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

Can a banking bot become a travel bot?


I believe it can and will in the future. The concept of personal assistants, such as Siri and Alexa, will expand to allow cross-application interactions and recommendations. This is a highly complicated task, but by leveraging data, and with the right classifications using AI, this could be achieved.

In the meanwhile, we can leverage cross-bot and cross-vertical learning, mostly when approaching common use cases. Some of our banking use cases are similar to our travel/flight bot use cases and even insurance use cases or enterprise internal use cases, such as ticketing systems. For example, checking on the status of <item>.

For the banking use case, it could be:

What is the status of my loan application?

For the travel bot or flight status bot, it could be:

What is the status of my hotel reservation/flight?

For the enterprise ticketing or insurance use case, it could be:

What is the status of my ticket/my claim?

While the use cases are fairly different...