All marketing aims to change human behaviour – and the best changes it on a grand scale – so it’s no surprise that understanding why people do what they do is constantly on our minds. We all want to know what we stimulus should we be applying, plus where and when to apply it, in order to get the result we want. After all, that kind of knowledge is powerful stuff, capable of making you a shedload of cash. Especially if your name’s Malcolm Gladwell.
When Gladwell released The Tipping Point, back at the turn of the century, it went on to sell millions worldwide, precisely because it seemed to offer marketers a magic formula for creating epidemics - “the law of the few.” According to this “law”, also known as the Influentials theory, you only need convert a few, highly influential individuals round to your way of thinking and they’ll spread your message for you. It was a highly seductive theory and one that sent marketers everywhere off on a hunt for the trendsetters in their market.
Eight years later, however, and marketing doesn’t seemed to have moved much further on. The problem, it seems, is that whilst Gladwell tells a good story, life’s just not that simple. In fact, life isn’t just complicated, it’s complex.
As Mark Earls writes in his book Herd, “A jumbo jet is complicated, mayonnaise is complex”. The former is made of millions of tiny parts that can be studied individually, taken apart and recombined. The latter is neither reducible nor re-combinable. It’s the interaction of its ingredients that makes mayonnaise what it is. In the same way, the social systems we live in are complex mixtures of millions of ingredients all reacting together. The problem is that we try to study them as if they were complicated.
As the philosopher Alan Watts said in The Wisdom of Insecurity, "If you want to study a river you don't take out a bucketful of water and stare at it on the shore. A river is not its water, and by taking the water out of the river, you lose the essential quality of river, which is its motion, its activity, its flow." Truly understanding behaviour means considering it as part of a much bigger, highly complex system.
So how do you get your head around a complex system? Well, it’s pretty bloody difficult, as you’d expect. Luckily, however, it’s also pretty bloody interesting, so there’s a whole branch of science dedicated to it. “Complexity theorists” are experts in evaluating systems where a myriad of independent variables interact with each other in a myriad of ways. As technology gets ever more advanced, what this merry band of data crunchers is discovering is that mathematics can often shed more light on patterns of human behaviour than psychology - and that makes them exactly the kind of people we should be talking to.
A good example is Professor Duncan Watts, network theory scientist at Columbia University, whose massive, data driven experiments provide a convincing challenge for Gladwell’s Influentials theory. Whilst Gladwell structured much of his thinking around Stanley Milgram’s 1976 “six degrees of separation” experiment - which concluded that the majority of information flow within a society is controlled by just a few extremely well connected individuals (“Connectors”) - the reality was that the experiment was only based on a sample size of a few dozen. When Watts re-created the experiment online, using 61,000 people, he showed that whilst well connected people do exist, the vast majority of information moves through democratic paths, from one weakly connected individual to another.
To test the Influentials theory further, Watts then built a computer simulation featuring 10,000 “people” living in a virtual society, governed by a few simple interpersonal rules. Each could communicate with people around them, with a small chance of “infecting” another following communication. Each also paid attention to what was happening around them, so if lots of people were adopting a trend than he or she would be more likely to join (or vice versa if not). The top 10% were designated Influentials and they could affect many more people than the average Joe, or Josephine. The problem for Gladwell’s theory was that even when the Influentials were programmed to have 40 times the reach of a normal person, the rank-and-file citizen was still far more likely to start contagion. Watt’s conclusion was that whilst there is always a first mover in a trend, they generally stumble into the role – and the implication is that since you can never know who’s going to set off an epidemic you should aim the ad at as broad a market as possible and not waste money chasing “important” people.
Of course, established theories – and especially highly entertaining ones - die hard and the discussions rage on between these camps. What Watt’s research points to, however, is a future in which our insights will often be drawn from mathematical analysis, rather than pure observation. Chris Anderson, author of the Long Tail, takes this thought to its extreme, suggesting that “this is a world where massive amounts of data and applied mathematics replace every other tool that might be brought to bear... With enough data, the numbers speak for themselves… We can stop looking for models. We can analyze the data without hypotheses about what it might show. We can throw the numbers into the biggest computing clusters the world has ever seen and let statistical algorithms find patterns where science cannot.”
Whilst I’m not sure how good data mining will be at generating new discoveries on its own, what does seem clear is that large scale analysis of data can open our eyes to the way life works on a system wide scale – something we desperately need to do if we’re to make sense of something as complex as why people buy stuff. The granular nature of marketing means that there will always be a need to understand things on both a qual and a quant level, but it seems more than likely that it’ll be quantitative research which makes the real leaps forward in the years to come – and that it’ll be the mathematicians and complexity scientists, rather than the sociologists and psychologists, who uncover many of tomorrow's marketing paradigms.
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