Table of contents :
1. Sentiment analysis
It is an automatic analysis of texts. This analysis detects the feelings expressed in the texts written by your customers. The objective is to facilitate your analysis work.
2. The 5 possible statuses
Positive: a positive emotion is detected. These are often beautiful testimonials from your customers. This is the type of text you want to share with your employees and concerned people.
Negative: a negative emotion is present. These texts are often constructive.
Mixed: both a positive and a negative emotion are present. These texts will often contain a conjunction such as 'but', 'against', etc.
Neutral: no sentiment detected. The text is rather descriptive or informative.
No text: no text has been written by the client.
3. How does it work
This analysis is done automatically by artificial intelligence. Essentially, a robot is trained to determine the sentiment expressed in a text, in English or in French.
The training is based on the analysis of millions of texts, so it is very accurate.
4. How it is presented in InputKit
In the list of answers
In the feedback forms
In the comments report
In a sentiment report (available soon)
To go further
Not only does this analysis make your work easier and save you a lot of time, it will also allow you to go further.
All positive comments can be automatically sent to the employees associated with the file. The goal is to ensure that all the great comments and testimonials end up in the eyes of the right people: your employees who are working hard to provide the best possible experience. By having more positive feedback on their work, you will have more motivated employees who are more aware of the quality of their work.
What do you think of this new feature?
Don't hesitate to write to us, your feedback helps us to improve the InputKit solution.