There are two fundamental differences between conversational experiences, like IVR, voice and chatbots, and graphical user interfaces, like web and mobile experiences. These differences demand a different approach.
Learned vs Instinct
Web and mobile are learned experiences. They use physical metaphors like inertial scrolling, desktops and filing cabinets. But the interaction we have with them is learned.
We learn to use a touchscreen or mouse. We discover how to navigate the user interface. We adapt to the technology. And we can do that because we have big flexible brains that can adapt our behaviour to our environment. That’s what helped us populate every corner of the globe and imagine, build, and use digital devices.
But language is different. Conversation is different. We learn language at such a young age that we can’t unlearn it. Harvard Professor Steven Pinker describes language as an instinct. Just as babies instinctively attach to their parents for food and protection, they instinctively develop language. And we can’t un-learn it.
The other big difference is that most of the channels we use to interact with bots started as ways to interact with humans: the telephone, text messaging, web chat, WhatsApp and Facebook Messenger. These were all originally used for talking with other humans. Bots joined the party later. So customers interacting on these channels don’t just need bots to speak and listen like humans do. They also expect them to be smart, helpful and resourceful in solving problems, just like humans are.
Web and mobile experiences don’t have that human expectation problem. Most web and mobile customer service experiences are like forms and documents, in-store adverts or shopping catalogs. We expect those things to be useful and easy to understand. But we don’t expect them to be smart, helpful and resourceful.
These two differences set a really high bar when it comes to building bots.
We adapt to use web and mobile experiences, and we expect them to be useful. But we won’t, in fact we can’t adapt to the way bots talk, and we do expect them to be smart, helpful and resourceful.
They need to speak and listen like a human, then understand and act like a human would too.
A different approach
The best Artificial Intelligence (AI) algorithms today can match or exceed human performance in specific, narrow areas. We don’t have a generalized form of AI with anything like human levels of flexibility and robustness. But there is a fix for this.
You need to treat your bots like a workforce, that needs leading and managing, just like humans do. You need clear job descriptions for your bots, so they can excel in their narrow areas of expertise. And you need to review their performance and coach them to improve, just like you would do in regular 1-2-1s with your staff. We call it HR for AI.
It’s a big mindset shift, but once you look at your bots from that perspective, getting maximum ROI from your investments in conversational AI becomes as simple (and difficult) as applying management best practice to your bots.
Why voice and conversational AI is on the rise
UX is changing fast, and businesses will have to learn new types of interaction design. Voice promis…
Designing conversational AI chatbots and what we can learn from IVR
Conversational AI chatbots are a hot topic. Looking at our Twitter and LinkedIn feeds, the interest …
Multichannel Considerations in IVR & Conversational AI Design
At a time when new channels are emerging, the differentiators for retailers are going to have an awf…