Your Customers Are Already Shopping Through AI. Is Your Store Showing Up?

Curtis Keller
Apr 7
11 min read

TL;DR

AI-powered search — ChatGPT, Google AI Overviews, Perplexity, Gemini — is no longer a trend to watch. It's already where your customers are making purchasing decisions. Traffic from AI platforms to retail websites grew 693% during the 2025 holiday season. Those visitors convert at 14.2% compared to Google organic's 2.8%. The brands getting found are not the ones ranking #1 on Google — 80% of URLs cited by AI engines don't even rank in Google's top 100. This is a different game. Here's how to play it.

Something Changed and Most Brands Missed It

Think about how you personally search for things when you actually want to buy something. If you're looking for the best stim-free pre-workout, the cleanest protein powder, or a running shoe for trail use in wet conditions — are you typing that into Google and clicking through 12 blue links?

Or are you typing it into ChatGPT and getting a direct recommendation in 10 seconds?

If you're doing the latter, so are your customers.

In July 2025, Adobe surveyed 1,000 consumers. 770 of them reported using ChatGPT as a search engine. Not as a writing tool. Not as a chatbot. As a search engine — specifically to find products and make purchase decisions.

Gartner projected a 25% drop in overall search engine volume by 2026 as users shift toward AI tools. That drop is happening now, in real time, in your category.

For e-commerce brands, the stakes are different from any previous shift in marketing. SEO changes have historically been about ranking — fighting for position on a list. AI search is different. AI doesn't give your customers a list. It gives them one answer. Or maybe three. The brands in that answer win. Everyone else is invisible.

This is not something to plan for next year. This is already your competitive landscape.

What Is GEO and Why Is It Different From SEO?

You've heard of SEO. You probably have some version of it running — keyword optimization, backlinks, blog content, page speed. Traditional SEO is about telling Google what your pages are about so it ranks them when someone searches.

GEO — Generative Engine Optimization — is the practice of making your brand and products easy for AI engines to find, understand, trust, and recommend.

The difference is not subtle. In traditional search, you're trying to rank. In AI search, you're trying to get cited. There's no page 2. There's no rank 6. There's just whether the AI mentions you or not when someone asks a question you should be the answer to.

Here's the stat that makes this concrete: according to Ahrefs research from August 2025, approximately 80% of URLs cited by AI platforms like ChatGPT, Perplexity, Copilot, and Google's AI Mode do not rank in Google's top 100 results for the same query.

Read that again. 80% of AI citations come from pages that traditional SEO would tell you don't matter.

This means two things. First, your current SEO rank is not protecting you in AI search. Second, it's possible to earn AI visibility without dominating traditional search — if you understand how these systems work.

How AI Engines Actually Decide What to Recommend

This is the part that most "AI SEO" content glosses over, but it's the part that actually matters for what you do next.

AI engines like ChatGPT, Gemini, and Perplexity are not running real-time searches every time someone asks a question. They're drawing on a combination of their training data (what they learned during training) and, increasingly, live web access and curated sources they're set up to trust.

When someone asks "what's the best protein powder for building muscle without bloating," the AI isn't ranking pages. It's constructing an answer based on what it understands about the topic — and it's citing the sources that gave it that understanding.

What earns that trust and citation comes down to a few consistent factors:

Clarity and structure. Pages with well-organized headings, clear definitions, and structured information are 2.8x more likely to be cited in AI search results. AI engines are essentially skimming your content the way a very smart reader would — and they favor content that's easy to extract useful answers from.
Third-party mentions and reviews. LLMs (the technology behind these AI tools) are trained heavily on content from Reddit, YouTube comments, review platforms, and editorial publications. If your brand is being talked about in those places — especially favorably — you have a far higher chance of being cited. Brand mentions across trusted sources now outweigh backlink profiles as a signal of credibility for AI systems.
Structured data (schema markup). This is technical, but it's not complicated. Schema markup is a standardized code that tells AI systems exactly what your content is — product name, price, availability, reviews, ingredients, use cases. Pages with complete, accurate schema markup are dramatically easier for AI to cite because the information is machine-readable and verified.
Content that reads like actual expertise. With the internet now flooded by AI-generated filler content, genuine expertise stands out sharply. AI engines are getting better at recognizing and favoring content that demonstrates real knowledge — first-person experience, specific claims, detailed explanations, and authentic customer reviews.
Authority of the page overall. This is where traditional SEO and GEO overlap. High-authority pages are still more likely to earn citations. But authority here includes your product review ratings, your presence on third-party platforms, and how consistently your brand appears across sources — not just your domain authority in a tool like Ahrefs.

The Platforms Your Customers Are Using (And What Each One Means for You)

Before you optimize, know the landscape.

ChatGPT holds 80% of the AI chatbot market share and is used by over 800 million people weekly. It increasingly has shopping-specific functionality, with users asking for product recommendations and using it to make purchasing decisions before ever visiting a brand's website. In February 2026, OpenAI launched an advertising pilot generating $100M in annualized revenue almost immediately — which tells you everything you need to know about where the commercial opportunity is heading.

Google AI Overviews now appear on 14% of shopping-related queries. For informational queries tied to purchasing — "best," "top," "recommended" — the AI Overview presence jumped from 5% to 83% in a single year. If you sell products in a category where people research before buying (which is most e-commerce), the top of Google's search results is now an AI-generated summary, not a ranked page. Your content either feeds that summary or it doesn't.

Perplexity is smaller but punches above its weight in purchase intent. It functions like a research engine — it synthesizes answers with citations, and its users tend to be high-intent and detail-oriented. An outdoor gear brand or supplement brand with thorough, well-sourced product content is exactly what Perplexity surfaces.

Google Gemini and Meta AI (integrated into Instagram, Facebook, and WhatsApp) round out the major platforms. Meta AI reaching 39% monthly usage is not a small number. It means product recommendations can now happen inside social conversations without a user ever leaving their feed.

The common thread: all of these platforms favor brands that have clear, authoritative, well-structured content and a visible presence across the web — not brands that have optimized a handful of landing pages for a few keywords.

What This Means for Your E-Commerce Store, Specifically

Let's make this concrete for a brand selling physical products — supplements, fitness equipment, activewear, health-focused consumer goods.

The Product Page Problem

Most e-commerce product pages are built for humans to skim, not for AI to extract. They have a headline, a short paragraph, a bullet list of features, a price, and a "Buy Now" button. That's it.

AI engines look at that page and struggle. There's no schema telling them what the product actually is. There's no FAQ section answering the questions buyers actually ask. There's no contextual information explaining what problem the product solves, who it's for, and how it compares to alternatives. There are no customer reviews rich enough to build trust signals.

The result: your product exists in your store, but not in the answer when someone asks an AI tool for a recommendation in your category.

The Content Gap

Most e-commerce brands have two modes: product pages and the occasional blog post. AI-optimized content requires more than that. It requires content that answers the questions your customers are asking at every stage of the decision process.

"What's the difference between whey isolate and whey concentrate?" — that's a question someone asks before buying protein powder. If your site answers it clearly and correctly, you've established relevance for the category before the purchase intent even crystallizes.

"What should I look for in a running shoe if I have high arches and run trails?" — that's a question your ideal customer is asking an AI tool right now. If your site has content that genuinely answers it, you're a candidate for the citation. If you only have product listings, you're not.

The Review and Trust Problem

AI engines treat reviews and third-party mentions as credibility signals. A product with 400 genuine customer reviews on your site, on Google, on Amazon, or discussed in Reddit threads is dramatically more likely to be recommended than a product with 12 reviews and nothing else.

This is one of the fastest and highest-leverage changes most e-commerce brands can make: a systematic, consistent approach to building review volume across multiple platforms.

The Practical Playbook: What to Actually Do

Here's what to work on, in order of impact, without needing a developer for most of it.

1. Audit and Complete Your Schema Markup

Schema markup is code that tells AI systems (and search engines) exactly what your pages contain. For e-commerce product pages, the key schema types are Product schema (name, description, price, availability, SKU, brand), Review schema (aggregated ratings and individual reviews), and FAQ schema (questions and answers on the page).

Most e-commerce platforms — Shopify, WooCommerce, BigCommerce, even Wix — have apps, plugins, or built-in tools that handle this without writing a line of code. If you don't know whether your product pages have schema markup, use Google's Rich Results Test (it's free) and paste in your product page URL. It'll tell you exactly what's there and what's missing.

This is not glamorous work. It is the highest-leverage technical change you can make for AI visibility right now.

2. Rewrite Your Product Descriptions for Clarity and Context

Most product descriptions are too thin for AI engines to work with. A two-sentence description with a bullet list of specs tells an AI very little about why someone should buy your product, who it's for, and what problem it solves.

Rewrite your product descriptions to include: what the product is in plain language, who it's designed for, what specific problems or goals it addresses, what makes it different from alternatives, and any relevant context about use cases or compatibility. Aim for at least 250–400 words of substantive content on core product pages. This is not filler — it's the information that AI engines extract when constructing recommendations.

For a fitness supplement brand, this means your creatine product page shouldn't just list "5g creatine monohydrate per serving." It should explain who benefits most from creatine, what the research shows about timing and dosage, what to look for in a quality product, and why yours specifically delivers on those criteria.

3. Build Out a Real FAQ Section on Product Pages and Key Category Pages

FAQ content is disproportionately cited in AI search results. When users ask questions, AI engines look for content that answers those exact questions — and FAQ-structured content with clear questions and direct answers is the easiest thing for an AI to extract and cite.

Think about every question a buyer asks before purchasing your product. Answers to those questions belong on your product pages. What are the ingredients? Is it third-party tested? Will it work if I have X condition or Y goal? How does it compare to the alternative? When will I see results?

FAQ schema (paired with FAQ content on the page) signals directly to AI systems: "This page answers specific questions — here they are."

4. Earn Third-Party Mentions Aggressively

The single biggest lever for AI visibility that most brands are ignoring is this: AI engines trust what other sources say about you more than what you say about yourself.

That means: getting reviewed by relevant content creators and bloggers, pursuing editorial coverage in your category (trade publications, health and fitness media, outdoor industry outlets), encouraging customers to post reviews and discussions on Reddit, participating in relevant subreddits as a brand (transparently), building a YouTube presence where people discuss your products, and ensuring your Google Business Profile and third-party retailer listings are complete and current.

90% of AI citations come from earned and owned media — not paid placements. Content marketing and PR are not dead. They're the primary input into AI visibility.

5. Clean Up Your Site Architecture

AI engines crawl your site the same way search engine bots do. If your product pages are buried four or five levels deep, important pages aren't getting indexed or understood fully. Good site architecture means your most important products are reachable in two or three clicks from your homepage, your category pages clearly define what's in them, and your internal linking connects related content in ways that make your site's expertise clear.

This also means your robots.txt file isn't accidentally blocking AI crawlers — which is a real and surprisingly common issue. If you're not sure, have someone check it.

6. Start Creating Content That Answers Buyer Questions

This is the medium-term play, but it compounds fast. A library of genuinely helpful content — buying guides, comparison articles, use-case explanations, ingredient explainers — makes your brand a primary source of information in your category, which AI engines then draw from when constructing answers.

For a supplement brand: "Everything You Need to Know About Pre-Workout Ingredients," "How to Choose a Protein Powder Based on Your Goal," "The Difference Between Creatine HCl and Creatine Monohydrate." These articles don't just generate organic traffic — they train AI engines to recognize your brand as a credible source in the category.

For a broader fitness or wellness brand: category guides, how-to content, and comparison articles are the content types most likely to be cited in AI Overviews and AI chatbot responses.

What Not to Do

A few things that won't help and will potentially hurt you:

Don't generate thin AI content to fill pages. AI engines are getting very good at identifying AI-generated filler. Generic, low-substance pages won't earn citations. Worse, a site full of shallow AI content signals to these systems that your brand isn't a credible source.

Don't just copy what's working for your competitors' SEO. As established, AI citation visibility doesn't correlate cleanly with traditional search ranking. Your competitor might rank #2 on Google and still never appear in a ChatGPT recommendation. Focus on the GEO fundamentals, not on mirroring a traditional SEO strategy.

Don't ignore your review presence. If you have a great product and almost no reviews, you're invisible to AI systems for recommendation purposes. Get a systematic process in place for requesting and collecting reviews — on your site, on Google, and on relevant third-party platforms.

Don't wait for this to "mature." The brands earning AI visibility right now are building compounding authority. The longer you wait to establish your presence in this space, the more ground you'll need to make up when the full transition arrives.

The Bottom Line for E-Commerce Brands

The buyer journey has changed. Someone who wants to buy a pre-workout supplement, a pair of trail running shoes, or a resistance band set is increasingly starting that process by asking an AI tool for a recommendation — not by running a Google search and clicking through links.

The decision about whether your brand appears in that recommendation is happening in the background, right now, based on how your website is structured, how much authoritative content you have, and how prominently your brand exists across the web.

This is not a future threat to prepare for. It is the current competitive landscape. The brands investing in GEO today are the ones who will own the recommendation when someone asks an AI tool for exactly what they sell.

The question isn't whether to optimize for AI search. The question is how far behind you want to be when you finally start.