Signal, Sentiments and Intentions

When feedback data is ingested into Birdie, it undergoes an AI-powered enrichment process to extract deeper meaning and structure from unstructured text. This process classifies each feedback entry based on three complementary dimensions:

• Signal – whether the feedback contains valuable, actionable content

• Sentiment – the emotional tone expressed in the feedback

• Intention – the purpose or intent behind what the user is saying

These classifications help filter out irrelevant inputs, highlight meaningful themes, and enable smarter analysis across teams.

Signal Detection

Definition

The goal of Signal Detection is to filter out irrelevant or low-quality feedback (referred to as "noise") and retain only the valuable content (referred to as "signal") that contains meaningful information for analysis.

Purpose

This task ensures we focus our analysis only on feedback that contributes actionable insights, improving model performance and dashboard relevance.

Examples

• Noise: “Good morning!” (greeting), “#@@#” (nonsense), “Good” (too short)

• Signal: “The new feature is useful.”, “I need help to understand this…”

Sentiment

Birdie’s AI identifies and tags sentiments expressed in feedback. Each piece of feedback may include more than one sentiment, and Birdie classifies them accordingly.

Sentiment	Sentiment Level	Description
Positive	Only positive	All feedback sentences contain only positive sentiments
	Mostly positive	More than half of the feedback sentences contain positive sentiment, even if combined with other sentiments.
	Any Positive	There is some mention containing positive sentiment in the feedback sentences.
Neutral	Only Neutral	All feedback sentences contain only neutral sentiment.
	Mostly Neutral	More than half of the feedback sentences contain neutral sentiment, even if combined with other sentiments.
	Any Neutral	There is some mention containing neutral sentiment in the feedback sentences.
Negative	Only Negative	All feedback sentences contain only negative sentiment.
	Mostly Negative	More than half of the feedback sentences contain negative sentiment, even if combined with other sentiments.
	Any Negative	There is some mention containing negative sentiment in the feedback sentences.

Intention

Intention classification captures the underlying purpose of what the user is expressing. A single feedback entry may include multiple intentions.

Intention	Description
Compliment	Sentences that express admiration or positive recognition regarding some aspect of the product or service.
Problem	Sentences that express a problematic situation, difficulty, or challenge that the feedback author is facing.
Question	Sentences that seek specific information or clarifications and are generally formatted as a question.
Request	Sentences that express a request, desire, or need for something.
Information	Sentences that provide information or clarifications without necessarily expecting a response. Similar to a neutral description of a situation before mentioning a Praise or Problem.
Solution	Sentences that propose a response, solution, or method to resolve a Problem or situation presented by the feedback author.