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In the Feedier Platform, some of the data processed is unstructured data (textual feedback). Analysing this data can be tedious.
Today, Feedier uses artificial intelligence (AI) to carry out 3 types of analysis:
1: Sentiment analysis
2: Entity detection
3: Theme (topic) detection
General configuration
Feedier AI uses the context of the business to enable our models to deliver results that make sense in the operational context.
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Each verbatim analysed is assigned to a sentiment: Positive, Neutral ou Negative.
Sentiment | Explanation | Sentiment rate |
|---|---|---|
| The verbatim is linked to a positive emotion on the part of the customer: Joy, Confidence, Serenity, Admiration. | [95%-100%] |
😐 | The verbatim is not directly linked to an emotion or the emotion is not expressed strongly enough to be categorised. | 50% |
😠 | The verbatim is linked to a negative emotion on the part of the customer: Anger, Contempt, Sadness, Disgust. | [1%-5%] |
| Note |
|---|
The verbatim is analysed along with the question. It is therefore important to ask the right question to get a meaningful analysis. |
| Info |
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How is the sentiment rate calculated for a theme? This is the average of the sentiment scores for each verbatim related to a theme. |
Here are a few examples:
| 10 | 10 | 15 | 5 |
|---|---|---|---|---|
😐 Number of neutrals | 0 | 10 | 10 | 10 |
😠 Number of negatives | 0 | 10 | 5 | 10 |
Sentiment rate | ~ 100% | ~ 50% | ~ 66% | ~ 40% |
Type 2 : Entity detection
With Feedier, the "entities" extracted from the verbatims are added as attributes.
Attribute | Explanation |
|---|---|
| The value corresponds to a personal name. The value can contain the surname, first name or both. |
| The value corresponds to the name of a company in the public domain. |
| The value corresponds to company products that are not necessarily in the public domain, but are detected as being products mentioned by the customer. |
| The value corresponds to a physical location. |
| Note |
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The models may not detect 100% of entities and/or there may be a margin of error. Please do not hesitate to pass on any such information to the support@feedier.com team. |
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Track the development of themes
Organise themes by sub-theme
Filter themes using the different Feedier filters
| Best practices if you are manually adding themes to ensure effective results: |
|---|---|
| We strongly recommend that you do not use keywords in addition to the AI to recognise themes. |
| We strongly recommend using short themes that encapsulate one idea at a time. |
Only administrators and editors can create/modify/delete a theme.
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