In February 2016 The Tab built and released Tabitha a friendly chatbot to manage their on-boarding process. This was an ambitious plan considering they could have used a form. However we believed that chatbots would play a large part in The Tab’s future and the best to learn is by building. 3000 conversations later I thought it would good to reflect on what this taught us and how that shaped Tabitha’s evolution into a Facebook Messenger Chatbot.
Flow based conversations using natural language processing gets complicated quickly
There is a reason that most conversational UI’s use buttons to get people through a flow as doing it with natural language is very hard. There are so many different ways of saying the same thing that it becomes very difficult very quickly with natural language.
Wit.ai is a good free tool for natural language processing
Facebook’s “free” chatbot toolkit otherwise know as wit.ai is a very good place to start building natural language processing chatbots. The latest version is constantly being iterated on and has some nice features that allow all levels of technology competence to contribute. However as with all free services you are without an SLA and although sometimes responsive via support it can take days to get a response.
The words you use are very important in driving the conversation forward
As language is the UI you need to be very careful what you use. We were constantly surprised how people would respond to questions/intents that seemed very clear to us. I read through the majority of the conversations that Tabitha had to find these edge cases and then iterated towards much less ambiguity in our language. Having to support both UK and American authors made this even more difficult.
When people get confused give them clear instructions
Making sure you have a really good way of showing people how to get help when they get confused. In the worst case scenario give them the ability to contact a real person through other means.
Being available 24/7 has its advantages when running a global business
Previously we had to run multiple shifts across the UK/US to do our best to service as many new authors as possible. Tabitha was available 24/7 and it surprised me how many people sign up in the middle of the night.
A lot of people still think they are talking to a human
One of my biggest surprises at looking at a lot of conversations is how many people think they are talking to a human even though the fact it is a chatbot is clearly stated. Building the right level of personality in definitely helps conversations but can getting this right is a tricky balance to strike.
This particular experiment is now closed with The Tab now using a simple form and list based approach to help people sign up and get their first assignment. However what we were able to learn has enabled Tabitha to become a cornerstone of the automation of author conversations. Chatbots seem to me to be best suited at the moment for small pieces of personalised information delivered over time that give you context to a larger process. The more personal the information the better it is opened and enjoyed.