Around two years ago, the term chatbot shot into our vocabulary and onto the agendas of CIOs and CMOs everywhere. The idea that a customer could simply “chat” with a robot anytime, anywhere made so much sense — or did it? Any technology solution or product implemented without a clear problem in mind is just wasteful. And it is this lack of planning that put chatbots on a fast path to nowhere in many 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 we’re constantly hearing the phrases “our chatbot proof of concept was not what we hoped” or “we tried chatbots and they didn’t work” rolling off the tongues of those same CIOs and CMOs.
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.
Automation needs a purpose
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.
As mentioned above, companies waste valuable resources when they implement new technologies without first establishing an actual problem to solve. The same theory applies to automation, AI, and chatbots.
For chatbots to survive, they have to solve a business problem. Period. Executives must clearly define this problem and distill it into real use cases that have true ROI and/or net promoter score implications — meaningful implications.
As soon as a team clearly maps out the use cases, the case for automation comes next. Can the company solve this problem 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 the higher-ups give automation the green light, the company must spin up myriad other technologies in order to create an effective system that solves the problem long term. As an example, if the business problem were around customer service and the use case were 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 would need to work in unison to provide a complete solution.
Rethinking the word ‘chatbot’
You’re now probably wondering where the chatbot comes 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 visual experience the bot presents to a consumer is in the form of a chat. Developers program this conversation inside the chatbot using either decision trees or natural language understanding.
If I had one wish for this industry, it would be that we get rid of the term “chatbot” and instead call this user interface built around conversations a CI, or conversational interface.
CIs done properly, with a true business problem in mind, will reach deep into the backend through a persistent and secure messaging channel, allowing the customer to do business — anytime, anywhere, and, most importantly, happily.
Richard Smullen is the CEO and founder of Pypestream, a company that brings the on-demand economy to enterprises everywhere by leveraging the power of smart messaging, pragmatic AI, and chatbots.
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