On the latest episode of our Emotion Lab podcast, we had the pleasure of speaking with Max Wiggins, Insight and Innovation Lead at VERJ, a LAB Group agency. VERJ is a behavioural science agency that is working to improve digital experiences by properly understanding audience psychology. VERJ integrates science, innovation and design to uncover novel insights, solve client problems and develop creative solutions. With a background in cognitive neuroscience and psychology, Max uses his knowledge and expertise in human behaviours to solve commercial problems in digital environments. We sat down with Max to talk about all things computational psychology, the future of behavioural science in the context of digital, and some of the other exciting projects he’s been working on.
The study of cognitive biases and heuristics has been the mainstay of psychological research over the past few decades. The mental shortcuts, judgements and behaviours we choose to exhibit in our approach to making a decision or solving a problem is of significant interest to researchers, commercial organisations, the government, and society writ large. The exponential growth of technology, and the digitisation of most industries has seen increasingly large sections of the population turning to their computers, smartphones and tablets to conduct their daily affairs, be it banking, talking to their doctor, or simply ordering their groceries. Like railroad tracks converging on the horizon, the twin factors of behavioural psychology and technological expansion – once considered parallel and unrelated – are increasingly recognised as being closely linked. Max and his team at VERJ work with a range of clients to leverage data, human factors, and behavioural science to understand how and why audiences interact with tech and digital solutions, in turn providing actionable insights and delivering results.
Max paints the example of two hypothetical ‘form-fillers’, A & B, purchasing car insurance. A completes the form quickly, paying little regard to the Ts&Cs or help icons adjacent to each question. B is more considered and takes their time, carefully studying each question. From this, A can be inferred to be time-pressured, someone for whom car insurance is a necessity and the subject of little interest. B is perhaps a more conscientious buyer, a ‘maximiser’ in psychology speak, keen to ensure they’re getting the best product. This has important implications for the insurance provider. For A, they may want to provide a faster, more seamless user experience with a less cluttered interface, whilst for B providing as much salient information as to best inform their decision might be preferred.
Max is quick to concede that, of course, A & B’s kinetic behaviours – that is to say their scrolling, typing and deleting habits – are more than the product of the UI or stimulus shown alone. A may have been hurried because he was running late to pick up his son from school, or perhaps B was just having a particularly slow day at work and had the time to labour over car insurance. He speaks to the importance of two factors in mitigating this. Firstly, the importance of setting controls and establishing a baseline, in a manner that is context-dependent and cognisant of individual variability. Max also highlights the need for quantitative data collection; an alignment between quantitative findings and qualitative data, may help to confirm that the observations are due solely (or at least, largely) to the stimulus alone.
The team at VERJ are keen to transition from this descriptive study towards more prescriptive study, which is emblematic of the paradigm shift in behavioural science and computational psychology more generally. Tagging consumers and service users as ‘time-pressured’ vs ‘conscientious’, whilst informative, is of little practical relevance for organisations. The challenge lies in using this data to generate meaningful, actionable and personalised insights, to inform and influence behaviour. With the growth of Machine Learning (ML) models, Max envisages a not-too-distant future in which AI is able to provide adapted and curated content to particular types of customers. Personalised content that serves everyone’s needs, in a manner perceptive to individual intelligence, vulnerabilities, and neurodiversities, and not just those in the middle of the bell curve, should be a key priority of human-factor and UX/UI experts.
For all its promise, Max is mindful that, in the wrong hands, personalised content may be misused. Digitisation in the banking sector has been borne out of supply rather than demand, meaning that many adults have had their hands forced into going online, in the absence of telephone or face-to-face alternatives. Financially vulnerable adults are particularly susceptible to scams or being missold products. Recognising the importance of regulatory technology (or RegTech), and installing necessary safeguards to protect financially vulnerable adults, Max and the team at VERJ have recently been awarded an Innovate UK grant to conduct a proof-of-concept study researching the kinetic behaviours of adults as they complete a fictional loan application. The study involves a network of expert psychologists and ML specialists at City University, London, and hopes to produce an algorithm to detect financial vulnerability.
If you want to get in touch with Max, you can reach out to him at: firstname.lastname@example.org.
To learn more about VERJ and the exciting projects they’re currently involved with, head to: https://verj.co.uk.