Do We Really Need A System 3?

Rory Sutherland, founder of Ogilvy Change, is as much behavioural raconteur as behavioural scientist – but he’s a brilliant writer who’s done more than anyone else in the UK to popularise behavioural economics and decision science among marketers. So we tend to pay attention to his ideas – even (especially!) the cheeky ones.

The Mad Thinker – a System 3 pioneer?

In his latest “Wiki Man” column, Rory gives a quick overview of System 1 (fast) and System 2 (slow) thinking, then suggests that maybe we need to consider a third system of thinking. System 3, says Rory, is what happens when human beings augment their brains with computer-assisted decision making. He gives so-called freestyle chess as an example, where chess masters use chess computers to play at a far higher level.

Going For Goal

We’ve talked a lot at BrainJuicer about the elephant and the rider as a metaphor for human decision making. Imagine an elephant and its rider: we like to believe the rider is in charge, but really the rider has much less agency than we think. So what does control the elephant?

The elephant is led by a bunch of things: its training, its mood, what it can see any other elephants doing, and what the environment is leading it to do. And it carries the rider along with it. The human mind is very similar. Conscious, considered decisions are led by feeling, by copying, by environmental framing, and by habit – not the other way around.

That’s why, when we talk about behaviour change, we talk a lot about moving the elephant, and building paths for it. You don’t change behaviour by appealing to the rider – you change it by making things easier for the elephant.

A World Without Nudges

The increasing interest by Governments worldwide in “nudging” to promote behavioural change has not gone un-noticed by people opposed to any kind of Government intervention. Nudges, say those of an anti-Governmental or libertarian persuasion, are nannyish, dangerous and illiberal. This is conveniently forgetting, of course, that it’s not just Governments who use psychological biases and heuristics to influence behaviour – retailers, brands and advertisers have been doing it for years.

So nudging is here to stay. But what if it wasn’t? Or – more specifically – what if regulators decided that informed consumer choice required people to be informed of particular psychological techniques companies might be using? Like priming, for example – the controversial effect where apparently unrelated, subconscious cues can trigger behaviour.

Smoggy Thinking

You may have seen a picture doing the rounds of a sunrise on a television screen in a smoggy Beijing. The story behind the picture – and why it spread – tells us quite a lot about how people choose what they believe.

It’s a dramatic picture, and was reported by UK newspaper the Daily Mail with a strong story hook. Beijing’s air pollution has got so bad, said the Mail, that the Government has put up a giant screen to show the sunrise, and residents are flocking to see it.

Except, as this Quartz story points out, that’s not remotely what’s happening. The TV screen is an advertising billboard, which happens to show the sunrise image as part of a larger reel. The Chinese Government had nothing to do with it. And residents aren’t “flocking”, they’re just passing it by.

Research Is Doomed! (Part 759)

Every few months one of the business sites publishes a piece having a go at market research. Usually these articles are a heady mix of dramatic predictions, weirdly dated assumptions about what researchers do, and – let’s be honest – a few sharp truths.

This one, in Forbes, is no exception. The gist is that “Big Research” is going to get kerb-stomped by “Big Data”, so the piece combines its downer on research with a bouncy optimism about the infinite powers of big data. I’m not going to go through it point-by-point, and anyhow plenty of other commentators have outlined where big data and research fit with each other. But this line stood out.

“What possible similarity is there between a person in 1972 and today in terms of how they respond to an ad?”

1972 – too remote to matter?

What indeed? Let’s start with biology, psychology, emotions, how they make decisions, the fundamental needs they might be trying to fulfil… but no – in a world transformed by technology none of those things matter.

NGMR Disruptive Innovator 2013

We at BrainJuicer are thrilled to bits that Chief Juicer John Kearon won the prestigious NGMR Disruptive Innovation award, announced today at The Market Research Event 2013.

This is the third time we’ve been recognised for innovation in the last few years – we also topped the GRIT survey of innovative research firms in 2010 and 2011 – and it means an awful lot. Especially since, quite frankly, the competition to be innovative in market research is fearsomely tough right now, and getting tougher all the time. This is not your parents’ research industry – it’s not even your older sibling’s.

Off The Menu

At the ESOMAR conference a couple of weeks ago I saw a really great case study about buying food. It wasn’t by us – but it was interesting because it shows how behavioural ideas are right at the heart of research, even if it’s not framed that way.

The brand in question makes sauces, stock, spice mixes, rubs and so on. A lot of these aren’t the kind of items you stock up on – you might get them as part of your menu planning. So menu planning becomes a very important thing for the brand to understand.

I won’t summarise the details of the research – it was excellent and robust, but the methodology doesn’t matter as much as the outcome. What they found out is that a large number of people don’t plan their meals until they’re actually buying fresh produce – meat or vegetables. They don’t make a plan then go looking to fulfil it. They make an on the spot decision on a main ingredient then buy other things around that.

Once you say that, it sounds obvious. So what did the brand do about it? They moved their products next to the meat and produce aisles. Sales boomed.

Doctor Who And The Anchoring Effect

Certain sections of the Internet – including me, I admit – are very excited today at reports that some of the legendary “missing episodes” of Doctor Who have been found. (Very short version for non-Whovians: the BBC once had a policy of destroying old shows. Most 60s Doctor Who episodes were destroyed but copies of many have since been recovered.)

This gives us an excellent opportunity to demonstrate a classic behavioural principle: how things are framed affects your perception of them.

The exact number of recovered episodes is under embargo until midnight tonight. Let’s assume it’s 9, just because that’s a number that’s flying around Twitter. Now consider this.

Recovered episodes are very rare. In the last 25 years, just 8 missing episodes have been found. The BBC today announced the recovery of 9 episodes.

What’s the appropriate reaction to that? Gobsmacked delight, I’d say. But now look at this.

106 episodes of Doctor Who are missing. Rumours suggested that a find of up to 90 episodes has been made. The BBC today announced the recovery of 9 episodes.

That’s still good, right? 9 episodes? Great! But it’s not exactly 90, is it?

Now, both of these statements are true. Episode finds ARE rare. But the rumours WERE of a really colossal find. So depending on which frame you applied, your reaction to the biggest single haul of episodes in decades might be ecstasy or mild disappointment. If you’d anchored your expectations with 8 finds in 25 years, you’ll be happier than if your anchor was the 90 supposedly found.

The specific lesson is to try and not pay TOO much attention to rumours – even if they come true a bit, you might be disappointed. And the general lesson is that by anchoring people with a particular number, you can easily manipulate their perception of the real number – if people think they might have to pay $1000 for something, then $500 sounds like a good deal. You might almost say the anchoring effect makes numbers seem bigger on the inside.

 

Return To A World Without Questions

Tom Ewing’s World Without Questions paper recently won its second ESOMAR award. 18 months on, he looks at the arguments in the paper and what’s changed since writing it.

At the ESOMAR Congress in Istanbul last week I was delighted and honoured to get another award for the paper I co-wrote with Bob Pankauskas of Allstate Insurance, Research In A World Without Questions. The paper won the Excellence Award for the best paper at any ESOMAR event this year – a flattering claim!

(If you want a copy yourself, let me know – I’ll get it to you ASAP.)

But the paper was published a year ago, and written almost 18 months ago. So I thought I should take a fresh look at it, and see if there’s anything I should add or update.

Too many questions!!

Here are five extra thoughts about the World Without Questions.

Context Is King. The paper’s central theme was that market research can and must move away from a reliance on direct questioning, and think more about the context of decisions and behaviour. This focus on context seems more important than ever. Not only that you need to know deeper context to fully understand behaviour – and you can’t always get at it by asking questions – but also that the immediate context of behaviour can often only be accessed by observation. For instance, the actions of other people, or the way choices are framed, can be critical influences at the moment of decision.

System One Has Won. Since I wrote the paper, Daniel Kahneman’s Thinking Fast And Slow has become a surprise global bestseller, and Kahneman’s ideas about decision-making have become common boardroom currency. Obviously we had nothing to do with Kahneman’s rise! But our instincts about his importance were right. 18 months ago we used to get standard research briefs and talk about System 1 and 2 in our proposals. Now more and more briefs are specifically asking about implicit and unconscious decision-making, and there’s less expectation that direct questioning is the way to go.

Brains Are In Fashion. If I was writing the paper now, I’d give more space to location analytics and especially to neuroscience, which got slightly short shrift. Scalable neuroscience – from biometrics to facial coding – has emerged as a big part of the “System 1” toolkit, though it shouldn’t be the only part: it’s not great at taking social or environmental influences into account, for starters. But its promise of direct access to the subconscious mind is finally starting to be fulfilled after a decade-plus of hype.

The Battle For Big Data: I also didn’t spend a lot of time on “big data” – not because it isn’t important but because I felt that most researchers wouldn’t have the skills to deal with it and that the research industry didn’t carry a lot of weight in the conversation anyhow. For all the noise about big data, I haven’t seen a lot since then to suggest I was wrong. A lot of the big shifts seem to be in infrastructure – moving from discrete packets of data (generated by projects) to continuous flows, which inevitably reshapes how analysis and “insights” work. Researchers need to adapt to this – the subject of many other fine papers given at recent conferences – but have little control over it, and it seemed important in the paper to examine the practical changes we could make.

Never Mind The Insights: One thing that struck me reading the paper again is how much it assumes the role of the researcher is essentially advisory, not proactive. I made the case for “research without questions” based on coming up with better insights and recommendations. While these are important, what we’ve found in the 18 months since is a real hunger for actually implementing, experimenting and iterating in research. Don’t just recommend a behavioural intervention – set up a control and a test sample and experiment with it. Think an ad might be better in a different edit or with different music? Make and test it yourself. If there’s one thing which has changed in my everyday working life since writing the paper, it’s this greater emphasis on moving beyond recommendation into testing. Our appetite for questions may be diminishing – the desire for evidence isn’t.

E.ON’s Boomerang Effect

Further evidence that behaviour change is moving into the mainstream – energy provider E.ON has announced the release of an “energy saving toolkit” which is explicitly upfront about having “behaviour change” as its aims. What does it do? Basically, it shows you data – on your own usage over time, but also your usage against a group of 100 other random, anonymised households. So you’ll be able to see where your energy use ranks and – presumably – you’ll be motivated to take steps to control it.

“In your face, social norms!”

Will it work? E.ON’s intervention is taken straight from a classic behavioural study – Wesley Schultz and his colleagues’ examination of social norms and energy usage, from 2007. And this offers encouraging news for E.ON – people told they were using more energy than their neighbours really did drop their usage. Like most UK energy suppliers, E.ON has faced accusations of greed as bills rise – and Schultz’ results suggest that their initiative really will help some people save energy.