Understanding NLP in Customer Service: Key Insights

Natural language processing (NLP) is a non-negotiable part of an efficient and personalized customer service experience. 

Gone are the days when people used to refer to technology or computer systems as “dumb” because they needed human input to perform the basic functions. Nowadays, computer systems have become very smart and capable of “learning” from past interactions. 

The widespread use of NLP in customer service is one of the major occurrences underscoring this phenomenon, as the NLP market size is projected to reach, $36.42 billion in 2024. 

In this article, we discuss the meaning of NLP, its benefits, and 7 major applications in customer service scenarios. From NLP AI chatbots to sentiment analysis, here are some vital details about NLP in customer service.

What is NLP?

NLP is an acronym for Natural Language Processing. It is a form of artificial intelligence technology that allows computer programs to understand, interpret, and respond to human “natural language.”  This wonderful piece of technology is the reason why you can speak to Siri like you’re talking to a friend. It’s also the technology that makes OpenAI’s ChatGPT understand your funny queries and even respond with your preferred level of humor. 

NLP technology, like most other AI systems, works by learning from plenty of data. More specifically, NLP learns from written and spoken text. AI experts and linguists work together to help it understand vital components of human conversations, such as context, grammar, syntax, and even the ability to recognize the objects and subjects in a sentence. As a result, it “understands” different prompts phrased as if two people were having a simple conversation. 

NLP in customer service helps to process and analyze unstructured data. Therefore, it is able to interpret, understand, and respond to customer inquiries like human agents. Whether it is support tickets, emails, or tweets, an NLP AI chatbot can understand what the customer wants and respond effectively. As a result, businesses can now offer their customers quick, accurate, and personalized responses, and customers love that.

Related Read: What is Natural Language Processing.

Benefits of NLP and NLP AI Chatbots in Customer Service

Integrating NLP in customer service operations is like painting an old building with fresh paint; it makes customer service better in a lot of ways. The following are some of those benefits: 

1. Scalability

These days, businesses have greater customer service responsibilities. They’re servicing a larger number of customers who want to connect with the customer service team across multiple channels like social media, chat, email, and phone. And AI integration, handling all the different queries across these different channels can be very difficult, even if the business hires multiple human customer support agents. 

NLP AI chatbots can reduce this workload significantly. Not only do they help automated systems understand customer inquiries, but they can also handle routine tasks like answering frequently asked questions (FAQs).  As a result, the business can now cope better with its growing customer service demands without increasing its workforce. 

2. Better Customer Experiences 

Improved customer experiences are one of the most significant benefits of using NLP in customer services. The NLP AI chatbots are not only able to manage thousands of conversations simultaneously, but they also handle these conversations in ways that please the customers. 

Here’s why. 

First, they provide accurate responses and personalized experiences. Their ability to learn from each customer interaction also makes it easy for them to single out what the customer really wants. Once they figure it out, they tailor their responses according to the customer’s needs. At the end of the day, the customer ends up satisfied after contacting the business, which is a good thing for the bottom line. 

3. Increased Productivity and Efficiency

Both the customer and the service agent save time and cost with NLP AI chatbots. For example, the NLP AI chatbot has the ability to automate responses to routine customer inquiries like FAQs and booking confirmations. In this case, the customer gets quicker responses while the service agent frees up their time to handle other complex tasks. 

As a result, the business can maintain its current workforce regardless of increasing customer queries. 

Likewise, NLP technology can help the business to sort and automate support tickets based on their level of urgency and importance. Consequently, the customer support team can now resolve urgent issues promptly so that customers spend less time while the entire support operation becomes more efficient. 

4. 24/7 Customer Support

Unlike human agents, NLP AI chatbots are capable of providing uninterrupted, round-the-clock customer service. This boosts customer satisfaction, efficiency, and, ultimately, the business’s profitability. 

5. Insights Gathering

Using NLP in customer service can also give businesses very insightful details about their customers that could be used to shape their value offerings. The ability of this technology to analyze and identify valuable insights from customer feedback, user reviews, and surveys can be used to identify what the business is getting right or wrong. 

In shaping the business’s direction, these insights are very valuable. As such, it can help steer the business in the right direction. 

How to Use NLP in Customer Service: Top 7 Applications of NLP in Business Customer Service

The numerous applications of NLP in customer service aim to augment existing service operations to improve overall customer satisfaction. The following are some specific descriptions of NLP customer service applications that play a major part in this overall goal.

1. Live Agent Support and NLP AI Chatbots

Live agent support and NLP AI chatbots are two different customer service communication channels. While live agent support means a human agent chatting directly with a customer, the NLP AI chatbot means an AI NLP agent doing the same thing without human intervention. Many businesses combine both methods to deliver a flawless customer inquiry process. 

Let’s say a customer is chatting directly with a human agent. In this situation, the agent doesn’t always have the specific answers a customer seeks. NLP can be of help here by quickly understanding the intent behind the customer’s inquiries and automatically searching for all connected knowledge bases for the best responses. So, the live agent doesn’t have to go through the stress of research themselves. Instead, NLP takes care of it for them. 

Likewise, the NLP AI chatbot itself can also facilitate a seamless interaction independently. This is similar to what Siri and Alexa do. As a result, the customer gets faster and more accurate responses and a pleasant experience all around. 

2. Training and Knowledge Base Improvement

The ability of NLP programs to analyze large amounts of unstructured data and spot patterns can also be used to train and improve an organization’s knowledge base. 

For instance, if the NLP program notices that customers repeatedly ask a particular question that isn’t covered in the existing knowledge base, it could flag it and raise awareness. Consequently, the support team or supervisor will be prompted to examine the commonly raised queries and create knowledge base content that addresses them. This way, the support team gets to reduce the amount of queries they get based on that issue because customers can now target it themselves. 

In addition, NLP can also help to train the live agents based on past interactions. As we noted earlier, it identifies the common issues and the best resolution methods based on historical data. 

3. Sentiment Analysis and Prompt Support

Since NLP programs can understand human language, they can help the customer service team detect customer sentiments from call and chat interactions. This is important because it tells the organization how well they’re doing and even how they can improve. This applies to both live agent and chatbot interactions (call and chat.)

NLP programs can be trained to provide in-depth conversational AI analytics for spotting sentimental statements. These sentimental statements can either be positive or negative from the customer. Regardless of the case, the good thing about it is that customer service supervisors can easily spot them and decide how to react to them early. Without NLP, businesses have to rely on human agents to point out customer sentiments, and this may not be accurate as agents are dealing with plenty of customers. So they may forget or even make errors. 

Basically, NLP makes it easy to identify both happy and unhappy customers quickly so that the customer service team can spring into action quickly and salvage any situation as quickly as possible. 

4. Interactive Voice Responses (IVR) 

An IVR system is an automated telephone system technology that customer service teams use to help callers submit their queries using voice or menu inputs without speaking to a live agent. It’s the piece of technology that allows you to call up a customer service team and just say who you want to talk to, like, “connect me to the tech department,” and it routes you directly. This system contrasts sharply with the programmed menu options, where you have to press certain numbers before you’re connected. 

This piece of technology makes this happen with the help of NLP technology. The advantage is that it’s just simpler for the user. Because NLP technology understands contexts and natural human language, customers can describe their problems in their own words, and they’ll get routed accordingly. 

More importantly, it reduces wait times and the frustration often associated with programmed menu options, thus increasing efficiency.  

5. Support Ticket Routing 

NLP can also route support tickets quickly and accurately to the right customer service departments. 

Most support ticket systems lacking NLP functionalities usually have to resort to manually sorting through all submitted support tickets before they can assign each to the right department. However, the fact that NLP understands human language and contexts helps it to identify the key phrases used in support tickets and identify the department best suited to resolve them. 

For example, when a customer submits a ticket titled, “I got debited twice,” the NLP program quickly spots words like “debited” and interprets the ticket as a problem that can be solved by the finance department. 

The result? 

The finance team gets this ticket on time, and also solves it on time to reduce the customer’s waiting period. It also automates the entire process by tagging tickets as they come in before routing. 

6. Business Data Analysis

From feedback and reviews to customer conversations, NLP has the ability to analyze them all based on multiple variables depending on what a business is optimizing for. As a result, it is capable of providing valuable insights that may be very difficult to get using both traditional analysis processes and even simple machine learning operations. 

What stands out in this use case is NLP’s ability to go a step further during analysis to understand the language and contexts within which all these data are used. It doesn’t just make conclusions and recommendations based on the surface data. 

For instance, most feedback and survey systems ask customers to categorize their feedback under major headings. A survey based on how satisfied the customers are with the customer service team could have general categories like “Satisfied, Fairly Satisfied, and Unsatisfied.” Then, the customers would have to provide further information in a text box. Without NLP, it might be difficult to understand why a customer who selects “Satisfied” chooses that option. But, with NLP, the program tracks certain keywords used to gain context. 

Consequently, NLP is able to provide more insights into what the business is getting right and what it needs to improve upon. 

7. Voice-based Virtual Assistants 

Voice-based virtual assistants are another popular application of NLP programs that significantly improve customer experiences. These applications enable customers to do amazing things like accessing their accounts or evoking certain functions on a business’s platform. They can also be used to translate a customer’s query from one language to the other. 

All of these applications are only possible because NLP can understand and interpret their voice inputs. As such, it gives the customer an opportunity to interact with the business or organization via a hands-free approach. It is accessible and convenient, and customers love it. 

Conclusion

Businesses have so much to gain from integrating NLP into customer service operations. From live agent support and sentiment analysis to support ticket routing and voice-based virtual assistants, NLP technology is already being applied across numerous customer service use cases. And it’s not just for the fancy nature. 

These applications make a business’s customer service operations scalable, more productive, and efficient. Furthermore, it delivers a better customer experience to the customers. 

So, what’s not to love? 

Your business can also enjoy the benefits of AI integration if you hire AI developers at an AI development company like Debut Infotech. Whether you want to build an NLP AI chatbot or a support ticket routing system, they have the right expertise working with diverse AI models sure to propel your business forward. 

Get in touch! 

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