Your on-line retailer ought to make it easy for purchasers to search out and purchase the merchandise they need. As extra folks use AI to assist them store, it’s necessary to provide AI purchasing brokers sufficient clear data to allow them to present your merchandise to potential consumers.
Getting your merchandise beneficial by AI isn’t about having an enormous model or spending so much on adverts. AI assistants desire shops that make issues simple for them. If you happen to present clear, structured data, you’ve gotten a greater probability of reaching buyers.
Let’s take a look at Reply Engine Optimization (AEO), which suggests organising your retailer so AI instruments can simply learn and suggest your merchandise.
If somebody asks ChatGPT for a “forged iron skillet,” the AI creates a listing of choices. To do that, it checks web sites for data that matches the patron’s request. In case your retailer is on that record, you’re reaching somebody who’s able to make a purchase order.
AI fashions ignore your web site’s design and focus in your knowledge, however they don’t deal with all content material the identical manner. There’s a form of “confidence hierarchy,” so the place you place your product particulars impacts whether or not AI brokers can use them.
- Structured knowledge contains issues like schema markup, Service provider Heart feeds, and product knowledge fields. This data is made for machines to learn immediately. For instance, a Product schema subject that claims “suitable with: induction” helps AI brokers match your product to somebody trying to find a cast-iron skillet.
- Structured content material is data that’s organized in a manner that’s simple for AI to know, like spec tables, FAQ sections, or a “Supplies and care” part with bullet factors. It’s a lot simpler for brokers to learn a transparent desk than to search out particulars hidden in a paragraph.
- Unstructured advertising copy is the kind of data AI brokers belief the least, so they may ignore it. For instance, should you write “Constructed to final generations in any kitchen,” the agent has to guess what which means and doubtless received’t match it to an induction-compatible skillet. As a substitute, use a transparent spec like: “Suitable with gasoline, electrical, and induction cooktops.”
Right here’s an instance exhibiting the distinction between a daily advertising description and one which’s structured for AEO.
| Earlier than | After |
| The Foundry No.10 is our most beloved piece of cookware. Made with care and constructed to final generations, it’s the proper addition to any kitchen. Whether or not you’re searing steaks, baking cornbread, or slow-cooking a Sunday stew, the Foundry No.10 delivers the efficiency residence cooks {and professional} cooks depend on. | #H2 The Foundry No. 10 12-inch cast-iron skillet
The Foundry No. 10 is designed for stovetop searing, oven roasting, and campfire cooking. – Diameter: 12 inches (10-inch cooking floor) |
The primary model has no matchable attributes, whereas the second has 8. If a consumer asks for a “pre-seasoned 12-inch forged iron skillet suitable with induction,” the second model matches on 3 factors, however the first doesn’t match in any respect.
Ideas for writing product descriptions
These suggestions can actually assist once you’re writing product descriptions:
- Identify the use case. “Designed for high-heat stovetop searing and oven-to-table cooking” fairly than “Constructed for the fashionable kitchen.”
- Embody unfavourable qualifiers. “Not beneficial for glass-top stoves” and “Not appropriate for acidic meals in the course of the seasoning interval” assist brokers exclude your product from queries the place it’s a nasty match.
- Specify compatibility exactly, like “suitable with gasoline, electrical, and induction cooktops.” “Not suitable with glass-top stoves” offers an agent clear knowledge. “Works with most cooktops” makes it guess.
- Point out who the product is for. For instance, say it’s designed for residence cooks switching from non-stick pans who need higher warmth retention for searing. Extra buyers now inform AI assistants issues like “I’m a newbie cook dinner,” “I’ve an induction cooktop,” or “I want one thing oven-safe.” In case your web page names its viewers, it offers brokers extra data to match with these requests.
- The order issues. Begin with the important thing attributes, then share the story. AI brokers learn the highest of your description first, whereas people who find themselves will preserve studying for extra particulars.
AI brokers take a look at your whole retailer. Listed below are some necessary areas to give attention to:
1. Class pages
Many class pages solely present product grids and don’t embody useful textual content. Including a brief paragraph on the prime that solutions a query like “What to search for in a forged iron skillet” offers AI a abstract of what you provide.
In WooCommerce, you’ll be able to add this in WP Admin underneath Merchandise → Classes, after which edit the Class description. It doesn’t must be lengthy — only a brief paragraph about use circumstances, key specs, and who the class is for.
2. Steadily Requested Query blocks
If you happen to can’t match all of the product particulars into the principle description, add FAQ blocks on the backside of the web page. For a cast-iron skillet, you would embody questions like “Is that this skillet suitable with induction cooktops?” or “How do I season it for the primary time?”
3. Coverage pages
Return insurance policies, delivery occasions, and warranties are necessary belief indicators for AI instruments. As a substitute of hiding your phrases in lengthy authorized paperwork, use clear labels and precise numbers, like “30-day return coverage” or “ships inside 2 enterprise days.”
4. Add an llms.txt file
Make a file known as llms.txt and put it in your web site’s root listing at yourdomain.com/llms.txt. This plain Markdown file offers AI brokers a abstract of what your retailer sells and the place to search out your most necessary pages. llms.txt helps sure AI instruments shortly perceive your corporation by emphasizing pertinent classes and pages, making it simpler for them to match your retailer to shopper queries.
Presently, Anthropic and Perplexity help studying llms.txt, however Google doesn’t, so its advantages are restricted to these AI platforms for now. Whereas there isn’t any direct proof but that including llms.txt will routinely enhance how typically your retailer is beneficial by AIs, it’s a easy approach to set up and make clear your data for techniques that use it.
Right here’s an instance of what the Markdown file ought to seem like:
# Foundry Kitchen Co.
On-line retailer specializing in cast-iron cookware, carbon metal pans, and cooking equipment for residence cooks {and professional} kitchens.## Key pages
- [Shop all cast-iron skillets](https://instance.com/cast-iron-skillets/)
- [Carbon steel cookware](https://instance.com/carbon-steel/)
- [Seasoning and care guides](https://instance.com/care-guides/)
- [Shipping and returns](https://instance.com/delivery/)
- [About us](https://instance.com/about/)
Add the file to your root listing subsequent to robots.txt. In WooCommerce, you are able to do this shortly with FTP or a file supervisor.
If you happen to use Yoast search engine marketing or Rank Math, you don’t want FTP. Each added built-in llms.txt era in 2025, ranging from Yoast search engine marketing model 22.0 and Rank Math model 1.4.0. Be sure to are working no less than these variations to entry the function.
To test your model, go to the extensions web page in your WordPress dashboard. Activate llms.txt era within the dashboard, and it’ll create and replace the file for you.
Methods to inform if it’s working
In the intervening time, there isn’t one excellent dashboard for monitoring AI site visitors, so that you’ll have to do some handbook checking:
1. Verify your referral site visitors for AI sources
In GA4, go to Acquisition, then Site visitors acquisition, and filter Session supply by chat.openai.com, perplexity.ai, and gemini.google.com. You may see only some visits at first, so don’t get discouraged. Observe the numbers every month and see which product pages are getting visits.
2. Check it your self
Each month, sort a purchasing query into ChatGPT or Perplexity that ought to present your merchandise. Verify in case your retailer is beneficial, see which opponents seem, and notice the explanations the AI offers for its decisions.
3. Run common schema validation
Go to search.google.com/take a look at/rich-results, paste in a product web page URL, and test which schema varieties it finds, in the event that they’re legitimate, and if there are any errors or lacking fields. You can even use Google Search Console and look underneath Enhancements within the left menu. In case your schema is detected, you’ll see a Merchandise report exhibiting errors and warnings in your complete web site.
Your subsequent finest step is to choose your highest-traffic product pages and examine them via a machine’s eyes. If you happen to discover gaps the place technical particulars are lacking, rewrite them into a transparent bulleted record. You possibly can even have an LLM (massive language mannequin, equivalent to ChatGPT) learn via these pages and provides its personal suggestions, since they are going to be public.
Subsequent, take a look at your highest-traffic product pages as should you had been an AI. If you happen to discover lacking technical particulars, rewrite them as a transparent record. You can even let an LLM assessment these pages and counsel enhancements, for the reason that pages are public.
Start by reviewing your 10 most-visited product pages. For every, depend what number of matchable attributes it lists, equivalent to supplies, dimension, weight, use case, viewers, compatibility, and any unfavourable qualifiers. If there are fewer than 5, AI brokers could also be skipping that web page.
After you collect this data, plan to rewrite these product descriptions. Start along with your highest-traffic pages, test your AI referral sources after a month, and alter as wanted. Whenever you make adjustments, give attention to together with any lacking attributes equivalent to dimension, materials, compatibility, or beneficial use. Search for methods to make compatibility particulars extra particular or outline who the product is supposed for. This manner, each replace you make helps AI brokers extra successfully match your merchandise to buyers’ wants.
Feeling caught along with your ecommerce resolution? Let’s discuss.
Julia Callicrate leads Product Advertising at Woo, serving to world companies uncover new methods to scale their shops with the WooCommerce platform. A storyteller at coronary heart, Julia bridges the hole between merchandise and prospects. Previous to her work at Woo, Julia had spent over a decade as a product supervisor and marketer in healthcare, banking, and SaaS industries. She presently lives in Virginia along with her household. Julia additionally has two cats that at all times appear to pop up on her video conferencing.
