There was much to talk about at this year’s Market Research Society’s Behavioural Science Summit… but also some pertinent questions.
We appear to be at a funny point for the application of Behavioural Science research, as many researchers are still feeling their way though what is a seismic shift in how we look at the world of insight. It’s important to realise that this is only a basic introduction. Books such as Heuristics and Biases by Thomas Gilovich give a far more comprehensive view on the topic. Though, if you want an introduction which is both informative and funny, go for Irrationality by Stuart Sutherland, who taught me this stuff 30 years ago and I got to work with him for a short while afterwards.
The first question raised was the intrinsic difficulty of trying to apply Behavioural Science to commercial problems. Something that people rarely consider is the fundamental difference between academic research and market research. Market research is often questions posed by people who are very much taking a top down view of a problem. They are looking at the issue from a helicopter view, seeing an end result that comes from a set of complex interactions between numerous causes and, moreover, they need an answer to a problem.
In contrast, academic research is much more of a bottom up dissection of a problem into its constituent parts. This is often done by creating a factorial study design (only one of which was part of the conference yesterday and sadly it was not my paper) which controls all the complexity so you are only manipulating one or two things to produce a result. However this only gives a limited answer and often prompts even more questions. So, in effect, applying academic style research to commercial problems is a real skill. You would need to include enough control to produce a reliable result while at the same time creating a piece of research that produces an answer without asking many more questions. It can be done, as Google’s messy middle paper showed, but it is a tricky balance to get right.
The second question, and more interesting point, was how many papers were keen to create new behavioural models that were based on research that used techniques that have always been used. Quite rightly, there has been a shift towards ethnographic and behavioural observation. For example, in the paper by Dr Martins and Liverpool City Council’s work on road safety, both relied on behavioural observation. Both these papers had taken advantage of looking at people’s behaviour in an environment that already existed. However they both had goals where there was a need to test new ideas. In Dr Martins case it would be necessary to build fixtures in stores to see what worked, which is expensive and a logistic challenge. In the case of Liverpool City Council they would have to change the layout of a whole street to see if their ideas worked. Imagine changing a whole street layout and finding out it had little effect?
Papers such as this are music to the ears of someone, who fell out of Behavioural Economics and into immersive technologies such as Augmented Reality (AR) and Virtual Reality (VR), because these are the kinds of questions that can be answered using AR and VR. Creating virtual versions of new product ideas, new fixtures in store and new street layouts is standard practice on the research studies we’re involved with and, importantly, it’s quicker, more cost effective and infinitely more scalable than creating physical examples.
New ‘rules’ based on old ‘tools’ still appears to be the model which is still based on current behaviour. It will only reflect current behaviour and does not necessarily predict future reactions when people are immersed in a new context. To better predict future behaviour we need new tools to simulate new contexts or new things to test. New tools, such as 3D AR products and 360º VR environments, make people feel ‘present’ with new ideas so researchers can better predict future decisions.
As a fan of Behavioural Economics, it’s a genuine concern that the industry remains reliant on research that only observes current behaviour, as it runs the risk of only being able to hypothesise rather than prove future behaviour. This is something that clients need to understand. New tools like AR and VR are successfully being used in research, are proving their value to accurately predict behaviour and this can greatly benefit Behavioural Science research.
Dr Ali Goode, Cognitive Scientist, Gorilla in the room.
Recent Comments