Text Analytics

Text Analytics is the set of techniques HR teams use to analyze unstructured text such as CVs, employee surveys, chat logs and performance notes to extract actionable insights.

What is Text Analytics

Text analytics combines linguistic rules and statistical models to convert words into measurable data. In HR it turns free text into themes, sentiment scores and named entities like skills or roles.

How does it work

Common methods include natural language processing, sentiment analysis, keyword extraction and topic modelling. These methods classify text, detect trends and highlight risk or opportunity areas for people decisions.

Extracting trends from open text improves hiring, engagement and risk management.

Practical usage in HR

Where and why it is used:

• Recruitment: screen resumes and surface relevant skills at scale
• Employee experience: analyze survey comments to guide engagement programs
• Compliance and risk: detect concerning language in reports or communications
• Performance and L&D: identify skills gaps from manager notes

Related HR concepts

Text analytics is closely tied to people analytics, HR analytics, sentiment analysis and resume parsing. It often complements Applicant Tracking Systems and workforce analytics to improve talent decisions.