Conversational AI is a result of a sophisticated set of technologies like Natural Language Processing (NLP) and Natural Language Understanding (NLU) along with complex artificial intelligence (AI) algorithms that create context-aware computer responses to human queries.

Conversational AI works by:

• Understanding the context & the intent of what is being said with NLP and NLU
• Determining the right response using machine learning
• Developing a human-like response using natural language generation

Conceptually, building a conversational AI assistant happens in three phases: build, train and test. But the devil is in the details:

• Build involves developing the model and all the intent flows for the use-cases that you want to solve for. This including leveraging NLP and NLU as well as pre-trained or proprietary Language Models to providing an initial starting point for the models. Getting the necessary training and testing data is also part of this.
• Train involves using the training data to generate a new ML model that understands the world that the training data signifies and then tuning this ML model until you can see the behavior you expect
• Test involves using test data to test the working of this solution and iterate through build, train and test until the solution is able to deliver responses with a certain level of accuracy,

Conversational AI refers to the technologies that enable computers to communicate with humans in a similar manner to human to human communication. It is a set of technologies that enables computers to recognize human language along with the context of what is being said, develop a human-like response, and respond to humans.

As a result, artificial intelligence technologies like AI Chatbots have become a reality and gaining significant popularity in several areas including customer support automation in online commerce, online lending, digital healthcare, online insurance & more.

Conversational AI is extremely essential in this day and age where:

• Human to human conversations to get help are hard to scale from a cost and human availability standpoint
• Businesses cannot possibly have human agents available 24*7 to field user questions and provide help
• Users increasingly prefer to get help on their own quickly rather than wait to talk to a human
• Users don’t like rigid selection options when they are doing research or need help since such options don’t help them in 90% of the cases which leaves them dissatisfied and in turn dissatisfied with the brand

All of those can be mitigated by conversational AI powered assistants.

As users continue to come to your site and that too at all hours of the day, they will always have questions about your products that they need answers to, before they make the purchase. Also, users who have made purchases from your site may need help with their purchases.

By having an AI chatbot on your site, you can enable your users to get all the information they need at any time of the day, without having to wait to talk to a human agent, thereby increasing the willingness of the user to move forward and purchase your products, in turn driving more sales for you. On the other hand, the same AI chatbot can help answer your users’ questions around past purchases as well as help them take actions such as returns, exchanges, or updates to orders, without them having to wait to talk to an agent. This saves you the cost of having human agents front such requests while also helping your users get the help they need asap, thereby increasing your CSAT.