Text Analysis

Text Analysis

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

  • Analyze large volumes of open-ended survey responses efficiently
  • Automatically generate tags based on recurring themes in responses
  • Categorize feedback into Positive, Neutral, and Negative sentiments
  • Identify key strengths, pain points, and emerging issues
  • Track how customer feedback changes over time
  • 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
    • Automatically detects themes and groups similar responses
    • Creates structured categories (tags) for easier analysis
  • Run Sentiment Analysis
    • Classifies responses into:
      • Positive
      • Neutral
      • Negative
    • Helps quickly gauge overall customer perception

Understanding the Dashboard

After running analysis, you can explore insights through multiple visualizations:

  • Tag Overview
    • Shows distribution, volume, and performance of different tags
    • Highlights which topics are most discussed
  • Sentiment Summary
    • Displays overall sentiment distribution across responses
  • Top Positive & Negative Tags
    • Identifies what users like most and key areas of concern
  • Tag Volume Change
    • Tracks which topics are increasing or decreasing over time
  • Trend Analysis (Tags Trend)
    • Visualizes how feedback evolves across time periods
  • Verbatim Responses
    • View individual responses along with assigned tags and sentiment

Working with Verbatim

  • View and analyze individual responses in detail
  • Edit, add, or remove tags manually
  • Filter responses by:
    • Tags
    • Sentiment
    • Time period or other mapped fields
  • Search specific keywords to find relevant feedback
  • Train the model by refining tags for better accuracy over time

Important Features

  • AI Tagging – Automatically categorizes responses into meaningful themes
  • Sentiment Classification – Instantly understand customer mood and perception
  • Custom Tag Management – Create, edit, and organize tags as needed
  • Filtering & Segmentation – Narrow down insights using multiple filters
  • Search Functionality – Quickly find specific responses or topics
  • Trend Tracking – Monitor how feedback changes over time
  • Model Training (Train Verbatim) – Improve tagging accuracy by refining outputs

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