AI Search Rewards Local Domains Over Global Brands in Key Markets

Local answers are beating global brands

The clearest lesson from the latest cross-market AI search analysis is uncomfortable for any agency built around a single global playbook: in key countries, the local domain often wins. Across 10 markets, the click-producing layer of AI search, the traffic that arrives after someone taps a citation or link inside an AI-generated answer, repeatedly favored useful local results over bigger international brands.

That matters because the study was not looking at vanity impressions. It examined about 87.6 million AI search visits and 57,696 domain-market entries, then tracked where the clicks actually went after the answer was shown. In that layer, Bol.com led Dutch ecommerce, MercadoLivre led in Brazil, Bahn.de led in Germany, and Lefrecce.it led in Italy, even when global giants such as Amazon or Booking.com were in the mix. The message is blunt: local relevance is not a side quest in AI search. In many markets, it is the main event.

Why AI search rewards usefulness, not just scale

This is not simply a story about brand size. It is a story about the answer being the most useful one for the query in that country. When a user needs route information, market-specific availability, or country-level product detail, the local domain often has the cleaner, more directly usable response, and AI systems appear to reward that utility.

The analysis also reminds agencies that AI search is not one uniform surface. It blends behavior across ChatGPT, Perplexity, and Google AI Mode, which do not behave identically. That is exactly why broad assumptions break down so quickly: a domain can look dominant on paper and still lose downstream clicks in the market where the query is most specific and the local answer is simply better.

The sector split changes the strategy

The market pattern is only half the warning. The other half is vertical concentration, which varies sharply by industry. In the sample, ecommerce captured 39.3 million AI clicks across 14,454 domain-market entries. Finance brought in 30.7 million clicks across 22,313 entries. Travel and tourism generated 17.6 million clicks across 20,929 entries.

Those numbers point in different strategic directions. Ecommerce is relatively concentrated, finance is much more distributed, and travel is fragmented. That means the same AI search framework will not work across all client types. A regional retailer, a financial infrastructure brand, and a local service company will not win visibility in the same way, because the mix of query intent, trust signals, and local utility changes by sector.

What agencies should change now

The practical response is not to chase every AI platform with the same template. It is to build a market-by-market system that treats each country as its own discovery environment.

A strong response includes:

• Country-specific content architecture, so the site answers the questions local users actually ask.
• Market-level schema, so machines can identify the right entity, product, route, or service in the right geography.
• Local entity signals, including language, location, and regional business details that reinforce relevance.
• Localized authority signals, because the strongest answer in one market may not be the strongest brand globally.
• Regional digital PR, so the brand is embedded in the local web ecosystem rather than floating above it.

This is the strategic shift agencies need to make for multinational clients: stop assuming that global authority will automatically carry into AI search. In many cases, local usability is the deciding factor.

Why measurement has to get more granular

The old habit of reporting one worldwide AI visibility number is becoming less useful by the month. The study covered the United States, United Kingdom, Spain, France, Germany, Italy, the Netherlands, Australia, Mexico, and Brazil, and that mix alone shows why country-level reporting matters. If one market is won by a local domain and another tilts toward a global brand, averaging the two hides the real story.

That is especially important because the dataset was built from click-producing traffic, not just answer exposure. Agencies need to know not only whether a client is mentioned inside AI results, but whether that mention produces a click in each market. The new benchmark is not “did we appear?” It is “did the local market choose us when the answer appeared?”

The traffic reality behind the hype

The broader referral picture makes the stakes even clearer. Similarweb reported that AI platforms generated over 1.13 billion referral visits in June 2025, up 357% from June 2024. At the same time, ChatGPT accounted for more than 80% of AI referrals to the top 1,000 domains in that sample, showing how concentrated the ecosystem still is even as it expands.

But search behavior is still punishingly selective. Pew Research Center found that Google users were less likely to click a traditional result when an AI summary appeared, with clicks dropping to 8% of searches with an AI summary from 15% without one. Pew also found that users very rarely clicked the sources cited inside the summaries themselves. That combination is why AI visibility is no longer just a branding issue. If the answer surface absorbs attention and the cited links draw little action, then winning the right local citation becomes a traffic strategy, not a cosmetic one.

Google has also expanded AI Overviews to more than 120 countries and territories and 11 languages, and its own help materials describe the feature as a way to provide a snapshot with links to dig deeper. As the feature spreads, agencies cannot afford to treat AI search as a distant experiment. The environments where local relevance matters are growing, not shrinking.

The new international SEO playbook

For multinational clients, the next phase of international SEO will be won by teams that think like local publishers and local operators, not just global brand managers. The winning move is not to build one perfect global page and hope it travels. It is to create country-specific answers, reinforce local entities, earn regional authority, and measure performance market by market.

That is the real warning in the data. In AI search, the biggest brand is not always the best answer, and the best answer is often the one that feels native to the market asking the question.