Two kinds of traffic, one name
When people say ChatGPT traffic they usually mean one of two things, and the distinction is not pedantic: they arrive by different mechanisms, are recorded by different systems, and are worth different amounts.
| Agent fetches | Referred humans | |
|---|---|---|
| What it is | The assistant requesting your page | A person clicking a link in an answer |
| Runs JavaScript | No | Yes |
| Visible in analytics | Never | Yes, as a referrer |
| Where it is visible | Your server logs | Your analytics |
| Typical volume | Higher | Lower |
| What it is worth | It decides whether you get recommended | Direct conversion |
Seeing the agent half
It comes from your own request log, which makes it exact rather than sampled. What you want out of it is four things, and all four are properties of your infrastructure rather than estimates of somebody else’s.
- Which platforms fetched you, classified from real header samples rather than guesswork.
- What you served each one: the format, the size and the render time.
- Your answer rate: how many of those requests produced something useful.
- The miss log: the URLs they asked for and did not get, ranked by frequency.
The miss log is the one worth acting on first. It is a list of things the market asked you for, in the order it asked, which is a rarer artefact than it sounds.
The referred half, and why it converts
People arriving from an assistant have usually had their question answered already and are arriving to act rather than to browse. Retail measurement over Cyber Week 2025 put the conversion rate of AI-referred visitors around 38% above search-referred ones.
That is the commercial argument for the agent half: the fetch is what decides whether the recommendation happens, and the referral is what you collect afterwards. Optimising the second without the first is collecting from a funnel you never filled.