Importance of NLP & NLU Across All Customer Service Channels
Natural Language Processing(NLP) and Natural Language Understanding(NLU), along with other technologies like big data analytics form the core part for providing great Conversational experiences.
Though these technologies have been there for many years, it is only recently that they have obtained the level of accuracy for being adopted by people.
In this article, we will understand how important NLP and NLU are across all of your customer service channels. But first, let us have a basic discussion about the customer service channels and the technologies we are talking about: NLP and NLU.
Different customer service channels refer to the different mediums in which your customers can engage with you to solve their problems.
Phone calls, live chats, and ticket systems are some of the basic examples. However, other forms of channels like Emails, Knowledge bases, forums too provide great help.
The knowledge bases and forums don’t necessarily need to be manually accessed by your customers though, you can use conversational bots that get content from then and serve to the customer (more on this later!)
Another channel that is getting popular lately is social media and also messaging apps like Whatsapp to stay in touch with customers! As you may have predicted, those use conversational experiences.
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Natural language understanding and natural language processing are very much related and have slight differences. If we talk about NLU vs NLP, one is concerned more about understanding the semantics and correcting the mistakes of natural languages while the other is concerned regarding understanding the entities in the language and splitting the sentences into tokens, etc…
While they might be rule-based initially, many recent versions of NLU and NLP technologies are increasingly being reliant on Machine learning, which are basically statistical models that learn to do all of the things by themselves without manually providing all the logic when large amounts of training data is given to them.
For once, let us think that you have no NLP & NLU across any customer service channels. Much of everything would have to be done manually by your customers. They need to solve their problem by themselves through Knowledge bases or by helping each other out through forums. When they are not able to solve the problem, you need to have dedicated staff personnel for live chat, forums and also answer raised tickets. This would be very costly and is also inefficient.
A customer service chatbot that is powered by NLP and NLU works really fast and can generate responses quickly! No more waiting for any customer service personnel to take up the request and solve it.
Today’s technology in NLP and NLU helps to provide conversational experiences in various languages. Not only a literal plain translation, but they would also translate the sentences in a way so that the original intent and tone of the statement do not change. With this, you can achieve a reasonable localization out of the box!
Conversational experiences powered by NLP and NLU are not only able to understand the general meaning of what customers say but also their emotions. With sentiment analysis, your chatbots can clearly understand how the users feel about the service, and by analyzing many instances, they can provide general insights about the efficacy of the customer service.
Integrate knowledge from various sources
There are a lot of sources where useful knowledge exists for customers. Take knowledge bases and forums for instance. With your chatbot readily having access to them, it can easily fetch data that might be or might not be asked directly by the user.
Chatbots do not only have immediate information regarding the customer but a pool of big data regarding you. With this information, it can easily determine what you need and tailor the entire experience in a way that suits you.
Less cost and low number of employees
Although you have to spend certain time and money on initial training, which is sometimes challenging, in the long run, virtual assistants cost fairly less than employing a high number of people for doing the same tasks.
Another main thing to consider is the varying volume of requests. In the traditional sense, if you hire employees, they are fixed and if an unusually high volume of requests come, they can’t handle and if a very low volume of requests come, they sit idle.
Virtual assistant software can easily work with any kind of volume: they scale up fastly when there is a huge need. With this, there would not be any kind of worrying about the volume!
Help customer service staff to perform better
Even Though the NLP and NLU enabled virtual conversational agents are very powerful, there would be some cases in which they cannot solve the whole issue. In that scenario too they would be useful.
The way they help is to present a complete picture of the problem to your customer service agent. That includes details of the conversation, sentiment analysis, and also, all of the appropriate data regarding the customer.
Along with them, there would be many other use cases for NLP in your customer service channels.
Recent developments in NLP and NLU along with general artificial intelligence and machine learning have taken them to a level that is highly usable and economical.
Implementing AI-enabled conversational experiences in all your customer service channels provide a great advantage through rapid response, personalization and localization, integration of various sources of knowledge, and more.
In all senses, NLP and NLU provide great advantages in all customer service channels including Emails, Live Chat, Social media platforms, and others.
There are also a lot of platforms and NLP services that provide you out-of-the-box tools that you can easily use to develop your own conversational experiences that satisfy your needs.
Do this and improve customer service engagement and provide an overall positive customer service experience!
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