What is different about stores
An online store asks AI assistants a different kind of question from a local business. A person looking for a plumber wants a name. A person shopping wants to compare. "Best running shoes for flat feet," "is this blender worth the money" and "what is a good gift for a new gardener" are shopping questions. The answer is usually a short list of products, sometimes with the shops that sell them.
That changes what the assistant needs to read. It needs accurate facts about products, honest opinion about how they perform, and clear reasoning about which suits whom. A store that supplies those is easy to use. A store that supplies only a photograph and a price makes the assistant look elsewhere for the story.
Two definitions first. An LLM is a large language model, the kind of software behind ChatGPT, Claude and Gemini. GEO, generative engine optimization, means making your content and reputation easy for those systems to use. AEO, answer engine optimization, is the same idea aimed at direct answers. You will see all three used loosely.
The ordinary ecommerce work still applies, including clean category pages and fast loading. Our guide to AI search optimization for ecommerce on the playbook side covers the store mechanics in depth. This page focuses on what is new, and our overview of hiring out the work covers how a team could take it off your hands.
Tier one: product data an assistant can trust
Product data is the cheapest tier and the one that blocks the others. If a machine cannot read your products correctly, nothing else helps.
Complete, plain descriptions. State what the product is, what it is made of, its size, its weight, what it works with, and who it suits. Skip adjectives that carry no fact. "Premium, high quality" says nothing. "Stainless steel, 24 ounces, dishwasher safe" says three things.
Consistent names and variants. The same product should have the same name everywhere, and each size or color should be clearly labeled. Confusing variants lead to wrong answers about price or availability.
Structured data. Schema markup tells machines the price, availability, brand and rating in a standard format. Most store platforms add some by default. Check that it is accurate and that nothing contradicts what the page shows.
Readable pages. Key facts should be in the page text, not locked in images or loaded only after scripts run. Open a product page with scripts off and see what remains.
Honest availability and shipping. Say where you ship, how long it takes and what returns look like. Shoppers ask assistants these questions, and an assistant cannot recommend a store whose policy it cannot find.
None of this is glamorous, and all of it is binary. Fix it first.
Tier two: reviews on products, not just on the store
For stores, reviews work at two levels. There are reviews of the store, about service, shipping and returns. And there are reviews of each product, about how it performs. Assistants answering shopping questions lean hard on the second kind.
A product with no reviews is a product with no independent opinion. A product with fifty reviews that say "great" is only a little better. What helps is specific detail: "fits a size ten foot with a wide toe box," "kept my coffee hot for eight hours," "the lid cracked after three months." That detail lets an assistant match the product to a buyer's question, and be honest about trade-offs.
Ask buyers for it. A follow-up message a week or two after delivery, with a direct link and a question such as "how did you use it, and what stood out," produces better reviews than a generic request. Do not write reviews for customers and do not reward positive ones. Our page on reviews and AI recommendations covers the asking and the pitfalls.
Show reviews on the product page as readable text, not only as a widget that loads late. Reply to critical ones calmly. An honest mix of praise and complaint is more believable than a wall of five stars.
Also collect store-level reviews on third-party sites. Those are independent evidence about you as a seller.
Tier three: comparison and buying guide content
Shopping questions are comparisons in disguise. "Which is better for a small kitchen" and "what is the difference between these two models" want a reasoned answer, and assistants build one from pages that reason clearly.
If your store sells the products, you are well placed to write that content, because you know the differences. Useful pieces include:
- A buying guide for each main category, which explains what to look for and what to ignore.
- Side-by-side comparisons of products you stock, with honest trade-offs.
- Answers to the questions that come before buying, such as sizing, compatibility and care.
- Plain explanations of terms shoppers do not know.
The key word is honest. A comparison that always crowns your most expensive product reads as a sales page and is quoted less. A guide that says "choose the cheaper one if you only use it twice a year" earns trust, and trust is what gets quoted. Our playbook page on comparison pages for ecommerce shows how to build them.
Start each section with a one-sentence answer. Assistants often lift one passage, and a clear first sentence is the one most likely to be taken. Keep the claims specific and the conditions attached.
Tier four: marketplace listings and outside mentions
For stores, the outside evidence is wider than for a local business. It includes places that sell your products, places that review them and places where people talk about them.
Marketplaces. If you sell on one or more large marketplaces, your listings there are read by assistants. Keep the title, description and specifications accurate and consistent with your own site. Contradictions between the two make a product look unreliable.
App stores and platform directories. If you sell software, an app, or something that connects to a platform, the store listing is a major source. Complete every field, keep screenshots current and answer the reviews.
Independent review sites and guides. Niche sites that test or compare products in your category are often cited. Send samples where honest testing is the norm, and let the reviewer say what they find.
Forums and communities. Hobby and enthusiast communities discuss products candidly. Take part honestly, as described in Reddit and AI search, and never fake it.
Press and creators. A mention in a relevant publication or by a trusted creator is another independent voice.
Pick the few places that matter in your category and do them well. Hundreds of thin listings help less than three good ones.
What stays the same for a store
None of this replaces ordinary ecommerce SEO. People still search and click, and many assistants read pages that already rank. The base is the same.
Category pages that explain what you sell, product pages that load quickly, clean navigation, working internal links and a sound technical setup all still matter. So does avoiding duplicate or thin content, where hundreds of near-identical product pages dilute each other. Our AI SEO for online stores guide goes through the store-side fundamentals.
Do not dismantle what works. Add to it. A store with strong traditional foundations and no outside voices is missing half the picture. A store with plenty of buzz and unreadable product pages is missing the other half.
It also helps to keep the commercial side honest. Assistants answering a shopping question may name a product without sending anyone to your shop that day. A shopper may then search your store by name, or buy through a marketplace. Judge the effect with that in mind, and look at branded searches and overall sales as well as referral clicks.
Check that AI crawlers can actually reach your store
A surprising number of stores block machines by accident. It is worth ten minutes.
Open your robots file, found at /robots.txt, and read it. See whether broad rules block crawlers you want to allow. Our glossary entry on robots.txt explains the format. Decide on purpose which crawlers get in.
Check whether a security or bot protection service challenges automated visitors. Many online stores run one, and some challenge every crawler without telling you. Ask whoever manages your hosting or platform.
Check that product pages show their main content without scripts. Some themes load descriptions and reviews late. A crawler that does not run scripts sees an empty page.
Check your sitemap lists the products you sell now, not discontinued ones. A stale sitemap sends crawlers to dead pages.
If anything is off, fix it before anything else. Great content behind a locked door is invisible.
How a store should measure progress
Standard analytics will not show you whether an assistant recommended your products. You need a small, steady habit.
Write 20 real shopper questions. Mix "best X for Y," comparisons between two products and questions about your category generally. Use the words buyers use.
Ask them in two or three assistants, monthly, in a clean session. Note which products and which stores are named and how they are described.
Keep the questions fixed. Changing them erases the trend.
Watch the side effects. Branded search volume, direct visits and marketplace sales may rise before referral clicks do.
An AI visibility checker gives a quick first reading. After that, your own dated notes are enough to see direction. Keep expectations steady, since different assistants move on different timelines.
An illustrative example, not a real store
A made-up example shows how the tiers fit together. It is invented and labeled as such.
Imagine a small store that sells ceramic coffee equipment. A shopper asks an assistant, "What is a good pour-over setup for someone who has never made pour-over?" The assistant needs to name a few products and perhaps a few places to buy them.
The store has a product page for a dripper. The description says "beautiful, handcrafted, perfect for coffee lovers." That tells the assistant nothing it can use. A better page would say the dripper is ceramic, holds one to two cups, fits a standard size of paper filter and suits a beginner because it is forgiving of pouring speed. Those are four facts a system can match against the shopper's question.
The page has two reviews, both saying "love it." Better reviews would say "my first pour-over, it took two tries to get the pour right but the cup was clean." That is a believable detail from a real beginner.
The store has a short guide titled "Choosing your first pour-over setup," with an honest note that a cheaper plastic dripper works fine for someone unsure. That page is quotable because it answers the shopper's exact question and does not push the dearest product.
Finally, an independent coffee guide mentions the dripper, and a hobby forum thread recommends the store for beginners. Now the claim on the page and the voices outside it agree. That is the picture to aim for.
A word on platforms and apps
Whatever you sell on, the same principles apply, but the practical steps differ a little.
On Shopify and similar hosted platforms, themes and apps add structured data and load reviews through widgets. Check what each one actually outputs. Some review apps load their content late through scripts, so the reviews are invisible to a crawler that does not run them. Look at the page source, not just the screen.
On WooCommerce and other WordPress setups, plugins add flexibility and also risk. Several plugins can output overlapping or conflicting structured data. If two plugins both claim to describe the same product, a machine may see contradictions.
On any platform, avoid description text that is copied from a manufacturer. If dozens of stores publish the same words, an assistant has no reason to prefer yours, and you gain nothing from the repetition. Rewrite descriptions with your own knowledge of the product, even if only for your top sellers first.
If you sell through a marketplace as well as your own site, keep the facts identical. A product that is 12 ounces on one page and 16 on another looks unreliable. The store-side fundamentals are covered in our ecommerce guide to AI search.
How RunOctopus handles this for stores
For a store, the heaviest part is writing and publishing the buying guides, comparisons and answers that assistants can quote. That is the part RunOctopus takes off your hands.
RunOctopus is a done-for-you service. Its AI, Ollie, researches a business, then writes and publishes pages directly on the business's own website. A team plans, writes, reviews and publishes alongside Ollie. It works with Shopify, WordPress, WooCommerce and Wix. There is nothing to install, nothing to approve, nothing to upload and nothing to schedule, and pages go live on their own.
The first week brings 8 long-form articles, 6 pages and a custom interactive tool built for the business's niche. After that it is 175+ pieces of content a month, written, published and linked. RunOctopus also reports on where ChatGPT, Perplexity, Claude and Gemini name the business. The 90-day promise is more visibility on Google and in AI answers within 90 days, measured against the 90 days before joining, or every dollar back.
For scale, All Angles Creatures, the reptile supply store where RunOctopus started, went from 0 to 4,500+ Google clicks a month in five months (Google Search Console, 28 days to Sep 29, 2026).
You can see the plan before deciding anything. Paste your address into the free site read and Ollie reads the site and shows the plan. No account, no call.