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Google answers questions about brands itself – why classic rankings are losing importance

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Published on: October 27, 2026 / Updated on: October 27, 2026 – Author: Konrad Wolfenstein

Google answers questions about brands itself – why classic rankings are losing importance

Google answers questions about brands itself – why classic rankings are losing importance – creative image on the topic, with AI: Xpert.Digital

Google's AI cites these sources – and classic top 10 rankings are often not enough

Brands in the AI ​​Age: Why official information and regional content are becoming more important

AI instead of clicks: Why companies need to remeasure their visibility

When people search for a brand on Google, they no longer just see its website and the classic search results. Increasingly, AI-generated responses summarize information, cite sources, and thus shape the first impression – even before users visit a company page. A study of 1,000 brand search terms each in the US and Germany reveals the varying frequency with which AI overviews appear and why good rankings alone no longer guarantee visibility. Google frequently cites pages that don't even appear in the organic top 10. ChatGPT also draws on different sources depending on the query: official information is used for specific facts, while external opinions gain weight for comparisons and recommendations. For companies, this means they must not only monitor their position in the search results but also the information and sources that AI systems are displaying about their brand.

Google answers brand-related questions itself – making traditional rankings a secondary consideration

Even if someone ranks number one on Google, they can still remain invisible in the AI ​​response.

The rules of the game for digital visibility are fundamentally changing. Anyone searching for a specific brand on Google no longer sees only the official website, company profiles, and traditional search results. Increasingly, an automatically generated AI overview intervenes – deciding which information and sources are noticed first.

An analysis of 1,000 brand-related search terms each in the US and Germany reveals the extent of this development. In October 2026, an AI overview appeared for an average of 82.5 percent of the US search queries analyzed. In Germany, the figure was significantly lower at 40.4 percent. Each search query was checked three times, with the German results fluctuating considerably more between individual queries.

AI is positioning itself between brand and user

For companies, this means that even with a clear search for their own name, direct contact with the user is no longer guaranteed. Google aggregates information about the brand before the searcher visits the company website – if they even visit it at all.

In Germany, an AI overview appeared for only 29.6 percent of the brand search terms examined across all three test runs. This shows that the AI ​​output not only depends on market, industry, and search volume, but can also change even for identical search queries.

This diminishes the significance of traditional monitoring of individual positions. A company can achieve excellent organic rankings yet barely appear in AI summaries. Conversely, pages that rank far down in traditional search results can be prominently highlighted by Google as sources.

Visibility arises beyond the top 10

The sources of the AI ​​Overviews often do not match the classic Google search results. In the US search queries examined, 62.2 percent of the pages for a brand cited by Google were not among the first ten organic results. In Germany, this figure was even higher at 68.5 percent.

The discrepancy is particularly pronounced for product pages. In US search queries, 92.6 percent of the cited product pages were outside the organic top 10. For "About Us" pages, this figure was 84.6 percent. Only for homepages was the overlap with the classic top results significantly greater.

Google's AI-driven response apparently doesn't just evaluate which page ranks highest overall. Rather, it focuses on which individual subpage best supports a specific statement about a product, service, price, or company. A strong homepage alone is therefore no longer sufficient.

Companies need precise product and service pages, easily understandable company information, and clearly structured answers to typical customer questions. Every important statement about the brand should be clearly substantiated on a suitable, publicly accessible page.

 

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The new era of digital visibility

Google prioritizes sources

The way sources are presented is also not consistent. On October 15, 2026, Google announced that it would more frequently include links directly in the text of AI Overviews and AI Mode and place them higher up within the answers. Additionally, the company is testing a dedicated section for official websites when users need a reliable original source for a specific task or information.

This generally creates more opportunities for website operators to be visited directly from an AI response. However, Google has not published any figures on whether the new display actually leads to more redirects to external pages.

The crucial question is therefore no longer just: "Where does our website rank?" Companies also need to know whether they are mentioned in the AI ​​responses, which of their pages Google cites, and what statements other sources provide about their brand.

Regional proximity provides an advantage

Local and regional sources play a particularly important role in German-language search queries. Overall, 51.1 percent of the AI ​​citations analyzed led to domains ending in .de, .at, or .ch. When international domains with a German language or country directory are also considered, 64.9 percent of the sources exhibited a recognizable German-language or regional signal.

In the finance and insurance sector, the share of local country-code top-level domains was 69 percent. German-language AI searches in these sensitive subject areas thus rely particularly frequently on regionally based sources.

A simple translation of English-language content is therefore often insufficient. Companies need content that incorporates German terminology, regulatory specifics, prices, units of measurement, and typical market-specific questions. A clear URL structure with German directories or local domains can also help to clearly indicate regional targeting.

ChatGPT trusts official information

While Google consults numerous different websites for brand-related search queries, ChatGPT shows a strong preference for official sources when it comes to specific factual questions. In a study of 20,000 US queries, 84.4 percent of the responses regarding prices, product features, or company data contained at least one reference to an official source.

For comparative questions such as "Product A or Product B?", this figure dropped to 68.3 percent. For purely factual questions, 63.4 percent of all citations came from official websites; for comparisons, this figure was only 46.4 percent.

For companies, this means a clear separation: prices, technical data, performance characteristics, and company information should be clearly and up-to-date documented on their own website. For reviews and comparisons, however, independent trade publications, test reports, comparison portals, and other external sources are gaining importance.

No recommendation without a user profile

ChatGPT is increasingly trying to clarify user requirements before recommending products in purchase inquiries. In 79.4 percent of the analyzed purchase inquiries, a form or structured follow-up question appeared first. This often concerned the available budget.

This brings AI closer to a digital sales conversation. Instead of immediately providing a general list of top products, it first determines which product might fit the price range, intended use, and personal requirements.

For manufacturers and retailers, it is therefore becoming increasingly important to describe their offerings based on specific usage scenarios. Information about which target groups, budgets, and application scenarios a product is suitable for can become just as relevant for AI as technical specifications.

Top lists as self-promotion

One particularly problematic area is supposedly independent rankings. A study of more than 18,000 software queries on Google, ChatGPT, Gemini, Claude, and Perplexity revealed that, depending on the AI ​​system, between 34 and 47 percent of the cited lists came from a vendor who sells products in the respective category.

Of these self-promoting lists, 93 percent named their own product. 87 percent placed it in first place, while only 16 percent clearly indicated that the provider themselves stood behind the content.

This creates a conflict of interest that is difficult for users to recognize. A professionally designed ranking list can appear neutral, even though its primary purpose is to sell the company's own product. When AI systems adopt such content without sufficient context, self-promotion takes on the appearance of an independent recommendation.

Companies can certainly use this mechanism to increase their own visibility. However, in the long run, a transparent presentation is more credible: Anyone comparing their own product should disclose the source, use verifiable criteria, and objectively present the strengths and weaknesses of their competitors.

Brand management becomes source work

SEO isn't disappearing, but its scope is expanding. Traditional rankings remain relevant, but are no longer sufficient to capture a brand's true visibility. AI overviews, ChatGPT responses, source citations, and direct product recommendations are now also crucial.

Companies must therefore control what information about them is available in machine-readable form, which subpages serve as evidence, and which external sources shape their market position. Their own website thus becomes simultaneously a data source, knowledge base, and reference point for AI systems.

The new key metric is no longer solely "ranking". What matters now is whether a brand appears in the AI ​​response, how it is presented there, and which source ultimately holds the interpretive authority.

 

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From visibility to trust: Your scalable path with Xpert.Digital

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Instead of relying on loud marketing promises, this model puts the relationship at the forefront. Companies start with clearly defined, easily calculable measures and then decide, based on their own experience, how far they want to expand the collaboration. A key factor for this undisturbed trust-building process: The platform completely avoids annoying advertising ads, so the editorial focus remains solely on the companies' expertise.

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