Introduction
Open-ended comments provide valuable insights into the consumer's perception of a product, and help in identifying areas for improvement. However, analyzing such comments can be time-consuming and challenging. With remark labeling, the comments can be easily categorized and analyzed, which saves time and effort while providing meaningful insights.
This feature require panelists to provide detailed feedback about a product using a remark question type, which can be labeled and analyzed to extract meaningful insights.
With this functionality, users can assign specific labels to open-ended comments that panelists have provided about a product. These labels can be anything from positive or negative sentiments, to specific product characteristics or attributes. Once the comments have been labeled, the labels can be used as categories to analyze the frequency of the mentions of a particular product for that specific label using EyeOpenR.
Set Up Your Questionnaire
To use the Remark Labelling functionality the questionnaire must contain at least one question of the type General Question --> G-Text or H- Remark/Comment which allows you to collect open ended answer from your consumers or panelists.
When answers have been collected, go to the Data tab and select Remark Labeling.
You can select from the dropdown list and click on apply Labels Manually.
Select the question you want to add the labels to. Select the remark question type and add the labels for the question with shared attributes.
Select the label you want to allocate to which specific comment and click "Confirm".
Analysis through EyeOpenR
Once have you labeled all your remarks, the data can be analyzed in EyeOpenR. Open EyeOpenR directly from the project in the Data tab, by clicking the icon.
Data can be threated as CATA data, and analysis such as the Cochran and McNemar analysis can be done.
In Counts (pairwise): The table and graph display the number of times a label appears per product.