Behavioural myth busters: Self-reported data
Attitude often doesn’t precede behaviour, people lie and they can't tell the truth even when they want to. So why on earth do we let them inform our marketing strategies, asks Will Hanmer-Lloyd
Many clients and research, media and advertising agencies often rely on building multiple static attitudinal audiences or personas around claimed attitudinal data. This is an outdated way to think about consumers, riddled with methodological flaws and practical disadvantages. We must stop using self-reported data to build attitudinal audiences.
We use many resources such as TGI, Mintel and Qual research which are built on asking consumers what they think, do and consume, and then we build audiences, strategies and plans off of this. But we should be very careful as consumers are not reliable witnesses to their own decisions, motivations and behaviour.
The first reason for this is that people simply lie. In his fantastic book Dataclysm, Christian Rudder - one of the three founders of OKCupid - found that straight men aged 25 to 50 stated that they desired women only a few years younger than themselves.
However, when it came to rating the attractiveness of photos of prospective dates, they consistently rated pictures of women aged 21 to 22 as the most attractive, regardless of their own age, and sent messages to in-between their stated and actual preferences.
People can’t tell you the truth
The bigger issue though is not that people lie, but that even when they want to tell you the truth they are very unreliable narrators of their own life.
This is because our decisions are driven by our unconscious ‘emotional’ brain; 98% of mental activity is intuitive and not consciously cognitive. There is 10:1 ratio with emotion-rational brain data exchange and our emotional response happens five times faster than our rational response. This means that most of our decision making process is hidden from us and not driven by rational thought.
The wiring of our brains are designed to help us survive in hunter gatherer groups, not capture a perfect record of what we buy or why we bought it. They can remember what helps us take the right action in the right situation; whether we should eat the purple berries, not when we last ate them.
This means that humans are very bad at predicting our past behaviour, future behaviour, what we actually think about things, and why we have done what we do.
For example in a 2005 study, academics recorded 800 respondents who said they drank a certain drink brand daily, but 42 per cent of them then didn’t consume the brand once in the next week.
Attitude often doesn’t precede behaviour
Another reason people can’t tell you why they do what they do is because we don’t understand the real drivers of our decisions. This is captured in numerous behavioural science experiments. One famous example was carried out by esteemed psychologist Dan Ariely for the Economist who sent out two mailings with very similar, but noticeably different offers.
Offer number one – consumers choose the best package
- Online subscription for $59 or online and print subscription for $125
– Online (68%)
– Online and print (32%)
Offer number two – consumers choose the best package
- Online subscription $59, print subscription $125 or online and print subscription $125
– Online (16%)
– Online and print (84%)
You would think that before receiving these offer consumers would be able to state whether they had a preference for print or online reading. But the way the offer is communicated changes this.
What’s more, after making the decision the consumer will then post-rationalise that they chose online and print because they like magazines, it is practical, or they enjoy time away from a screen, when their decision was in fact driven by how the choice was framed.
This all means that when we ask consumers to explain their behaviour they often provide false post-rationalisations that can mislead marketers.
Use new data sources
Taking this into consideration, we should shift our focus from using claimed data to build audiences and focus our efforts on finding data on actual human behaviour – examples include Google Trends, location tracking, or Touchpoints passive data - and core motivations that behavioural science shows drives our decision making – examples include personality type, emotions.
One big area that should be focused on and substantially grown is the use of rigorous ethnography, capturing actual behaviour, and seeing how it changes with differences in context and settings.
Finally, big data offers a potential panacea to this issue. Though currently some of the dishonesty that infects consumer’s conversations is also prevalent in our industry when it comes to the usage of big data.
As Ariely says, “big data is like teenage sex: everyone talks about it, nobody really knows how to do it, everyone thinks everyone else is doing it, so everyone claims they are doing it.”
Will Hanmer-Lloyd is Total Media's head of behavioural planning. He contributes monthly to Mediatel News, examining the ways behavioural science radically challenges some of the historic approaches of the ad industry.