{"id":27717,"date":"2025-11-20T13:51:14","date_gmt":"2025-11-20T12:51:14","guid":{"rendered":"https:\/\/digitalnimarketing.si\/google-loves-you-but-chatgpt-doesnt-why\/"},"modified":"2026-07-08T10:19:19","modified_gmt":"2026-07-08T08:19:19","slug":"google-loves-you-but-chatgpt-doesnt-why","status":"publish","type":"post","link":"https:\/\/digitalnimarketing.si\/en\/google-loves-you-but-chatgpt-doesnt-why\/","title":{"rendered":"Google loves you, but ChatGPT doesn&#8217;t: why?"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">Generative models such as ChatGPT, Gemini, and Perplexity are increasingly becoming the entry point for information. Companies assume that a good ranking on Google will automatically translate into frequent appearances in LLM responses. A new analysis by Search Atlas clearly shows: this connection is much weaker than we think.  <\/p>\n\n<h2 class=\"wp-block-heading\">Google \u2260 LLM<\/h2>\n\n<p class=\"wp-block-paragraph\">The study compared which domains and URLs Google displays in top positions versus those extracted by the three largest models. The results are surprising: <\/p>\n\n<ul class=\"wp-block-list\">\n<li><strong>Perplexity<\/strong> covers approximately <strong>25\u201330% of the same domains<\/strong> as Google.<\/li>\n\n\n\n<li><strong>ChatGPT<\/strong> matches Google in only <strong>10\u201315% of domains<\/strong>, and even less for URLs.<\/li>\n\n\n\n<li><strong>Gemini<\/strong> is the most selective \u2013 <strong>it shares only about 4% of domains<\/strong>.<\/li>\n<\/ul>\n\n<p class=\"wp-block-paragraph\">Even if a website is number one on Google, it does not mean an LLM will mention it at all, let alone cite it.<\/p>\n\n<h2 class=\"wp-block-heading\">Why such a difference?<\/h2>\n\n<p class=\"wp-block-paragraph\">LLMs do not &#8220;rank&#8221; content like Google. They do not operate based on classic SEO signals, but rather: <\/p>\n\n<ul class=\"wp-block-list\">\n<li>select sources that appear in their training data or trusted lists,<\/li>\n\n\n\n<li>prioritize simply structured content,<\/li>\n\n\n\n<li>often ignore commercial or sales pages,<\/li>\n\n\n\n<li>sometimes do not cite sources at all (ChatGPT) or filter them heavily (Gemini).<\/li>\n<\/ul>\n\n<p class=\"wp-block-paragraph\">SEO optimization alone is therefore not enough for visibility in generative responses.<\/p>\n\n<h2 class=\"wp-block-heading\">What does this mean for marketing?<\/h2>\n\n<p class=\"wp-block-paragraph\">Online presence is shifting from search engines to conversational interfaces. If you want models to recognize you as a relevant source, you need a different logic for content creation: <\/p>\n\n<h3 class=\"wp-block-heading\">1. <strong>More emphasis on authority, less on classic SEO tricks<\/strong><\/h3>\n\n<p class=\"wp-block-paragraph\">LLMs prefer to cite authoritative, expert, and well-structured content rather than aggressively optimized commercial pages.<\/p>\n\n<h3 class=\"wp-block-heading\">2. <strong>Topics that answer questions<\/strong><\/h3>\n\n<p class=\"wp-block-paragraph\">Because models attempt to simulate an &#8220;answer,&#8221; articles written as clear explanations or guides \u2013 without unnecessary marketing jargon \u2013 have an advantage.<\/p>\n\n<h3 class=\"wp-block-heading\">3. <strong>Transparent sources and references<\/strong><\/h3>\n\n<p class=\"wp-block-paragraph\">Clearly citing sources and research increases the likelihood that content will be recognized as trustworthy and thus included in LLM responses.<\/p>\n\n<h3 class=\"wp-block-heading\">4. <strong>Structure that models can easily digest<\/strong><\/h3>\n\n<p class=\"wp-block-paragraph\">Short paragraphs, clear statements, concise subheadings. &#8220;LLM-friendliness&#8221; is more important here than mere readability. <\/p>\n\n<h3 class=\"wp-block-heading\">5. <strong>Strengthening presence across multiple channels<\/strong><\/h3>\n\n<p class=\"wp-block-paragraph\">Blogs, interviews, reports, expert studies, collaborations \u2014 all of this helps content find its way into training sets and external references more frequently.<\/p>\n\n<h2 class=\"wp-block-heading\">A paradigm shift<\/h2>\n\n<p class=\"wp-block-paragraph\">SEO hasn&#8217;t disappeared, but it has become only half of the equation. With the rise of generative AI tools, a parallel ecosystem is emerging \u2014 one where algorithms do not rank the most relevant results for the user, but instead generate a single answer based on their own assessment of trust. <\/p>\n\n<p class=\"wp-block-paragraph\">The gap between Google positions and LLM citations will likely continue to grow. The winners will be those who understand the dynamics of both worlds in time. <\/p>\n\n<h2 class=\"wp-block-heading\">Sources<\/h2>\n\n<h2>Sources<\/h2>\n<ul>\n  <li>\n    <a href=\"https:\/\/www.searchenginejournal.com\/new-data-finds-gap-between-google-rankings-and-llm-citations\/561492\/\" target=\"_blank\" rel=\"noopener noreferrer\">\n  Search Engine Journal \u2013 New Data Finds Gap Between Google Rankings and LLM Citations\n    <\/a>\n  <\/li>\n\n  <li>\n    <a href=\"https:\/\/sparktoro.com\/blog\/llms-are-not-search-engines\/\" target=\"_blank\" rel=\"noopener noreferrer\">\n  SparkToro \u2013 LLMs Are Not Search Engines (Rand Fishkin)\n    <\/a>\n  <\/li>\n\n  <li>\n    <a href=\"https:\/\/moz.com\/blog\/google-vs-generative-ai\" target=\"_blank\" rel=\"noopener noreferrer\">\n  Moz \u2013 Google vs. Generative AI: How Search Is Changing\n    <\/a>\n  <\/li>\n\n  <li>\n    <a href=\"https:\/\/www.perplexity.ai\/hub\" target=\"_blank\" rel=\"noopener noreferrer\">\n  Perplexity AI Hub \u2013 How Perplexity selects and cites sources (official documentation)\n    <\/a>\n  <\/li>\n\n  <li>\n    <a href=\"https:\/\/openai.com\/index\/introducing-chatgpt\/\" target=\"_blank\" rel=\"noopener noreferrer\">\n  OpenAI \u2013 ChatGPT: principles, limitations, and use of sources\n    <\/a>\n  <\/li>\n\n  <li>\n    <a href=\"https:\/\/www.nature.com\/articles\/d41586-023-02292-7\" target=\"_blank\" rel=\"noopener noreferrer\">\n  Nature \u2013 Large Language Models Don\u2019t \u201cKnow\u201d Things the Way Search Engines Do\n    <\/a>\n  <\/li>\n<\/ul>\n\n","protected":false},"excerpt":{"rendered":"<p>Generative models such as ChatGPT, Gemini, and Perplexity are increasingly becoming the entry point for information. Companies assume that a good ranking on Google will automatically translate into frequent appearances in LLM responses. A new analysis by Search Atlas clearly shows: this connection is much weaker than we think. Google \u2260 LLM The study compared [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":27718,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[608,594,604],"tags":[606,610,620],"class_list":["post-27717","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-analytics","category-artificial-intelligence","category-search-engine-optimization-seo","tag-ai","tag-google","tag-openai"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Google loves you, but ChatGPT doesn&#039;t: why?<\/title>\n<meta name=\"description\" content=\"Generative models such as ChatGPT, Gemini, and Perplexity are increasingly becoming the entry point for information. 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