Topic Analysis and Retagging

With the digitization of HR in recent times, there has been a surge in many tools and models, to help us understand our employees better. It is all about data, now more than ever. We, at EngageRocket, take pride in presenting data in the most usable way through Topic Analysis and Retagging, an artificial intelligence model to make your data cleaner and easier to act on.

Topic Analysis is a natural language processing (NLP) technique that automatically tags relevant topics to open ended text responses. One can save hours of manual work and effort to skim through the thousands of responses - EngageRocket now does it all for you.

When toggled on, all responses to open-ended questions are tagged to relevant topics, thus making the data easier for leaders to view.

Seen below is a sample of how responses are tagged to topics:

image

In addition, you may add, remove or edit the topic assigned to a response simply by clicking on the Edit button. This provides you with the flexibility to include custom topics, that are relevant to your organization context.

Screenshot 2022-01-26 104611

It's 2022 and we at EngageRocket are excited about all that we have planned for you this year. Along with a new set of HR solutions focused on retaining employees, we are also soon upgrading to a research backed State-of-the-art (SoTA) Natural Language Processing (NLP) that's going to help reduce your workload.

This model is trained off hundreds of thousands of employee information and covers over 75 languages.

To know more on how to use this feature on EngageRocket, refer to this step-by-step guide on Topic analysis for open-ended responses or reach out to your Customer Success Manager.

Did this answer your question?