The Role of Automation in Customer Service Jobs

The Landscape

For the last few years, the drive to implement robots and automation into customer service (CS) has increased, along with the hype surrounding it. In 2018, it’s very easy to find articles about AI and automation being the future of CS right alongside articles vilifying it as a stealer of jobs; a risk to the CS job market. Implemented correctly, automation can offer companies huge savings (at Gnatta, we’ve saved just one client £3.2M a year). And it can also increase efficiency during the customer care journey and, thereby, improve the customer experience.

In February, Gartner predicted that 25% of companies would adopt bots or virtual assistants by 2020, up from 2% in 2017. They even go so far as to predict the use of virtual realities — to create immersive solutions for customers — within 2 years. So, it’s safe to say that automation and AI are here to stay. But is it ready to take over the industry and remove the human operator from the equation?

Robots vs. Humans

Robots are the talk of the town this year. They can gather data from the customer, call external systems to retrieve information, and use all that to answer customer queries. For example, we found that — for our clients — up to 78% of customer queries were FAQs; simple questions that needed simple answers. Bots can effectively answer these questions with no reduction in customer experience and cut down on a business’ contact volume. This can provide cost savings like those we mentioned earlier. For one client, we were able to take their average of 12 contacts per hour and bump that up to 20, simply through the use of automation.

On the surface, that sounds pretty threatening to the role of the CS agent. But bots are not intelligent enough to replace jobs, at least not yet. To take over from humans entirely, you’d need a true AI. Here’s why:

Despite bots being able to handle 78% of interactions, there’s still another 22% of contacts that need answering. These are complex queries that a bot is not intelligent enough to understand. These bots utilise a natural language understanding engine, meaning they’re able to recognise language and interpret its meaning, which is a pretty impressive leap forward from a few years ago. But, if it fails at any of these points, it’s default is still to pass the conversation to a human. E.g. if a customer can’t provide their order number, the bot is simply unable to figure out what to do next (besides giving the problem to a human). A true AI (artificial general intelligence) is closer to a human in its intelligence and — given enough time to learn — would likely be able to come up with a solution to this scenario. But the technology behind this is still spotty at best and, compared to simple bots, producing them is incredibly expensive. In reality, this kind of AI technology is still over 10 years away.

And that’s without mentioning emotions. Although there have been attempts to give robots emotions, the bots currently being used in CS are far from those capabilities — just one of the key things that give humans the edge over their robotic counterparts. If a customer becomes angry or upset about a missing order, the bot can’t interpret this; they can only carry on with their assigned tasks. But, it’s possible to program backup options into bots so that when an emotional situation arises, the conversation can be passed onto a human operator who has the skills to deescalate the situation and, in due course, resolve the query.

Automation and Humans: The Dream Team?

Working together in this way — robots picking up the initial interaction and gathering data and humans focusing on resolving queries and providing an outstanding experience — is the automation solution we recommend to our clients. Working alongside these bots is something that human operators will have to become accustomed to in the future because it’s currently the best balance between cost-efficiency and customer experience.

So, what does it look like? As we said before, bots can pick up the initial query and gather needed data. But, through automation software (called workflows), the bot can also pass all the information to a human operator. Bots can take a customer’s question and decide things like what kind of question it is, what external data it may need to access, and what information it will have to ask for (such as order numbers or account details). That means that by the time an interaction is passed on to the operator, the bot should have collected all — or most — of the data the operator needs. This makes the job of the operator easier since they don’t have to waste time asking for the information themselves. With Gnatta, operators can receive an interaction and already begin working on the solution right after they say hello.

Beyond bots, automation software is also a CS operator’s dream. Workflows are good for a whole lot more than sending data. They’re actions that fire based on pre-configured triggers. They can be used for all sorts of things, such as to send follow-ups after an interaction has finished, including asking for reviews. This job would usually fall to the operator but automation means that businesses can automatically send out those follow-ups and give even more time back to the operator. And, in Gnatta, if a negative review comes back, workflows route that review into an open interaction so operators get to act pro-actively and turn the review around.

As another example, workflows can be used to prioritise interactions and route them appropriately so that an operator doesn’t get swamped with interactions or end up with nothing to do at all. Interactions with higher priorities can be dealt with immediately and lower priority interactions (such as those on slower channels like email ) can be dealt with when the operator has closed all the others. Automation means operators don’t have stress during peak and don’t have to wait around during slow periods.

We at Gnatta believe that, when it comes to hiring CS operators, automation is your friend. We won’t promise that automation is the shining revolution of CS because automation will enhance, not replace, the job role of human agents. By implementing automation, a business can not only create a better customer experience, but also a better operator experience. This, ultimately, means operators are more productive and, by extension, means customers are happier. And, besides, it’s the empathy and compassion behind a great customer experience that gives humans the upper hand over their digital counterparts. That’s not about to change any time soon.

Artificial Intelligence Timeline - Infographic
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Deepa Khatri