A shopper is about to buy running shoes. But before they hit Google, before they browse Amazon, they do something that's becoming increasingly common.
They ask ChatGPT: "What's the best running shoe for flat feet under $150?"
ChatGPT gives them three recommendations. With reasons. One of those recommendations is your competitor.
The shopper clicks through to your competitor's site. Reads about the product. Buys it.
You never knew this customer existed. You never had a chance to compete for them. They bought based on AI's recommendation before they ever saw your product.
This is happening thousands of times a day across every product category.
Shopping behavior is quietly changing
The old e-commerce discovery funnel: customer searches Google, sees your ads (you paid for that click), lands on a comparison site, eventually finds your product, maybe converts.
The new reality: customer asks AI a specific question about what they need, gets a recommendation they trust, goes directly to the recommended product, buys.
The new path is shorter. More trust-based. Lower friction. And if you're not in the AI recommendation, you're not in the consideration set at all.
This isn't about replacing Google or Amazon. It's about a growing segment of shoppers who start their purchase journey by asking AI for advice. And that segment is growing fast.
The economics of e-commerce AI visibility
You know your acquisition costs. Google Shopping CPCs that keep climbing. Social ad costs that erode margins. Amazon fees that make profitability challenging.
AI visibility is fundamentally different. There's no cost per click. No bidding war. No platform taking a cut of every sale.
When AI recommends your product, the shopper comes directly to you with pre-qualified intent. They're not browsing. They asked a specific question and got your product as the answer. Conversion rates are higher because trust is already established.
Build the foundation for AI recommendations once, and it keeps working. Unlike ads where you pay for every visitor, AI visibility compounds.
Why your products are invisible
AI can only recommend products it knows about and can differentiate. Most e-commerce brands make both of those difficult.
Your product descriptions are thin. "Great running shoe. Comfortable. Durable." That describes every running shoe. AI has no way to know when your shoe is the right answer for a specific question.
You haven't created content that helps AI understand use cases. "Best for flat feet" or "ideal for marathon training" or "designed for wide feet". Without this context, AI doesn't know which questions your products answer.
Your review presence is weak or scattered. AI weighs social proof heavily. If you don't have meaningful reviews on your site and on third-party platforms, you lack the credibility signals AI looks for.
You're not invisible because your products are bad. You're invisible because you haven't given AI the information it needs to recommend you.
What drives e-commerce AI visibility
Rich, specific product information.
"Running shoe" is a category. "Stability running shoe with 8mm drop designed for overpronators" is a match for a specific question.
Go through your product descriptions. For each product, ask: what specific questions does this product answer? Then make sure that information is clearly stated.
Use case information matters more than you think. "Best for daily training", "ideal for trail running in wet conditions", "designed for runners over 200 lbs". This is the context AI needs to make recommendations.
Content that positions you as the category expert.
Buying guides. "How to choose running shoes for your foot type." Product comparisons. "Trail shoes vs road shoes: which do you need?" Educational content. "Understanding shoe drop and why it matters."
This content does two things. It helps AI understand your products in context. And it positions your brand as the authority worth recommending.
Brands that only have product pages are leaving money on the table. The brands winning AI recommendations have content libraries that help AI understand the entire category.
Review presence AI can trust.
Reviews on your site are good. Reviews on third-party platforms are better. Coverage in product review publications is best.
AI synthesizes all of this. When recommending "best running shoe for flat feet", it weighs which products have reviews specifically mentioning flat feet performance.
Don't just collect reviews. Encourage customers to mention specific use cases. "These were perfect for my flat feet" is more valuable than "great shoes" for AI visibility.
The prompts that drive buying decisions
Focus on prompts where someone is ready to buy.
Product-specific: "Best [product type] for [use case]" or "recommended [product] for [specific need]". These are people with intent and specificity.
Problem-solution: "What helps with [problem your product solves]" or "product for [specific need]". These are people looking for answers you can provide.
Comparison: "[Your brand] vs [competitor]" or "[competitor] alternatives". These are people actively evaluating and potentially winnable.
Category: "Best [category] brands" or "top [category] products". These are people starting their research.
Track all of these. But prioritize the ones with clear buying intent.
Building e-commerce AI visibility systematically
Start with your top products. Not your entire catalog. The products that drive revenue and have clear differentiation.
Audit their visibility. Sign up for Mentionable. Track prompts for each product and your category. See where you're being recommended and where you're not.
Enhance product content. Add use case information. Add specific details about who the product is best for. Make it easy for AI to understand when to recommend each product.
Create category content. Buying guides, comparisons, educational resources. Content that helps AI understand your products in context.
Build review presence. On your site, on third-party platforms, through product review coverage. The social proof that AI weighs in recommendations.
Monitor and improve. Track visibility changes. Watch when competitors gain or lose recommendations. Fill gaps. Double down on what works.
The brands that get this are pulling ahead
While most e-commerce brands fight over the same Google Shopping clicks and Amazon listings, a small number are building AI visibility systematically.
They're getting recommended for high-intent queries. They're capturing customers their competitors don't even know exist. They're building a sustainable discovery channel that compounds instead of requiring constant ad spend.
The window is open. Most brands aren't thinking about this yet. By the time they catch on, the brands building AI visibility now will have an entrenched advantage.
Your competitors are being recommended somewhere. Make sure you are too.
Start tracking your e-commerce AI visibility today.