This helped businesses free up some manpower. Today, chatbots do more than just converse with customers and provide assistance – the algorithm that goes into their programming equips them to handle more complicated tasks holistically. Now, chatbots are spearheading consumer communications across various channels, such as WhatsApp, SMS, websites, search engines, mobile applications, etc.
With the addition of more channels into the mix, the method of communication has also changed a little. Consumers today have learned to use voice search tools to complete a search task. Since the SEO that businesses base their marketing on depends on keywords, with voice-search, the keywords have also changed. Chatbots are now required to “interpret” user intention from the voice-search terms and respond accordingly with relevant answers.
A more modern take on the traditional chatbot is an AI chatbot with NLP that is equipped with programming to understand natural human speech. This is technically termed Natural Language Processing (NLP). A chatbot usa student data that can “understand” human speech and provide assistance effectively is a smart AI chatbot designed for automated customer support.
An NLP chatbot is smarter than a traditional chatbot and has the capability to “learn” from every interaction that it carries. This is made possible because of all the components that go into creating an effective NLP chatbot. Let’s take a look at these components.
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Components of NLP Chatbot
A Convincing UX
The primary purpose of an NLP chatbot is to engage with consumers. Unless the speech designed for it is convincing enough to actually retain the user in a conversation, the chatbot will have no value. Therefore, the most important component of an NLP chatbot is speech design.
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