AI search is changing how people discover brands, but perhaps not in the way many expected.
Recent research from SimilarWeb found that brands recommended by ChatGPT are 2.5 times more likely to receive a website visit within seven days. The surprising part? Most of those visits don’t arrive through a direct AI referral. They come through branded searches on Google or Bing instead.
That tells us something important. AI isn’t replacing traditional search: it’s influencing the journey that leads people there.
Someone might ask ChatGPT for the best running shoes for marathon training or the most reliable espresso machine under £300. After receiving recommendations, they often head to Google to search for the brand by name, compare options, read reviews or visit the retailer directly before buying.
So while some informational searches are generating fewer clicks, the value of good content and technical SEO hasn’t disappeared. It’s simply shifted further down the funnel into branded searches, direct visits and more qualified traffic.
That’s why judging AI visibility by referral traffic alone misses the bigger picture. The brands succeeding today aren’t choosing between SEO and AI search. They’re structuring their websites to perform across both.
What AEO and GEO Actually Mean for a Product Page
Discussions around answer and generative engine optimisation can feel complicated, but remember: they’re not competing disciplines. They’re different outcomes of the same well-structured page.
Let’s simplify it by looking at a basic product page.
Imagine you’re selling wireless headphones.
A typical page might contain a hero image, a bullet-point specification list and a paragraph describing “premium sound quality” and “innovative design”. It technically answers the brief but doesn’t add much value to the potential customer.
A page designed for both traditional and AI search goes further. It answers questions buyers actually ask, like:
- Are these true wireless headphones?
- Do they support noise cancellation?
- How long does the battery last?
- Can I connect them to multiple devices?
- Are they suitable for running?
- What’s included in the box?
Alongside those answers, it presents structured specifications, comparison tables, delivery information, return policies, customer reviews and stock availability in a clear, crawlable format.
That’s where the relationship becomes simple:
- SEO earns the ranking.
- Answer engine optimisation helps your content become the direct answer.
- Generative engine optimisation increases the likelihood of your brand being referenced in AI generated responses.
What eCommerce Brands Need to Be Visible in AI Search
The biggest shift in search isn’t technical. It’s strategic.
Instead of thinking purely about keywords, we need to think about the intent behind every page we publish.
Structure Pages by Intent, Not Just Keywords
Every page exists to answer a different customer question.
A category page answers: “Show me the best options in this range.” That means it should do more than list products. It should explain the differences between categories, highlight buying considerations and help shoppers narrow their choices.
Product pages answer: “Is this right for me?” Don’t rely solely on specifications. Address common hesitations, explain who the product suits, cover compatibility, sizing or performance, and include trust-building details like delivery times and returns.
A buying guide answers: “Help me understand what to choose.” The strongest guides take a clear position rather than sitting on the fence. Explain why one material lasts longer, why one feature matters more than another or which option suits different budgets.
Comparison pages answer: “Which one should I buy?” This is where many retailers miss an opportunity. Generic statements such as “both are excellent choices” rarely get surfaced by AI systems. Honest side-by-side comparisons with strengths, weaknesses and recommendations are far more useful.
Finally, FAQs answer: “Can you solve this one specific concern?” The more precise the question and answer, the more likely it is to satisfy both search engines and AI models looking for concise information. Check in with your customer-facing teams to see what topics come up most frequently and use those answers to build your FAQ content.
Build on Strong Technical Foundations
Before worrying about AI visibility, make sure the basics are solid.
Your site should have:
- Clean URL structures.
- Logical internal linking.
- Fast loading speeds across desktop and mobile.
- Clear heading hierarchies.
- Structured data where appropriate.
- Product and category pages that can be crawled and indexed easily.
If Google struggles to understand your catalogue, AI systems relying on the same web signals will struggle too.
Why Trust Signals and Real Content Matter More Than Ever
The web is saturated with AI generated content.
Much of it targets keywords effectively enough to achieve temporary rankings, but it often lacks originality, expertise and genuine usefulness. As Google’s 2026 core updates continue to roll out, that kind of content is increasingly losing visibility.
The same pattern applies to AI search.
Models don’t simply reward whoever says something first. They favour content that appears credible, specific and trustworthy.
For ecommerce businesses, that means investing in information competitors can’t easily replicate. Include founder insights explaining why products were chosen. Reference customer feedback you’ve genuinely received. Share testing results, buying trends or specialist recommendations from your own experience.
Trust also comes from transparency. Publish clear policies. Use original photography instead of supplier images where possible. Display authentic reviews and comparison tables that help shoppers make decisions rather than simply persuading them to buy.
We’ve found that as AI generated content becomes easier to produce, genuinely useful human expertise becomes even more valuable.
Get Found Beyond Your Own Website
Your website is no longer the only place AI systems learn about your brand.
Large language models (LLMs) regularly surface information from review sites, buying guides, comparison articles, forums and community discussions alongside your own content.
That’s why brand mention gap analysis is becoming increasingly important.
Instead of focusing solely on backlinks, ask where competitors are being recommended while your brand is absent.
Are they featured in buying guides that don’t mention you? Are Reddit users discussing alternatives but overlooking your products? Are review platforms dominated by competitors with richer customer feedback?
Closing those gaps often means practical work rather than technical SEO.
Encourage customers to leave detailed reviews instead of simple star ratings. Build relationships with publishers creating comparison content. Participate where appropriate in relevant communities. Strengthen your presence across trusted review platforms.
It’s also worth tracking prompts rather than only keywords. People ask AI systems conversational questions, and those prompts vary significantly across different stages of the buying journey.
Own the Moment Someone Searches for Your Brand
Remember that SimilarWeb finding: AI recommendations frequently lead users back to traditional search.
When that happens, your branded search presence needs to do the heavy lifting.
Ask yourself:
- Do we own the top organic position for our own brand name?
- Are competitors bidding on our branded keywords?
- Do our review profiles inspire confidence?
- Are our sitelinks useful and up to date?
- Is our Google Business Profile complete?
- Do our product and category pages appear prominently for brand plus product searches?
If the answer to any of those questions is no, AI visibility alone won’t convert into business results.
The recommendation is only the beginning. Your branded search experience still has to close the deal.
Where This Leaves eCommerce Brands
The retailers performing best across Google, AI Overviews and generative search are building websites with strong technical foundations, structuring pages around user intent, investing in original expertise and reinforcing every claim with genuine trust signals. They’re also making sure their brands are visible beyond their own domains, because that’s increasingly where recommendations begin.
The relationship between SEO and GEO isn’t competitive. Nor is answer engine optimisation something separate to bolt on afterwards. Strong pages naturally support all three.
At TH3, we build ecommerce websites with that philosophy from day one. By combining search visibility, usability and conversion focused design, we help brands perform across both traditional and AI driven search.
If your online store needs to work harder wherever customers discover you, we’d love to help. Get in touch today.
Research:
- Adam Landis (2026). 5 AI Search Findings Every Enterprise Marketer Needs to Know. Search Engine Journal.
- Jacob Poushter, Moira Fagan and Manolo Corichi (2025). How People Around the World View AI. Pew Research Center.
- Malte Landwehr (2026). What Matters In An AI Prompt? Intent or Keywords? Search Engine Journal.
- Matt G. Southern (2026). AI Chatbot Use Hits 49%, But Skepticism Stays High. Search Engine Journal.
- Matt G. Southern (2026). AI-Recommended Brands Saw 2.5x More Site Visits: SimilarWeb. Search Engine Journal.
- Tom Wells (2026). A beginner’s guide to brand mention gap analysis in AI search. Peec AI.