How NLP has Revolutionized the Customer Care Experience

What is Natural Language Processing?

Natural Language Processing grants AI the ability to mimic human speech patterns. The human language is filled with many ambiguities that make it difficult for the AI to understand the intended meaning. Homophones, sarcasm, idioms, metaphors, grammar, and usage exceptions are few features of the human language that even humans have struggled with for many years. NLP assists computer programs in translating text from one language to another. It also responds to spoken commands and condenses large volumes of text expeditiously. 

Several service sectors have implemented NLP, which has showcased its efficiency. The customer servicing sector always tends to have a massive load of work. By using NLP, companies have lessened the burden of customer care agents. Now agents can focus on more complex issues and leave the simple tedious work to AI (learn about the evolution of NLP here).

NLP uses many tools such as speech recognition, grammatical tagging, word sense disambiguation, named entity recognition, sentiment analysis, and many more to accurately interpret the intent behind a statement and improve the quality of the task at hand. 

NLP makes customer service better

• Accurate call routing with IVR systems: Going through ten different options to answer a simple question tends to get frustrating for many customers. Often, one cannot even get in touch with any department, and the call seems like a waste of time. NLP makes this process easier through accurate calling routing with Interactive Voice Response (IVR) systems. Conversational AI within IVR systems can ask customers to explain how they need help. Customers don't need to "listen to the following options" to reach the correct department. 
  

• Routing support tickets: Every company has a different department to handle various aspects: a tech department, a finance department,  a customer care department, a sales department, etc. Usually, if a customer has an issue, they get directed to customer care, and then they are further guided to a department that can help them. For example, if a customer wishes to change their billing details, they would first convey their issue to the customer care department, creating a support ticket for the finance department. The finance department would then take over the case. NLP helps in streamlining this process, saving time and money for both parties involved. It would focus on the word billing and automatically connect the customer with the finance department.
  

• Understanding customer feedback: Customer feedback is essential to any growing business and. Can utilize NLPs to understand their customer feedback efficiently. It helps in identifying issues to improve upon and aspects that customers appreciate. Both of which are terrific foundations for marketing and advertising campaigns. Spending hours manually combing through this type of qualitative data can be pretty cumbersome and time-consuming. NLP can filter through all this data and identify words that sum up the feedback statement. For example, "The products are pretty affordable." NLP pinpoints the word "affordable" in this case.
  

• NLP and customer service chatbots: A 24/7 team might not be viable for every company's budget. That's where virtual assistants and chatbots come into play. Not only are they more cost-effective, but they also save time for both the company and the customers. It is also convenient to click and type in any last-minute queries instead of waiting for the next day to get them answered. It doesn't matter whether the support inquiry has grammatical errors or incomplete sentences. NLP is astute enough to understand the idea behind the message and respond without the need for human mediation. 
  

• Speech-to-text applications: Devices like Google Home, Amazon Alexa, and Siri behave like personal assistants and have reformed the term 'personal touch' in customer satisfaction and experience. Alexa and  Google Home are extensively used and can handle bills and everyday house chores like turning off the lights, ordering products online, and an alarm. Adding voice recognition systems can set a company apart from its competition, like allowing customers to access their account with their voice, translating a customer's query in their native language to the language used, or integrating the software with a voice assistant. One can also ask these AI questions to which they can have funny responses.
  

NLP has produced overall improved productivity. Not to mention how time-saving and cost-efficient NLP is. To approach anything new, people tend to harbor apprehension. Taking the first step of communication helps in building a relationship with a potential customer. By streamlining many services, one invites more business. Technology has come to a point where simple queries do not require an actual human to be present. NLP uses speech recognition, grammatical tagging, word sense disambiguation, named entity recognition, and sentiment analysis to ensure an excellent outcome. The more data NLP and AI have, the more they can consistently improve their systems.  By incorporating NLP with AI, handling complex issues would be a piece of cake for the system. AI is adaptive but cannot behave like a human. NLP is the final piece of the puzzle.