Traffic sources and attribution
How to measure traffic from AI assistants
Identify visible AI referrals carefully and evaluate whether those visits match your goals.
Visits from AI assistants can be difficult to classify consistently because referrers vary and some journeys arrive without a usable source. Treat the report as a partial view.
Define what counts as an AI referral
Create an explicit, maintainable list of referrer domains and review it periodically. Do not label all direct traffic as AI traffic; direct means the source was not identified under your rules. Campaign parameters can help when you control the link, but cannot recover every untagged recommendation.
Put it into practice
See your traffic, funnel steps and site performance clearly in Alexander.
Try Alexander freeStudy the landing experience
Compare landing pages, engaged actions and outcomes for identified visits. Many visitors arrive with a focused question, so a clear answer and relevant next resource may matter more than broad browsing. Small volumes and changing referral behaviour make short-term rate comparisons unstable.
Use the evidence without overclaiming
Record the classification rule, date range and known gaps. Combine observed referrals with customer research and search performance. Keep content accurate and useful for people; do not invent a separate optimisation trick based on a handful of visits.