Feature #02


Thumbs up/down are rare. Instead, implicit user feedback is abundant and can be derived from the subtle nuances embedded within conversations, linguistic cues and tone.

Automatically extract every bit of user feedback to improve your LLMs.

The user feedback feature efficiently gathers and analyzes all forms of feedback from users interacting with your language models. While explicit feedback, such as thumbs up or thumbs down, is straightforward but rare, implicit feedback, which is subtly embedded in the nuances of user conversations, is rich and abundant.

‍This feature automatically organizes user feedback into four distinct categories, each providing valuable insights:

• Negative Implicit Feedback
This category captures subtle indications of dissatisfaction or problems that are not directly stated by users but can be inferred from their interactions, such as abrupt conversation endings or critical language usage.

• Positive Implicit Feedback
Includes subtle cues within conversations that indicate approval or satisfaction, such as continued engagement or complimentary language, even if not directly expressed.

• Negative Explicit Feedback
Involves direct expressions of dissatisfaction or complaints, such as users giving a thumbs down or writing negative comments.

• Positive Explicit Feedback
Consists of direct affirmations or praise from users, such as thumbs up or positive ratings.