> For the complete documentation index, see [llms.txt](https://docs.new-vue.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.new-vue.com/visual-guides/guestexperience/surveys.md).

# Surveys

{% embed url="<https://app.supademo.com/demo/cmuefki4a0003uo0jcwjqt2zh?v_name=Gitbook&v_email=EMAIL&v_company=COMPANY&utm_source=link>" %}

### Overview

This page shows guest satisfaction based on post-visit surveys, with a focus on how likely guests are to recommend a visit to others.

{% hint style="info" icon="alt" %}
Calculations Used In This Report

* [NPS Score](/glossary/calculations/guest-experience-calculations.md#nps-to-date)
* [NPS To Date](/glossary/calculations/guest-experience-calculations.md#nps-to-date)
* [NPS YTD - Cards](/glossary/calculations/guest-experience-calculations.md#nps-ytd-cards)
* [NPS YTD LY - Cards](/glossary/calculations/guest-experience-calculations.md#nps-ytd-ly-cards)
* [Number of Surveys YTD - Cards](/glossary/calculations/guest-experience-calculations.md#number-of-surveys-ytd-cards)
* [Number of Surveys YTD LY - Cards](/glossary/calculations/guest-experience-calculations.md#number-of-surveys-ytd-ly-cards)
* [Survey Responses](/glossary/calculations/guest-experience-calculations.md#survey-responses)
  {% endhint %}

### Recommendation Score Year-to-Date

This card compares how likely guests are to recommend a visit so far this season with the same point last season. It gives leadership a quick way to see if guest loyalty is improving year over year without having to look at the full trend chart.

### Survey Responses Year-to-Date

This card shows how many surveys have been completed so far this season compared to the same time last season. It helps you see if your survey program is reaching more guests, which affects how much you can trust the recommendation score above.

### Survey Volume and Recommendation Score Trend

This chart shows monthly survey responses and how likely guests were to recommend a visit during each month. It also includes a running average to smooth out month-to-month changes. This helps you see if changes in guest loyalty match up with changes in the number of survey responses. A real shift in guest sentiment should appear as a change in the score, not just in the number of responses.