# LLM Traffic Report LLM Traffic Analytics helps you identify, quantify, and understand website sessions driven by AI assistants like ChatGPT, Claude, Gemini, and Perplexity. When you integrate with GA4, Fibr gives you a clean way to benchmark LLM vs non-LLM traffic, compare engagement quality, and spot opportunities for AEO and content expansion. *** ### Why it matters AI assistants are quickly becoming discovery channels. That changes the job for marketers and content teams. You do not just need more traffic. You need to know: * which AI platforms are sending visitors * what those visitors do after they land * whether they engage and convert differently from other channels LLM Analytics gives you one structured view so you can make decisions with real behavior and conversion data, not assumptions. *** ### Key Capabilities

Feature	Purpose
GA4 Integration	Syncs sessions, events, conversions, and referrers weekly; builds a unified dataset with 3+ months of lookback.
Traffic Identification	Detects AI referrals from OpenAI, Claude, Gemini, Perplexity, Grok, etc.; flags unknown LLM sources for review.
Total LLM Traffic	Tracks overall LLM session share, trends, and week-over-week change.
Conversion Comparison	Side-by-side LLM vs non-LLM performance to assess impact and quality.
Platform Trends	Interactive chart visualizing traffic split by AI platform with per-platform filters.
Top Platforms Table	Ranks AI sources by sessions, bounce, engagement, and conversion metrics.
Multi-Channel Comparison	Benchmarks LLM against Paid, Organic, Direct, and Social traffic for holistic performance.
Top Pages by LLM	Surfaces URLs and page groups receiving the most AI-origin traffic.
Content Topic Clustering	Groups content by topics and performance clusters to reveal gaps and scale areas of success.
Demographic Views	Breaks down LLM sessions by geo, device type, and engagement to guide localization.
Quality & Outcomes	Provides engagement quality score (0-100) to gauge traffic health and depth.
Benchmarks	Validates AI traffic quality versus traditional channels for better resourcing decisions.

### Tips from the Fibr team * Treat LLM traffic as a performance layer. Watch patterns over time before you change budgets. * Prioritize content clusters with rising LLM referrals. Early wins here compound. * Compare engagement quality, not just volume. AI visitors often behave differently from paid or organic users. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://support.fibr.ai/fibr-tools/llm-traffic-report.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.