How to leverage sentiment analysis data to boost employee engagement and satisfaction

AI is revolutionizing the digital world, and how! Thanks to sentiment analysis data, computers can now decipher our feelings, opinions, or emotions from text or speech. Earlier, though it could process and analyze data quickly and faster than humans, it couldn’t understand the emotions and meanings that could be derived from human writing. Now, with sentiment analysis algorithms, computers can do that, too.

Several industries benefitted from this new technology. Human resources found it an invaluable tool for building a people-centric workforce that thrives on innovation. This article discusses employee sentiment and how it can help businesses grow.

Understanding Employee sentiment

Tracking, measuring, and deciphering employee sentiment is challenging for organizations. Especially since companies are trying to improve the employee experience to create a satisfied and productive workforce, let’s find out about their challenges.

Subjectivity and context: Employee sentiment analysis is tricky because it is subjective and depends mainly on the situation. Every individual will uniquely express their sentiment, so it is impossible to standardize measurements and determine a conclusive result.

Language and communication: Lack of proper communication by employees also makes it challenging to decipher employee sentiment. Also, certain words can have different meanings in different contexts. For example, “good” can be used positively and sarcastically. Often, opinions get lost in translation due to differences in culture or the native language spoken.

Data collection methods: Capturing sentiments takes work. Traditional surveys fail to record real-time sentiments; on the other hand, sentiment analysis tools can’t understand subtle sentiments. What is required is a tool that can communicate effectively with employees and decipher the slightest change in employee sentiment.

Anonymity and trust: An open and honest discussion is only possible when the employee feels safe in the work environment and doesn’t fear judgment or adverse consequences from higher authorities for voicing their opinions. It is essential to maintain anonymity and confidentiality to make this happen and get unbiased data for sentiment mapping from the workforce.

AI-powered Amber can provide a comprehensive solution to all these challenges and help organizations build an engaged and confident workforce. Amber is an AI bot that uses conversational AI and people analytics to help understand how employees really feel, uncovering the real sentiment and turnover indicators, especially for the top talent.

They do this through the Pulse survey mainly, which helps in understanding gaps in an organization’s remote culture, and teams. These surveys can be used at any time, for any purpose, and are highly customizable depending on the current needs. 

Implementing Employee Sentiment Analysis: Tools & tips

Let’s find out the best practices and sentiment analysis tool features required to implement employee sentiment analysis-

Anonymous Surveys: Empowering employees with an anonymity feature helps foster a culture of trust and confidence and increases response rates.

Personalize chats at scale using sentiment analysis: The tool, like Amber, should keep track of employee conversations when their journey begins in the company. Her empathy and dynamic questions create a safe and trustworthy environment.

Regular and Real-Time Feedback: Feedback and reviews can’t be a yearly phenomenon anymore. It should be a continuous process to capture real-time sentiments to enable quick responses to problems coming to the fore.

Amber uses GPT-3 (via OpenAI) to categorize an employee’s answer sentiment during chat sessions. The algorithm uses questions and answers to build context and improve the accuracy rate. Amber analyses different kinds of questions; for textual ones, it examines both question and answer and then follows up with questions based on the answer chosen by the employee.

Diverse Data Sources: Surveys shouldn’t be the only source of sentiment analysis data. Combine reports from social media monitoring, focus groups, one-on-one reviews, or interviews to develop a comprehensive report to understand employee experience.

Contextual Analysis: Consider all the external and organizational factors that might affect sentiment analysis data to ensure better interpretation.

Employee Involvement: Understand your employees’ perspectives in the employee sentiment analysis process and get their feedback to discover the pain points and the predominant themes.

Amber curates a thematic analysis of textual responses in exit chats to help HR teams identify pressing points that lead to attrition in their organization. The feature uses GPT-3 (via OpenAI) to categorize employee responses for questions in defined themes, such as job satisfaction, work flexibility, and work-life balance, professional growth, etc., to help.

Sentiment mapping: Unveiling insights

Organizations can make informed strategic decisions and enhance employee engagement by using Sentiment mapping techniques and harnessing their advantages.

Exploring Sentiment Mapping Techniques and Their Advantages

Sentiment mapping uses sentiment data analysis to identify trends and patterns in employee sentiments across various departments, teams, or timelines. Techniques and tools like natural language processing, machine learning, and data visualization help to get an all-rounded understanding of employee sentiments. It can address areas of concern, recognize strengths, and gain a deeper perspective of the employee psyche.

Using Sentiment Maps for Strategic Decision-Making and Employee Engagement

Sentiment maps are valuable tools for making strategic decisions and increasing employee engagement. Businesses can discover challenges, improvement areas, and potential risks affecting employee self-confidence and productivity. Supervisors can use these insights to execute targeted interventions, create a thriving work culture, and enhance employee experience. Sentiment mapping can also measure employee engagement initiatives' fruitfulness and track sentiment changes, enabling data-driven decision-making.

Use of Employee Sentiment in different industries: Benefits and applications  

Healthcare sector

• Patient Feedback: Helps healthcare professionals understand patient satisfaction and identify improvement areas.
• Social Media Monitoring: Allows monitoring of public perception, addressing issues, and strengthening reputation management.
• Drug Safety Monitoring: Facilitates early detection of adverse drug reactions and patient sentiment toward medicines.
• Employee Engagement: Understanding staff sentiments leads to improved morale and productivity.
• Public Health Tracking: Sentiment analysis of public health-related discussions helps in timely interventions.

IT industry

In the IT industry, sentiment analysis data is used to determine customer satisfaction, track brand reputation on social media, evaluate user feedback on products/services, and improve employee engagement and sentiment within the organization.

Amber can help in gauging employee sentiment within the organization. Take, for example, the Inspira Enterprises case. They struggled to identify the disengaged and unhappy employees and couldn’t quite capture the true sentiment of their entire workforce. 

When they used Amber, it helped them engage meaningfully with their 1300+ employees. The sentiment analysis data reports from these conversations helped them prepare insightful accounts for the top leadership. Moreover, managers could identify disengaged employees and encourage them to share anonymous feedback about sensitive issues.

Amber helped them achieve 21X ROI on employee engagement.

Banking sector

In banking and finance, sentiment analysis data is used to understand customer preferences, evaluate brand perception, analyze feedback on banking products and services, detect potential risks, and enhance customer experience and loyalty.

Digit Insurance realized 4.2x ROI on employee engagement with AI-powered Amber. They have over 2500 employees, and keeping the conversation going with each was difficult for the HR department. With Amber, employees got more engaged, and Amber’s sentiment analysis breakdown helped interpret data to create intuitive reports for the company leaders. 

Leverage Amber to enhance employee engagement through sentiment analysis.

Amber helps understand how employees feel, diagnosing the sentiment gaps, especially in top talent. It can track individual employee journeys, use empathy and sentiment analysis data on all feedback, and integrate moments that matter across the employee lifecycle.

All this cumulatively helps the talent force thrive and increase productivity and Employee experience helps attract and retain top talent.