Bots are about to get better at customer support than humansGeekheads Team
Thanks to machine learning, AI-enabled bots could gain a competitive advantage over human chat exchanges.
In 2018, AI-enabled bots will provide a better customer experience than human-to-human chat exchange, following the explosion of messaging services that have changed the way companies interact with their customers. Today, more than two billion messages are exchanged between people and companies every month on Facebook Messenger alone. Other major players have been investing heavily in the space, creating platforms to support companies in their pursuits to engage customers where they are and in the way they prefer. In 2018, this will give rise to AI customer-service agents that we are happy to deal with.
However, many organisations will fail to create the customer experience they desire because of a fundamental misunderstanding of human-to-machine interaction. In their belief that human agents give the best experience, many will develop messaging applications that stress person-to-person conversations. But companies will learn that using AI-powered bots, supported by human “escape hatches”, which seamlessly pass on the interaction to a human, will provide a vastly better experience than a standalone human-to-human exchange.
This feels counterintuitive. But consider this. Human-to-human chat exchanges are limited to text inputs. Moreover, they are often open-ended conversations, creating a less guided experience for the user. Bots, on the other hand, can respond immediately, and combine prompt buttons and other visual cues along with supporting textual conversations to offer a much richer, guided user interaction. More importantly, AI can scale and apply its knowledge much faster and more consistently than a human as its algorithms improve and it learns. Human agents, on the other hand, need to be trained, respond inconsistently and need to be motivated to care about the customer.
As customers interact with a company, bots can capture data to learn behaviours, habits and preferences – and then anticipate needs. These interactions then improve the entire user base’s customer experience. To try to capture and apply this same data is hard when it is free flowing, non-guided text, and nearly impossible when it is human-to-human chat.