Conversational UI (CUI) is nothing new, but it is making a big comeback in the mainstream market because of advancements in AI. With the number of chatbots and voice assistants that exist today, CUI is an active medium for organisations and brands. But what should you know before jumping on the bandwagon? We rounded up our top five tips to consider to get your CUI just right.
Trigger and channel
First, you must pinpoint an incentive as to why your audience should engage with a CUI. Will it help users complete a task, solve an issue or exist for entertainment? Once you understand why there is a need for a conversational interface, it’s time to think about how you can trigger the user to engage and map out the channels to carry the conversation. For example, will the entry point start on a website before switching to another platform? Will it incorporate text or voice?
One of the advantages of using this medium is its ability to create a truly personalised experience for each user. But to do this, it will need some context beforehand, and the best way to get this information is through data. Allowing data access is necessary because it creates a framework for a seamless, one-on-one conversation for every user. Recording data also gives the CUI a reference point for future discussions.
Fall back plan
AI technology has come a long way, but it’s inevitable there is a hiccup now and then. To avoid frustrating conversations with continuous “I don’t know” responses, you need to think of a plan B. Offering a link to a contact centre, redirecting the conversation back to its original context or offloading the chat to a real human are all viable alternatives.
We like to think of developing a personality as more of a characterisation. What we mean by that is it’s essential to use copy and media together to not only ensure the conversation completes the right action, but it does so in a way that’s fun, interactive and consistent, to ensure the CUI maintains a distinct tone of voice in every interaction.
User testing is crucial to make to ensure your project meets expected outcomes and, above all, is usable. Defining parameters helps set the bar to measure results and determine which elements need further development. In most cases, this could mean optimising the NLP so that it not only recognises what a user is saying, but also the variety of expressions to say it.