AI Chatbot Series - Episode 3 - Best Practices of building AI Chatbots

What should I keep in mind for developing an AI Chatbot? Chatbots work well when domain is well understood by the AI system. As the AI chatbot relies on NLP to understand the semantics of the input message, unless the NLP parser is trained on the domain, the accuracy of recognizing the intent and topics of interest would be very low or not as per acceptable criteria.

Take an example of a shopping chatbot which advises user what to buy based on the latest fashion trends.

Consider 3 queries below from a user –

Query 1 – Show me medium size trending black and white dresses for Christmas party

Query 2 – Show me white color, 3 inches platform heels

Query 3 – Find And black and white floral dress under 2000

Here the chatbot needs to understand the following

Understand the shopping language. Understand the intent – It’s a shopping query Understand the domain – Its shopping query for apparel and shoes. (i.e. there can be multiple domains – grocery, electronics, books etc.) Understand clothing shopping category and terminology – Category – dresses, sandals etc. Variants – sizes (medium/large etc.), color (various colors and combinations like black and white), heel size (3 inches. etc.) Prices and ranges – 2000, etc. Brands like – AND, Nike etc. Out of the box, any chatbot implementation wouldn’t understand the domain. You need to train the chatbot on the custom domain to recognize the context and the language.

View this week’s episode to get deeper insights on some of the limitations of AI Chatbots