Text Analytics
AI-Powered Insight Extraction from Unstructured Text
Text Analytics helps organizations turn reviews, support tickets, surveys, and customer conversations into structured insight. It reveals sentiment, topics, entities, and emerging issues so teams can act on what customers are actually saying instead of letting critical signals go untouched.
The Gap in Business Insight Extraction
Organizations generate huge volumes of reviews, support tickets, surveys, and customer conversations every day. Without an intelligent system to process this data, valuable insights remain hidden and manual analysis becomes too slow and inconsistent to support modern decision-making.
Challenges Organizations Face
Feedback piles up without being analyzed, teams miss sentiment changes and emerging issues, survey and support data rarely informs strategy, and multilingual text creates extra complexity for consistent insight extraction.
How It Works
Sentiment Analysis Engine
Classification models detect positive, neutral, and negative signals across reviews, feedback, and survey responses.
Named Entity Recognition
NER identifies brands, people, products, and locations to add structure and meaning to raw text.
Topic Modeling
LDA and BERTopic group large text datasets into emerging themes without manual tagging.
Multi-Language Processing
Transformer-based language models support consistent insight extraction across regional and global markets.
Key Features
- ✔ Voice of customer insight from large text collections
- ✔ Faster issue detection through real-time sentiment shifts
- ✔ Structured entity and topic extraction from unstructured data
- ✔ Competitive intelligence from brand and competitor mentions
- ✔ Multi-language analysis for regional and global operations
Technology & Intelligence
Text Analytics uses transformer-based language models for sentiment, entity, and intent recognition, together with topic modeling techniques such as LDA and BERTopic to uncover hidden themes and trends across large volumes of unstructured text.
Industry Use Cases
Customer support and contact center teams
Product, marketing, and CX organizations
Survey, feedback, and research operations
Global teams handling multilingual customer text
Business Impact
Clearer voice-of-customer signals for product, marketing, and CX teams
Faster issue detection from sentiment shifts and topic changes
More confident strategy decisions grounded in large-scale text insight
Better competitive intelligence through brand and competitor monitoring
Conclusion
Your company handles huge volumes of communication, customer reviews, and feedback every day, but much of it goes unread. Codework's Text Analytics turns that unstructured text into precise, actionable insights so teams can make faster and better decisions based on what customers are actually saying.
Get a Personalized Demo of Text Analytics.