Why the new SEO trend "mention building" can ruin your website: Are mentions the new backlinks?

SEO in the AI ​​Age: Why purchased brand mentions could be your biggest mistake in 2026

The new spam policy: How Google penalizes websites that try to manipulate AI responses

The world of search engine optimization is undergoing a fundamental reinvention: Generative AI systems like ChatGPT, Perplexity, and Google AI Overviews are increasingly taking over the role of traditional Google search. In this new era, where users expect direct answers instead of blue links, a new currency counts: brand mentions. Fearing they will remain invisible in AI-generated responses, many companies are currently embracing a new trend – mention building. Service providers promise rapid visibility by artificially placing brand mentions across large networks. However, what is being marketed as a smart SEO hack for the AI ​​age (Generative Engine Optimization) turns out, upon closer inspection, to be a ticking time bomb. Google has drastically tightened its spam policies and, with its AI detection tool "SpamBrain," is now directly targeting the manipulation of AI responses. Those still relying on artificially generated mentions risk not only a short-lived surge in reach, but in the worst-case scenario, complete exclusion from the search index – with devastating consequences for their entire digital traffic. This in-depth analysis explains why the supposed shortcut of mention building leads to an expensive dead end, how a Google crash affects ChatGPT, and what genuine quality measures you can take to sustainably position yourself for AI search.

Why trying to buy AI visibility costs more than it brings in

Mentions as the new currency of digital visibility

The way brands are found in the digital space is undergoing a fundamental transformation. Where backlinks once reigned supreme as the gold standard of search engine optimization, a new form of signal has taken center stage: the mention, or "brand mention." This shift is not a short-term trend, but rather the result of a structural change in how people search for information and how systems respond to those searches. According to a 2024 analysis by BrightEdge, 58 percent of all online searches already trigger AI-generated responses, and this percentage continues to grow.

Behind this shift lies the rapid proliferation of generative AI systems as the primary interface between users and information. Platforms like ChatGPT, Google AI Overviews, Google AI Mode, Perplexity, and Microsoft Copilot function differently from traditional search engines. They no longer deliver a list of linked pages, but rather synthesize answers from multiple sources, mentioning brands, products, and services. In this new paradigm, the ranking is no longer solely determined by which page performs best, but rather by which brand appears in the generated answer. According to estimates from 2026, Google AI Overviews will appear in 50 to 60 percent of all US search queries.

Understanding this development is the necessary starting point to grasp why the topic of mention building has attracted so much attention so quickly – and why the associated risks are just as quickly underestimated.

The new playing field: Generative Engine Optimization

The term "Generative Engine Optimization," or GEO for short, refers to the practice of structuring and preparing content so that AI systems cite it in their search results. The logic of this discipline shifts the goal from appearing on the first page of Google search results to becoming part of the answer itself. The difference may sound subtle, but it has far-reaching economic consequences: those not mentioned in the answer effectively don't exist for a growing number of users. This is fundamentally different from the world of blue links, where second or third place could at least still generate clicks.

A key finding from a 2024 Princeton study on Generative Engine Optimization empirically supports this: Content optimized with citations, statistics, and authoritative structure achieved up to 40 percent more visibility in generative search engine results compared to unoptimized pages. Backlinks alone did not produce this effect. This strongly suggests that AI systems use different relevance indicators than traditional search engine algorithms—even if the two systems are not completely decoupled.

For companies, this presents a twofold challenge: they not only have to continue cultivating traditional SEO, but also tap into a new dimension of visibility that follows its own set of rules. Given this complex situation, it's hardly surprising that a market has emerged for services that promise precisely this new visibility – in the fastest and most technically automated way possible.

The business model behind mention building

Mention-building services have developed a tempting promise: They analyze which topics or search terms a brand is not yet represented in the responses of AI systems and then ensure that mentions are generated – through automatically generated requests to publishers, negotiated placements in articles, forums, and blogs, or by building their own networks of websites that send the appropriate brand signals. This sounds like a logical extension of traditional link building. In fact, it's structurally related: Previously, you bought links; today, you buy mentions.

A concrete example from German practice illustrates the scale this market segment has already reached: Providers operate networks with over 650 of their own projects and specifically offer brand mentions in thematically relevant articles on supposedly established websites – with the explicit goal of increasing visibility in AI-generated responses such as ChatGPT, Google Gemini, or Perplexity. The underlying argument follows a superficially plausible logic: If AI models measure brand presence to assess relevance, then more mentions must lead to greater brand visibility.

This logic has a serious flaw that lies at the heart of economic incentive structures: it confuses the signal with the underlying reality that the signal is supposed to represent. AI systems don't measure mentions to count popularity, but to assess trust and content relevance. Artificially generated mentions don't reflect this trust—they merely imitate it until the detection systems identify the imitation as such.

Google's official position: A clear warning

In May 2026, Google published its official guidance document on optimizing for generative AI features, a document that garnered significant attention within the SEO community. In it, Google explicitly addresses a number of myths that had arisen surrounding GEO optimization. Under the "Mythbusting" section, there is a point that directly targets the mention-building industry: searching for inauthentic mentions is not as helpful as it might seem. Google's core ranking systems focus on high-quality content, while other systems block spam. And: generative AI features depend on both.

This wording is remarkably direct for an official Google document. Even more significant is the context: shortly before, also in May 2026, Google had expanded the definition of spam in its Search Spam Policies by adding a crucial sentence. The previous wording referred to techniques aimed at manipulating search systems to rank content. The new wording explicitly adds: "or attempting to manipulate generative AI responses in Google Search." A single sentence, but with far-reaching consequences for the entire GEO industry.

This amendment closes a gray area that had emerged in previous months. Until May 2026, providers of mention-building services could argue that their methods were not explicitly covered by Google's spam policies because they influenced "only" AI responses and not traditional search rankings. This argument is no longer valid.

The cascade effect: Why Google's losses hurt everywhere

A critical argument from mention-building providers is that their activities primarily target ChatGPT, Perplexity, and similar systems—and are therefore largely independent of Google's sanctioning mechanisms. This logic overlooks a fundamental connection that is well-documented by real-world data. Researchers at the Berlin-based company Peec AI empirically investigated the relationship between Google visibility and AI visibility, demonstrating a clear cascade effect: When a company loses visibility on Google, it almost simultaneously loses visibility on ChatGPT, Perplexity, and Google AI Overviews.

The underlying mechanism is technically explainable: ChatGPT demonstrably uses Google's search index via SerpAPI for its responses. Anyone who receives a lower ranking in the Google index or is removed from it disappears not only from traditional Google search results but from the entire AI search ecosystem. Google's search index is the common denominator upon which all these systems rely – directly or indirectly. The illusion that one can build AI visibility while simultaneously violating Google's spam policies has thus been empirically refuted.

Google's March 2026 spam update provides a vivid example of the power of these sanctioning mechanisms: The update rolled out globally in under 20 hours – the fastest officially documented spam update in the history of the Google Search Status Dashboard. Online shops using questionable SEO tactics experienced traffic drops of 80 percent or more, while shops with an authentic brand strategy remained virtually unaffected.

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SpamBrain and the machine detection of manipulation

Behind Google's ability to detect manipulative patterns lies an AI-based system called SpamBrain, which is continuously being developed. SpamBrain doesn't analyze individual pages in isolation, but rather recognizes systemic patterns: similar text rhythms, unnatural clusters of mentions within a short period, atypical linking structures, and the appearance of brand mentions on thematically irrelevant or low-quality platforms. The sophistication of this system lies in the fact that it doesn't search for a specific technique, but rather for the characteristic that all manipulation attempts have in common: their statistical abnormality compared to organic, natural behavior.

Crucial to understanding today's risk landscape is the fact that the detection accuracy of SpamBrain and similar systems is not static, but improves with each update. What went undetected twelve months ago is now routinely detected. What remains undetected today will be detected in twelve months. Therefore, anyone investing in mention-building services today is not just paying for a tactical measure, but for a time-limited exposure risk with an uncertain maturity date. This represents a structurally unfavorable cost-risk profile.

The consequences Google can impose for violations range from algorithmic demeanor—a loss of visibility without explicit notification—to manual action after review by a human Google team, all the way to complete exclusion from search results. Recovery periods after manual action range from six to 18 months; recovery after exclusion from AI Overviews is unclear in its duration and potentially permanent.

The illusion of rapid visibility: An economic miscalculation

From an economic perspective, mention building can be described as a classic risk substitution problem: it trades the long-term problem of difficult visibility for the short-term risk of abrupt loss of visibility. Its business appeal lies in the speed – providers promise measurable AI visibility within weeks – and in the predictability, which seems to pit a defined budget against a defined effect. However, this apparent predictability is countered by an unpredictable variable: the point at which Google's detection systems classify the efforts as spam.

Another aspect that often remains under-examined in the debate is that Google's spam policies don't apply to individual pages, but can affect the entire domain and thus the entire brand's digital presence. Anyone who uses an external agency or mention-building service to implement measures that violate Google's guidelines bears the full risk themselves – not the service provider. An agency whose clients are penalized loses business. The affected company may lose its entire organic traffic channel for months or longer.

The situation is particularly problematic for B2B brands, where visibility in organic search and AI systems is often the primary channel for generating inquiries and leads. An 80 percent loss of visibility – as documented for aggressively manipulative pages after the March 2026 update – equates to a near-complete collapse of digital customer acquisition in such business models.

Backlinks versus mentions: What really determines visibility

To fully understand the topic, a sober assessment of the relationship between backlinks and mentions as ranking signals is necessary. The blanket statement that mentions are "the new backlinks" is analytically insufficient. Both signal types address different systems with different functionalities. Backlinks feed PageRank algorithms and determine domain authority for traditional search – a 2023 correlation study by Ahrefs showed that pages in the top three Google results had 3.8 times more referring domains than pages in lower positions. This causal relationship remains intact.

Mentions, however, operate in a different context: They provide signals for retrieval augmented generation (RAG) systems, which "ground" (support with facts) AI answers by retrieving and synthesizing current web pages from the search index. For these systems, contextual association, content relevance, and the quality of the source on which the mention appears are more important than mere frequency. A mention in a credible academic publication carries considerably more weight than a hundred mentions on low-quality social media pages—and the latter increase the risk of spam without achieving significant visibility gains.

The smartest strategy is therefore neither an exclusive focus on backlinks nor on mentions, but an integrated approach that understands: those who are quoted in trade publications typically also receive backlinks. Those with strong backlinks appear more frequently in the index from which AI systems draw their data. Those who build authentic brand signals benefit on all channels simultaneously – without the risk of sanctions.

What really works: Visibility through substance

Google's official recommendations for optimizing for generative AI features can be distilled into one central principle: Content that is valuable and satisfying for human users also performs better in AI-powered search environments. This isn't marketing hype, but rather a statement about the architecture of RAG systems: They retrieve content from an index structured by traditional quality signals and favor sources that are clearly structured, up-to-date, authoritative, and unambiguous in their content.

Specifically, this means: clear answer structures within content—so-called TL;DR summaries, FAQ sections with real answers, precise definitions—Schema.org markup for machine-readable structure, verifiable author expertise through verifiable CVs and author profiles, and a consistent brand presence across relevant platforms: Google Business Profile, LinkedIn, industry directories, and Wikidata for established brands. All of this is slower than buying mentions in a network. But it's the only thing that provides lasting results.

Another factor that is often underestimated in practice is the importance of genuine depth of content. Google's May 2026 guidance document explicitly distinguishes between "commodity content"—generic content that reproduces general knowledge—and "non-commodity content"—content that offers unique, experience-based, or expert-dense perspectives that could not be produced by generative AI itself. Paradoxically, the most valuable content for the AI ​​age is that which conveys human experience, direct observation, and original expertise—precisely what cannot be automated.

The maturation of an industry and the end of the gray area

The evolution of the GEO industry follows a pattern familiar from the history of traditional SEO. After a period of rapid growth, during which various shortcuts and tactics operate in the gray area between optimization and manipulation, regulatory clarification closes this gray area. March 2024 marked this turning point for traditional content spam; May 2026 marks it for the manipulation of generative AI responses.

The practical consequence for marketing managers and digital strategists is clear: Any external agency or service provider that advertises guarantees of AI visibility within a short timeframe exposes the client's budget and reputation to an incalculable risk. A brand that has systematically attempted to manipulate AI Overviews cannot regain the trust of Google's systems through a simple cleanup – the damage to digital brand perception can be felt across all channels. The only sustainable response to the shift towards AI-powered search remains what has always been true: creating content that deserves to be quoted.

The risk simply isn't worth it

The economic analysis of mention building leads to a clear result: the ratio of potential short-term gain to concrete long-term risk is structurally unfavorable. On the gain side, there is a possible, temporary improvement in visibility in AI-generated search results—depending on whether the systems even classify the signals as relevant and how long they remain undetected. On the loss side, there is a potentially complete and long-term loss of organic visibility, not only in Google search, but also, due to the cascading effect, across all relevant AI search platforms simultaneously.

Since May 2026, Google's spam policies have explicitly targeted the manipulation of generative AI responses. SpamBrain is becoming increasingly precise. The geo-trick industry is undergoing a structural maturation process that will weed out its short-sighted practitioners. What remains is a simple principle that runs through the entire history of search engine optimization: those who write for users, structure their content clearly, demonstrate genuine expertise, and build a consistent brand presence automatically optimize for the next generation of search systems—without risking being penalized by those very systems. This is less convenient than buying mentions, but it's the only strategy you can rely on in the long run.

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