‘Big Data’ Analytics can quite easily help preempt calls into the call-centre. Next step, AI to mimic empathy?

http://www.ft.com/cms/s/0/fca8c484-e071-11e5-9217-6ae3733a2cd1.html#axzz41uxq5yop

This article is a fantastic piece on how technology can be applied. Basically, a bank is introducing AI to answer customer calls; the AI is an attempt at mimicking empathy.

One of the issues with using IVRs is that people used to complain that there was no human warmth, just cold efficiency and sometimes there were no relevant options, wasting precious time, worse still aggravating the caller further.

Technology has moved so much since the early days of IVRs. Initially, a caller was ‘faced with having a menu to navigate through by choosing options read to them, over and over, continually narrowing down the options until the ‘reason for the call’ is isolated and hopefully the issue could immediately addressed.

Simple usage statistics can help make the menu relatively more relevant, from simple counts to assign option priorities based on relative usage, sometimes based on the time or the customer demographics,  to slightly more complicated paths based on costs, expected probability of eventually having to go through to a call agent. 

Usually such menus are designed to try and resolve the issues before the caller resorts to the agent, or at least narrow down the issue to facilitate the work of the human agent. After all, human agents ‘cost more’ than machines.

The next step in the improvements to call agent systems is to preempt the calls. This involves finding out the ‘reasons of call’ and pro-actively contacting the customer with a solution before the customer picks up the phone to call into the call centre. 

While finding the events that usually lead to customer calling into a call-centre is relatively easy, I was initially skeptical whether there would be time to contact the customer before the call is made. But after working this issue with real customers, I was pleasantly surprised to find that even in these days of mobile phones and instant gratification, people would most often not immediately call into a call-centre for less than critical issues. For sure people would immediately call in if their card was swallowed by a machine or physically cut by a cashier, but even if their card was declined, people do not always immediately call to query the issuing bank. Most people having more than one card relationship helps; but this pattern also occurred in non card-related issues. People are more patient than I had expected.

Hence it is possible to anticipate who is likely to call into the call-centre and in many cases propose a solution before the customer calls in as illustrated above. This can be refined by adding an extra filter where the decision is made whether the organization wants to allow the call through, for cross-sell purposes for example.

The technological improvement highlighted in the FT article further minimises the chances of a call reaching a human agent that ‘costs more’ than the machines. The AI can mimic empathy and the customer can have his/her issue resolved without the coldness of a machine.

A combination of anticipating the call, deciding whether to preempt it, and possibly having the AI respond to the customer is a great way to control the customer experience and cost.

My question is whether mimicking emotions will be enough for customers, or would knowing that you are ‘talking to a machine’ albeit one that sounds human make you feel better.