AI crawler analytics
Measurement of confirmed AI-bot visits to a website.
What is AI crawler analytics?
Crawler analytics records pages requested, bot identity, response status, frequency, and time. It shows discovery behavior, not whether the content was used for training or cited in a particular answer.
In practiceWhat does this look like in a real AI answer?
A documentation release receives a spike in verified AI crawler requests over the following week.
Why it matters for AI visibility
AI answers can shape awareness and buying decisions before a person visits a website. Understanding ai crawler analytics helps teams connect what a model says with the prompts, sources, and technical signals that influenced the result. The useful next step is to observe the evidence, compare it over time, and act on the specific gap.
How to measure or use it
- Define the scope. Choose the relevant market, prompts, models, locations, and time window.
- Keep the evidence. Save the complete answer, its citations, and the page or claim being evaluated.
- Compare patterns. Look for repeated movement across prompts and models instead of reacting to one response.
- Take a specific action. Improve the owned page, correct a claim, earn third-party inclusion, or create better evidence.