NLP for Call Center: Improving Customer Service Quality

AI is transforming the call center industry by utilizing technologies such as real-time voice recognition, intention analysis, conversation management, and conversational analytics. Call centers are using NLP (Natural Language Processing) to make processes more efficient and create a more accessible customer experience. In this article, we will discuss how NLP can improve customer service and problem resolution in the call center.

What is NLP?

As we previously explained in this article, Natural Language Processing (NLP) is a field of study within Artificial Intelligence that focuses on examining the interaction between computers and the language used by humans.

In the early speech technology systems, only a small set of words (usually isolated numbers) was recognized. Later, systems capable of automatically transcribing voice messages were developed, leading to the creation of conversational assistants such as Siri, Cortana, or Google Assistant.

How does NLP work in Call Centers?

Call centers are utilizing natural language processing (NLP) technology to improve efficiency and reduce human capital costs. Below, we’ll look at some of its most common applications.

Automatic assistants

NLP-powered virtual assistants allow customers to express themselves in their own vocabulary and direct them to the right option, thus improving the user experience. Chatbots and other means can answer frequently asked questions in real-time, reducing wait times and increasing customer satisfaction. In this way, NLP technology can reduce operational costs and improve the efficiency of customer service agents, leading to its adoption by more companies.

Outbound calling systems

Outbound call centers are more complicated to manage than inbound ones, as they have to initiate a conversation rather than process and respond to received information. These can be divided into debt collection services and message promotion services.

In the case of debt collection services, the customer’s psychological experience is not as important as long as a clear intention and purpose is expressed in the conversation. On the other hand, message promotion services require better user experience design due to people’s tendency to be suspicious or annoyed with automated calls, which presents challenges for integrating AI and NLP.

Call record data analysis

NLP is used to analyze call record data and evaluate users’ emotions, intentions, and thoughts, providing personalized services and improving the customer experience. Overall, the use of NLP in call centers allows companies to predict trends and potential dissatisfactions, reduce complaint rates, and create more personalized and satisfying experiences for customers. This is especially useful for cloud call centers, which can more efficiently review their services thanks to NLP technology.

Sentiment analysis

Sentiment analysis identifies the emotions and intentions of customers, allowing call centers to improve customer service by identifying problem areas and studying customer abandonment rates. When agents understand the sentiment, they can be better prepared to match the consumer’s tone and effectively deal with callers.

Sentiment analysis in NLP software can also discern the intent behind customer comments, whether recorded or written. This information is turned into data to help the software learn which actions lead to positive customer experiences. It can be used to predict consumer behavior, tailor training and best practices, and evaluate agent performance.

Agent support

NLP not only benefits customers, but is also useful in supporting agents during their working hours. NLP software can quickly provide solutions to customer concerns, reducing the time agents would spend searching for answers and enabling faster and more efficient service. It allows team members to see customer queries in real time and for contact center software to provide relevant information to improve call resolution, while during calls, NLP technology can suggest suitable resources to help agents and generate additional cross-selling or upselling opportunities.

Voice-to-text applications

Natural Language Processing technology is being used in call centers to offer voice-to-text applications that allow customers to access their accounts through their voice, translate calls in different languages, and create documents through dictation. The voice-to-text functionality creates a written record of interactions between customers and agents to improve customer service and streamline contact processes, providing a consistent customer experience and resolving queries more efficiently.

Benefits of implementing NLP in Call Center

There are multiple benefits for both customers and agents when implementing NLP and PLN technologies in a call center.

Customer service

NLP is used in call centers to enhance customer service. An automated assistant interprets customer speech and determines the best way to handle their queries, either through automated solutions or by routing them to a contact center agent. Intelligent routing also uses NLP technology to assign calls to the most suitable agents to handle queries. Both functions help resolve queries more quickly and effectively, reducing customer frustration by minimizing wait times and providing accurate answers.

Although many customers prefer the attention of a human agent, an increasing number of people are adopting automated and self-service options. Natural Language Processing technology provides a more satisfying customer experience by providing accurate and fast answers to queries, enabling better customer service.

Team productivity

Companies that use natural language processing can achieve significant productivity improvements in a competitive labor market with high turnover. Self-service options reduce the workload on employees by handling routine inquiries, while agents can provide faster and more efficient service by having access to the information they need before answering the call, reducing research time and increasing productivity. NLP also saves time by automating manual processes such as reading large amounts of documents, emails, or conversations, making business decision-making easier.

Omnichannel support

Today’s consumers use multiple channels to communicate with companies, which poses a challenge for omnichannel solution providers in the contact center. Natural language processing allows agents to provide efficient and consistent omnichannel support regardless of the channel used by customers to make their inquiries. 55% of customers expect consistency across all channels they use, making the use of suitable software and an efficient dashboard necessary to provide a satisfying customer experience.

Cost efficiency

Using NLP-based self-service options and chatbots, which operate 24/7, is a way to address customer service issues without the need to hire more agents. In fact, studies indicate that these options can save up to 30% of customer service budgets and speed up response times by 80% for routine inquiries.

Retaining customers

The application of NLP can contribute to improving customer retention in several ways. One of them is through more agile resolution of their problems, as positive experiences are associated with reduced waiting times.

On the other hand, sentiment analysis is useful for studying the reasons behind customer churn by analyzing their interactions with the company. With this information, warning signs indicating possible customer loss can be identified, allowing agents to address issues more effectively, predict customer churn, and reduce complaint levels.

How can Upbe and our NLP system help you?

Upbe and its dashboards allow you to make quick and flexible decisions. Having easy-to-access and navigate dashboards is essential for success in operating a Call Center and taking advantage of all the benefits we have mentioned before, without spending weeks learning how to use the tool.

If you are looking for a Conversational Intelligence tool to benefit your business and provide you with freedom and flexibility with an easy-to-install self-service platform, you can request a demo, and we will tell you all the details.