Everyone these days is eager to jump into an us vs. them mentality. Clippers vs. Lakers, peanut butter vs. jelly (okay, haven’t heard that one yet, but it’s coming sooner than later, I can almost guarantee it). It’s an easy mindset to slip into, but I want to challenge you to think of “and” instead of “vs.” When you put things together instead of making them oppose one another, you often get something better than the sum of its parts.
For instance, in the world of customer service, the idea of chatbots is often presented as a way of replacing customer service reps. It’s the idea that a machine can do a person’s job, and as AI-powered chatbots have become more and more common, the threat to customer service agents has grown.
But does it need to? Is that really the reality of the situation or are we simply entering a new chapter of customer service, one in which machines and humans work together to improve the experience of everyone.
The Machine Takeover?
I’m not going to be naive. Chatbots have fundamentally changed the way that companies utilize customer service, and it’s not just a few. As the technology has become more ubiquitous, more and more companies have added chatbot functionalities to their websites. In fact, IBM estimates that 80% of all customer inquiries will be answered by chatbots this year.
That’s a huge shift in very little time. Whenever a rapid transition like this happens, people are going to panic. However, I believe that the days of customer service reps are not over. In fact, if companies are smart, this is going to be a golden age of customer service, when customers can get the answers they want quickly and customer service reps have a better quality of life.
Chatbots & Humans: An Unstoppable Team
So how can chatbots help customer service reps? Let’s take a look at what exactly chatbots do well.
Customer service agents usually get flooded with basic questions. “Is X product available?” “Do I qualify for Y policy?” “Is it possible to have B service by C date?”
These questions can usually be answered with a simple yes or no after asking getting some basic information. Sometimes, these questions even have straightforward answers that most customers could find the answer to on websites with just a little digging. However, for whatever reason, they didn’t bother looking, much to the irritation of customer service agents everywhere, who have to answer for the umpteenth time that yes, that policy would cover XYZ procedure.
Chatbots, on the other hand, do not get annoyed by answering the same question again and again. In fact, that is their bread and butter. Not only do they not get tired of repeating the same information, they do it 24/7 with a smile on their digital faces.
Advanced, AI-powered chatbots, like the ones we use, can even answer more complicated questions and look at the customer’s data and pull in relevant information to help address customers’ needs.
However, even the most advanced chatbot has limitations. For instance, a chatbot might have a hard time detecting a customer’s emotional response, whereas a customer service agent can quickly respond to an upset customer’s tone. Chatbots might also have a hard time finding answers to questions that require a bit more nuance.
You see where I’m going with this? In most cases, you still need both humans and machines. When we start thinking about chatbots and customer service reps, you get something beautiful.
Consider this: If a situation requires customer service agents’ attention but all the representatives are busy, a chatbot can be used to schedule customer service appointments while humans are addressing other customers’ needs. This is not a unique situation and it also highlights the strengths of both bots and humans.
This is the dream scenario–chatbots triaging basic questions, freeing up customer service reps to answer more complicated queries.
Us and Them
So what’s the ultimate moral of all this? If the expression peanut butter vs. jelly seems ridiculous to you, then so should the idea of chatbots vs. humans. Humans and chatbots complement each other, and companies should understand the limitations and strengths of both. When you put them together, you get the best of both humans and machines.