It was recently announced that Walmart is seeking a patent for the design of a biometric shopping trolley. While it’s very exciting that such a large business should be considering physiological measurement when it comes to better understanding its customers, you can’t help but think of a whole heap of problems in getting accurate and insightful data. Perhaps most obviously, people don’t hold onto their trolleys all the time, so the biometric data gathered via the handle (in itself a fairly unreliable method) will be sporadic at best. And how about the change in skin temperature which Walmart hopes to use to alert their staff that a customer is having an issue? How happy might we be if suddenly confronted with a store assistant asking if we’re OK as a result of picking up a tasty, but not so healthy, tub of ice-cream from the freezer or a sausage roll from the hot counter? This kind of scientific innovation is great, but only when it’s coupled with the use of the scientific method to extract meaningful data that can drive improvements in the customer and employee experience.
Read more: Shopper Experience: How AI Can Optimize the Everyday Customer Experience.
The best way to truly understand any experience is objectively. The problem in the past has been that this objectivity – the independent reporting of the impact of an experience on the customer or employee going through it – has proved elusive. Asking people what they experienced is limited by their memory, by their vocabulary, by their sensory sensitivity, by the question they are asked, who asks it, where they are asked it and so many other factors that consciously and/or unconsciously may influence and bias the responses you receive. No matter how much interpretation and analysis you conduct on this data, it will still be subject to the rule that poor data in means unreliable output at the other end. And, asking people to commentate during, rather than after, their experience is just as open to anomaly, because the very act of consciously monitoring an experience introduces a variable that will inevitably influence the response.
The scales we use and the ratings we ask customers to self-report by, while handy for researchers because they are numerical and so can be easily analysed, are meaningless in the context of the actual experience to customers and employees – humans just don’t think in those terms. Our brains ‘report’ based on comfort and discomfort (and these are not actually even on the same spectrum!), whether expectation is matched or not and then take steps to monitor and correct as necessary. The more you think about it, the more ridiculous it is to base any kind of commercial activity on the numbers we get from subjective research.
However, asking questions is pretty straightforward, and (let’s face it) cheap, and generates numbers (however meaningless and/or inaccurate), and businesses and senior board members brought up on the standard market research practices since the 1950s do like a number! It seems to matter little what modern neuroscience is now telling us about how little we are consciously aware of the things that influence our actual behaviour or decision-making.
Is there an alternative? Yes! What’s needed is an objective measure of what affects and influences people. We need to monitor, subtly and discreetly, how their bodies react to the real world and the various stimuli that we as businesses devise and deliver to them. We can then use that information to design better experiences that match customer and employee expectations (thus aligning to the way that human brains navigate the world) and remove, mitigate or compensate for the uncomfortable moments in the experience – the Tripping Points® as we call them – that cause customers and staff to abandon their shopping carts or jobs, question their decisions and tell any number of their family, friends and acquaintances how rubbish that product or service was! Science offers us biometric tools to do this and they are getting more accurate, more wearable, more available than ever before, offering up a world of possibilities in experience measurement and benchmarking, in the testing of new experience design and in ongoing, long term tracking for further refinement and improvement.
A number of these tools are reviewed in an academic paper we recently co-authored and, in our recent post, we looked at Heart Rate and Electrodermal Activity as ways of measuring physiological responses to experience. In our next post we’re going to look at some other measures, including eye-tracking and EEG, to see how they stack up to the practical demands of delivering real-time feedback from real customers and employees in the real world.
At CX Lab we believe in the ‘science of experience’ (rather than the rhetoric) to better understand and improve experiences for customers and employees.
