What belongs in an AI agent traffic log for a storefront
Merchants already log search crawlers and bot traffic. AI shopping agents deserve their own structured record, because their visits turn into orders, refunds, and support tickets. A storefront that cannot attribute agent traffic cannot set policy for it.
The identity claim, and the evidence behind it
Every entry should start with what the visitor claimed to be: the user-agent string, any declared agent or assistant name, and whether it presented a credential such as an authenticated API key, a signed token, or a verified checkout grant. The claim and the evidence are different fields. An unauthenticated user-agent that says "shopping-assistant" goes in one bucket; a request carrying a verified session for a named assistant goes in another. If you cannot separate these two in your logs, you cannot enforce any rule about them.
What it did, in sequence
Log the session as a sequence: pages read, product data pulled, prices and inventory checked, carts created or modified, and whether a checkout was attempted, completed, or abandoned. Include timestamps and the session or token identifier so the whole journey reconstructs. Agent sessions look different from human ones: they read specs systematically, compare variants programmatically, and rarely trigger the scroll and hover events human analytics expect. Sequence-level logging is what lets you see the difference.
The outcome that matters
Each agent session should end with an outcome record: completed order (with order reference), abandoned cart, failed checkout (with the failure reason), or read-only browsing. Failed checkouts deserve detail, because agent failures cluster around specific steps: address validation mismatches, payment method declines, coupon application errors, or CAPTCHA and bot-challenge blocks. If your bot defenses are stopping legitimate agents, the log is where you will notice.
What to exclude
Do not log full card numbers, CVVs, or authentication secrets in agent traffic logs. Payment instrument details belong in the payment processor's vault, not in your request logs. Strip PII to what attribution needs: the pseudonymous identity of the agent, the claimed user authorization scope, and the transaction outcome. Logs with less personal data survive security reviews and data requests with fewer problems.
Reviewing the log like a channel report
Once the log exists, review it weekly like any other channel report. Which claimed agents visit most? What share of sessions authenticate? Where do agent checkouts fail? Which products do agents read but never buy? The answers feed policy: rate limits per agent class, which user-agents earn trusted status, where the checkout flow needs an agent-friendly path, and whether AI-driven traffic is a channel worth courting or a cost worth capping. Stores that treat agent traffic as a reportable channel will set the terms. Stores that do not will discover the terms set for them.
How long to keep the log
Retain raw agent traffic logs long enough to spot patterns and answer questions: ninety days of request-level detail, twelve months of aggregated session summaries. Ninety days covers most billing disputes, refund investigations, and bot-incident reviews. Aggregated summaries, sessions per claimed agent, completion rates, and failure categories by week, stay useful for a full year of policy decisions. Anything older than that is for trend historians, not operators. Whatever retention you choose, write it down as policy, because a log with no retention rule either grows forever or gets deleted on someone's whim.