As the deployment of Natural Language Processing (NLP) is remolding the call center operations, Humanizing handles customer problems and solves their queries automatically.
As stated by Gartner, 30% of interactions with technology would be through “conversations” with smart machines- many of them by voice. In addition, research has found that live chat can handle 80% of customer communications.
What is Natural Language Processing in a Call Center?
Natural Language Processing, often abstracted as NLP, is a side stream of artificial intelligence (AI) which focuses on the interaction between computers and the language used by humans. The principle is to enable computers to understand, interpret, and generate human language in a meaningful and useful manner.
In essence, NLP can appear as a chatbot. This is another kind of machine learning software that horizontally handles customer conversations.
It has been reported that “More than 67% of consumers utilized Chatbot for customer support in the past years.”
Snapping back on the question, what is NLP in a call center?
Natural language processing (NLP) in a call center refers to optimizing AI technology to understand and analyze human language in a conversational context. NLP allows call center systems to interpret and respond to customer inquiries automatically.
Despite that, call centers have always been on the vanguard of using Natural Language Processing (NLP) to drop-ship very tangible business and generative customer experiences.
The key to the effective deployment of artificial intelligence (AI) in contact center solutions is NLP. NLP offers many benefits, including improving workplace efficiency and decreasing human capital costs. NLP can help intelligently route callers to the agents with the right skill set for the issues they are calling about for inbound calling. Intelligent routing produces faster resolution by matching agents and surfacing the proper scripts.
The lead to the compelling stationing of artificial intelligence (AI) in contact center solutions is NLP. NLP intelligently routes callers to the appropriate agents who have the right skill set for the issue they are calling about for inbound calling.
Top 5 Use Cases of NLP in call centers
Call centers operating natural language processing (NLP) technology improve efficiency and reduce human capital costs. Below, we’ll look at some popular use cases of NLP in call centers.
1. Conversational AI
One of the most significant use cases of NLP at call centers is resolving customer inquiries with specific information using conversational AI or say, virtual attendant. IVRs are the elementary technology, converting phrases like “make a payment” or “update my credit card” into transferring you to the billing department. When Conversational AI upholds the system, one can accurately divert their call to the most relevant line, and their IVR becomes an intelligent virtual assistant (IVA).
2. Sentiment Analysis
Sentiment analysis in NLP, understands the intent behind customer feedback or comments, whether written or recorded. This can be used to predict consumer behavior, tailoring best practices and therefore evaluating agent performance. When agents understand the customer’s sentiment, they can better prepare to coordinate with the customer’s tone and effectively deal with callers. For example, sentiment analysis using NLP can interrupt those words like “awesome, quicker” mentioned by customers as an emotion.
3. Customer Service Chatbots
NLP is smart enough to acknowledge the message and respond without human intervention. Research shows that about 42% of consumers would rather connect with a company via live chat versus 23% for email and 16% for social media. NLP technology propounds appropriate resources to support agents in generating additional cross-selling or upselling opportunities.
4. Voice Transcriptions
You must be aware that voice search is on the soar! Researchers predicted that almost 30% of all searches will be conducted without a screen. NLP technology used in call centers offers voice-to-text applications, allowing customers to access their accounts through their voice and therefore create documents through dictation.
5. Call record data analysis
NLP can optimize call record data and evaluate user’s emotions, intentions, and thoughts. This allows call centers to predict trends and potential dissatisfactions, decrease complaint rates, and create more personalized experiences for customers. One of the best use cases of NLP, especially useful for cloud-based call centers, is to assist in reviewing their services.
Conclusion
Wanna know one hidden gem? Have a look; NLP is equal to better user experiences. Call to mind that NLP is a midst aspect of machine learning (ML) and you should use it in your customer service departments. NLP Call center improves efficiency, its applications include automatic assistants, outbound calling systems, and agent support.