Conversational Ai, Explained

When you consider the idea of having to anticipate the 1,700 ways a person might ask one straightforward question, it’s clear why rules-based bots often provide frustrating and limited user experiences. Compare this to conversational AI enabled chatbots that can detect synonyms and look at the entire context of what a person is saying in order to decipher a customer’s true intent. Two of the core technologies underlying AI chatbots are natural language processing and machine learning . NLP is a subfield of conversational ai bots artificial intelligence, the goal of which is to understand the contents of a message, as well as its context so that the technology can extract insights and information. A chatbot that connects to your support systems means it can pass on information to automate ticket creation and equip agents with conversation history when their expertise is needed. Even better, using artificial intelligence, your chatbot may even be able to deliver recommended answers, knowledge base articles, and more to your agent.

Integrate – Depending on your use cases, you might want to also integrate with your other back-end systems like your CRM or accounting software. This way, the conversational AI can actually pull in data from these sources to resolve customer service issues on an individual basis without human intervention. Because conversational AI doesn’t rely on manually written scripts, it enables companies to automate highly personalized customer servi