AesirX Features: Consent Behavior Metrics

Most consent tools reduce user behavior to a single opt-in rate, which hides how consent is actually applied and changed. This makes it difficult to understand whether users are actively accepting consent, selectively allowing categories, relying on default settings, or withdrawing consent later. Without this clarity, changes in data availability are often misattributed to technical issues or campaign performance rather than consent behavior.

Consent Behavior Metrics addresses this by showing a structured breakdown of consent states, including opt-in, opt-out, partial consent, rejection, and revocation. These states are recorded as they occur, reflecting both explicit user actions and default consent models applied through configuration or regional rules. From a technical perspective, the data is derived directly from consent state changes within the CMP, rather than inferred signals or secondary analytics.

This visibility allows organizations to review how consent choices evolve over time, identify patterns that may indicate friction or disengagement, and better contextualize shifts in analytics data. It also supports clearer internal and external reporting by grounding explanations in observable consent behavior. Over time, these insights help teams refine consent design and decision-making based on measured patterns, without relying on assumptions about user intent.