You see, any technology solution or product implemented without a clear problem in mind is just wasteful. And it is this lack of understanding that is to blame for why chatbots are on a fast path to nowhere in most companies.
Two and a half years ago, there were only a handful of chatbot providers. A year ago there were thousands. Any remotely adept coder could “whip a bot together” in a few hours and surprise-surprise, VCs went in hot pursuit of companies to fund.
Fast forward to today and hearing the phrases “our chatbot proof of concept was not what we hoped” or “we tried chatbots and they didn’t work” flowing off those same CIO and CMO’s tongues as quickly as those overused buzzwords.
But we’re not surprised. In fact we welcome the demise of pointless technology. When we last checked, Facebook Messenger had over 100,000 chatbots, many of them are failing to impress, leaving users underwhelmed and frustrated.
So, is this the end of chatbots?
It certainly is the end of companies creating chatbots for the sake of having a chatbot. But, it is the beginning of a major technology shift, a quasi-revolution called AI-based automation — and chatbots certainly have an important role to play.
For chatbots to survive, they have to solve a business problem. Period. This business problem has to be clearly defined and distilled into real use cases that have true ROI and/or net promoter score implications. And, meaningful implications driven by a marketing purpose.
As mentioned above, technology implementation without a problem being solved is wasteful. So, with automation, AI and chatbots, the same theory applies.
As soon as the use cases are clearly mapped out, the case for automation comes next. Can this problem be solved by removing the human element in the backend? If so, there will undoubtedly be a cost benefit to the company. A smart design here will allow for escalation to human agent in the (hopefully) shrinking contact center.
Once automation is given the green light, a myriad other technologies need to be spun up in order to create an effective system that solves the problem long term. As an example, if the business problem was around customer service, and the use case was automating bill pay, then payment gateways, an asynchronous messaging channel, an authentication system, encryption and privacy layer, feedback loop, API bridge into the billing system and others need to work in unison.
You’re now probably wondering what this has to do with a chatbot or rather, where does the chatbot come in? Well, therein lies the point of this article: a chatbot only has a role to play if it delivers utility to the customer. In the case of bill pay, the experience the customer will be presented visually is in the form of a “chat”. And this conversation is programed inside the chatbot using either decision trees or what we call in the AI world, natural language understanding (or NLU).
If I had one wish for this industry, it would be that we get rid of the term chatbot and instead call this experience a CI.The evolution to a user interface built around conversations i.e., a conversational interface or a CI.
CIs done properly with a true business problem in mind, will essentially reach deep into the business’s back end, into the business’ processes and through a persistent and very secure messaging channel, allowing the customer to do business. Anytime, anywhere and most of all, happily.
Originally published in VentureBeat.