The invisible battle for brand visibility: Why companies invest millions in tools that nobody sees

The new paradigm of digital visibility

The rules of digital capitalism are being rewritten, and most companies don't even realize it. While marketing departments continue to focus on traditional search engine optimization, a tectonic shift is taking place in parallel, shaking the foundations of digital business models. The question is no longer whether a website appears on Google's first page, but whether a brand even appears in the responses of the artificial intelligence that increasingly determines what millions of people see, know, and buy.

Adobe has launched the LLM Optimizer, a tool designed to address precisely this new reality. Generally available since October 2025, the tool promises companies transparency and control over how their brand is represented in AI-generated responses. However, behind this technological innovation lies a broader economic transformation that is putting pressure on publishers, platforms, and brands alike.

The figures are both clear and alarming. Between July 2024 and May 2025, US retail sites saw a 3,500 percent increase in AI-driven traffic, while travel sites experienced a 3,200 percent rise. By September 2025, AI-driven traffic to US retail websites had increased by 1,100 percent year-over-year. These users not only spend 12 percent more time on the site than visitors from traditional sources, but they also make purchases 5 percent more frequently. What at first glance appears to be a success story, upon closer inspection, turns out to be a double-edged sword.

While some websites are benefiting from this new traffic, others are experiencing dramatic losses. CNN saw a traffic decline of approximately 30 percent compared to the previous year, while Business Insider and HuffPost reported drops of around 40 percent. Mail Online even reported that click-through rates plummeted by as much as 89 percent when Google's AI Overviews appeared over their content. This discrepancy reveals a fundamental truth of the new era: visibility in AI systems is becoming a crucial competitive advantage, while invisibility is becoming an existential threat.

Anatomy of a new market standard

The Adobe LLM Optimizer positions itself as a holistic analysis and optimization solution for generative AI search. The tool combines several functional layers that together paint a complete picture of a brand's AI visibility. At its core, it analyzes which content is used by Large Language Models such as ChatGPT, Google Gemini, or Perplexity to generate answers to user queries.

The system's functionality is based on a three-stage framework: automatic detection, automatic suggestions, and automatic optimization. It continuously analyzes LLM activities and identifies opportunities to improve brand presence. It utilizes specially trained models to suggest technical optimizations and enables the implementation of these solutions with just one click after user approval. Licensing is based on a model of prompts per year, where a prompt is a text input that generates outputs, insights, or recommendations.

Of particular note are the AI ​​traffic analysis functions, which recognize and evaluate so-called agentic traffic—that is, visits originating from LLMs and AI agents. Benchmarking enables a direct comparison of your own visibility with competitors, both thematically and according to product focus. The technical analysis identifies classic SEO problems such as faulty metadata, hidden pages, or structural issues that are specifically relevant to AI systems.

Another key element is the content recommendation function. This suggests relevant topics, questions, and semantic keywords that AI systems preferentially process. The contextual visibility analysis evaluates how AI systems prioritize content based on external references such as Wikipedia or forums and shows how this prioritization can be influenced.

Adobe has also released a free Chrome extension called “Is Your Webpage Citable?”. This extension instantly shows which website content is visible to LLMs and which is not. In a practical test with OnlineMarketing.de, it achieved a citation readability of 98 percent, meaning that almost all content can be correctly read and incorporated into AI-generated responses.

The attribution feature directly links AI visibility to user behavior and business results, enabling the concrete impact of GEO measures to be demonstrated and communicated internally. Out-of-the-box reports allow teams to quickly share insights organization-wide and communicate the business impact.

Adobe's own marketing team used the LLM Optimizer to boost the visibility of Adobe Acrobat. Citations for Firefly increased fivefold within a week. Acrobat's visibility increased by 200 percent compared to competitors, while AI-driven traffic to Adobe.com grew by 41 percent. This success story highlights the potential but also raises questions about scalability and applicability to smaller businesses.

The ecosystem of competition

Adobe is far from the only player in the burgeoning market of Generative Engine Optimization tools. An entire ecosystem of specialized vendors has emerged, each with its own focus and pricing model. The competitive landscape ranges from affordable entry-level solutions to enterprise platforms with comprehensive features.

Peec AI, a Berlin-based startup, has established itself as a leading provider. The tool monitors brand mentions and citations across ChatGPT, Gemini, Claude, and Perplexity, delivering real-time analytics. The pricing structure is clearly tiered: the Starter plan begins at €89 per month for 25 prompts, the Pro plan costs €199 for 100 prompts, and the Enterprise plan starts at €499 for over 300 prompts. All plans offer unlimited countries and unlimited users. The company was founded in 2025 and has received a five-star rating.

Profound positions itself as a premium enterprise solution with the most comprehensive feature set. The Lite plan starts at $499 per month, while Enterprise plans are priced individually. The tool monitors over 300,000 unique websites with a catalog of three million answers and offers real-time visibility tracking. Profound works with a dedicated AI Search Strategist who assists teams with optimization. Customers include Ramp, IBM, Walmart, Target, MongoDB, and Chipotle. Ramp was able to increase its AI visibility from 3.2 to 22.2 percent and climb from 19th to 8th place in the Accounts Payable category.

AthenaHQ was founded by former Google Search and DeepMind experts Andrew Yan and Alan Yao and received $2.2 million in funding from Y Combinator. The Lite plan starts at approximately $270 to $295 per month, the Growth plan costs $545 to $900, and Enterprise plans start at $2,000. The tool offers comprehensive brand intelligence, source intelligence, and sentiment analysis. The platform takes a holistic approach and describes itself as a one-stop shop for everything related to AI search.

Other key players include Goodie AI, which specializes in rapid insights; Rankscale, with real-time ranking tracking on GPT and other platforms; and Otterly, which stands out for its ease of use. BrightEdge Prism builds on BrightEdge's established SEO suite but struggles with a 48-hour delay in AI data. Semrush and Ahrefs have also integrated AI visibility features into their existing platforms.

The price differences reflect not only varying feature sets but also different business philosophies. While more affordable tools like Peec AI and Otterly focus on scalability and widespread adoption, Profound and AthenaHQ target enterprise customers willing to pay for comprehensive strategy support. Adobe, with its established enterprise cloud infrastructure, positions itself somewhere in between and benefits from seamless integration with Adobe Experience Manager sites.

The economic dimension of a silent revolution

The Generative Engine Optimization market represents more than just a new product category; it symbolizes a fundamental shift in the digital economy. The global GEO services industry was valued at $886 million in 2024 and is projected to reach $7.318 billion by 2031, representing a compound annual growth rate (CAGR) of 34 percent. Other estimates project $848 million in 2025, with growth expected to reach $33.68 billion by 2034 at a CAGR of 50.5 percent.

This explosive expansion occurs within the context of an already robust SEO market. The global SEO market was valued at $65.87 billion in 2024 and is projected to grow to $176.16 billion by 2033, representing a CAGR of 11.55 percent. Other sources cite $82.3 billion in 2023, with growth to $143.9 billion by 2030. IDC forecasts that by 2029, companies will spend up to five times more on LLM optimization than on traditional SEO.

The driving forces behind this growth are manifold. First, AI platforms are experiencing astronomical growth rates. ChatGPT reached 5.14 billion visits in April 2025, a year-over-year increase of 182 percent, surpassing Wikipedia in monthly website visits. Second, user behavior is fundamentally changing. Over 45 percent of people use generative AI weekly, often for personal research and recommendations. Gartner predicts that by 2026, one in four searches will be conducted using generative AI.

The economic consequences for publishers are dramatic. Zero-click searches now account for 69 percent of all queries. Between April 2022 and April 2025, search traffic to websites fell by 55 percent. The Washington Post experienced a decline of almost half in organic search traffic, while the share of organic search traffic for The New York Times fell to 36.5 percent in April 2025.

Studies show that 57 to 65 percent of search queries now result in zero-click results, where the answer is provided directly by AI without requiring a click on a website. Some industrial clients have reported traffic declines of up to 20 percent in Germany and 18 percent worldwide.

The content economy itself faces a paradox. AI systems rely on human-generated content, but by keeping users within their ecosystem, they deprive creators of precisely those users. An ARD podcast episode discussed how roughly half of all online content is now generated by AI, much of it of low quality. This leads to a self-reinforcing downward spiral of content quality.

The legal battles highlight the conflict between platforms and publishers. The Encyclopaedia Britannica Group and Merriam-Webster sued Perplexity AI for systematically copying content, siphoning off traffic, and copyright infringement. Nikkei and Asahi Shimbun also filed similar lawsuits. Reddit sued Perplexity in October 2025, accusing the startup of building a $20 billion company on stolen data. Dow Jones and the New York Post accused Perplexity of damaging their business by siphoning off customers and revenue from news publishers.

The platforms' reactions vary. Anthropic agreed to a $1.5 billion settlement to resolve claims related to the use of millions of pirated books to train its Claude chatbot. Perplexity launched Comet Plus, a $42.5 million subscription model to pay publishers. OpenAI reached an agreement with News Corp for over a quarter of a million dollars in licensing payments over five years.

Cloudflare introduced the Content Signals Policy, which allows websites to prevent their content from being used for AI Overviews via specific directives, similar to those in the robots.txt file. However, this is contingent on platforms respecting these guidelines, which is not guaranteed.

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AI search changes everything: How this SaaS solution will revolutionize your B2B ranking forever.

The digital landscape for B2B companies is undergoing rapid change. Driven by artificial intelligence, the rules of online visibility are being rewritten. For companies, it has always been a challenge not only to be visible in the digital mass, but also to be relevant to the right decision-makers. Traditional SEO strategies and managing local presence (geo-marketing) are complex, time-consuming, and often a battle against constantly changing algorithms and intense competition.

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The transformation of marketing disciplines

The shift from SEO to GEO doesn't just mean new tools, but a fundamental redefinition of what digital visibility means. While traditional SEO aimed for rankings in search results, GEO focuses on ensuring that content is cited and referenced in AI-generated responses. The fundamental difference is that companies are no longer optimizing for algorithms that rank pages, but for AI systems that synthesize information from multiple sources.

The method of measuring success changes accordingly. Instead of keyword rankings, ChatGPT visibility measurement focuses on specific prompts posed by the target audience. Context is more important than the frequency of mention: Is the brand enthusiastically recommended or only mentioned in passing? Is it positioned as a leader or a niche provider? Is it described precisely or with misunderstandings?.

Studies show that brands employing geo-marketing practices can achieve up to 40 percent greater visibility in AI-generated responses. Only 50 percent of AI citations overlap with Google's top results, meaning businesses need to expand their content presence beyond their website. Highly authoritative platforms like Reddit, Quora, and industry-specific publications, from which AI platforms frequently draw information, are becoming increasingly important.

The structure and presentation of content must adapt. AI systems prefer clear hierarchical headings, concise answers, and semantic clarity. FAQ pages are identified as particularly AI-friendly. Structured data such as schema markup for ImageObjects, FAQs, VideoObjects, and AudioObjects are becoming increasingly relevant for multimodal optimization.

Personalization is reaching new dimensions. 72 percent of marketers using AI and automation are personalizing customer experiences. Customers are increasingly formulating queries based on values ​​and preferences, such as sustainable brands, locally sourced products, or companies with strong ESG records.

The productivity gains are substantial. 93 percent of marketers use AI to generate content faster, 81 percent use it to gain insights more quickly, and 90 percent use it for faster decision-making. Marketers save an average of three hours per piece of content and 2.5 hours per day with AI tools. 84.86 percent confirm that AI has improved the speed of delivering high-quality content.

At the same time, the challenges are growing. Sixty percent of marketers using generative AI for content are concerned that it could damage brand reputation through bias, plagiarism, or value misalignment. The volatility of AI Overview rankings is higher than that of organic rankings: Over a period of two to three months, approximately 70 percent of the pages cited in AI Overviews changed, and these changes were not linked to traditional organic rankings.

The role of platforms in the new power structure

The major tech companies are positioning themselves differently in this new landscape. Google, which continues to hold a dominant position, has introduced AI Mode as part of its search strategy. Despite predictions that AI would diminish Google's dominance, Google saw astonishing growth of 21.64 percent in searches from 2023 to 2024, with over 14 billion daily searches. 99 percent of AI users continue to use search engines.

Nevertheless, Google faces considerable criticism. In Italy, the publishers' association FIEG filed a complaint against AI Overviews, criticizing the fact that generative answers directly in search results discourage users from clicking on original pages, with significant consequences for reach and advertising revenue. The EU competition authority was contacted by an Independent Publishers Alliance, which accuses Google of abusing its dominant market position to place its own AI summaries at the top of search results and disadvantage original content providers.

Google claims that AI overviews are well-received by users and lead to higher-quality clicks. The reality is different: An analysis by the Pew Research Center showed that users who encounter an AI summary are less likely to click on links to other websites than users without an AI summary. It is estimated that AI-generated snippets currently appear at the top of the results page for about 20 percent of Google searches.

ChatGPT has captured 61.3 percent of the generative AI market, but with 37.5 million searches per day, it still lags far behind Google. However, the platform has a massive user base and exerts considerable influence on brand recognition and purchasing decisions.

Microsoft, with its Copilot platform, and other players like Perplexity, Claude, and Gemini are further expanding the ecosystem. Each platform has its own preferences and algorithms, increasing the complexity for brands that want to be visible across multiple platforms.

Structural challenges and future prospects

The GEO landscape faces several structural challenges. The determinism issue is significant: ChatGPT responses can change because models sample, meaning results are inconsistent. This probabilistic nature of GEO differs fundamentally from the more deterministic nature of traditional SEO.

Measurability remains complex. Without separate tabs or simple filters in Google's Search Console, which capture AI-mode clicks, impressions, and positions but mix them with regular traffic, companies that don't intentionally track this traffic are flying blind. Attributing AI-mediated traffic to actual business results requires sophisticated analytics setups with custom UTM parameters.

Cost efficiency is improving. The shift to smaller models like TinyLlama reduces inference costs tenfold while maintaining the same response quality, enabling more frequent visibility tracking and larger query sets. This cost reduction democratizes AI monitoring for mid-sized companies that were previously excluded from comprehensive programs.

The geographic dimension is playing an increasingly important role. Asia-Pacific is considered the fastest-growing region in the GEO market, driven by rising internet usage, growing mobile-first populations, and strong interest in digital transformation. The region's diverse languages ​​and large user base create demand for localized and structured content that is compatible with generative search tools.

The development of vertical LLMs for specialized fields such as healthcare (Med-PaLM) and finance-focused LLMs creates separate visibility ecosystems that require dedicated tracking strategies. The integration of real-time fact-checking into Microsoft Copilot and other platforms raises the accuracy standards for AI-cited content.

The long-term effects on the open internet are the subject of intense debate. If AI systems discourage users from visiting original websites, they deprive content creators of their economic foundation. This could lead to a content drain that ultimately starves the AI ​​systems themselves, as they rely on human-generated content. Marie Kilka from the ARD podcast noted that the web, as something that connects different websites, is no longer accurately represented.

Publishers are responding with various strategies. Some are reinforcing their core values ​​through strong editorial identity and clear brand voices that encourage readers to return. Loyalty programs deepen relationships through exclusive access, community recognition, or tangible benefits. Others are diversifying revenue streams across subscriptions, events, consulting, and niche products.

The next five years will determine which media companies can maintain authority and revenue. Those that cultivate direct relationships, reinforce unique editorial strengths, and create richer on-site experiences will survive the volatility of platform-driven traffic.

Implications for strategies and investments

The strategic implications of this transformation are far-reaching. Companies must fundamentally rethink their digital marketing budgets. Allocation is shifting from traditional SEO and paid advertising to GEO, content syndication on high-authority platforms, and direct audience building.

Building an AI Visibility Center of Excellence requires executive sponsorship with clear ROI metrics, the allocation of cross-functional teams including SEO, data science, and brand teams, the standardization of KPIs and dashboard reporting across business units, and partnerships with experienced platforms like Profound for ongoing support.

The content strategy needs to evolve. Structured, fact-based content that AI platforms preferentially cite will become the standard. Using clear, hierarchical headings, concise answers, and semantic clarity increases the likelihood of citations. Diversifying your source presence beyond your own website will be essential.

Technology stack decisions are becoming more complex. Companies need to evaluate whether to rely on integrated solutions like Adobe LLM Optimizer, which work seamlessly with existing systems, or on specialized best-of-breed tools like Profound or Peec AI, which may offer deeper functionality.

Measuring success requires new frameworks. Traditional metrics like keyword rankings and click-through rates are losing relevance. Instead, metrics such as mention frequency, share of voice in AI responses, sentiment scores, citation quality, and attribution to downstream business outcomes are becoming central.

Organizational transformation is just as important as technological transformation. 75 percent of marketers' work is shifting towards strategy, while AI is taking over routine tasks. This requires retraining programs, new roles such as AI search strategists, and the integration of AI literacy into all marketing positions.

Concluding remarks on an unfinished transformation

The Adobe LLM Optimizer and its competitors represent more than just a new product category in the crowded martech ecosystem. They are symptoms and catalysts of a fundamental paradigm shift in the digital economy. Whether a brand appears in ChatGPT responses is no longer a technical curiosity, but a strategic priority at the C-level.

The economic dimensions are considerable. A market growing from less than a billion dollars to potentially over 30 billion dollars within a decade signals not just investment opportunities, but a tectonic shift in value. The traditional SEO business, already worth over 100 billion dollars, will not disappear, but it will increasingly merge with and be integrated into GEO.

The challenges are multifaceted. Publishers are fighting for their economic survival, while platforms are waging legal battles over copyright and fair compensation. Brands are navigating a probabilistic visibility ecosystem where control is an illusion and continuous adaptation is the norm. The content economy itself faces a paradox that can only be resolved through new business models and regulatory frameworks.

What remains is the realization that visibility in the AI ​​age is neither guaranteed nor passively achievable. It requires active investment, continuous measurement, and strategic adaptation. Tools like the Adobe LLM Optimizer are not solutions to a problem, but rather navigational instruments for a new terrain whose contours are constantly shifting. Companies that understand this and act accordingly will not only survive the invisible battle for brand visibility, but will define it.

The next few years will show whether the optimistic growth forecasts become reality or whether the pendulum swings back. One thing, however, is certain: the way billions of people discover, evaluate, and make decisions based on information has irrevocably changed. And in this new world, success or failure is no longer determined solely by algorithms, but by artificial intelligences that synthesize, interpret, and recommend. Those who want to be visible in this world must speak the language of these new gatekeepers and master the tools that make this visibility measurable and controllable.

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