Explicit feedback mechanisms

Explicit feedback mechanisms give users direct channels to evaluate, correct, or enhance AI outputs. These interfaces include:

• Binary options like thumbs up/down buttons work best for quick, emotional reactions when users are unlikely to invest time in detailed feedback.
• Numeric rating scales (1-5 stars, 0-10 ratings) allow for greater nuance while remaining low-effort.
• Categorical feedback lets users specify why something worked or didn't work without open-ended writing.
• Free-form text fields for detailed feedback provide the richest information but require the highest user effort. They capture nuanced explanations, edge cases, and unexpected issues that structured formats might miss. These work best when users are highly invested in improving the system or have encountered unusual problems worth explaining.

The placement and timing of these mechanisms significantly impact response rates. Feedback requests that appear immediately after value delivery, such as right after an AI generates a helpful response, tend to receive higher engagement. The visual design matters too.