Text Analysis Module
Overview
The Text Analysis module helps you analyze open-ended (text) responses from your surveys using AI. Instead of manually reading through hundreds of responses, the system automatically groups feedback into meaningful themes (tags) and classifies sentiment. This allows you to quickly understand what customers are saying, identify patterns, and extract actionable insights from unstructured data.
Key Use Cases
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Analyze large volumes of open-ended survey responses efficiently
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Automatically generate tags based on recurring themes in responses
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Categorize feedback into Positive, Neutral, and Negative sentiments
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Identify key strengths, pain points, and emerging issues
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Track how customer feedback changes over time
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Drill down into specific responses for deeper understanding
Creating a Text Analysis Project
How to Get Started
To get started, go to Text Analysis, create a project by giving it a name, upload your CSV file, map the relevant fields such as response text and metadata, and save the project to begin analysis.
Running Analysis
Once your project is set up, you can start analyzing data using AI:
Run Tag Analysis
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Automatically detects themes and groups similar responses
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Creates structured categories (tags) for easier analysis
Run Sentiment Analysis
Understanding the Dashboard
After running analysis, you can explore insights through multiple visualizations:
Working with Verbatim
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View and analyze individual responses in detail
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Edit, add, or remove tags manually
Filter responses by:
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Tags
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Sentiment
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Time period or other mapped fields
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Search specific keywords to find relevant feedback
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Train the model by refining tags for better accuracy over time
Important Features
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AI Tagging – Automatically categorizes responses into meaningful themes
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Sentiment Classification – Instantly understand customer mood and perception
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Custom Tag Management – Create, edit, and organize tags as needed
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Filtering & Segmentation – Narrow down insights using multiple filters
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Search Functionality – Quickly find specific responses or topics
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Trend Tracking – Monitor how feedback changes over time
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Model Training (Train Verbatim) – Improve tagging accuracy by refining outputs