Book Image

Voicebot and Chatbot Design

By : Rachel Batish
Book Image

Voicebot and Chatbot Design

By: Rachel Batish

Overview of this book

We are entering the age of conversational interfaces, where we will interact with AI bots using chat and voice. But how do we create a good conversation? How do we design and build voicebots and chatbots that can carry successful conversations in in the real world? In this book, Rachel Batish introduces us to the world of conversational applications, bots and AI. You’ll discover how - with little technical knowledge - you can build successful and meaningful conversational UIs. You’ll find detailed guidance on how to build and deploy bots on the leading conversational platforms, including Amazon Alexa, Google Home, and Facebook Messenger. You’ll then learn key design aspects for building conversational UIs that will really succeed and shine in front of humans. You’ll discover how your AI bots can become part of a meaningful conversation with humans, using techniques such as persona shaping, and tone analysis. For successful bots in the real world, you’ll explore important use-cases and examples where humans interact with bots. With examples across finance, travel, and e-commerce, you’ll see how you can create successful conversational UIs in any sector. Expand your horizons further as Rachel shares with you her insights into cutting-edge voicebot and chatbot technologies, and how the future might unfold. Join in right now and start building successful, high impact bots!
Table of Contents (16 chapters)
Voicebot and Chatbot Design
Contributors
Preface
Other Book You May Enjoy
Index

Building multiple personas


We have mentioned the possibility that your bot is serving more than just one target audience. In many cases, you can't identify your users, but in cases where you can, it can be useful to assign different bots to different users. Why is this necessary? While the general business logic of the bot may not change, the conversational flow and the content or information provided may differ to the extreme.

Let's take, for example, a banking bot. It is clear that an interaction with a millennial will be different compared to an interaction with a retiree. Their topics of interest will be different since they have different needs and different prospects. This is why what the bot offers should also diverge. Also, the way that they interact, their voice and style, and choice of wording will be different. A human agent would be able to identify those differences immediately and react to them accordingly, and so should your bot.

While it makes everything a bit more complicated...