Conversational Design – A date with Watson Conversational chatbot

Raj Joseph

I don’t know about you guys…but sometimes I feel when I have conversations with folks, I tend to think how the hell did I get into this as either the conversation has got into something I didn’t intend to or the other person has no clue of what Iam talking to.LOL! When I feel that way with “full” humans, Iam kind of skeptical about any conversations with man-made chat bots. This is where Conversational Chatbot comes in.

Conversation meaning is “the informal exchange of ideas by spoken words” per google search. The best synonym I like for conversation is “heart-to-heart” conversations. Who doesn’t love a heart to heart connection and conversation?

So, I decided to try some “heart-to-heart” conversations with some chatbots out there to see how effective they have designed it.

Here is my first part and my first try was with Watson Assistant Chat App which is trained for specific set of car capabilities.

This is how the conversation went…

I like the fact that it cared to ask what cuisine Iam interested in. However, when I didn’t give any choice and asked to pick one for me, the bot struggled. Also, when I said Iam not in a mood for tacos, it made it worse as it lacks sentiment analysis. More trouble started when it came down to when I asked to take me to the closest location as still it was asking whether the first, third or nearest and so on. I would have thought closest is synonymous to nearest and would have given me the nearest location.

From a Conversational design evaluation perspective, Iam looking at the following attributes for my rating –

• Personality – How does this bot differ from others? Does it have a taste of humor in its response?
• Content – Every word uttered by the bot matters, and use of emojis, gifs, images, videos, makes it more presentable
• Flow – A designer must create and build all of the paths the user could take to reach the end goal. The more storyline , path you have the better the experience in terms of the chat bot experience.
• Strategy – This involves the effort put in building the main conversational flows, determining the feature set including any web hooks/integrations we should have, text vs speech input mode, etc.,

Based on the above criteria, I gave the above bot created using Watson a rating of 5 out of 10 as it lacks personality, and fun content. The flow is moderately well designed but however there is not much support of strategy around it as it’s a simple example. Hope this gives an idea of how conversational design shall be applied to chatbots!

Let’s converse to build a conversational chatbot!

Related Read – AI Powered Chatbots with Use cases

Raj Joseph

Raj Joseph is the Founder of Intellectyx, a next-generation AI, Data, and Digital Transformation company specializing in Agentic AI, Generative AI, advanced analytics, and enterprise data platforms. With more than two decades of experience in technology leadership, product strategy, and digital innovation, Raj has helped organizations modernize operations, unlock value from data, and accelerate AI adoption across complex business environments. Throughout his career, Raj has led enterprise transformation initiatives spanning data management, business intelligence, analytics, cloud modernization, and AI-driven automation. Under his leadership, Intellectyx has delivered solutions for enterprises, government agencies, and high-growth organizations seeking to operationalize AI and build scalable digital platforms. Raj is a frequent contributor to discussions on Agentic AI, enterprise automation, intelligent data platforms, and the future of AI-powered business operations. His focus is on helping organizations move beyond experimentation and deploy production-ready AI systems that deliver measurable business outcomes.

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