Feedier uses Natural Language Processing (NLP) analysis to interpret and measure the overall sentiment of verbatim feedback.
Using NLP and sentiment analysis (weighting of five different sentiments) you can detect and analyse the sentiment of customer feedback beyond the words used. This model takes into account the question asked and the text response given, and analyses a large volume of text feedback in order to obtain a precise indicator - the Sentiment Score:
Instead of browsing all the feedbacks, you can use the sentiment score to quickly find negative or positive comments.
5 emojis are used to indicate the reputation of the most recurring keywords:
Angry: a product or service is frowned upon
Negative : a product or service is rather badly seen
Mixed: ------------------------------------------
Positive : a product or service is well appreciated
Happy : a product or service is very well appreciated
This is a weighted average made by the Feedier system between the positive and negative totals.
The model analyses the text comment, taking into account the question asked, using the 5 sentiments mentioned in this article. The sentiment score is a weighted average calculated from the scores of the most relevant sentiments in relation to the analysis carried out.
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