Learn how to make your retailer readable to AI buying brokers

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 essential to provide AI buying brokers sufficient clear info to allow them to present your merchandise to potential patrons.

Getting your merchandise really helpful by AI isn’t about having an enormous model or spending lots on advertisements. AI assistants choose shops that make issues simple for them. For those who present clear, structured info, you could have a greater likelihood of reaching consumers.

Let’s take a look at Reply Engine Optimization (AEO), which suggests establishing your retailer so AI instruments can simply learn and suggest your merchandise.

If somebody asks ChatGPT for a “forged iron skillet,” the AI creates an inventory of choices. To do that, it checks web sites for info that matches the consumer’s request. In case your retailer is on that listing, you’re reaching somebody who’s able to make a purchase order.

AI fashions ignore your web site’s design and focus in your information, however they don’t deal with all content material the identical approach. There’s a form of “confidence hierarchy,” so the place you place your product particulars impacts whether or not AI brokers can use them.

1. Structured information consists of issues like schema markup, Service provider Middle feeds, and product information fields. This info is made for machines to learn immediately. For instance, a Product schema discipline that claims “suitable with: induction” helps AI brokers match your product to somebody trying to find a cast-iron skillet.
2. Structured content material is info that’s organized in a approach that’s simple for AI to grasp, 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.
3. Unstructured advertising and marketing copy is the kind of info AI brokers belief the least, so they may ignore it. For instance, in the event you write “Constructed to final generations in any kitchen,” the agent has to guess what which means and possibly gained’t match it to an induction-compatible skillet. As a substitute, use a transparent spec like: “Appropriate with fuel, electrical, and induction cooktops.”

Right here’s an instance displaying the distinction between a daily advertising and marketing description and one which’s structured for AEO.

The primary model has no matchable attributes, whereas the second has 8. If a client 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 while you’re writing product descriptions:

1. Identify the use case. “Designed for high-heat stovetop searing and oven-to-table cooking” moderately than “Constructed for the fashionable kitchen.”
2. Embody unfavourable qualifiers. “Not really helpful 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.
3. Specify compatibility exactlylike “suitable with fuel, electrical, and induction cooktops.” “Not suitable with glass-top stoves” provides an agent clear information. “Works with most cooktops” makes it guess.
4. Point out who the product is for. For instance, say it’s designed for house cooks switching from non-stick pans who need higher warmth retention for searing. Extra consumers now inform AI assistants issues like “I’m a newbie prepare dinner,” “I’ve an induction cooktop,” or “I want one thing oven-safe.” In case your web page names its viewers, it provides brokers extra info to match with these requests.
5. 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 complete retailer. Listed here are some essential areas to concentrate on:

1. Class pages

Many class pages solely present product grids and don’t embody useful textual content. Including a brief paragraph on the high that solutions a query like “What to search for in a forged iron skillet” provides AI a abstract of what you supply.

In WooCommerce, you may add this in WP Admin below Merchandise → Classesafter which edit the Class description. It doesn’t should be lengthy — only a quick paragraph about use instances, key specs, and who the class is for.

2. Often Requested Query blocks

For those who 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 instances, and warranties are essential belief indicators for AI instruments. As a substitute of hiding your phrases in lengthy authorized paperwork, use clear labels and actual numbers, like “30-day return coverage” or “ships inside 2 enterprise days.”

4. Add an llms.txt file

Make a file referred to as llms.txt and put it in your web site’s root listing at yourdomain.com/llms.txt. This plain Markdown file provides AI brokers a abstract of what your retailer sells and the place to search out your most essential pages. llms.txt helps sure AI instruments shortly perceive your online business by emphasizing pertinent classes and pages, making it simpler for them to match your retailer to shopper queries.

At the moment, Anthropic and Perplexity assist studying llms.txt, however Google doesn’t, so its advantages are restricted to these AI platforms for now. Whereas there isn’t a direct proof but that including llms.txt will routinely improve how usually your retailer is really helpful by AIs, it’s a easy solution to arrange and make clear your info for programs that use it.

Right here’s an instance of what the Markdown file ought to appear like:

# Foundry Kitchen Co.
On-line retailer specializing in cast-iron cookware, carbon metal pans, and cooking equipment for house 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.

For those who use Yoast web optimization or Rank Math, you don’t want FTP. Each added built-in llms.txt era in 2025, ranging from Yoast web optimization model 22.0 and Rank Math model 1.4.0. Be sure you are working at the very least these variations to entry the characteristic.

To verify 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.

Learn how to inform if it’s working

In the mean time, there isn’t one excellent dashboard for monitoring AI visitors, so that you’ll must do some guide checking:

1. Verify your referral visitors for AI sources

In GA4, go to Acquisitionthen Visitors acquisitionand filter Session supply by chat.openai.com, perplexity.ai, and gemini.google.com. You would possibly see just a few visits at first, so don’t get discouraged. Monitor the numbers every month and see which product pages are getting visits.

2. Check it your self

Each month, sort a buying query into ChatGPT or Perplexity that ought to present your merchandise. Verify in case your retailer is really helpful, see which rivals seem, and be aware the explanations the AI provides for its selections.

3. Run common schema validation

Go to go looking.google.com/take a look at/rich-results, paste in a product web page URL, and verify which schema sorts it finds, in the event that they’re legitimate, and if there are any errors or lacking fields. You may also use Google Search Console and look below Enhancements within the left menu. In case your schema is detected, you’ll see a Merchandise report displaying errors and warnings in your complete web site.

Your subsequent greatest step is to choose your highest-traffic product pages and think about them via a machine’s eyes. For those who discover gaps the place technical particulars are lacking, rewrite them into a transparent bulleted listing. You’ll be able to even have an LLM (giant 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 in the event you have been an AI. For those who discover lacking technical particulars, rewrite them as a transparent listing. You may also 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, measurement, 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 info, plan to rewrite these product descriptions. Start along with your highest-traffic pages, verify your AI referral sources after a month, and alter as wanted. Once you make adjustments, concentrate on together with any lacking attributes equivalent to measurement, materials, compatibility, or really helpful use. Search for methods to make compatibility particulars extra particular or outline who the product is supposed for. This fashion, each replace you make helps AI brokers extra successfully match your merchandise to consumers’ wants.

Julia Callicrate leads Product Advertising at Woo, serving to international 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 at the moment lives in Virginia together with her household. Julia additionally has two cats that at all times appear to pop up on her video conferencing.