Sometimes things do not go your way. This is the case in life, but it is definitely also true when interacting with chatbots and voice assistants. Conversational AI often does not go the way we want it to. It leads to disappointing experiences, and ultimately a rejection of the experience.
Luckily, there are ways to design conversational experiences in a way that makes chatbots and voice assistants more helpful, natural and persuasive. And an important element of designing better experiences, and unlocking the potential of conversational AI, is through error handling.
Conversations are messy. We misunderstand each other, or our thoughts wander off and we did not listen to the question that we were asked. Humans have developed amazing techniques to deal with such situations. We ask for clarification, or we share more details to get the other person to engage with us.
If we translate this to conversation design, we can say that we pretty much have techniques for when there is a no-input and when there is a no-match. Let’s discuss both error handling types and discuss some examples to explain these concepts.
Sometimes you ask a question and the other person does not respond. Imagine walking into a hotel lobby and having the following conversation:
Because we do not engage with the question that we are being asked, the receptionist adds more information to the question in the next turn. It tries to feed us more information to increase the chance of us engaging with her. In conversation design, we call this escalation detail – or prompt verbosity.
For every node, in a perfect world, you want to write 3 error handling messages for a no-input. You want to add more information to the question to help your user engage with you.