Key terms and concepts in agentic commerce, from protocols to business strategies.
A2A is Google's open protocol that allows AI agents built by different providers to discover each other, communicate, and collaborate on tasks.
ACP is Shopify's protocol that lets AI agents discover products, manage carts, and complete purchases on behalf of users.
JSON-LD is a lightweight data format that embeds structured, machine-readable information into web pages using JavaScript Object Notation.
MCP is an open standard that lets AI models connect to external tools, APIs, and data sources through a unified interface.
Schema.org is a collaborative vocabulary standard that defines how to describe products, businesses, and other entities in a machine-readable format.
UCP is a platform-agnostic protocol designed to make any ecommerce store discoverable and shoppable by AI agents, regardless of the underlying platform.
AI readiness measures how well an ecommerce store's product data, technical infrastructure, and content prepare it for discovery by AI agents.
Agentic commerce is the emerging paradigm where AI agents autonomously discover, evaluate, and purchase products on behalf of human users.
AEO is the practice of optimizing content to appear as direct answers in AI-powered search engines and voice assistants.
GEO is the practice of optimizing content and product data so that AI-powered search engines and agents accurately surface and recommend it.
LLM SEO is the practice of optimizing product data and content to be accurately represented in large language model outputs and recommendations.
A product feed is a structured data file containing your store's product catalog, used to distribute listings to shopping platforms and AI agents.
RAG is a technique where AI models retrieve relevant external data before generating responses, enabling access to current information beyond training data.
Semantic search is a search approach that understands the meaning and intent behind queries rather than matching exact keywords.
Structured data is machine-readable information embedded in web pages that helps search engines and AI agents understand product details precisely.
Tool use is the ability of AI models to call external functions and APIs to take actions or retrieve information beyond their training data.
An Amazon AI feature that enables its assistant to browse and purchase products from third-party retailer websites on the user's behalf.
A built-in shopping feature in ChatGPT that lets users discover and purchase products through conversational AI.
AI-generated summaries that appear at the top of Google search results, synthesizing information from multiple web sources.
Microsoft's AI shopping feature that integrates product discovery and assisted checkout into the Copilot assistant and Bing search.
Perplexity's product discovery feature that integrates shopping recommendations directly into AI-generated answers with source citations.
Shopify's implementation of the Model Context Protocol that exposes store product data to AI agents in a structured, machine-readable format.
A metadata standard originally designed for social media sharing that now influences how AI systems preview and represent product pages.
Structured data markup using Schema.org vocabulary that describes product details in a machine-readable format for search engines and AI agents.
A proposed web standard that lets website owners declare permissions, capabilities, and restrictions for AI agents interacting with their site.
A proposed web standard that provides AI language models with a structured overview of a website's content, purpose, and key pages.
The practice of using and adapting the robots.txt standard to manage how AI crawlers, training bots, and shopping agents access website content.
An AI system that autonomously assists users in discovering, evaluating, comparing, and purchasing products across e-commerce stores.
A metric that measures how effectively a merchant's products and store data are structured and accessible to AI shopping platforms.
An AI-powered system that provides direct, synthesized answers to user queries instead of returning a list of links to external websites.
The practice of improving the likelihood that AI systems cite, reference, and recommend your products and brand in their responses.
The evolving dynamics of how purchases happen when AI agents mediate product discovery, comparison, and checkout in e-commerce.
A search paradigm where AI generates synthesized, original answers to queries by reading and combining information from multiple web sources.
The depth and breadth of a website's expertise on a specific subject, which influences how AI systems evaluate and cite its content.
A search outcome where the user gets their answer directly in the search results page without clicking through to any external website.
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