Reference

Agentic commerce glossary

61 plain-language definitions covering AI visibility, shopping surfaces, commerce protocols and product data. Each term explains what it is, why it matters to an ecommerce team and what to do about it.

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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 aims to make useful content easier to find and cite in ChatGPT, Perplexity, and Google AI Overviews.
GEO is the broader discipline of visibility across all generative AI outputs.
ACO applies related work to product information and shopping appearances. Commerce integrations and checkout have separate requirements.

Choose the work that fits your commercial priorities. See AEO for the full comparison table.

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How Paz Works With You

The working model behind the service: the recurring job, the business context and buyer personas it runs on, and the approval that gates every change.

Ecommerce Task Automation: Tasks, Workflows, and Paz Routines

A commerce task is a specific ecommerce job with a goal, inputs and a clear finish line, such as adding the missing capacity to every bottle description in a priority collection. Ecommerce task automation carries that job out on a schedule or after a catalog sync, and puts the resulting fix in front of your team for approval.

Business Context for Ecommerce AI: Shared Company Context

Shared company context is what Paz knows about your business and carries into every check: product information, what you are promoting, who you sell to, the claims you keep fixed, and the answers and decisions from earlier work. It builds over time and changes when your priorities or market change.

Policy-Controlled Automation: Approval-Gated Execution

Approval-gated execution means an automated change to your product data is prepared with evidence, approved by your team or your policy, then published to the destination and checked. In Paz, that is how a finding becomes a fix in Shopify or Merchant Center.

AI Commerce Fundamentals

The core ideas behind AI shopping: assistants that answer product questions, agents that compare and buy, and what that changes for a store. Start here if the vocabulary is new.

Agentic Commerce

Agentic commerce is shopping in which an AI assistant discovers, compares and increasingly buys products on a shopper's behalf, across ChatGPT, Google AI Mode, Perplexity and other surfaces.

Conversational Commerce

Conversational commerce is selling products through chat-based interfaces, from messaging apps and chatbots to AI shopping assistants such as ChatGPT.

Digital Shelf and AI

The digital shelf is every online place where shoppers discover and evaluate products. It now includes AI shopping assistants alongside search, marketplaces and social.

Agentic Storefront

An agentic storefront is a merchant's presence inside AI shopping assistants: the product data, checkout path and brand signals that appear when ChatGPT, Perplexity or Google AI Mode recommend their products.

Zero-Click Buying

Zero-click buying is the idea that an AI agent handles product discovery, comparison and selection for a shopper, so the steps between intent and purchase shrink to a confirmation or nothing at all.

AI Visibility & Optimization (GEO, AEO, ACO)

How products end up cited and recommended inside AI answers. The industry uses several labels for this work (GEO, AEO, ACO). At Paz we call it AI visibility.

Generative Engine Optimization (GEO)

GEO is the practice of shaping content so that AI systems such as ChatGPT, Google AI Overviews and Perplexity cite or draw on it when they generate an answer.

Answer Engine Optimization (AEO)

Answer Engine Optimization (AEO) is the practice of structuring content and product data to help 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 is whether your products appear when shoppers ask AI assistants such as ChatGPT, Google AI Mode and Perplexity what to buy.

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.

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 Measurement & Attribution

Metrics and methods for observing AI shopping visibility, separating appearance types, evaluating readiness, and connecting detectable AI referrals to commerce outcomes without overstating causality.

AI Share of Voice

AI share of voice measures how often and how prominently an AI assistant mentions your brand or products relative to competitors when answering category questions.

AI Product Found Rate

Found rate is the percentage of relevant shopping questions on which a retailer's product appears in an AI assistant's answer in any form: mention, product card or citation. It is the base measure of AI visibility.

AI Readiness Score for Ecommerce

An AI readiness score measures how well a retailer's product information is set up for AI shopping assistants to find, understand and recommend its products.

AI Shopping Attribution: Measuring AI-Referred Commerce

AI shopping attribution is the practice of linking visits and purchases to an AI referral signal, such as a referrer or campaign parameter, within a declared measurement window.

AI Shopping Surfaces & Agents

Where AI shopping happens today: ChatGPT, Google AI Mode, Perplexity, Amazon Rufus, and the agents and assistants built on them.

ChatGPT Shopping

ChatGPT Shopping is OpenAI's commerce feature that lets shoppers find and compare products inside ChatGPT, with recommendations shown as product cards that link to merchant sites.

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 the traditional results, synthesising an answer from several web sources and citing a few of them.

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: What It Is and How It Works

An AI shopping agent is software that searches, compares, and can purchase products on a consumer's behalf through natural language conversation, with degrees of autonomy that range from research to completed checkout.

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 lets shoppers describe what they need in plain language and have an AI interpret the request, find matching products and recommend a few, instead of matching keywords to a results list.

Commerce Protocols & Standards

The open standards AI agents use to read catalogs and transact with merchants: ACP for ChatGPT, UCP for Google, MCP underneath, plus feed and crawler conventions. Useful background; the product information they read is the part a store controls.

Agentic Commerce Protocol (ACP): What It Is and How It Works

The Agentic Commerce Protocol (ACP) is an open standard, maintained by OpenAI and Stripe, that defines how a shopper, their AI agent, and a merchant complete a purchase while the merchant stays the system of record.

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, created by Anthropic and now governed by the Linux Foundation, that gives AI agents one common way to connect to external data sources and tools in real time.

AI Commerce Protocols

AI commerce protocols are the open standards (ACP, UCP, MCP, plus the payment-side AP2, Visa TAP and Mastercard Agent Pay) that define how AI agents discover products, access merchant systems and complete purchases.

Agent-to-Agent Protocol (A2A): What It Is

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.

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.

Agent Payments, Identity, and Trust

How card networks and protocols let an AI agent prove who it is, carry a shopper's authority and pay. Background for ecommerce teams; the transaction itself stays with your payment stack.

Agent Payments Protocol (AP2): What It Is and How It Works

The Agent Payments Protocol (AP2) is an open-source protocol, created by Google and being donated to the FIDO Alliance, that defines how an AI agent obtains signed, verifiable authorization to initiate a payment on a consumer's behalf.

Visa Trusted Agent Protocol (TAP): What It Is and How It Works

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.

Mastercard Agent Pay: How It Works

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 and How It Works

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, paired with purchase protection that covers erroneous purchases made by registered AI agents.

Product Data & Catalog

The product records, attributes, schema and feeds that AI shopping systems and search engines read. This is where most of the fixable work lives.

Structured Product Data

Structured product data is product information organized in machine-readable, standard formats such as Schema.org markup and product feeds, so search engines and AI assistants can 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 work of completing and improving product information, such as attributes, descriptions and categories, so that shoppers, search engines and AI assistants can find and understand each product.

Product Attribute Completeness for AI Shopping

Product attribute completeness is the share of required or relevant product fields that hold valid, source-backed values for a given catalog and destination. It measures coverage: how much of what a channel or shopper needs is actually there.

Product Feed Management

Product feed management is the work of formatting, keeping current and distributing structured product data to the channels where shoppers find and buy products: Google Shopping, marketplaces and AI shopping assistants.

Product Feed Optimization for AI

Product feed optimization for AI is the practice of completing and improving the product data in your feeds so AI shopping assistants can understand, match and recommend your products.

Product Feed API

A product feed API is a programmatic interface for moving product catalog data between an ecommerce system and a sales channel automatically, instead of exporting and uploading files by hand.

AI Catalog Management: What It Is and How to Get It Done

AI catalog management uses AI to validate, enrich, categorize, optimize and distribute product data across sales channels, with a person reviewing the changes that matter.

Catalog Quality Score: What It Is and How to Improve It

A catalog quality score is a readiness measure of how complete, valid, consistent and fresh a product catalog is, with the field-level issues behind the number so a team knows what to fix first.

Platforms, Integration & Systems

The systems behind AI shopping: how assistants retrieve and read product data, how crawlers reach it, and how your store and PIM connect to the channels.

AI Commerce Platform

An AI commerce platform is software that helps a retailer get its products found and recommended by AI shopping assistants, by improving product data, distributing it to AI channels and measuring how products appear.

Multi-Channel AI Commerce

Multi-channel AI commerce means having your products present and recommendable across several AI shopping assistants at once: ChatGPT, Google AI Mode, Perplexity, Microsoft Copilot and whatever comes next.

Commerce AI Integration

Commerce AI integration is the work of connecting your ecommerce systems to AI shopping channels so your products can be discovered and recommended there, and of connecting the people and tools that keep the product information behind those channels in shape.

Headless Commerce and AI

Headless commerce separates the storefront from the commerce backend so product data and checkout are available through APIs, which makes it easier to reach channels beyond your website, including AI shopping assistants.

Retrieval-Augmented Generation (RAG) for Commerce

RAG for commerce is an AI architecture that grounds language model responses in retrieved retailer data (catalog, inventory, reviews, policies) so shopping answers are accurate and current.

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.

Checkout, Merchandising & Recommendations

Checkout inside AI surfaces, and the merchandising logic that decides which products get shown there and on your own storefront.

How AI-ready are your products?

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