Queue｜LLMOナビにて35領域の2026年10月調査を公開

Queue’s release of its “2026 October survey covering 35 industry domains” provides the first comprehensive benchmark of AI‑generated traffic patterns across e‑commerce, media, finance, health and nine other sectors. The report reveals that bots powered by large language models now account for roughly 22 % of total pageviews in retail sites and 18 % in news portals, with a marked rise in “contextual recommendation” bots that scrape content to feed personalized chat interfaces. For website owners, this surge means a larger share of inbound requests will be flagged as LLM‑driven rather than traditional crawlers. The traffic spikes are especially pronounced during product launches and breaking news cycles, potentially inflating analytics and straining server resources. Moreover, the survey highlights that many of these bots ignore standard robots.txt directives, opting instead for domain‑wide crawling to harvest training data, which raises privacy and compliance concerns. **Actionable tips:** 1. Update your llms.txt file to explicitly list allowed and disallowed endpoints for LLM bots, using the new “Bot‑Category” tag introduced in the survey (e.g., `Bot-Category: recommendation`). 2. Implement rate‑limiting rules in your web server or CDN that trigger when a single IP exceeds the survey‑average of 1,200 LLM‑bot requests per minute, mitigating overload. 3. Integrate llmscentral’s real‑time bot‑tracking widget to tag incoming LLM traffic in your analytics dashboard, enabling accurate segmentation of human vs. AI‑generated visits.