Humans versus Robots: Applying Behavioral Science to Deliver Better CX

Using Behavioral Science to Improve CX in Financial Services

In 2017/8 I worked on a project with partners at OEE Consulting (now GoBeyond Partners), a leading services and operations management consultancy. The client was an outsourcer that ran a call center for one of the UK’s largest savings banks (having over 20 million customers). OEE Consulting were developing a number of new processes and systems, based on lean principles, to deliver better processes in the call center. These had both an efficiency (i.e. money-saving) objective and an effectiveness one (i.e. delivering better service for customers). 

I was brought in to advise on how we could deliver better customer service through addressing what customer service representatives (CSRs) were saying on the phone. That is, using behavioral nudges to improve the quality of outcomes for both customers (more successfully answering their reason for calling, such as making a balance transfer) and the bank (reducing the duration of calls so they could handle more, as well as encouraging customers to take up online and paperless offerings). 

One example: our analysis found a surprisingly high number of people were failing the mandatory security checks. After listening to calls, we discovered this was because the framing of these checks was very formal, and slightly confrontational. CSRs were in effect saying that if customers could not prove their identity, the bank could (and would) not help. With older customers in particular, this interrogatory approach was causing them undue stress – which has been proven to affect mental availability and the ability to recall information. As a result they would frequently panic and get their answers to the mandatory security questions wrong. This lengthened the call, as well as making it unsuccessful and frustrating for the customer.

With a few small tweaks to the wording, we changed the scripts to frame them more positively (e.g. from “if you prove your identity” to “when you prove your identity”) and even said to customers that they could “take their time”, to put them more at ease – a counter-intuitive solution. By slowing down the conversation, this would actually reduce the overall length of the call. 

It is an example of how behavioral science tells us that how you say something is as important as what you are saying – if not more so. 

This was one of multiple interventions (nudges) employed. For practical reasons it was not possible to run a full randomized controlled trial to isolate each nudge. Instead we ran a controlled pilot where a representative sample of CSRs in the call center were trained and coached in using these nudges over a 12-week period, and we monitored the outcome of those calls versus the rest of the call center.

Although we were not isolating the impact of each intervention to the standard required by an academic journal, we were using data to build an accurate picture of what worked; we verified it through experimentation; and we had hard data on what was actually happening through data based on behavioral outcomes (the outcome of the phone call). There was a clear, direct link between what our decisions were as a business, and a behavioral outcome. 

Consequently, we could say with confidence whether we had delivered a positive impact on the business. 

Over the course of the pilot, there was an 11% reduction in the duration of calls versus the control, worth potentially millions of pounds due to the thousands of calls handled every day. Customer satisfaction levels increased, and we could prove overall success in terms of efficiency and effectiveness based on behavioral outcomes. Subsequently the training and process was rolled out to the other 300 CSRs in the call center. 

Humans Versus Robots 

Recently, I was sharing this case study with a group of MBA students, and I was asked: “Could these improvements not have been delivered by automation instead? If they had replaced all the people with robots (chatbots), would it not have achieved the same effect?” 

One thing you notice in a call center (for example) is that skilled customer service representatives can instinctively tell within a few seconds (or less) how a call is going to go – they pick up subtle voice cues that tell them if the caller is seething with rage about a perceived injustice, and adapt their tone of voice and responses accordingly. To deliver a good service they will reflect this in their own tone and language (the psychological technique known as mirroring), and respond sympathetically. 

In this project described above, there was a large discrepancy between the typical age of callers and that of the staff. The oldest caller I heard was 97 years old, and some call center staff were recent school leavers – an age gap of 80 years!  

Some calls were complex, requiring rigorous security processes, meaning a lot of calls were an exercise in patience for both parties. To a certain extent, these problems were addressed successfully through the previously described script changes, which put customers at ease, recognized their more emotional, system 1 behaviors and better explained the processes. But it was clear that some more instinctive, ‘softer’ skills were also required. One of the best CSRs I listened to was a young student (studying part-time), who was endlessly patient, helpful and highly effective at dealing with the more difficult, older customers.

I asked how she was able to keep calm and still deliver great service after a lengthy, challenging conversation with a customer. 

“I just imagined I was talking to my grandmother,” she said. 

This is a great example of the differences between human-to-human and human-to-robot interaction, and how businesses often underestimate the importance of psychological and behavioral factors in creating better experiences for customers (humans). In this case, the CSR was one of the best performers because she had empathy with customers, and the technique used – imagining she was talking to an elderly relative – was one others could learn from. 

An automated, generic response from a digital robot assistant (a chatbot) – a cheery “How are you today?” for example – that shows no empathy with a customer complaint, will simply deepen their anger, not lessen it. The ‘computer says no’ response immortalized in the famous ‘Little Britain’ sketch struck a chord precisely because it reflects the type of experience we have all had – where a product, service or system has been designed without an understanding of the humans using it. These lead to a significantly worse experience, and likely lose a business a customer (or several, if they tell their friends about it on social media). 

To these systems (and the engineers who create them), a non-rational, emotional human response is often simply seen as a bug. Yet this is the very thing that makes us human, a product of thousands of years of evolution, and distinguishes us from the fictional, Spock-like, emotional vacuum of neoclassical economic thinking – as well as robots. 

It is only by using, and applying, behavioral science, then we can optimize customer experience in this way, and make processes that work for the humans using these systems – rather than the robots providing them. 

About the Author:

Richard Chataway is a Vice President of BVA Nudge Consulting UK, the founder of Communication Science Group, and a board member of the Association for Business Psychology. This article is extracted from his book, ‘The Behaviour Business’, published by Harriman House.