AI Can Now Recommend Your Products. But Only If It Understands Them.

Your Shopify store is already inside ChatGPT, Copilot, Google's AI Mode, and Perplexity. Shopify flipped that switch for millions of merchants in March. You didn't have to install anything. Your products are discoverable in AI conversations by default.

But discoverable and recommended are two different things.

When someone asks ChatGPT "what's the best moisturizer for dry skin under $40," the AI doesn't just pick randomly from every moisturizer in the Shopify Catalog. It reads your product data, tries to understand what you sell, who it's for, and whether it matches what the person is asking for. If your data is clear and specific, you have a shot. If your data is vague, incomplete, or written for humans browsing a pretty product page rather than an AI trying to categorize what you sell, you get passed over.

It's about whether the information in your Shopify admin accurately and completely describes what you're selling. Most stores have gaps.

Your product titles are doing more work than they used to

A product title like "The Luna" tells a human nothing and tells an AI even less. "Luna Face Moisturizer - Hydrating Cream for Dry Skin - 2oz" tells both of them exactly what the product is.

AI platforms parse your product titles to understand category, product type, key attributes, and use case. If your titles are brand-forward and description-light (the way a lot of DTC brands style them), the AI has to guess what you sell based on other signals. Sometimes it guesses right. Often it doesn't, and your product gets skipped in favor of one whose title actually says what it is.

This doesn't mean your titles need to be ugly keyword strings. But they need to include what the product actually is. "The Luna" can become "The Luna | Hydrating Face Cream for Dry & Sensitive Skin" and still look good on your storefront while being readable by AI.

Go through your top 20 products. If someone who's never heard of your brand read just the title, would they know what the product is? If not, add the missing context.

Descriptions need to answer questions, not just sell

Most product descriptions are written to convince someone who's already looking at the product page. They set a mood. They use evocative language. They talk about the brand story.

AI doesn't care about your brand story when it's deciding whether to recommend your product to someone. It's looking for specific information: what is this product made of, what is it for, who is it for, what size/weight/volume is it, how is it different from similar products.

Compare these two descriptions:

"Crafted with care using only the finest natural ingredients, our signature moisturizer brings a touch of luxury to your daily routine."

"A lightweight daily face moisturizer with hyaluronic acid and ceramides, designed for dry and sensitive skin. Fragrance-free, non-comedogenic. 2oz pump bottle. Apply morning and evening after cleansing."

The first one sounds nice on a product page. The second one gives an AI everything it needs to match this product to a customer asking for "fragrance-free moisturizer for sensitive skin." You can have both. Keep your brand voice in the description, but make sure the specific, factual product information is in there too. Ingredients, materials, dimensions, use case, who it's for, what makes it different. If someone asked you "what is this and why should I buy it" in a conversation, your description should contain everything you'd say.

Variants and attributes need to be complete

If you sell a t-shirt in five colors and three sizes but only the default variant has a full description and proper images, the AI can only work with that one variant. The others show up as incomplete data.

Make sure every variant has its own image, accurate inventory, correct pricing, and any relevant attributes filled in. Shopify's product data structure already supports this, but a lot of merchants only fill out the default and leave the rest sparse.

This also matters for how AI handles comparison queries. If someone asks "what are the best black running shoes under $100" and your shoe has a black variant but it doesn't have its own image or the color attribute isn't properly set, the AI might not connect it to that query.

Images need alt text. Yes, really.

Alt text on images has been an SEO best practice forever, and most merchants still skip it. For AI discovery, it matters even more. AI platforms can analyze images to some degree, but they rely heavily on alt text to understand what's in the photo.

"IMG_4392.jpg" tells AI nothing. "Luna hydrating face cream 2oz pump bottle on marble countertop" tells it exactly what it's looking at. It takes about 10 seconds per image to write, and most merchants have never done it for a single product in their store.

Your store policies are content now

Return policies, shipping information, FAQs, about pages. AI platforms read all of it. When someone asks ChatGPT "does this brand offer free returns," the AI looks for that information on your site. If your return policy is a generic template you haven't touched since you set up the store, that's what the AI has to work with.

Shopify added a Knowledge Base feature in the admin specifically for this. It lets you provide structured brand and policy information that AI platforms can access directly. If you haven't touched it yet, it's worth spending 20 minutes filling in accurate returns, shipping, and brand information.

None of this is new advice

Everything that makes your product data better for AI also makes it better for Google, for your own site search, for customers browsing your store, and for any other channel you sell on. Writing clear product titles, complete descriptions, accurate variant data, and real alt text has always been good practice. AI just raised the stakes because now there's a discovery channel where data quality is the whole game. You can't buy your way in with ads. You can't compensate with backlinks. The product data is either clear enough for AI to understand or it isn't.

Merchants who've already been thorough with their product information are going to benefit from this shift without lifting a finger. Everyone else has some catching up to do.

If you're not sure where your product data stands, we do store audits that include product data review. We've been looking at this stuff since 2014, and the shift toward AI-readable data is the biggest change in what "good product data" means since Google Shopping.