Improve your chatbot capability with Natural Language Processing

The use of chatbots have increased in recent times in different business use cases to enhance conversational experience in terms of quick and more accurate response. Still organizations are struggling in the effective implementation of chatbots as conversational interface.

Chatbots right now work on predefined responses programmed. But the integration of Natural language processing can improve its capability to interact with human being. With the help of NLP, chatbots can learn from human interaction to improve its output.

Organisations use chatbots to interact with customers or user in text or on voice, integrated with different platforms such as websites, Facebook messenger etc. until and unless chatbot does not understand human language, context and intent within the text, it cannot deliver seamless user experience.

What is NLP?

It is a process that enhance chatbots ability to understand the human talk (in text or voice) in more effective manner. Natural language processing extends he learning capability of chatbots to understand human interaction, context behind user input and respond accordingly.

Why NLP?

Using chatbots to communicate with human can has limitation that programmer cannot predict each question that a human can ask to chatbots. Thus, setting default response for unpredictable queries can frustrate the user and this will reduce the utility of chatbots. With the help of NLP, organisation can train its chatbots with different ongoing interaction and this learning will streamline the further response.

Ways to improve your chatbot functioning using Natural Language Processing

NLP assist chatbots in understanding semantics and structure of the user input text. It helps to understand the context and intent of unorganised data to provide more accurate and relevant response of human queries.
NLP enables chatbots to understand morphemes or idioms in different languages input by user. NLP helps chatbots to learn slangs, understand abbreviations like a human being. So, chatbots can talk like human rather a machine.
NLP extends chatbots ability to respond based on predefined keywords to understand human context. NLP can answer both close and open-ended questions.
With the help of NLP, bots can prioritize the unsatisfied or angry customer and connect them automatically with human agents.
NLP helps chatbots in sentiment analysis as it provides with the ability to understand emotions and sentiments behind user input text and voice and respond accordingly in more accurate way to improve conversational experience.
Using NLP, an organisation can improve its market research and social listening ability. As it facilitates summarization of huge amount of unlabelled data, scanning trends with analytics and identifying the things with which customers are happy and they are dissatisfied.
NLP offers opportunity to the organisation to have access on strategic information as it understands user input dialogue on posts or social media, comments regarding company's offerings, and intents behind text in articles, blogs and discussion forum.

Extracting this valuable information from conversational chatbot platform about the customer, helps an organisation to transform these unstructured data into actionable intelligence and improves user conversation experience. it also saves human effort and times as well as company's cost and ensures focused attention towards more strategic work.

Source: HOB

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