Reference
Agentic Commerce Glossary
56 definitions across AI visibility, commerce protocols, shopping surfaces, product data, and infrastructure. Each term includes a concise definition, supporting research, FAQs, and links to related Paz blog posts.
How the four optimization disciplines relate
SEO, AEO, GEO, and ACO overlap but optimize for different outputs. The short version:
- SEO ranks HTML pages on Google and Bing for human readers.
- AEO gets content cited inside AI-generated answers in ChatGPT, Perplexity, and Google AI Overviews.
- GEO is the broader discipline of visibility across all generative AI outputs.
- ACO is the commerce-specific subset: product feeds, attributes, and protocols so AI shopping agents can recommend and transact your products.
Most retailers need all four running in parallel. See AEO for the full comparison table.
Browse by category
AI Commerce Fundamentals
The concepts that define the shift from humans browsing websites to AI agents discovering and buying products. Start here if you are new to agentic commerce.
Agentic Commerce
Agentic commerce is the emerging category where AI agents autonomously discover, compare, and purchase products on behalf of consumers across platforms like ChatGPT, Google AI Mode, and Perplexity.
Conversational Commerce
Conversational commerce is the practice of selling products through chat-based interfaces — from messaging apps and chatbots to AI shopping agents.
Digital Shelf and AI
The digital shelf is every online touchpoint where consumers discover products — now expanding to include AI shopping agents alongside traditional search and marketplaces.
Agentic Storefront
An agentic storefront is a merchant's presence within AI shopping agents — the product data, checkout integration, and brand representation that appears when AI agents recommend their products.
Zero-Click Buying
Zero-click buying is the emerging concept where AI agents handle the entire product discovery and recommendation process, minimizing the steps between consumer intent and purchase.
AI Visibility & Optimization (GEO, AEO, ACO)
The disciplines of getting your brand and products cited, recommended, and surfaced inside AI-generated answers. This is where the most vocabulary changed in 2025-2026.
Generative Engine Optimization (GEO)
GEO is the practice of structuring digital content to maximize visibility in AI-generated responses from ChatGPT, Google AI, and Perplexity.
Answer Engine Optimization (AEO)
Answer Engine Optimization (AEO) is the practice of structuring content and product data so AI answer engines like ChatGPT, Perplexity, and Google AI Overviews cite your brand as a source.
Agentic Commerce Optimization (ACO)
Agentic Commerce Optimization (ACO) is the practice of structuring product data, feeds, and site signals so AI shopping agents reliably discover, understand, and recommend a retailer's products.
Query Fan-Out: How AI Search Decomposes One Question Into Many
Query fan-out is how AI search systems decompose a single user question into 8 to 12 parallel sub-queries, retrieve passages for each, and synthesize one answer.
Passage-Level Retrieval: Why AI Search Cites Sections, Not Pages
Passage-level retrieval is when an AI search system pulls and cites a specific passage of text rather than ranking a whole page, treating each passage as an independent retrieval unit.
LLM SEO
LLM SEO is an umbrella term for optimizing content so large language models like ChatGPT, Claude, and Gemini understand, trust, and cite your brand. It overlaps heavily with AEO and GEO.
AI Visibility for Commerce
AI visibility for commerce measures how discoverable your products and brand are when consumers ask AI agents for shopping recommendations.
Entity Optimization for AI Search
Entity optimization is the practice of structuring a brand's identity so AI engines resolve it to a single, trusted entity in their knowledge graphs and cite it consistently.
AI Share of Voice
AI share of voice measures how often and how prominently an AI engine mentions your brand relative to competitors when answering category queries - the AI-era equivalent of traditional share of voice.
Branded vs Unbranded AI Queries
Branded AI queries include a brand name ("is Nike good for running?"); unbranded queries do not ("best running shoes"). The two require different AI visibility strategies.
AI Product Found Rate
Found Rate is the percentage of relevant shopping queries on which a retailer's product appears - text mention, product card, or otherwise - across AI engines. The base AEO/ACO commerce metric.
AI Shopping Surfaces & Agents
The platforms where AI shopping actually happens: ChatGPT, Google, Perplexity, Amazon Rufus, plus the shopping agents and assistants that run on top of them.
ChatGPT Shopping
ChatGPT Shopping is OpenAI's built-in commerce feature that lets consumers discover and compare products inside ChatGPT, then click through to merchant sites to purchase.
Google AI Mode Shopping
Google AI Mode Shopping integrates product recommendations and purchasing directly into Google's AI-generated search results, combining Google Shopping data with conversational AI.
Google AI Overviews
Google AI Overviews are AI-generated summaries that appear above traditional search results, synthesizing answers from multiple sources and appearing on roughly 48% of searches as of early 2026.
Perplexity Shopping
Perplexity Shopping is an AI-powered product discovery and purchasing feature that lets consumers find, compare, and buy products directly from Perplexity search results.
Amazon Rufus Optimization
Amazon Rufus optimization is the practice of structuring product listings so Amazon's generative AI shopping assistant surfaces and recommends them in natural-language shopper queries.
ChatGPT Apps SDK
The ChatGPT Apps SDK is OpenAI's developer framework for building interactive applications that run inside ChatGPT, announced at DevDay 2025 and built on the Model Context Protocol.
AI Shopping Agent: How It Works in 2026
An AI shopping agent is software that autonomously searches, compares, and purchases products on behalf of a consumer through natural language conversation.
AI Shopping Assistant
An AI shopping assistant is a conversational AI that helps shoppers discover, compare, and buy products. It can run on a retailer's own site or inside a platform like ChatGPT, Perplexity, or Amazon Rufus.
AI Shopping Search
AI shopping search replaces traditional keyword-based product search with natural language, conversational queries that AI agents interpret to find and recommend products.
Commerce Protocols & Standards
The open standards that let AI agents discover and transact with merchants: ACP for ChatGPT, UCP for Google, MCP as the underlying data layer, plus feed and crawler standards.
Agentic Commerce Protocol (ACP): How It Works in 2026
ACP is an open-source checkout protocol by Stripe and OpenAI that enables AI agents to complete purchases on behalf of consumers.
Universal Commerce Protocol (UCP)
UCP is an open standard by Google and Shopify that enables AI agents to handle the full commerce journey from discovery to post-purchase.
Model Context Protocol (MCP)
MCP is an open standard originally created by Anthropic that provides a universal way for AI agents to connect to external data sources in real time.
AI Commerce Protocols
AI commerce protocols (ACP, UCP, MCP) are the open standards that define how AI agents discover products, complete checkouts, and access merchant systems.
ChatGPT Product Feed: Format and How to Submit
The ChatGPT product feed format is a JSONL-based spec by OpenAI that retailers use to syndicate catalogs into ChatGPT Shopping for AI-driven product discovery.
llms.txt for Ecommerce
llms.txt is a proposed web standard that provides AI systems with a structured, plain-text summary of a website's content for faster and more accurate comprehension.
Product Data & Catalog
The inputs that power every AI shopping surface. Rich, structured product data is the single largest lever for AI visibility and agentic commerce performance.
Structured Product Data
Structured product data is machine-readable product information organized in standardized formats like Schema.org, enabling search engines and AI agents to understand and recommend products.
Product Schema Markup
Product schema markup is structured JSON-LD data embedded in a product page that tells search engines and AI systems what the product is, what it costs, whether it is in stock, and what buyers think of it.
Product Data Enrichment
Product data enrichment is the process of enhancing raw product information with additional attributes, descriptions, and metadata to improve discoverability and conversions.
Product Feed Management
Product feed management is the process of creating, optimizing, and distributing structured product data to sales channels like Google, Amazon, and AI agents.
Product Feed Optimization for AI
Product feed optimization for AI is the practice of structuring and enhancing product data specifically for discovery and recommendation by AI shopping agents.
Product Feed API
A product feed API is a programmatic interface that enables automated exchange of product catalog data between ecommerce systems and sales channels, including AI shopping platforms.
AI Catalog Management
AI catalog management uses artificial intelligence to automate product data creation, enrichment, categorization, and optimization across sales channels.
Platforms, Infrastructure & Measurement
The platforms retailers use to orchestrate agentic commerce, the infrastructure that makes it work (RAG, crawlers, integrations), and the metrics that measure readiness.
AI Commerce Platform
An AI commerce platform is infrastructure that connects product catalogs to AI shopping agents, handling protocol compliance, feed optimization, and checkout integration.
Multi-Channel AI Commerce
Multi-channel AI commerce is the practice of distributing product catalogs across multiple AI shopping platforms simultaneously — ChatGPT, Perplexity, Google AI Mode, and others.
Commerce AI Integration
Commerce AI integration is the process of connecting ecommerce systems to AI shopping platforms, enabling product discovery and purchasing through AI agents.
Headless Commerce and AI
Headless commerce separates the frontend presentation from backend commerce logic — a critical architecture for connecting product catalogs to AI shopping agents.
Retrieval-Augmented Generation (RAG) for Commerce
RAG for commerce is an AI architecture that grounds language model responses in live retailer data - catalog, inventory, reviews, policies - so shopping answers are accurate and up to date.
AI Crawler Management (GPTBot, ClaudeBot, PerplexityBot)
AI crawler management is the practice of configuring robots.txt and server rules to allow the right AI crawlers (GPTBot, Google-Extended, ClaudeBot, PerplexityBot) while managing load and cost.
AI Readiness Score for Ecommerce
An AI readiness score measures how well a retailer's product data, feeds, and site infrastructure are structured for AI shopping agents to discover, understand, and recommend products.
Checkout, Merchandising & Recommendations
Transaction completion and the merchandising logic that decides which products get shown - inside AI surfaces and on the retailer's own storefront.
Instant Checkout (ChatGPT) - Discontinued
Instant Checkout was ChatGPT's in-conversation purchase feature, active from September 2025 to March 2026. OpenAI discontinued it in favor of a discovery-and-redirect model where users purchase on merchant sites.
AI Checkout
AI checkout refers to commerce capabilities within AI platforms. As of March 2026, most AI shopping operates as discovery-and-redirect: AI agents recommend products and direct users to merchant sites to purchase.
AI Merchandising
AI merchandising uses artificial intelligence to automate product assortment, placement, pricing, and presentation decisions across traditional and AI-powered sales channels.
AI Product Recommendations
AI product recommendations use machine learning to suggest relevant products to consumers based on intent, behavior, and context — increasingly through AI agents rather than on-site widgets.
Other Terms
Terms not yet assigned to a category.
Agent Payments Protocol (AP2): What It Is in 2026
AP2 is Google's open protocol that lets AI agents authorize and execute payments on behalf of consumers using a digitally signed Mandate.
Visa Trusted Agent Protocol (TAP): 2026 Guide
Visa TAP is Visa's agent-payment authorization protocol that verifies AI agents at transaction time and lets them initiate payments on behalf of cardholders.
Agent-to-Agent Protocol (A2A): What It Is in 2026
A2A is an open protocol launched by Google and donated to the Linux Foundation that defines how AI agents communicate, coordinate, and delegate tasks across systems.
Mastercard Agent Pay: How It Works in 2026
Mastercard Agent Pay is Mastercard's agent-payment infrastructure that authenticates and authorizes AI-initiated transactions on the Mastercard network.
Agent Mandate: What It Is in 2026
An Agent Mandate is a digitally signed authorization a consumer issues to an AI agent that defines exactly what the agent can spend on, with what limits, and for how long.
American Express ACE: Agentic Commerce Experiences
ACE (Agentic Commerce Experiences) is American Express's developer kit for AI-initiated payments, including industry-first purchase protection for registered AI agent purchases.
How to Structure Product Data for AI Agents (2026 Guide)
Structuring product data for AI agents in 2026 means publishing a complete, attribute-rich, schema-tagged product catalog that AI shopping platforms can retrieve, parse, and confidently recommend.
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