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AI assistants are quietly reshaping how people discover products and documentation online. But most analytics systems treat AI bot traffic as noise, filtering it out instead of learning from it. In this episode/article, we explore how to uncover real user intent hidden inside AI assistant traffic and turn bot logs into actionable insights for product and SEO teams.

You’ll learn:

* Why AI assistant traffic is fundamentally different from traditional bot traffic, and why filtering it out creates a major blind spot in modern analytics

* How prompts sent to tools like ChatGPT, Claude, or Perplexity translate into bot visits, and what these patterns reveal about real user questions, product research, and integration needs

* A practical framework for analyzing AI bot logs, helping teams extract user intent signals that can inform documentation improvements, product decisions, and SEO strategy

If you’d rather read than listen, the full article (with diagrams, code examples, and implementation details) is available on Substack:

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PODCAST — Understanding User Intent Through AI Bot Traffic: A Practical Framework