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

The bot as an intelligent assistant


One of the chatbot/voicebot's challenges is to provide the user with the the most optimal result it can, based on the parameters it was able to collect explicitly and implicitly. So, can a bot also make recommendations? Can it filter the data for the user?

Trying to provide a more human-like, conversational interaction with a chatbot or voicebot also means being able to filter the enormous amount of data that the user is used to consuming from his/her web-browsing experience. A good chatbot experience will not present us with an endless number of results (obviously this is not even possible when we think about a voicebot).

So, how can we filter 500 (or 5000!) options and give the user the one or two options that fit them best? How can we make sure our bot is advising users? The bot should not only collect information and reply to automatically configured questions, but should also come back with suggestions and recommendations that are specific and accurate...