Chatbot prompt analytics: Identify knowledge gaps and user behaviour

Chatbots now sit on almost every documentation and help site, and customers have become surprisingly skilled at prompting them.

But the most valuable moment is not when the chatbot provides an answer. It’s when it cannot.

Every unanswered, failed, or incomplete prompt is a signal.

It reveals a gap in your knowledge base, highlights customer confusion, and points directly to content your audience needs but cannot find.

In this webinar, you’ll learn how to transform chatbot failure data into a practical content strategy.

We’ll show you how to analyze prompts at scale, group them into meaningful topics, identify high-impact content gaps, and use customer language to better understand audience needs and intent.

Key Takeaways

Treat every unanswered prompt as data

Failed answers map directly to missing, incomplete, or unclear content in your knowledge base.

Turn insight into action

Use the gaps to create new articles or update weak sections of existing ones.

Cluster at scale

Given the volume of prompts, group them into topics so you fix the most important content gaps first, not random ones.

Read the customer behind the prompt

Word choice, prompt length, and question style reveal user personas and intent you can design content for.

About the Speaker

Selvaraaju Murugesan received the B.Eng. degree in Mechatronics Engineering (Gold medalist) from Anna University in 2004 and the M.Eng. degree from LaTrobe University, Australia, in 2008. He has received his Ph.D. degree in Computational mathematics, LaTrobe University. He is currently working as a Senior Director – Data Science at Kovai.co. His interests are in the areas of Business Strategy, Data Analytics, Artificial Intelligence, and Technical Documentation.