We first wrote the piece below back in 2012 and it is interesting to see how everything predicted at that time has, in fact, come to pass. Ultimately resulting in the election victory for Donald Trump and the near-election victory for Jeremy Crobyn. The key point is about how you can use the fusion of data on rational and emotional measures of human opinions to predict what they do next. In reality the underlying basis of such modelling and analyses relies only on understanding the primeval instincts behind the “Fight or Flight” decision process so well-documented by anthropologists. But if you understand that process, and then align your data in the right way, you can make powerful insights into what people will like and not like, and do and not do. It even ‘predicts’ the findings observed in “behavioural economics”, which is itself the study of actual as opposed to ideal situations.
We begin in the 1960’s. It was the computer in the 1960s that changed the way that companies took marketing decisions. They were able to process masses of quantitative data, which promised greater scientific number-based decision making. Gradually this was enhanced by more and more data on buying habits – Nielsen Retail Audit data, Consumer Panel data from Audits of Great Britain (which went on to be what we known today as WorldPanel), then transaction data direct from retailer scanning systems and loyalty cards and the creation of mathematical models based on recorded behaviour, income, geography and anything else that could be tangibly measured. Then came the era of “Big Data”, fuelled largely by social media.
But much of this reliance on hard data analytics and hard data modelling to analyse and plan the marketing effort was focussed on the mechanics of the sale rather than on data to understand the psychology of why consumers buy. For most companies, the results that came from all the analytical work on the hard data were disappointing – marketing programmes didn’t quite deliver the expectations that the modelling said they should deliver.
By the 1980s, scientists were beginning to explore the brain and the way it handles information and makes decisions. Called neuroscience, this, combined with the resurrection of Behavioural Economic theory, not new but becoming fashionable once again, combined to create what is commonly known as ‘behavioural research’ and promoted as the only way to understand and predict consumer buying behaviour.
Of course, none of this is new – what goes around, comes around. Between the 1930s and the 1960s, it was known as ‘motivational research’. A term that we at RedRoute International prefer to use.
Classic economic theory works on the principle that we take rational buying decisions by weighing up cost against benefit and making a logical choice based on this. Of course, this is not what we do at all. We all, at one time or another, buy things we don’t need, at arbitrary prices and for silly reasons.
As America moved into the era of plenty, where supply outstripped demand creating competitive battles between brands for a share of the consumer’s wallet, advertising agencies in particular needed better insights into consumer preferences than they were able to get from quantitative data that polling techniques had been supplying since the late 19th century.
Then, in 1938, along came Dr Ernest Dichter. His development of motivational research and the insights he extracted from this changed advertising, brands and the fortunes of companies such as Proctor & Gamble, Chrysler and General Mills.
Dr Dichter’s principles were based on the theories of Sigmund Freud, formulated over a century ago. Of course, this meant that many of his insights had strong sexual connotations – not in itself necessarily wrong, but sometimes a bit odd. He explained that smoking was like sucking on a nipple; a phallic shaped lipstick sells more because it offers a subconscious fellatio; baking is an expression of femininity, pulling a cake from an oven being the equivalent of giving birth; and, perhaps oddest of all, to increase sales of typewriters they should be modelled on the female body so that the keyboard was more concave and receptive. Some people like to fantasise.
From 1946 and through the 1950s, Dichter’s business boomed as companies queued up for his insights and advice, but inevitably, like all charismatic salesmen with implacable self-belief, he went too far. He was hired by Pepsi to advise on their new television campaign. He told them that they must never show Pepsi served with ice, because ice meant death. Dismissed as bonkers, he was thrown out.
He sank into obscurity, a discarded guru, long before his death in 1991, his motivational research tools and techniques pushed out by the new science of analytics driven by ever cheaper computers and data storage. But the core problem facing brand owners is that all the data and all the analytics didn’t give them the insight as to why consumers preferred one brand over another. Human behaviour continued to remain mysterious.
Enter the new discipline of neuroscience, which, (surprise, surprise), came with scientific findings that concluded that it is emotion and not reason that drives purchasing decisions. The resurrection of ‘Behavioural Economics’ – which is not new, but the old ‘re-branded’ – takes us back to the days of Dr Dichter, but this time with men wearing white lab coats.
But before you get carried away with neuroscience or measuring the pupil dilation response to brand logos, just pause and reflect on what this little piece of history tells us.
Numbers without attitudes give you an incomplete picture; attitudes without numbers is the same. But having attitudes and numbers combined – that’s how you create actionable insights to help improve your business.
That, in turn, is the basis of RedRoute’s Marketing Effectiveness service. Using Attitudes and Circumstances to predict Behaviours using our Motivational Modelling approach that we call “Effective Net Preference” or ENP™.
The data sources you have at your disposal these days to do this are legion. What is needed is a process. RedRoute is working with the Institute of Promotional Marketing to understand the impact and ROI in Experiential Marketing using exactly this technique – and it is proving to be highly beneficial to agencies and clients alike. We also use it in our CRM service, OPIUM, where optimising insights into customer personas enables you to be your customer’s or your consumer’s best friend in the category. And, ultimately, it is used to predict future behaviour like, for example, when one of our clients asked us to predict the impact of the post-Brexit devaluation on their sales. The situation was new and unique and many people thought it was a hard task. Our models, however, produced predictions which the client later described spontaneously as “Spot on”. We’ll take that as an endorsement of our approach!
To find out more about RedRoute’s ENP model and how it is applied, just review our web pages or get in touch and we’ll be delighted to help talk things through.
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