The weather in Dublin was unseasonably splendid last weekend. Taking the DART to Bray, which becomes ever more scenic as the carriages trundle past Dalkey, I dipped back into Daniel Kahneman’s Thinking Fast, and Slow.
I read about a series of fascinating experiments by Kahneman that aimed to pit logic against emotion.
The experiments had to do with how people (erroneously) thought about the probability of things, and set theory. It’s best to read the chapter, but in short: the experiment showed that it is far less probable, in Berkley College in the 1970s, that a women would be a librarian and a militant feminist than solely a librarian.
But, contrary to both logic and probability, the experiment showed that people tended to believe more in the least probable option.
In other words, richer descriptions feel more true.
On one level, this highlighted the power of stereotypes. The profile written for Kahneman’s experiment described a particular kind of woman without any reference to profession – it was only the options that suggested these – yet, despite no evidence being provided for it, most people tended to choose the more detailed option because it seemed to confirm their stereotypes.
Interestingly, the experiments also revealed that when stereotypes are deployed this way, we become especially confused between probability and plausibility.
Probability is numeric – it can be calculated. For example, for a project, I once asked one of my data science colleagues the probability of being on a bus with a person who had experienced domestic or sexual abuse – the answer was shocking.
But plausibility is different – this is how most people think about probability, which means we call on other sources of information and cognitive biases to reach a more believable conclusion.
The learning is this: believability is additive. Our cognitive biases impel us to believe more in conjunctions that reinforce pre-conceived associations – in this case, we see being a librarian and a feminist as more likely because the richer description makes it easier for us to picture that person. Due to ‘availability bias’, the fact that we apply more truth value to richer information that’s easier to recall, or feels familiar, is self-reinforcing.
The use and misuse of consumer personas
The chapter made me think about the ‘consumer personas’ we so often write in this industry.
A marketer’s goal in writing them is to give as rich and vibrant a description of a ‘typical’ or ‘ideal’ person shopping for a brand’s product. Personas are indented as stimulus to give direction in marketing and advertising campaigns. They attempt to crystallise our mountains of information, data and intuitions into a digestible form that can be used.
But how accurate or useful are they, really? How data-driven are they? How statistically representative are they, and does it matter? Marketing positivist, Bryon Sharp, insists segmentation and personas are bullshit.
But aren’t consumer personas just the same thing as our librarian feminist?
Don’t consumer personas developed by marketers themselves confuse plausibility for likelihood?
Personas may indeed be useful and powerful and convincing exactly because they exploit our cognitive biases, but they can cause problems if too narrow.
From experience, every marketer is taught that the more detail you can bring to a persona, the more ‘alive’ they are and, therefore, the more helpful they are in developing creative and media strategies.
This shouldn’t be a problem. We all enjoy a good story, we identify with fictional characters as if they were real. It’s a basic, human trait – we’re a species programmed for storytelling. Yet apart from the logical and epistemological conundrum the experiments expose, it can also be a problem for business.
So much of business is about numbers – trends, data, profit/loss – placing a bet on a consumer profile that feels convincing but isn’t backed up by research and data can be a serious problem.
At the same time, data-driven segments can be incredibly uninspiring if not themselves injected with a good dose of creativity.
Provided we are aware of our biases and tread carefully when conjuring ‘consumers’ out of the mist of evidence, albeit intuitively tempered by experience, hopefully we can strike the right balance.
Because: if the personas we create neither link with business reality nor inspire ourselves and business to bring campaigns to life, the world of marketing would be a very boring place.