Have you heard about “the one thing” productivity hack? If not, it’s the ONE thing you can do such that by doing it everything else will be easier or unnecessary.
Chatbots too, have ONE thing.
I’ll get to that in a minute but first, some backstory. We built a natural language chatbot using IBM Watson. IBM has a solid suite of tools, cognitive services, and cloud infrastructure required to build sophisticated AI-powered applications.
A chatbot is one such application. As we got familiar with the Watson environment, capabilities, and limitations we came to places where we debated going left, right, or straight ahead.
If you’re thinking about deploying an NLU chatbot I have a set of guidelines learned from doing it.
5 Strategic Recommendations
1. Have a Vision. Because vision is the ONE thing. Who is the bot going to help and how is it going to do that? Before we started making our bot I envisioned a person driving through town, both hands on the steering wheel, asking Siri to book a flight. You can read how we got to that point in
AI Will change the customer experience: a look five years forward.
2. Build to your vision. At one point during development it became clear that dialog buttons could be used to expedite the project. Dialog buttons are Yes/No; Small/Med/Large, options in a conversation.
When we hit that point in development the thought occurred “should we or shouldn’t we?” That’s where vision our vision led the way. Can a motorist with both hands on the wheel engage in chatbot dialog with buttons to press? There would be no buttons.
I’m not saying we are locked into this vision for eternity. Product and market evolution might require a change of course and that’s OK.
3. Keep it simple. Natural language chatbots need to be trained in the language of the domain in which they are used. The tighter the bot’s purpose, the less data it needs for training. Start with a few tasks for easier development and ongoing improvement.
4. Understand the data flow. Chatbot conversation can take place through any number of UIs ranging from Facebook Messenger to smartphone assistants to your own app. You’ll want to understand who has access to your data and how it’s governed by your own and regulatory data protection and privacy policies.
5. Analyze. Natural language dialog is a new and rich window into the customer experience. part of your pilot program should include testing the system that will capture and analyze this information.