Mon. May 20th, 2024

What is Sentiment Analysis in Call Center

In today’s competitive market, brands prioritize keeping their customers happy and satisfied. To achieve this, many companies outsource their customer service to BPOs or call centers, allowing them to focus on other important aspects of their business such as marketing and development.


What is Sentiment Analysis in a Call Center
What is Sentiment Analysis in a Call Center


Despite the best efforts of call centers to maintain a high customer satisfaction (CSAT) score, some factors outside their control may cause some customers to feel dissatisfied. To address this, call centers employ various techniques such as identifying the root causes of customer dissatisfaction through ACPT, verbatim analysis, quality checks, and other means.

One widely-used method of analysis, not just in call centers but in other industries as well, is sentiment analysis. This involves analyzing customer feedback to determine the overall sentiment or emotional tone behind it, which can help businesses better understand and address their customers’ needs.

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In our today’s blog, we will discuss more about Sentiment Analysis in detail.

What is Sentiment Analysis in Call Center?

As the name refers Sentiment analysis is related to the

Sentiment of the customer’s voice and is focused on analyzing the VOC (Voice of the Customer) by assessing the emotional tone or words used during the voice call or chat.

This technique is used to evaluate the sentiment of the words used during a call or chat interaction, providing insights and helping businesses understand their customers better.

How to do a Sentiment Analysis in Call Center

The two most commonly used tools used to perform sentiment analysis in call center:

  1.  Excel along with Azure Machine learning
  2.  Python with Logistic regression algorithm.

The process of performing sentiment analysis is quite simple. With the help of the above-mentioned tools we can categorize customers’ sentiment into 1, 0, and -1, where 1 denotes Positive, 0 denotes neutral and -1 denotes negative. Further after analyzing these numbers, we can easily get insights into customer sentiment.

Advantages of doing Sentiment Analysis in Call Center

Irrespective of the domain or industry, the benefits of Sentiment analysis pervade everywhere. Performing Sentiment Analysis can give some meaningful insights to a company or a call center which can be used to mitigate the loopholes in the system.

Especially call center industry which is completely customer-driven, the use of sentiment analysis becomes more significant.

Below are some advantages of doing a Sentiment Analysis in Call Center

1. Increase CSAT: 

CSAT is one of the most important metrics in every industry, especially in a call center. By utilizing sentiment analysis, we can find out the root cause of customer dissatisfaction. This helps determine whether the issue is related to the product, pricing, or agent’s handling of the interaction. 

Sentiment analysis in Call Center
                         Sentiment analysis in Call Center

By working on customer feedback and insights we can mitigate errors and improve the quality of customer service, which in turn increase the customer satisfaction of CSAT.

2. New market strategies: 

By leveraging sentiment analysis, businesses can evaluate customers’ needs and preferences regarding product features, feedback, and potential drawbacks in product usage. 

Companies can then use this information to make strategic decisions such as launching a new product, incorporating additional features into existing products, and exploring new market strategies based on customer feedback.

3. Increase Revenue: 

A Call center can assist in generating meaningful insights with the help of sentiment analysis by assessing customers’ feedback related to the post-sales service of a brand.

By utilizing the insights produced with the help of Sentiment analysis, a brand can work on those segments where the chance of revenue is higher.

4. Identifying trends:

One of the major advantages of performing sentiment analysis on the customer’s data is to identify the historical trend of customer service.

By assessing the language, tone, and voice of the customer during the interaction with the call center agent, sentiment analysis can help to gather insights about the overall satisfaction of the customer.

Overall, sentiment analysis can offer meaningful insights related to customer satisfaction, allowing a call center to work on loopholes and further make data-driven decisions to improve customer experience.

5. Monitoring Agent’s performance:

Using sentiment analysis, call centers can monitor their agents’ performance in terms of customer satisfaction metrics such as CSAT (customer satisfaction), NPS (Net promotor Score), CES (Customer Effort Score), and overall customer satisfaction. 

This technology can identify poor-performing agents, allowing the business process outsourcing (BPO) company to take corrective action.

Furthermore, sentiment analysis can provide valuable insights into which agents are effectively managing chat interactions with customers and providing exceptional service.

In addition to this sentiment analysis can help in identifying those areas where an expert needs more product training or support. 

Let’s assume a customer is not happy with the slow response or time taken by an agent to resolve the issue, this indicates that an agent needs more training in writing skills or understanding the customer’s issue.


Sentiment Analysis in Call Center is very important to analyze customer’s sentiment and getting insight out of it. Sentiment Analysis is also very helpful to make judicious business decisions from the analysis. Live sentiment analysis is like having a superpower for sales and support team managers. It helps them quickly figure out where they should focus their efforts.

Manual call monitoring and running through QA checklists to get the customer’s sentiment can be time-consuming and tedious exercise and sometimes not fruitful. When your contact center leverages Sentiment Analysis along with some you no longer need to manually monitor calls or study interaction transcripts to find out how customers feel about your business.


I hope this blog will help you to understand sentiment analysis in call center in a better way also the calculation given in the blog is self explanatory . Still if you have any questions do not hesitate to reach out to me at

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