Analytics measurement and metrics
How to identify bot traffic in website analytics
Recognise suspicious traffic patterns and keep automated visits from distorting decisions.
Automated requests can inflate visits or trigger events, but unusual traffic is not always malicious. Diagnose carefully before excluding a source or blocking legitimate services.
Look for combinations of clues
Sudden spikes, identical paths, impossible interaction patterns and unusual user-agent or hosting characteristics can warrant review. No single clue proves a bot. Compare server logs, analytics events and known monitoring or preview tools where available.
Put it into practice
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Use maintained bot filtering where appropriate and keep security controls separate from analytics exclusions. Ensure prefetching and link previews do not trigger conversion events. Document filtering rules because they change historical totals and can remove legitimate traffic if too broad.
Validate the business impact
Check whether suspicious activity changes a decision-relevant metric such as conversion rate or campaign cost. Report both filtered rules and remaining uncertainty. If abuse affects the application, involve the security and infrastructure owners rather than trying to solve it with a dashboard filter alone.