LLM traffic converts differently — what should brands do?

Traffic arriving at websites through LLMs (large language models — AI systems trained on vast bodies of text that can converse with users almost like a person) has recently proven fundamentally different from traditional paid-advertising traffic. According to an analysis published by Search Engine Land, the conversion rate for these visitors reaches 20% — 61% higher than what's typically achieved through PPC (pay-per-click advertising).

Marketer Jason Tabeling argues the reason for this gap is simple: AI has already shaped the user's decision before they ever land on the site. In other words, a customer arriving via an LLM doesn't come based on a single keyword, but with a context-rich understanding synthesized by the AI. That builds a higher baseline of trust in the brand, since the user perceives the AI's recommendation as impartial.

The traditional PPC model targets narrow, keyword-driven search intent: the user compares several options right on the landing page, forcing advertisers to rely on tight conversion funnels. Users arriving via LLMs take a completely different path. According to Google, the average query in its AI Mode (an AI-powered search experience) is three times longer than a traditional search, and one in six queries is entered not as text but by voice or image.

On top of that, the phenomenon of "zero-click search" is gaining ground: the LLM gives the user a direct answer, sending them to a site only when further evidence or an actual purchase is needed. Tracking which sources get cited most often also matters — YouTube, for instance, appears as a source in 16% of LLM results, underscoring how important video content has become for AI systems.

Experts note that to keep an LLM-referred visitor from bouncing, landing pages need consistent, authoritative content, rich resources, and easy navigation. The page should let visitors verify the depth of the information and, when needed, reach a live specialist. Pushy forms with no explanation, by contrast, can send a visitor straight back out the door.

The author proposes a four-part strategy for brands. First, boost the odds of being cited by an LLM through "information superiority" — original data, independent research, and expert commentary. Second, strengthen brand presence with contextual advertising around frequently cited websites. Third, engage conversation-driven customers using dynamic conversion paths and interactive qualification tools. Fourth, revisit how traffic sources are identified — adding "how did you hear about us" fields and tracking direct-traffic metrics.

In sum, while LLM-driven traffic volume still trails traditional search traffic, its high intent and trust levels fully justify the strategic investment. That's a major opportunity especially for brands able to offer an authoritative, context-rich experience instead of aggressive, keyword-driven pitches.