It’s dinner time. You’re on holiday and you are looking for a restaurant to eat in. You see one restaurant with lovely décor, a fantastic menu and friendly staff. But it’s completely empty. You see another restaurant that is less fancy and with a smaller selection of dishes. It’s filled with groups of people inside. A family pass you by and go to the waiter, requesting a table. They are clearly excited to eat there.
Which restaurant do you choose?
Chances are you will choose the second restaurant due to a phenomenon known as social proof (an established bias first noted in the 1935 study by Muzafer Sherif, one of the most influential founders in modern social psychology). This bias tells us that humans are more likely to follow the actions of the group. Sensing the happy faces and bustling groups of people, we are more likely to believe the second restaurant will provide us with the better experience, even if we lack the empirical measures to prove this.
How you design experiences must factor in such cognitive biases. This can be done through applying behavioural science.
The increasing importance of behavioural science in experience design
All companies should strive to create an exceptional customer experience. With consumers caring more and more about the experiential value in what they buy, strong customer experiences are no longer a nice to have, but a must-have. There are multiple strategies, methods and frameworks to help drive great customer experiences and improve business performance. KPMG’s Six Pillars of Excellence is a leading example of one framework, setting out the six key elements that drive exceptional customer experiences (Empathy, Expectations, Resolution, Time & Effort, Integrity, Personalisation, The Six Pillars of Customer Experience Excellence | KPMG).
But how can we use behavioural science in this space?
The term "customer experience" is self-explanatory. It is the experience of a human, in this case, the customer. This human is hard-wired and underpinned by emotional needs. Or, in other terms, they are more likely to be driven by System 1 thinking (intuitive, emotional, instant) rather than System 2 thinking (rational, measured, thoughtful) (Thinking, Fast and Slow; Kahneman Daniel; Penguin Books; 2012). By understanding the deeper instincts of the customer, we can design better experiences that are more likely to meet these deeper needs and desires. The result? Happier, more loyal customers and ultimately better returns of your organisation.
Behavioural science can be applied to three stages for this purpose. Mapping the current experience, designing the future experience and testing the experience for continual improvement. In this article we explore all three.
Stage one: Mapping the current experience and getting beneath the skin of the customer
The first step is to map the current “as-is” experience, in order to identify future areas of opportunity. Behavioural science can be used to gain a deeper understanding of the existing unmet needs, pain points, and moments that matter for customers.
The first rule of behavioural science is that what humans say and what humans do is often different. Behavioural science can help us mitigate this challenge by helping us get closer to the “truth” when collecting customer insight.
Firstly, behavioural science can be used when designing surveys (The role of surveys in the age of behavioural science). Care should be made to ensure questions are not leading, but instead allow for an answer that captures richer insight. Surveys should be designed to pivot away from standardised scale & ranking questions. Artificial Intelligence can be incorporated within the survey architecture to probe specific words after an initial response, encouraging longer responses with greater elaboration that gets to the heart of the customer’s perspective. Questions should be designed to get to the heart of the customers actions, as opposed to their opinions.
Secondly, allowing customers to feedback immediately after (or as close as possible) to the touchpoint in question creates a more accurate view. This is because humans have the tendency to post-rationalise moments and/or fail to recollect moments in an accurate way. It is for this reason some airports have stands that ask customers to press a button to “describe their experience today” with faces denoting good, okay and bad. These are deliberately placed just after the check-in point to allow for a live pulse check, rather than sent in a survey later that day when the moment is hazier. By using technology platforms like Medallia, surveys can be sent just after the touchpoint itself to collect insight.
Ethnography and on-the-ground observations
Thirdly, observing and speaking to customers through field work is another powerful way to gain insight into the experience itself. This is known as ethnography – an observational science around studying human behaviour. Being on the ground in the environment itself will allow organisations to witness and hear how customers interact at the different stages of the journey. KPMG recently deployed a team to do exactly this when working with a leading British airport to design a better customer experience. New tools allow for digital ethnography, a powerful way to virtually observe your customers’ journeys while they are interacting with your product or service.
Analysing the cognitive biases and heuristics at play
Once insight has been gathered, it is possible to identify the pain and gain points across the customer experience and map the end-to-end journey in the “as is” state. It is also key to map the Moments that Matter for the customer. Moments that Matter is a term used in the CX space that refers to those critical moments that could make or break the whole customer experience. They should be given priority, because this is where the customer will see the most value, should it be executed well and where most is at stake, should it be handled poorly.
Once the pain points, gain points and moments that matter have been identified across the customer experience, behavioural science can then be used to analyse these in more detail. For example, what are the cognitive biases that lie behind these?
Take a leading high-street coffee shop. A customer may cite that the length of time between making the order and waiting for the order to arrive is too long. It should be faster, in line with what they would expect from leading coffee shop. They also cite that when the coffee is eventually received, it is of an OK standard. Both are pain points that tie into what’s known as expectation theory, a bias that states our expectations of a product or service shape our perceived performance of them (The Choice Factory; Shotton, Richard; Harriman House; 2018 (p77-83)). The customer expected a fast coffee order and didn’t receive it. As such, the coffee tasted sub-par.
To address this, the coffee shop must ensure they deliver the coffee in a time-frame that is in line with what the customer expects from a leading high-street coffee shop (compare this to a niche coffee shop, where a longer waiting time might be expected).
By analysing the cognitive biases and heuristics at play, a richer understanding of the customer across the journey can be created.
Stage two: Designing the future experience and using nudge-theory to create desired behaviours
Once the as-is experience has been mapped, it is time to design the future experience and create a journey that will lead to a much more positive experience for customers.
One behavioural science application regularly applied at this stage is nudge theory, a concept that proposes positive reinforcement and indirect suggestions to influence the behaviour or decisions of an individual. It can be a powerful tool when used by organisations to prompt customers to behave in desired ways across the end-to-end journey.
One example of nudge is using slow, relaxing music within a restaurant environment to encourage diners to take longer at the table and in turn, increase the chances of them spending more (The Influence of Background Music on the Behaviour of Restaurant Patrons; Milliman, Ronald; The Journal of Consumer Research; Volume 13, No2, 1968).
When designing the future experience, organisations should consider where and how nudge theory can be used to address pain points and amplify the moments that matter. For example, if customers are frustrated at having to complete a lengthy and complex form when making their tax return, nudge theory can help reduce this challenge (and encourage customers to complete the process) by using existing data to pre-populate standardised fields and therefore make the process faster and easier.
To summarise, nudge theory is a powerful technique that can be used to design exceptional customer experiences and encourage the customer to move through the entirety of the journey (Nudge: Improving Decisions about Health, Wealth and Happiness; Thaler, Richard, Sunstein Cass; Yale University Press; 2008).
Stage three: Testing the future experience through constant iteration and improvement
Another fundamental aspect of behavioural science lies in experimentation and testing. Because human-beings have complex and evolving needs, it is critical that organisations seek to continually test the experience to ensure it delivers against (and exceeds) customer expectations over time.
Constant iteration is required (Chapter 3, Test Tube Behaviours in The Behaviour Business; Chataway, Richard; Harriman House; 2020 (p27-36)). This can be achieved through the development of prototypes which can be used to showcase immersive experiences and, in real-time, test customers reactions and identify areas of improvement. Behavioural science should be used regularly within agile product or service development cycles. KPMG recently used prototyping with a group of customers when designing a new money management app for a leading retail bank. It was used to understand what customers both enjoyed and didn’t enjoy in terms of the app features, resulting in an end-product much more desirable to the target users.
A/B testing in website design is another example of using behavioural science to continually test and optimise the customer experience. It allows organisations to effectively gather data on which of the two website versions (A or B) creates most engagement with customers.
It is critical that testing and experimentation is done on a frequent basis to keep up with the ever-evolving needs of the customer and ensure a desirable experience.