Sentiment Analysis Helps a Company Keep Staff Engagement High

Risk Management, Sentiment Analysis, Social Media Analysis

Sentiment Analysis for Employee Engagement

Staff Engagement Is Critical to a Company’s Success

Due to the COVID-19 pandemic millions of people left the labor market for various reasons: layoffs, fear of contracting Covid, minding kids during school lockdowns, etc.  Many industries are still struggling to find workers even as the job market has improved overall.

In this uncertain environment it’s critically important that companies figure out how to engage their current work forces better so as to improve their overall well-being and retention. Complicating this situation is the shift to remote work, which looks to be permanent. How can companies maintain high levels of employee engagement in a remote or partially remote work force?

Measuring Your Staff’s Level of Engagement

A first step is simply figuring out how to measure engagement. There is a concept, termed Level of Engagement, which has been around for a while. The Gallup Organization publishes annual surveys of employee engagement, generally divided into “Actively Engaged,” “Not Engaged,” and “Actively Disengaged.” The first category are the passionate employees with a strong connection to their company. The second are the ones who are checked out and sleepwalking through the day. The third are vocal about their unhappiness: they undermine all the productive activities of the company.

HR departments have to stay on top of this issue and make sure the most engaged employees remain strong advocates of the company while investigating and addressing the root causes of disengagement. In the past HR relied mainly on formal employee surveys conducted infrequently to gauge employee engagement. They tended to be long and unfocused and many employees didn’t want to take the time to respond. Now with the digitizing of the workplace, it is much easier to gather data from employees. For example:

  • Short pulse surveys, which are routinely sent via email at short intervals, e.g., monthly, and contain a small number of focused questions;
  • Anonymous feedback channels: for example, employers can offer a feedback app for the employees’ phones; a phone app is an ideal way to encourage quick feedback and it gets away from the tedious drawbacks of a long survey; it also allows employees to introduce their own topics; in all of this, of course, a company has to ensure privacy.

The formal survey is not to be abandoned, but it may need to focus more on free-flowing, textual feedback than just circling numbers. Finally, one very valuable source of data is that derived from exit interviews. Departing employees will be more likely to offer honest, unvarnished opinions.

Using Sentiment Analysis to Increase Employee Engagement

Given the volume of textual data that is generated by the above sources, organizations need automated help. Fortunately, an AI-based technology, Sentiment Analysis, exists that can help employers understand their work forces better – what causes dissatisfaction, what makes valuable employees leave, how to increase their levels of engagement. Obviously pay and benefits are among the main causes of employee unhappiness, but employees may also want greater control over their career paths, and perhaps most critically employees may want to know they are doing something that matters. A host of other issues may exist.

Sentiment Analysis can provide a holistic view of the status of staff engagement. Sentiment Analysis identifies the emotional attitudes of employees based on the unstructured text they produce.

The first generation of Sentiment Analysis products simply categorized texts or sentences as negative or positive or neutral. However, this approach couldn’t figure out exactly what is it that people feel positive or negative about.

The most recent generation of Sentiment Analysis products employ Machine Learning and AI techniques to analyze the linguistic context and derive a much more fine-grained analysis of the sentiment. This is known as Entity-Based Sentiment Analysis.

How Entity-Based Sentiment Analysis Can Be Used to Gauge the Level of Employee Engagement

Here’s a typical comment that an employee might make in an exit survey:

“I find the 401K match here to be good, but the pay is not competitive with the rest of the industry.”

There are two sentiments expressed here, one positive and one negative. The output of a Sentiment Analysis product would look like this:

  • sentiment: positive
  • sentiment predicate: good
  • entity: 401K match


  • sentiment: negative
  • sentiment predicate: not competitive
  • entity: pay

The two unstructured sentiments expressed by the employee have been normalized and transformed into structured data which can then be quantified and aggregated over a very large set of such comments. Sentiment Analysis can thus identify both the most pressing issues and the most valued aspects of a company. Newly emerging trends can also be detected giving a company an opportunity to address them early on before they become a larger problem.

One popular way of displaying and monitoring Sentiment Analysis data is via a dashboard which provides various interactive views of the data as well as the ability to drill down to the source text. At a glance, companies can discover their employees’ most common complaints and praises and can track sentiments over time.

In sum, Sentiment Analysis makes it possible for companies to understand precisely what is driving their employees’ satisfaction and dissatisfaction.