Benefits of NLP (Natural Language Process ) in Customer Service?

Do you know about voice-controlled devices like Alexa and Siri? In this 21st century, you’ll find it in most homes. Almost about 69.9 million people have smart home systems where they are using it to play songs or check the current weather.

Most of the people interact with technology rather than humans. Conservations with smart machines or AI systems have changed the living standards of people and most companies are using machine learning technology to improve their customer service interactions. Research from experts shows that chatbots can handle about 80% of customer communications.

Chatbots use natural language processing, so customer support works so well. NLP can improve customer service by providing 24-hour support and real-time interactions. By implementation, the costs can be reduced and human agents can focus on the complex tasks.

In this blog, you will get what is natural language process (NLP), is and the benefits of Natural Language Process in customer service.

Let’s Begin !!!

What is Natural Language Processing?

Natural Language Processing(NLP) can be defined as a branch of artificial intelligence that basically focuses on the interaction between computers and humans.

In the context of call centers, NLP can easily perform tasks like sentiment analysis, translation of language, and speech recognition. Natural Language processing can translate voice to text and can provide 24-hour customer support, which helps in providing quick responses.

How can NLP be used in customer service?

NLP plays a vital role in any smart service and AI that is able to analyze phone calls or reply to customers’ queries and support customer service teams. It can be used in a variety of ways in customer service, which includes improving customer-facing interactions with real-time coaching for agents, analyzing the sentiment of the customers, gathering information about customers, and many more. NLP plays a vital role wherever there is spoken or written language in the customer service journey.

Some of the use cases of NLP In customer service

1. Accurate call routing with IVR systems

Have you experienced a customer support line saying Billing to reach the finance department? If you have experienced then you were talking to an Interactive Voice Response(IVR) system.IVR is a technology that converts certain phrases (make payment) by transferring them to the appropriate department.

NLP understands the caller’s request and can assist them in a better way. By listening to the customer’s queries IVAS Can quickly analyze them and route the call to the appropriate department or support agents. It reduces the customer waiting time and eliminates the frustration.

2. Automated ticketing systems

Customer support operations can be enhanced with automated ticketing systems that use natural language processing (NLP)Incoming support tickets, such as emails, chats, and messages, can be analyzed using NLP algorithms. By the identification of the text, the system can analyze the types of issues that the customers are facing.

3. Chatbots and virtual assistants

With the help of AI chatbots, you can communicate with customers in a way where they provide real-time support and reduce the customer’s waiting time. NLP-powered chatbots are able to handle customer queries 24/7 by providing instant responses to their query.

Chatbots can understand multiple languages and can communicate with a global audience. By the use of NLP, chatbots can understand the customer messages even if they contain grammatical errors and reply to them.

4. Sentiment analysis

Sentiment analysis is a powerful application of Natural Language Processing(NLP) which enables businesses to understand the tone of the customer feedback and interpret accordingly. In order to improve customer satisfaction, companies can use sentiment analysis to analyze text data from a variety of sources and gather customer sentiment.

NLP helps in analyzing customer messages and detecting the emotions and sentiments of the customer in real-time, This helps in the identification of frustrated and angry customers so that they can prioritize and handle the interactions with care.

5. Content analysis and summarization

In content analysis and summarization, NLP helps manage and extract useful information from large amounts of text. Making information accessible and actionable improves the efficiency of customer support operations and You can find out how to troubleshoot and solve common issues by using this tool. Summarized content allows agents to quickly grab the key points of the lengthy documents without reading them entirely.

6. Speech-to-text applications

Recently, experts have identified that voice search is on rise:50% of people search their queries by voice on a daily basis. We use personal assistants like Alexa and Siri to remind us about important meetings and events and can use them while playing music as well.

You can use voice recognition systems like:

• You might allow customers to access their account by their voice.
• You can integrate the software with a voice assistant.

None of these situations works without NLP. You can use speech analytics, one of which more call centers must take advantage of it.

You might also like to know: What is Natural Language processing? Understanding NLP and its Applications

What are the benefits of Natural Language Process?

I. Improves customer satisfaction

Implementing Natural language processing(NLP) in customer service improves customer satisfaction by responding to customer queries earlier. The automated systems can provide instant responses to customer queries, which helps reduce waiting time.

NLP-powered chatbots and virtual assistants can handle customer queries instantly. By providing instant answers to frequently asked questions, this improves the customer experience. These chatbots are available 24 hours daily to solve customer queries across different time zones.

II. Increased Efficiency and Productivity

This technology automatically improves the efficiency and productivity of customer support by following routine tasks. The NLP is powerful as it can automatically categorize the support tickets based on the content.

This maintains the workflow and makes sure that the tickets are classified without humans. NLP is able to handle large volumes of inquiries simultaneously by allowing businesses to scale their support operations without a proportional increase in staffing.

III. Cost savings

With the help of automation, we can reduce the need for a larger customer support team, which will lead to significant cost savings. With the help of automated systems that handle common queries, training costs are reduced. The costs that need to be paid to the human agents will be reduced. With the integration of NLP, customer support can be handled by AI chatbots, which will reduce the number of human agents.

IV. Multilingual Support

Multilingual support, which is powered by Natural Language Processing (NLP) technology, enhances the business’s ability to provide effective customer service globally. By handling multiple languages and providing real-time translation, NLP makes sure that language barriers do not hinder customer satisfaction.

NLP is able to detect the languages of the customer queries, by making sure that each query is addressed in appropriate languages. By supporting multiple languages, businesses can provide responses to customer queries.

V. Better Resource Management

By automation of routine tasks, human agents can focus on complex issues as the chatbots help in handling the customer support giving high-priority for the agents to focus fully on the problems. Automating repetitive tasks helps in reducing the risk of burnout among the customer service agents which leads to higher job satisfaction and retention.

Conclusion 

The use of Natural Language Processing (NLP) in customer service has improved efficiency, reduced costs, and increased customer satisfaction. NLP helps to provide real-time support through different applications like chatbots, sentiment analysis, and more. The integration of NLP in customer service ensures 24/7 availability, multilingual support, and better resource management, which leads to improving the customer experience.

FAQS

What are the most common applications of NLP in customer service?

The use of chatbots and virtual assistants is the most common application of NLP. These automated systems use Natural Language Processing to understand and respond to the customer’s queries.

What is Natural Language Processing in call centers?

In call centers, Natural Language Processing is used to convert speech or audio into written text. Analyze voice calls which enables the automated handling of customer requests, sentiment analysis, and real-time assistance for call center agents.

What are some examples of NLP?

There are many examples of NLP, but the most common examples include virtual assistants like(Siri and Alexa).