Webropol AI Text Analysis – Analyse free text responses quickly and efficiently

Employee surveys are a powerful tool for collecting feedback from employees and gaining insights into the work environment, engagement and other key factors that influence organisational performance. Traditionally, analysing these surveys has been time-consuming and resource intensive, especially when it comes to handling large amounts of free-text responses. However, with advances in artificial intelligence (AI) and sentiment analysis, it has become possible to analyse large quantities of text in a more efficient and insightful way.

Sentiment analysis is a process that uses AI and machine learning to identify and extract subjective information from text data. This means that the system can determine whether a piece of text expresses a positive, negative or neutral sentiment. In the context of employee surveys, sentiment analysis provides an overall picture of how employees feel about different aspects of their work and work environment.

What are the benefits of Webropol AI Text Analysis?

One of the most obvious benefits of Webropol’s AI based sentiment analysis is its ability to process large amounts of text data quickly and efficiently. Where previously significant time and resources were required for manual analysis, AI systems can now analyse thousands of survey responses in minutes. This allows organisations to quickly react to feedback and act based on the insights.

Manual analysis of text data can be subjective and varies depending on the person performing the analysis. Webropol’s AI based sentiment analysis eliminates this subjectivity by using algorithms that apply the same criteria consistently to all free text responses. This ensures that results are objective and comparable over time.

Webropol’s AI Text Analysis is particularly adept at identifying patterns and trends that can be difficult to detect manually. By analysing sentiment over time, organisations can identify changes in employee attitudes and feelings, which can be early warning signs of potential problems or areas that need improvement.

By combining sentiment analysis with background data, such as length of service, department, job role or previous survey results, organisations can gain a much deeper understanding of the feedback. For example, it may turn out that employees in a particular department consistently experience higher levels of stress, or that new employees are less engaged than those who have been around longer.

Webropol’s AI Text Analysis immediately creates a summary of the content and essence of the free text responses, providing quick and clear insight into what employees are expressing. This provides valuable insights and an excellent starting point for further analysis of free text responses.

Book a demo and experience the future of text analysis today!