Shopify Catalog: What is it and why is it important in agentic search

At a glance:

Shopify Catalog is a centralised, structured database of product information collated from eligible stores on Shopify or sites using Shopify Agentic Plan
It serves the purpose of a structured source of product information that helps AI platforms and shopping applications understand your store's products.
It can contain all sorts of information such as titles, descriptions, images, prices, availability, product options and variants.
Shopify Catalog can search and surface product data in two ways: Global Catalog supports product discovery across multiple merchants, while Storefront Catalog searches within a specific merchant’s product range.
It’s an important platform to understand because the accuracy of product data and grouping could affect how easily an AI platform can match your product to a shopper’s request.

The way people discover products online is changing.

We’re all aware the way customers search for products is changing. Instead of opening Google, searching for a product and clicking through several category pages, shoppers can now ask an AI assistant a detailed question such as:

“Find me a button back 2 seater sofa, available in the UK for under £1,000.”

The AI can interpret the different parts of the search request, look for suitable products and present options that match the shopper’s requirements directly in the chat response.

Rather than simply returning a list of webpages like a traditional Google search, using AI search can shortcut much of the buyer journey. No longer do customers need to hop between several websites to narrow down their preferences. If the customer has inputted a very specific query, AI is now very good at serving a few product options that match and satisfy that query.

Furthermore, rapid development of agentic commerce capabilities will soon enable customers to instruct an AI agent to research, compare, select and then buy a product according to the query the customer makes.

All of which is where the importance of Shopify Catalog comes in. It’s one of the systems designed to support this process by making product information easier for AI systems to search and understand.

What is Shopify Catalog?

Shopify Catalog is a structured product data layer that makes product information available to supported AI platforms, shopping applications (such as the Shop app) and commerce agents.

It brings together product level information such as:

Titles and descriptions
Images
Prices
Stock availability
Sizes, colours and other options
Product variants
Categories and attributes
Product and checkout links

Shopify organises this information into a consistent format that shopping platforms and AI agents can search and understand with ease.

In basic terms, Shopify Catalog acts like a product feed for AI shopping. There are similarities with Google Merchant Center, although Shopify Catalog has been designed to support AI chat based searches and agentic commerce.

Instead of relying entirely on an AI assistant to visit and interpret individual webpages, an AI agent can request structured product information from specific Shopify endpoints (further info in their developer documentation) and receive products that match the shopper’s search request.

Shopify Catalog does not completely replace web crawling or other product feeds. As you’d expect, products will still be found through typical crawling, indexing and feeds supplied to other platforms. Catalog is simply another product discovery mechanism that complements existing frameworks and mechanisms for AI systems to find a product.

What does the data look like?

The exact response depends on the Catalog interface and type of query, however, the following simplified example demonstrates some of the important product information that can be returned:

{
  "title": "Harbour 2 Seater Sofa",
  "description": {
    "plain": "A compact two-seater sofa with deep cushions, rounded arms and a clean, modern shape."
  },
  "options": [
    {
      "name": "Colour",
      "values": [
        { "label": "Forest Green" },
        { "label": "Cream" }
      ]
    },
    {
      "name": "Material",
      "values": [
        { "label": "Velvet" },
        { "label": "Chenille" }
      ]
    },
    {
      "name": "Size",
      "values": [
        { "label": "2 Seater" },
        { "label": "3 Seater" }
      ]
    }
  ],
  "media": [
    {
      "type": "image",
      "url": "https://cdn.example.com/products/harbour-sofa-green.jpg",
      "alt_text": "Harbour 2 Seater Sofa in Forest Green"
    },
    {
      "type": "image",
      "url": "https://cdn.example.com/products/harbour-sofa-side.jpg",
      "alt_text": "Side view of the Harbour 2 Seater Sofa"
    }
  ],
  "price_range": {
    "min": {
      "amount": 44900,
      "currency": "GBP"
    },
    "max": {
      "amount": 69900,
      "currency": "GBP"
    }
  },
  "availability": {
    "available": true
  },
  "url": "https://www.example-store.com/products/harbour-sofa"
}

As you can see, key information about the price, currency, availability, size, material, images and more is returned in the response.

This is designed to reduce the amount of interpretation required and attempts to ensure consistency of product information that AI platforms will ingest.

Where this delivers change is when you view this in comparison to what’s on a traditional product page; important information might be spread across all parts of the PDP, for instance in the description, specifications, images, metafields, variant selectors and JavaScript-rendered components. The page may also contain recommendations and information about unrelated products.

Uniformly, and consistently structuring product information makes it easier for an agent to distinguish with confidence the factual attributes belonging to the product itself.

Global Catalog vs Storefront Catalog

It’s worth knowing too that Shopify Catalog comprises ‘Global Catalog’ and ‘Storefront Catalog’ and they serve slightly different purposes.

Global Catalog

Global Catalog is intended for product discovery across multiple merchants.

Essentially, AI assistants will use the Global Catalog when a user’s query is quite generic and non-brand specific e.g. “Recommend me the best navy running shorts under £50”

The Global Catalog can then search and retrieve products from multiple merchants to serve options that best match or are most relevant to the shopper’s request.

Global Catalog is intended to help serve as a broad product search engine for generic searches and comparisons, where the customer isn’t specifically focussed on a particular store.

Storefront Catalog

The Storefront Catalog on the other hand is a merchant specific product catalog.

It is more appropriate when a shopper has already chosen a store or is interacting directly with a merchant’s shopping assistant. As a hypothetical example, if a user specifies a particular store like Ikea, the AI assistant would look for products matching the users query within Ikea’s Storefront Catalog.

A query like “please find me a 4 seater white dining table on Ikea”, this could go directly to the Storefront Catalog and get a range of Ikea products matching this criteria and serve it up to the user.

Both interfaces support structured product discovery, but their scope is different:

Global Catalog: searches across multiple merchants.
Storefront Catalog: searches within one merchant’s product range.

Important to note, Shopify Catalog is aiming to make this available to stores outside of Shopify network, through Shopify Agentic plan. You can read more about this here.

So why is Shopify Catalog important for agentic search?

Users are rapidly moving away from traditional search engines for research and product discovery. Shopify Catalog gives supported AI platforms a direct and structured way to access eligible Shopify products without having to trawl through multiple websites.

1. AI agents benefit from structured product information

AI assistants can crawl websites, but crawling is not always the most dependable way to understand an ecommerce catalogue. Product information can be spread across page copy, metafields, JavaScript rendered components, images, variants etc. meaning it can be difficult to interpret product information to provide the most accurate and best product to the user.

2. Conversational searches can be much more detailed

Additionally conversational searches contain much more detail versus how users typically search using search engines.

For example, the typical search behaviour has been to search “blue bar stool”, followed by a requirement for the user to review the SERPs. However, now users can search much more specifically, for instance: “blue bar stool with pedestal silver base under x price”.

This type of query needs a better system to understand facets of a product which is more easily achievable through consistent structured data.

3. Variants can be matched more accurately

A product page might be relevant overall but only one of its variants may satisfy the shopper’s request.

For example, a dining chair might be available in six colours, but the shopper has specifically requested green. Structured option and variant information helps an agent identify and present the green variation rather than linking to the product without confirming that the requested option exists.

Does inclusion in Shopify Catalog guarantee visibility?

No.

Shopify Catalog supplies structured product data that an AI search platform can use, but the individual platform controls:

Which products it displays
How products are ranked
How recommendations are worded
What the shopping interface looks like

Good product data can improve the likelihood that a platform understands and matches a product correctly, but it does not guarantee inclusion or a particular ranking.

What should Shopify merchants do now?

Shopify Catalog is relatively new, but there are several practical steps merchants can take.

First, review the product information Shopify and AI platforms are likely to use, including:

Product titles
Product descriptions
Images
Product categories
Types, vendors, collections and tags
Barcodes and GTINs
Variant names and option values
Prices and stock availability

Shopify specifically recommends providing clear, accurate and detailed product information to improve the chances of products being matched to relevant searches.

Merchants with more complicated product structures should also review Shopify Catalog Mapping. This is particularly important where:

Colourways use separate product URLs
Product information is stored in metafields or metaobjects
Titles contain delimiters or internal naming conventions
Combined Listings are used
Variant names are unclear
One description is being applied across several different products

Finally, merchants should monitor performance within Shopify’s Agentic sales channel reporting and test how their products are represented when Catalog is queried.

All in all

Shopify Catalog is relatively new on the scene, however, we expect it could become more important as agentic product recommendations become increasingly mainstream.

We’ll be keeping an eye on client performance and be reporting back on insights learnt through testings and configuration tweaks.

Finally, if you’re keen to learn more, we’ll be releasing a follow up article on how to configure Shopify Catalog Mapping to make sure your products are well mapped together.