March 3

NLP is transforming CX delivery: what use cases can it serve in contact centers?

Natural Language Processing (NLP) is a subfield of artificial intelligence (AI) that focuses on the interaction between human language and computers.

Within a rapidly expanding contact center sector that is embracing automation, NLP is becoming increasingly important for delivering exceptional CX. It’s revolutionizing the way contact centers interact with customers reaching out to them. 

In this industry update, we will explore the different use cases of NLP in contact centers and how it is transforming CX delivery.

How NLP is gaining much prominence in key use cases within contact centers?

Modern contact centers handle a large volume of customer interactions every day through multiple channels, including calls, emails, and chats. 

The use of NLP in contact centers can improve the efficiency and effectiveness of customer service by automating repetitive tasks, reducing response times, and improving the quality of interactions.


NLP is commonly used in contact centers for the development of advanced chatbots.

They can be used to provide customers with quick and efficient responses to their queries and can be programmed to understand and respond to customer inquiries in a natural language, making them an effective tool for improving CX and swiftness of responses.

Sentiment analysis

This is another application of NLP in contact centers that involves analyzing customer interactions to determine their emotional state. 

Sentiment analysis can be used to identify customers who are dissatisfied with the service and address their concerns before they escalate. It can also be used to identify trends and patterns in customer feedback, allowing businesses to make data-driven decisions to improve CX.

Text classification

In contact centers, text classification can be used to automate the routing of customer inquiries to the appropriate agent or department. 

For example, customer inquiries related to billing can be routed to the billing department, while inquiries related to technical support can be routed to the technical support team. 

This can improve the efficiency of the contact center by reducing response times and ensuring that inquiries are handled by the most appropriate team.

Language translation

Language translation is another use case of NLP in contact centers. With the increasing globalization of businesses, contact centers often handle customer inquiries in multiple languages. 

NLP can be used to translate customer inquiries into the language of the contact center agent, allowing them to respond in a language that the customer understands. This can improve the quality of interactions and reduce the risk of miscommunication.

Refer to insights through CX forensics before Integrating NLP into your contact center 

NLP may not be the perfect fit for all contact center operations in terms of feasibility, effectiveness, and practicality. Like all solutions, NLP too has a host of benefits and challenges that change depending on the specific contact center operation in question. 

It is essential to strike a balance between automation and human interaction to provide exceptional customer service and decide on what use cases to automate and what use cases to assign to human agents.
Hence, it is recommended to refer to insights through reliable CX forensics to determine how best to approach NLP integration for your contact center.

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