The GEO Reading List: Essential Resources for AI Commerce Optimization
A curated collection of guides, documentation, and analysis for merchants preparing their product data for AI-powered discovery.
Generative Engine Optimization is new territory. The playbooks are still being written, the best practices are still forming, and most merchants are figuring it out as they go. That’s a problem when you’re trying to make decisions about your product data strategy.
We built this reading list to fix that. These are the resources we actually use and reference — organized by what you need to learn, not by where we found them.
Foundational concepts
Google’s Helpful Content Guidelines Google, Developer Documentation
Google’s framework for evaluating content quality applies directly to AI commerce. The core principle — write for people first, then structure for machines — is the foundation of GEO. If your product content doesn’t satisfy these guidelines, AI agents built on Google’s ecosystem won’t trust it either.
Schema.org Product Type Documentation Schema.org
The canonical reference for Product structured data. Every field an AI agent can read about your products is defined here. Bookmark this and refer to it when building or auditing your JSON-LD. Pay particular attention to Offer, AggregateRating, and additionalProperty — these are the fields most merchants skip.
Introduction to Structured Data Google Search Central
Google’s primer on how structured data works, why it matters for search, and how to implement it. Covers JSON-LD basics and links to every supported schema type. Start here if structured data is new to you.
Technical guides
Google Merchant Center Product Data Specification Google Merchant Center Help
The definitive spec for product feed data. Every field, every format, every validation rule. AI shopping agents — including ChatGPT Shopping — pull heavily from Merchant Center data. If your feed doesn’t meet this spec, you’re invisible to multiple AI discovery channels simultaneously.
JSON-LD Playground JSON-LD Community
Test and validate your JSON-LD markup in real time. Paste your product markup, see how it parses, catch errors before they go live. Use this alongside Google’s Rich Results Test for a complete validation workflow.
Google Rich Results Test Google Search Central
Test any product URL to see what structured data Google can extract. This is what AI agents see when they look at your product pages. If a field doesn’t show up here, it doesn’t exist as far as generative search is concerned.
Schema.org JSON-LD Examples Schema.org, Getting Started Guide
Practical examples of JSON-LD implementation across multiple schema types. The Product examples show the minimum viable markup and how to extend it with offers, reviews, and custom attributes.
Industry analysis and AI shopping
Google AI Overviews and Search Generative Experience Google Blog
Google’s own explanation of how AI Overviews work in search results. Understanding this helps merchants see how their product data feeds into AI-generated answers — and why structured data determines whether you’re cited or skipped.
Bing and Microsoft Copilot Shopping Experiences Microsoft Blog
Microsoft’s approach to AI-powered shopping through Copilot. Different from Google’s model but with similar data requirements. Merchants selling across multiple channels need to understand how each AI system discovers and evaluates products.
Perplexity Shopping Launch Perplexity Blog
Perplexity’s merchant-facing overview of their shopping feature. Notable because Perplexity crawls JSON-LD directly from product pages rather than relying on a feed intermediary. If your on-page structured data is weak, Perplexity can’t see you at all.
Feeds and data quality
Google Product Category Taxonomy Google Merchant Center Help
The full taxonomy Google uses to categorize products. Accurate categorization determines which queries your products can match. Miscategorized products get filtered out before the AI even evaluates them.
Content API for Shopping Reference Google Developers
For merchants managing feeds programmatically. This API reference shows every field available for product data submission — and reveals fields most merchants never populate, like productHighlight, productDetail, and shippingWeight.
Staying current
This list is maintained and updated as the AI commerce landscape evolves. New platforms launch, specifications change, and best practices sharpen. If you’ve found a resource that belongs here, let us know.
The single most important takeaway from all of these resources: AI agents don’t interpret your marketing. They read your data. The merchants who treat structured data as a first-class product asset — not an afterthought — are the ones AI agents will recommend.