Chatbots taking over Call Centre Jobs


The biggest threat to jobs might not be physical robots, but intelligent software agents that can understand our questions and speak to us, integrating seamlessly with all the other programs we use at home and at work. And call centres are, particularly at risk.

We are learning that it’s not only happening in developed countries alone but the truth is technology has no boundaries and its moving very fast, if you are in the call centre business or working in the call centre business chatbots are taking over your duties.

Most Zimbabwean banks and other early adopters of technology are aligning themselves with the latest technology. Live chatbots are able to answer simple queries in an efficient manner, far more quickly than a person ever could. However, humans have the ability to pick up on tone and subtext in a way that a chatbot could never master. Despite the progress made with Natural Language Processing, it remains vital to have a call center staffed by both bots and people; people can take over when the questions get tricky while bots field the quick fixes.

Call center staff need to stop thinking about how to stop chatbots; they need to think about how they can work effectively together with them. Customer expectations from chatbots are simple: they expect quick responses to simple questions and 24/7 support. They don’t expect friendliness nor expert answers from bots. And that’s where staff members can step in and set themselves apart.

In addition, chatbots can be used to handle the initial interaction with customers. Bots can take the customer details and information on the issue, before handing over to an agent. This reduces initial waiting time, meaning customers will already feel looked after and appreciated. If the query can immediately be handled by a chatbot, that means there’s no need for it to be handed over to a call center agent. If an agent is needed, the chatbot can assign the call to the most qualified person based on the information received.

Sooner or later, every company will need to employ a staff of customer service chatbots. In this way organizations can ensure work is done around the clock, human error will be reduced and expenses will be slashed. By using chatbots in your customer relationship management (CRM) strategy, you can be certain that customers are assisted efficiently and competently, but Call centre stuff need not worry a lot about their job security for now.

Call centres still need human intervenes, why, in complex situations where the customer is in need of more help or reassurance, or where the requirement falls outside the standard process, only a human will do. Where the interaction is more complicated or the customer is angry or dissatisfied with a product or service, the skills and attitude of the agent can make a tremendous difference to the outcome for the customer and to the relationship between the customer and the brand. This is reflected in the metrics we care about from contact centres.

“We’ve moved from “time to answer”, through “customer satisfaction” to more “outcome” based measures such as Net Promotor and Customer Effort Score.”

Chatbot can’t work alone, for all the advances in machine learning technology such as improved voice recognition, a chatbot is only as good as it is programmed to be. A customer-driven to their wit’s end by a faulty product, or looking for recommendations for their granddaughter’s birthday present would probably prefer to talk with a human, no matter how clever a chatbot’s AI or machine learning ability.

The truth is that humans and robots have very different but complementary skillsets; great customer service results when they work in harmony. When humans and robots collaborate effectively, it makes the role of call centre operative more enjoyable and more valuable, because they can concentrate on high-value tasks such as turning an irate caller into a satisfied customer. 

But the robots’ role goes much further than handling quotidian inquiries. Not only can AI chatbots replace dull, repetitive tasks. Machine learning can provide invaluable support for human agents.