Are you ChatGPT visible? 

We audited Athletic Greens, a brand spending millions on podcast ads and influencer deals. They appeared in 3 out of 12 ChatGPT shopping queries. Three.

That's the gap between brand recognition and AI visibility- and they are not the same thing.

ChatGPT, Gemini, and Perplexity now recommend products directly inside the conversation. Some let you buy directly in the chat. If your products don't show up when someone asks, "What's the best [your category]," you are losing sales to whoever does show up.

Most Shopify stores are invisible in these platforms- not because the tech is broken, but because their product data is.

The Gap Between Visibility and Product Data

Shopify automatically connects your catalog to ChatGPT through the Agentic Commerce Protocol (ACP). But here’s the catch: it only sends what you give it.

• Generic descriptions? That’s what ChatGPT reads.
• Missing alt text on images? Those products are invisible.
• No structured variant data? Good luck matching “blue medium cotton shirt” to anything.

We have audited hundreds of Shopify stores. On average, catalogs are only 60-75% ready for AI visibility. That means a quarter to a third of your products are either invisible or unavailable for purchase.

The worst case? Your product appears in search, but checkout is broken. The customer finds exactly what they want, clicks “Buy,” and nothing happens. They leave, and you will never know why.

What To Fix

1. Checkout

If users can’t complete a purchase, nothing else matters. ChatGPT uses two flags per product: enable_search and enable_checkout. Most stores have search enabled, but checkout is broken. Before optimizing descriptions or metadata, verify that checkout works across your ACP feed.

2. Descriptions

This is where most brands actually lack. “Premium quality cotton shirt” tells AI nothing. It can’t map that to “something for a casual office environment” or “breathable summer outfit.” AI doesn’t guess. It matches intent to explicit signals. Write strong product descriptions that answer:

• Who buys this?
• When would they use it?
• What does it go with?
• What should they know about sizing, fit, or function?

This is the foundation of prompt-optimized product descriptions, where every line adds context that AI systems can understand, synthesize, and confidently recommend.

3. Structural Data

Once checkout works and your descriptions provide real context, the next layer is structure. AI systems don’t interpret your pages the way humans do. They rely on explicit, structured signals to understand what a product is, how it varies, and whether it matches a specific request. That means a few fundamentals have to be consistently in place:

• Alt text on every product image, so AI can associate visuals with the product and its attributes.
• A populated brand field, so your products are clearly tied back to your brand across platforms.‍
• Variant data (size, color, material, and other options) need to live in structured fields that AI can parse and compare.

These small structural signals are often the difference between a product being discoverable or effectively invisible in AI-driven shopping.

Test Your AI Visibility

Before you start optimizing, it’s important to see what AI systems are actually reading from your store.

Start by running an AI Visibility Audit, it shows how your catalog appears to ChatGPT and which products are eligible to surface in AI shopping results.

Then test it manually. Open ChatGPT and ask the same questions your customers would ask: “Best [category] under $[price]" or “Recommend a [product] for [use case].”

If your products don’t appear, that’s useful signal. It tells you exactly where visibility breaks down. Most merchants never do this. They assume visibility because Shopify says “connected.” But connected ≠ visible. ‍

Seeing what AI sees gives you a clear starting point. Everything else follows from that.

The Multi-Platform Reality

AI shopping isn’t happening in one place. Each AI system looks at your store through a different lens:

• ChatGPT reads Shopify catalogs through the Agentic Commerce Protocol (ACP).
• Gemini relies on your Google Merchant Center feed.
• Perplexity discovers products through traditional web crawling.
• Claude pulls context from general web search.

When your product data is clean, structured, and contextual, it works across all of these systems at once. You don’t need a separate strategy for every platform. You need one solid foundation. Better data means consistent visibility, regardless of platform.

There is one additional step that’s specific to ChatGPT: adding an llms.txt file. It gives ChatGPT a reliable starting point, a concise, structured overview of your brand, your product categories, and the pages you consider most important.

You can generate an llms.txt file in minutes. For a step-by-step breakdown of what to include and how to add it to Shopify correctly, we’ve documented the full process in llms.txt Setup Guide.

What we Do

Atomz simplifies the entire process.

• The Catalog Agent enriches your product data at scale, filling missing attributes, formatting variants, and optimizing descriptions.
• The Discovery Agent transforms your on-site search to work like ChatGPT’s, matching intent instead of keywords.

You can try it without talking to anyone. Start with the AI Visibility Audit and see exactly how your products appear in AI-driven shopping.

Bottom Line

AI shopping doesn’t reward marketing spend, it rewards clean, structured, and intent-rich product data. If your catalog isn’t readable by AI, your brand doesn’t exist in the new era of discovery.

Related:

• What is AIO?
• Why 89% of Product Pages Are Invisible to GPTs