Agentic browsers blur the line between human and automated behavior. Traditional analytics tools assume traffic is either bot activity (typically ignored) or human visitors (analyzed). Agents complicate this picture because they act on behalf of users, so their activity shouldn’t be ignored, but they don’t represent direct human interaction either.  

Context matters too. An agent crawling a retailer site for competitor pricing data isn’t customer activity. It’s competitive intelligence gathering, and should be treated differently. An agent helping a customer compare products or complete a purchase, by contrast, represents genuine demand and should be analyzed alongside other customer data to understand experience, intent, and monetization. 

Sessions may also transition from human-driven interaction to agent-driven execution mid-stream. Legacy tools typically record this as a single continuous session, making it impossible to understand when or how behavior changed. Snowplow enables companies to detect these shifts by analyzing event-level interaction patterns, allowing human and agent activity to be measured and interpreted separately.