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How AI can have the sensitive conversations your call center can’t
by Mark K. Smith

In a sensitive business or commercial transaction, would you rather have a conversation with a human or a computer? Your first reaction may well be the former. Humans, after all, have higher levels of intelligence, emotion, and problem-solving skills. A machine might be better at processing basic information from you, but when it comes to complex and delicate cases, surely a human is better equipped.

This may be difficult to read, but humans may not in fact be better than machines at dealing with all emotional cases. Advancements in technology, and increased acceptance from consumers, means AI could have a wider application of conversational uses than previously thought.

This idea has roots that go back as far as modern computing itself. It started with Joseph Weizenbaum, a WWII vet who spent two years at MIT in the 1960s developing a chatbot – ELIZA – which could interact with humans through typed conversations in the style of a psychotherapist. Weizenbaum’s first test subject, his secretary, aware she was communicating with a computer, began to exchange in conversation with the chatbot before eventually turning to Weizenbaum and asking: “Would you mind leaving the room please?”

Far from being deterred by the fact that ELIZA was just a 'bot', Weizenbaum’s secretary engaged with it in confidence, oftentimes completely forgetting it was devoid of any real emotion - but lack of emotion, and lack of bias in particular, plays to a chatbot's advantage.

What humans lack

Everyone has bad days; everyone has their limits in what they can tolerate. Nowhere is this more obvious than in a busy contact center. We assume that empathy and sincerity are either unique traits that come naturally to humans alone or they can be taught and honed. However, even the most patient and attentive contact center employee can become agitated. It is this inconsistency – a trait that is truly unique to humans – which can result in customer frustration.

Recent research has found 52% of consumers stopped buying from a company during the pandemic due to their communication, with 17% of them quoting ‘insensitivity’ in engagement as the primary reason. For firms that have millions of customers across the globe, bringing that percentage down even marginally can represent significant revenue.

It’s not just consistency where machine communications outperform humans, however. They are starting to rank higher in terms of trustworthiness, too. A study by Canada-based market research firm Intensions Consulting found that 26% of Canadian adults believed an unbiased computer program would be more trustworthy and ethical than their workplace leaders and managers. That number was even higher among younger adults – those aged 20 to 39 ­– at 31%.

Only about 10% of people listen effectively. Our attention spans are constantly pulled in different directions by smartphones, our own priorities, and unwanted thoughts. Well-tuned machine learning programs suffer from none of those distractions. In situations where customers need to feel like they have the whole attention of whom they are speaking to and need to feel free from judgement – AI may be best for the job.

The evolving role of humans in the contact center

If AI is more effective than humans in processing and recording basic data, as well as having the higher-level conversations customers expect, then what is the future role of your staff in this dynamic?

This is where we need to make the distinction between conversations where emotions are valued more and those where lack of bias is valued more. For example, speaking to a customer who owes you debt is an emotional situation, but what they are likely to value far more than emotion is the feeling of being free from judgment. They want to feel like they are being treated fairly, with factors such as their likelihood to pay weighed up and factored into the solution. This is where a proactive conversation driven by AI can outperform, with machine learning programs able to put forth sensible resolutions that match their need.

But this approach is hardly appropriate for cases such as bereavement where that human connection is what is more valued. A cold, automated response by a machine is likely to be seen as, well, cold and automated.

These are two broad examples and of course these aren’t absolute statements. There are people in debt who will want to speak to a person for an emotional response, while there will be those who lose loved ones who simply want to deal with things in a straightforward way while they grieve.

The role of both humans and AI is to provide customers with this choice – a personalized, holistic approach to customer conversations. Businesses that can employ AI communications intelligently, where needed, across all stages and scenarios within a customers’ lifetime with you, will reap the benefits.

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