Overview

This feature helps you understand what a Tag is and how to create and apply tags to verbatim responses in Text Analysis.

A Tag is a keyword or label used to categorize and organize open-ended responses (verbatims). It allows you to group similar responses together, making it easier to analyze patterns and extract insights from customer feedback.

Using tags helps you identify common topics, organize feedback into themes, and perform more structured sentiment and text analysis. Tags are shared across the team, so once created, they are available to all members within the project.

When to use it:
Use tags when you want to structure open-ended responses and uncover meaningful insights from customer feedback.

Start with a small set of meaningful tags and expand as patterns emerge.

Key Use Cases

• Categorize open-ended responses into themes
• Identify recurring topics in customer feedback
• Group similar responses for easier analysis
• Filter responses based on specific themes
• Improve accuracy of sentiment and text analysis

How to Use Tags

How to Access Tags

1. Go to Text Analytics
2. Click Train Verbatim
3. Open the Manage Tag section

What is a Tag

A tag acts as a label that groups similar responses together, helping you organize feedback into structured categories. This makes it easier to analyze trends, filter responses, and understand customer sentiment at scale.

Since tags are shared across the team, any tag created by one member becomes available to everyone working on the project.

Create Tags

Tags can be created directly from the Train Verbatim section using multiple methods depending on your needs.

Available Methods:

• Generate AI Tags – Automatically generate tag suggestions based on responses
• Add Tags Manually – Create custom tags with full control
• Import from Survey – Reuse tags from existing surveys
• Import from CSV – Upload tags in bulk using a file

Generate AI Tags

AI can suggest relevant tags based on your survey responses, helping you quickly create meaningful categories.

AI-generated tags are a great starting point but should be reviewed for accuracy and relevance.

Add Tags Manually

Manual tag creation gives you full control over how responses are categorized.

To create a tag manually, go to Add Tags → Add Tags Manually. In the tag creation window, enter the tag name, optionally add a description, and include relevant keywords separated by commas.

Once saved, the tag becomes available for use across the project. 

Keywords improve automatic tagging by matching common terms in responses.

Import Tags from Survey

You can reuse tags from other surveys within the platform to maintain consistency.

To do this, go to Add Tags → Import from Survey, search and select the survey, choose the relevant questions, and review the available tags before importing them.

Import Tags Using CSV

If you already have a predefined list of tags, you can upload them using a CSV file.

Go to Add Tags → Import from CSV, download the template, update it with your tag details, and upload the file either by dragging and dropping or selecting it manually.

Ensure your CSV format matches the template to avoid import errors.

Apply Tags to Verbatim Responses

Once tags are created, they can be applied directly to verbatim responses during training.

Navigate to Train Verbatim and locate the response you want to categorize. Click the + icon next to tags, then either select an existing tag or create a new one by typing its name.

Manage Tags

The Manage Tag section allows you to view and organize all tags in one place.

Here, you can see all created tags, check how many verbatims are linked to each tag, search for specific tags, and organize your tagging structure for better analysis.

This ensures your tagging system remains structured and easy to use as your dataset grows.

Best Practices for Tagging

Using tags effectively is key to getting meaningful insights from text analysis.

• Start with 5–10 key tags to keep analysis simple
• Use clear and descriptive tag names
• Add keywords to automate tagging where possible
• Review verbatims before finalizing your tagging structure

Build your tagging structure gradually based on real feedback patterns rather than defining everything upfront.