> ## Documentation Index
> Fetch the complete documentation index at: https://docs.guidewhale.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Happiness

> Analyze how satisfied users are with your application and how likely they are to recommend it to others.

## Why it Matters

High happiness scores indicate happy, loyal users who are more likely to advocate for your product and renew subscriptions.

Analyzing NPS score response reasons can give you a clearer picture about the sentiment of your users and help you identify areas for improvement.

## Definition

Happiness score is calculated by normalizing the 90-day rolling NPS score into a 0-100 scale.

$\text{Happiness Score} = \dfrac{\text{Rolling NPS Score + 100}}{\text{200}}$

## Analytics

* **Rolling Happiness Score:** normalized 90-day rolling NPS score.
* **Total Responses:** how many times your users have answered selected NPS surveys.
* **Unique Users:** how many users answered selected NPS surveys.
* **Happy Users:** how many of your users are promoters in the selected period.
* **Net Promoter Score (NPS) Chart:** shows NPS score percentages and the final calculated rolling 90-day NPS score over time. This chart helps you identify trends and patterns in user satisfaction and loyalty.
* **Score Distribution Chart:** shows distribution of NPS survey answers for the selected period.
* **Recent Responses Table:** displays individual survey responses along with the reasons users provided for their score, helping you understand user sentiment and identify areas for improvement.

## Filters

* **NPS Survey:** select either all or specific NPS surveys to analyze.
* **User Segment:** select either all users or a specific user segment.
* **Date Range:** period during which to analyze user happiness.