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How does the Semantic module work?

In this article you will learn more about the Semantic module and how it works.

Where in Fidelity Suite?  

You need to go to the menu on the left and click: Semantic > Summary.

The Semantic module is an advanced tool that uses artificial intelligence to automatically analyze and detect the sentiment of comments received through surveys (Onsite and FollowUp), as well as reviews gathered in the Online module.  

In addition to identifying the overall sentiment, this tool classifies comments by specific areas or topics. This helps the hotel identify its operational strengths and its main opportunities for improvement.  

Within the Semantic module, the following indicators are measured and interpreted:

Comment Statistics:

  • Comments: Represents the total volume of texts analyzed within the selected period. The system also details the source channel of each one (Onsite surveys, FollowUp surveys, or Online reviews).

  • Mentions: A single comment can address multiple topics (for example, breakfast, the pool, or front desk service). The system breaks the comment into individual “mentions,” evaluating each one independently as positive or negative.



Semantic Index

This is a metric that calculates the percentage of positive mentions out of the total number of mentions found in customer surveys and/or reviews.

Formula: (Positive Mentions / Total Mentions) x 100

Reference Ranges:

  • Average: 79%
  • Acceptable: 88%
  • Outstanding: 93%

 

Index of Perfection

This indicator measures the percentage of completely optimal comments compared to the total volume of comments received.

  • Perfect Comment: A comment in which the system detects that 100% of its mentions are strictly positive.
  • Imperfect Comment: A comment that contains a mix of opinions, including both positive and negative mentions within the same text.

Formula: (Perfect Comments / Total Comments) x 100

Ranking of Topics and Areas

This section displays an ordered list of the concepts and departments that appear most frequently in guest interactions.

  • Topic: A specific element, keyword, or recurring concept expressed by the guest in their comment.
  • Area: The broader category or hotel department (for example, Housekeeping, Food and Beverage, or Infrastructure) to which that topic is automatically assigned.

Through this ranking, hotel management can visually identify the volume of mentions for each category and its corresponding satisfaction index, making it easier to support strategic decision-making.

Note: Because the analysis is performed using Artificial Intelligence, which is a technology in constant improvement, there is a possibility that some sentiment may be incorrectly assigned due to context or idiomatic expressions. If this happens, Administrator users can make the corresponding manual adjustments directly within the platform.