How AI and social media can improve customer service and reduce cost
Dan Patterson asked Joshua March, CEO and founder of Conversocial, how AI and social media can improve customer service and reduce cost.
Patterson: Artificial intelligence and machine learning are changing a number of industries, not to mention social media. Of course social media, but social media along with customer service for TechRepublic.
Josh, how is AI infiltrating social media to make customer service more efficient and less expensive?
March: Sure, and hey Dan, great to be on. A couple of years ago I was sitting at F8, which is Facebook’s developer conference, when Mark Zuckerberg announced the launch of the bot platform. This was the kind of first bot platform for messenger. Everyone went really crazy over it, I’m not sure if you can remember all of the hype that was happening at the time, but Zuckerberg himself was kind of heralding a future without phone calls where every app was going to shift over to being a bot within a few months, where it was the end of human customer service.
The reality was, you know, much, nowhere near what the hype was and everyone realized pretty quickly that if you build a very basic, kind of rule based chatbot, it’s not that effective for customer service. People tend to not like it, you can easily get frustrated and kind of upset people.
The whole area just kind of lost a lot of the luster. Now, since then we’ve actually seen some really big developments happen in machine learning and AI. A lot of businesses have been, like really starting to figure out what does work and what doesn’t work when it comes to implementing AI and bots and machine learning into messaging.
We’ve also seen along side it this huge rise of private messaging and messaging apps for business. You know two years ago when they first announced that, messaging was still pretty small. Over the last couple of years, now messaging has really just taken over the world, in terms of how people communicate with each other, within businesses and from businesses to consumers. We have all of these things starting to come together where we’re now starting to see how you can really implement machine learning, AI and bots, combined with human agents within messaging to really transform customer service.
We’re starting to see a lot of really big progress happening in that space. Even today with kind of simple implementations, if our clients are able to save 20, 30% of all the inbound messages, it can be handled automatically. I think over the next few years we’re really going to see a pretty dramatic shift in this area.
Patterson: Josh I’m glad you drew that distinction between the hype and the reality. Of course the realities of machine learning are, the potential is incredible but it’s a long way from here to there. I wonder if you could help us understand what some of the challenges that businesses experience from 2015 until now. What changed? What has made that big jump forward, to make conversational AI much more efficient?
March: Sure. So, I think the big mistake that people made initially was trying to build completely stand-alone chatbots. So they tried to create a bot that could hold the entirety of the conversation between, with the customer and the business. The fact is, even today with the most advanced AI, the most advanced machine-learning technologies, no bot is ever going to be able to handle the full complexity of any kind of customer service situation that could come up, especially for a big business.
So people kind of tried to build these bots and quickly realized that, while they could handle some certain very specific tasks or simple bits of a conversation, if you tried to leave them there too long, eventually it would frustrate the customer and cause a problem.
So it’s really been, a big thing that’s been a change of approach.
