people analytics (HR analytics) corporate culture

employee sentiment analysis

Employee sentiment analysis is the use of natural language processing (NLP) and other AI techniques to automatically analyze employee feedback and other unstructured data to quantify and describe how employees feel about their organization.

It is a specific application of sentiment analysis, also known as opinion mining, an NLP technique designed to identify the emotional tone of a body of text. Sentiment analysis is widely used to detect how customers feel about products, brands and services.

The feedback is typically collected through standardized or open-ended employee surveys that are conducted periodically to detect changes in employee satisfaction and other perceptions over time and measure the employee experience.

Employee sentiment analysis requires a comprehensive strategy for mining these opinions, transforming survey data into meaningful insights and aligning it with business outcomes.

Why is employee sentiment analysis important?

As employee turnover rates increase, annual performance reviews and surveys don't provide enough information for companies to get a true understanding of how employees feel about them.

That's where employee sentiment analysis comes in. Employee sentiment analysis provides a number of important capabilities, including:

  • Helping companies take the necessary steps toward change when they discover that employees are dissatisfied with how the company is handling key issues such as employee performance, productivity and customer service.
  • Encouraging transparency and more open communication. When a company takes corrective actions to reassure employees that their opinions matter, it results in transparency, better communication and higher employee engagement.
  • Providing an accurate picture of employee opinions. People learn about the least desirable companies to work at from former and current employees. Employee sentiment analysis can help organizations evaluate whether these opinions are based on inaccurate perceptions. If an inaccurate opinion is harming the company's image, human resources personnel can take actions to foster more positive impressions.

How does employee sentiment analysis software work?

To gather and analyze employee sentiment data at a sufficiently large scale, many organizations turn to employee sentiment analysis software that uses artificial intelligence and machine learning to automate the process.

Employee sentiment analysis may trump humans in accuracy

In a video, analyst Ben Eubanks says AI can beat humans at spotting employee sentiment.

The technology enables organizations to send out open-ended surveys that employees can answer in their own words. Then NLP tools review each answer, analyzing the sentiment behind the words and providing a detailed report to managers and HR.

The software uses NLP to determine whether the sentiment in combinations of words and phrases is positive, neutral or negative and applies a numerical sentiment score to each employee comment.

After these scores are aggregated, they're presented visually to managers and business leaders through the use of data visualization. Being able to visualize employee sentiment helps business leaders improve employee engagement and the corporate culture. They can also use the information to improve their performance management process, focusing on enhancing the employee experience.

Organizations can program sentiment analysis tools to determine how engaged their employees are throughout the day. For example, email-based sentiment analysis can identify exact words and phrases and help infer insights gleaned from departmental level or individual emails. Companies can then use this data to address specific issues or introduce company-wide changes.

How can employee sentiment analysis change HR?

Human resources has historically relied on quantitative and highly structured data mainly gleaned from payroll systems and other core HR sources. The problem is there is only so much insight HR can distill from numbers.

Employee sentiment analysis, however, enables HR to make use of the organization's unstructured, qualitative data by determining whether it's positive, negative or neutral and to what extent.

Qualitative data includes comments, onboarding and offboarding feedback, probation reviews, performance reviews, policy compliance, conversations about employee goals and feedback requests about the business.

Employee sentiment analysis also enables HR to more easily and effectively obtain useful insights about what employees think about the organization by analyzing how they communicate in the office environment.

It also helps HR keep a close eye on employee language, tone and interests in email communications and other channels to determine if workers are happy or dissatisfied with their role in the company.

Top employee sentiment analysis tools

Prominent players in employee sentiment analysis software include the following:

  • is a machine learning platform on which organizations can develop a wide range of applications, such as AI-driven chatbots, signature verification, sentiment analysis and brand analytics for marketing campaigns. It employs such technologies as NLP, text processing and deep learning to automate employee sentiment analysis. Using the software, companies can evaluate employee comments in text, such as emails, to identify and categorize their opinions.
  • KeenCorp has a platform that analyzes existing data in an organization's workflow to provide executives with real-time insights into employee sentiment. It uses predictive analytics technology with proprietary algorithms to analyze pattern irregularities in texts and emails. The user interface consists of two dashboards: MoodMetrix to spot trends in employee sentiment over time, and the Attitude Heatmap to help management understand what mattered, why it mattered and what action to take.
  • Lattice Sentiment Analysis tags every open-ended response with a sentiment score to help managers quickly identify anomalies, patterns and problems without having to read employee comments. Lattice's NLP engine uses AI and machine learning technology for fast, accurate sentiment tagging, according to the vendor. The software also helps companies to understand how employee sentiment and employee performance are linked, providing managers with actionable insights.
  • UltiPro Perception is an AI-based, mobile-friendly employee survey tool from Ultimate Software. The vendor says the system collects and helps companies understand employee feedback and sentiment, and can detect emotions from the data and open-ended responses collected in its employee engagement surveys. The software, which is powered by Xander, Ultimate's AI engine, gives companies insights for improving employee performance and retention, according to the vendor. It analyzes survey results to help organizations understand the reasons behind employee responses.
This was last updated in August 2020

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