Google cleans up Search Console data, AI Mode gets more actionable and agentic, and ChatGPT tests instant checkout. See what’s shaping search in October 2025.
Explore how AI and large language models disrupt SEO, drive “direct” traffic, and create new rules for measuring visibility in the era of answer engines.
The way people discover information online is undergoing its most seismic shift since the emergence of Google. For two decades, search engine optimization (SEO) has been about visibility in a ranked list of links with the ultimate goal of earning a click. But today, that foundation is cracking.
Large Language Models (LLMs) like ChatGPT, Gemini, Claude, Copilot, and Perplexity are reshaping the way users interact with the web. In 2025, ChatGPT alone earned more than 700 million weekly active users, reflecting a wholesale shift from keyword-based search to AI-powered conversations.
Traditional search engines are “link engines.” They connect people to other websites. LLMs, however, are “answer engines.” They synthesize information into a single, coherent response right inside their interface.
This shift is accelerating the zero-click trend. A study revealed that 64% of Google searches in the U.S. end without a click, a number that jumps when AI-generated overviews appear. In fact, Google’s own AI Overviews can cut organic click-through rates by 34.5% for the top-ranking links
That means the content brands create is being consumed by AI, but users aren’t always clicking through to the source.
In analytics, this disruption shows up as a surge in Direct traffic that doesn’t line up with marketing campaigns. Why? Because AI introduces a new “brand recall loop”:
Analytics records the visit as Direct or branded Organic, but the real influence came from AI. Studies show brands that increase LLM visibility see an average 28% lift in branded search volume within 60 days
This makes AI one of the largest unattributed drivers of traffic and conversions today.
SEO teams are noticing a striking pattern in Google Search Console known as the “open-mouthed crocodile.” Impressions climb dramatically as content surfaces both in blue links and AI overviews—but clicks flatten or decline.
Case studies show impressions jumping 50% or more while clicks plunge by double digits. The downstream effect? A delayed surge in Direct and branded search visits, as users circle back later through high-intent entry points
Marketers everywhere are asking the same question: is traffic from AI platforms more valuable than traditional organic search? The answer is complicated and depends heavily on context.
Some research paints a very optimistic picture. For example, one case study found that traffic referred by ChatGPT converted at an impressive 15.9% rate, compared to just 1.8% for traditional Google Organic. Other analyses show AI-driven visitors spend more time on site, view more pages, and bounce less frequently. In this view, AI has effectively compressed the funnel, allowing users to research, compare, and refine their intent inside a conversation before ever clicking a link. By the time they arrive on a website, they are primed to take action.
But the counter-evidence is equally compelling. A large-scale study of 672,000 LLM referral sessions revealed that AI traffic was less engaged in most industries. In consumer e-commerce, for instance, conversion rates were significantly higher from organic search than from LLMs. For B2B e-commerce, the gap was even starker, with organic outperforming AI referrals by a wide margin.
The best way to reconcile these findings is to understand that AI does not deliver traffic uniformly. Instead, it acts like a filter: eliminating much of the low-intent, informational traffic that would otherwise trickle through, while simultaneously sending over smaller but sharper waves of highly motivated visitors. The quality of AI traffic, then, isn’t universally higher or lower. It’s more polarized.
This shift has profound implications for strategy. Traditional SEO has always been about winning visibility in search results, climbing rankings, and capturing clicks. But in an era where large language models deliver answers before a user ever sees the SERP, visibility must be redefined.
Enter Large Language Model Optimization (LLMO). The goal of LLMO is not simply to rank. It’s to be cited, trusted, and remembered by AI systems themselves. That means creating content that AIs want to use: structured, data-rich, and verifiable. It also means extending influence beyond your own site. LLMs learn about brands through the broader web, so authoritative mentions in industry publications, research reports, and syndicated content are more important than ever.
For marketers, this is a philosophical shift. Instead of asking, “How do I win the click?”, the question becomes, “How do I win the answer?” Success is measured not just in sessions but in brand presence within AI responses, the sentiment of those mentions, and the downstream lift in direct or branded search that follows.
If impressions are climbing while clicks fall, it does not mean visibility is declining. It means visibility is evolving. The crocodile effect shows that content is being used, cited, and surfaced more often than ever. It’s just happening inside environments where attribution is murky.
The next frontier for search marketing will be embracing this murkiness, finding ways to measure indirect influence, and accepting that a brand remembered today may not be clicked until tomorrow. Those who adapt to this reality by balancing technical SEO excellence with proactive LLMO will define what winning looks like in the era of answer engines.
At GPO, we help brands claim space where it counts, whether users click or not. If you want to stay relevant in a world where Google is often the final destination, our content and search strategies can help you stay seen and top of mind. Get started with a quick consultation today.
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