How to track AI agent access to your website

AI systems can request pages from your website without producing the browser events used by ordinary web analytics. To understand this activity, start with the requests reaching your website infrastructure.

Salespeak Agent Analytics helps teams examine AI agent access to their websites. The useful starting point is concrete: which pages were requested, by which classified agents, and when.

Separate agent access from human referrals

An agent request is an access event. A human referral is a person arriving through a link from an AI service. These are different observations and belong in different reports.

A requested page was accessed. That does not establish that its contents appeared in a final answer, that the answer cited the page, or that a particular buyer saw it.

Likewise, an agent request does not expose the buyer's actual question. A visit to a pricing page may suggest an evaluation topic, but the topic is an inference.

Collect evidence at the appropriate layer

Browser analytics remain useful for human visits and conversions. For agent requests that do not execute browser JavaScript, examine data available at the server, edge or CDN.

Use a supported integration for your environment. Confirm which requests it covers, when collection began, how agents are classified and which verification signals are available. A user-agent string by itself should not be treated as unquestionable proof of identity.

Avoid comparing periods with different collection coverage without labeling the change.

Review the pages agents access

Start with product, pricing, documentation and comparison pages. Look for repeated access, changes over time and important pages that do not appear in the observed activity.

Then inspect the information available on those pages. Are product descriptions consistent? Are old prices still visible? Does the page explain limitations as clearly as capabilities?

Request activity can help prioritize this review. It cannot tell you exactly how an AI system interpreted each statement.

Turn observations into a useful action

Choose a page with a concrete information problem. Record the issue, make the approved correction and note when it went live.

Compare access before and after the change using consistent definitions and time windows. Account for collection changes, seasonality and shifts in agent behavior. A change in requests alone is not proof that your edit caused an improvement in answers or revenue.

For work on the information available to agents, explore Agent Optimizer. Keep that implementation work separate from claims about what an external AI system ultimately says.

Keep the measurement boundary clear

Use agent analytics to report observed access. Use human analytics to report referrals and conversions under their own attribution rules. Use a separate answer-evaluation process to assess answers or citations.

Salespeak cannot connect an individual agent request to a specific human visitor or deal. Presenting those measures separately keeps a useful signal from becoming an unsupported attribution claim.

Explore Agent Analytics to understand the agent access your website can observe.