Accept that your bot can’t – and won’t – do it all. Even AIs like Siri, Cortana, and Alexa can’t do everything – and they’re much more advanced than your typical customer service bot.
Also, attempting to answer every question under the sun poses a data challenge, Phillips said. Using data to train chatbots is key to building them right, so if your chatbot tries to answer everything, you’ll end up with too much data that will be difficult to keep up with. “Casting too wide a net will affect the performance of because you’ll just be overloading it with data and it’ll start to get confused,” said Phillips. “That’s where we see a lot of performance issues.”
Chatbot platform
Your audience should drive your chatbot platform choice if possible. If you can collect information on which messenger platforms your audience uses then this should assist your decision. Facebook Messenger is the most popular with over 1 billion active users as well as being constantly improved by the Facebook team. This is our favorite messaging platform. We particularly like the UI elements which we can provide using the Facebook platform. Have a look at our Customer Support chatbot to see an example of these elements.
Leverage omnichannel and micro-moments
Chatbots are in the perfect position to act as a bridge between a website or app and a brick-and-mortar store.
For example, our Decathlon client implemented a function to sign up new memberships within their chatbot, but also drove customers to the opening of their flagship store.
Easy Scalability
Unlike your live support, chatbots can effortlessly manage conversations at scale during peak business hours without additional customer service costs of adding extra manpower resources.
Cost savings are estimated to reach $7.3 billion globally with bots. Planning out a chatbot strategy helps businesses to save customer service costs of hiring resources that require additional costs such as salary, training, and infrastructure costs.
YakBot
Upon creating your first bot, a simple tutorial explains how the platform works. Basically, you develop your chatbot as a series of flows and triggers that specify how the bot responds to users messaging it. The most basic trigger is a new message:
In the above example, when a new message is received the bot will reply with either “Hello”, “Hi,” or “Hiya”. You can specify triggers for certain phrases and, consequently, specify a bot’s actions for those triggers. The bot can reply with either a message, a question, a card or some custom integration, e.g. linking to a Google Sheets document. And that’s basically how most chatbots are programmed, in a nutshell.