looks for `AggregateRating` with `ratingValue` and `reviewCount` in HTML ([Schema.org AggregateRating](https://schema.org/AggregateRating)). JavaScript-loaded reviews are invisible. The Ahrefs study of 75,000 brands (Q1 2026) confirms that brand mentions correlate strongly with AI visibility (r=0.66 to 0.71 depending on the engine), far more than classic backlinks ([Ahrefs, 2026](https://ahrefs.com/blog/ai-brand-visibility-correlations/)). ### 3. Documented shipping The agent looks for an accessible shipping policy with explicit timelines and costs. ### 4. Returns available Same logic as shipping: the agent verifies the return policy exists and is accessible. ### 5. Confirmed availability The agent verifies the product is in stock via `availability: InStock` in schema. ### 6. Identifiable brand The agent looks for a `brand` field in the Product schema. ### 7. Complete specifications Sufficiently detailed description (> 50 words) and structured product attributes. Baymard Institute's e-commerce UX research confirms that complete product specifications significantly reduce abandonment and increase the probability of recommendation by AI agents ([Baymard Institute](https://baymard.com/research)). ### 8. Claims/proofs coherence The agent compares marketing promises with verifiable data. ### 9. Crawlability The site must be accessible: open robots.txt, native HTML (not JS-only), working sitemap. ## The Decision Logic Shopping agents don't use a simple average. Some criteria are **blocking**: an invisible price or a robots.txt that blocks access can be enough to eliminate a store from recommendations, even if all other signals are positive. That's why it's essential to start with the fundamentals (price, crawlability, schema) before optimizing secondary aspects. ## How to Fix on Shopify Most corrections are achievable in a few hours: 1. Verify your theme's JSON-LD schema (source code → `application/ld+json`) 2. Configure your review app to inject AggregateRating 3. Create/verify policy pages (shipping, returns) in HTML 4. Open robots.txt to AI crawlers 5. Enrich product descriptions --- ## Related articles - See also: [AI Buyer Score: Would an AI Recommend Your Store?](/en/blog/ai-buyer-score-explained) - [Understanding Your GEO Score: 9 Factors Explained](/en/kb/geo-readiness) - [Schema.org Product: Why and How on Shopify](/en/kb/schema-org) - [AggregateRating: Making Your Reviews AI-Readable](/en/kb/aggregate-rating) - [Conversational Content: Writing for Humans AND AI](/en/kb/conversational-content) - [robots.txt and AI Crawlers: Don't Block Your Sales](/en/kb/robots-crawlers) --- **Ready to check your store?** [Run a free GEO audit →](https://verityscore.io) ## FAQ ### What is the AI Buyer Score and how does it work? The AI Buyer Score simulates how an AI shopping agent (like OpenAI Operator or Google Shopping AI) evaluates your store. It checks 9 criteria including price visibility, reviews, shipping policies, and crawlability, then gives a binary verdict: recommended or not recommended. ### Why is my Shopify store not recommended by AI shopping agents? Common reasons include: missing or incomplete Product schema.org, reviews loaded only via JavaScript (invisible to AI), blocked AI crawlers in robots.txt, missing shipping/return policy pages, or unverifiable marketing claims. ### What are the blocking criteria for AI shopping agents? Some criteria are deal-breakers: an invisible price (no Offer schema), a robots.txt that blocks AI crawlers, or a product showing as out of stock. Any of these alone can eliminate your store from recommendations, regardless of other signals. ### How do I make my products recommendable by AI agents? Focus on data completeness: add full Product schema.org with price and availability, enable AggregateRating in your review app, write clear policy pages, open robots.txt to AI crawlers, and ensure product descriptions have at least 50 words with specific details. ## Sources - [The Complete Product Data Optimization Guide for Google's AI Shopping (2026)](https://www.efulfillmentservice.com/2026/01/the-complete-product-data-optimization-guide-for-googles-ai-shopping-2026/) (industry) - [Perplexity Shopping: How to Optimize Your Store for AI (2026)](https://www.shopify.com/blog/perplexity-shopping) (official) - [Google AI Overviews Ranking Factors: 2026 Guide](https://wellows.com/blog/google-ai-overviews-ranking-factors/) (industry) - [AI Citation Report 2025: Sources AI Overviews Trust Most](https://surferseo.com/blog/ai-citation-report/) (industry) - [GEO: Generative Engine Optimization (Princeton, KDD 2024)](https://arxiv.org/abs/2311.09735) (academic) - [Ahrefs 75K Brands AI Visibility Correlation Study (Q1 2026)](https://ahrefs.com/blog/ai-brand-visibility-correlations/) (industry) - [Schema.org Offer Specification](https://schema.org/Offer) (official) - [Schema.org AggregateRating Specification](https://schema.org/AggregateRating) (official) - [Baymard Institute UX Research](https://baymard.com/research) (industry)