Fixing the false consensus effect

In 1977, Lee Ross from Stanford University asked 320 students to take part in a thought experiment.

Have a read of the screengrab below. It’s the thought experiment from Ross’ original paper.

After the students had read the story, Ross asked them what percentage of their peers would pay the $20 fine and what percentage would contest the fine in court.

Projecting likeness

Finally, he asked the participants to state which of the two options they would choose.

Ross found that people tend to assume their reaction was typical.

  • 72% of those saying they would pay the fine estimated that others would also pay the fine.
  • 52% of people who said they would contest the fine estimated that others would also contest the fine.

He termed the projection of our own behaviours and attitudes onto others the “false consensus effect“. In Ross’ words:

“The person who feeds squirrels, votes Republican or drinks Drambuie for breakfast will see such behaviour as relatively common.”

The findings persist

Ross ran this study more than 40 years ago, but the basic findings haven’t changed since.

Matthew Dunn, a psychologist at the University of Sydney, has conducted a more recent experiment.

In 2011, he asked 974 elite athletes to estimate the prevalence of drug taking in their sport.

Dunn found recent drug users estimated 45% of their competitors also cheated, whereas clean athletes put the figure at just 12%.

Just like Ross’ students, the sportsmen projected their behaviour onto others.

Agencies are biased

It’s not just students and athletes who are affected. The bias can also be seen among agency staff.

In the summer of 2016, Jenny Riddell and I asked staff at a leading media agency to estimate the percentage of the population with an iPhone. We then cut the data according to whether the respondent owned an iPhone or not.

The result? Those who owned an iPhone thought that half the population owned one, whereas people who didn’t estimated that only a third of people owned one.

The false consensus effects strikes again!

Demographic disconnect

Why is this an issue?

The fact that agency staff are as prone to the false consensus effect is a concern as the make-up of agency folk is at odds with the population as a whole.

That’s not speculation. On a broad range of criteria agency make-up and that of the population varies.

Age is the most obvious example, with agencies skewing much younger than the population.

  • According to the IPA census in 2019 just 6.3% of the agency workforce is over 50, compared to 38% of the population. There are also significant variations in terms of educational attainment and regionality.
  • These differences aren’t limited to demographics. There’s also a big variance in terms of political viewpoints. According to Andrew Tenzer’s research, agency staff are more likely to identify as left wing than the population.
  • And in terms of Brexit, only 8% of agency staff voted to leave. That’s staggeringly different from the population – even even 32% of Lib Dem voters opted to leave.

Socially out of step

There are also marked differences in terms of media behaviour. In 2016, Thinkbox ran an Ad Nation survey which compared 300 people working in agencies and a nationally representative panel.

The data showed pronounced differences. When they looked at social media usage in the last three months, 93% of agency staff had used LinkedIn and 81% Twitter.

That dwarves the figures for the nationally representative groups, which stood at 14% for LinkedIn and 22% for twitter.

That’s just three attributes – but the same point could be made if we looked at regionality, education level or shopping patterns.

What should you do?

Three solutions

There are three tactics for avoiding the dangers of the false consensus effect.

1. Be aware of the bias

That should give us pause for thought before extrapolating our own beliefs onto others.

2. Employ as diverse a team as possible

That way, assumptions about the universality of our own beliefs are more likely to be spotted before any campaign is aired.

3. Seek out more opportunities to spend time with your customers

That could be as simple as interviewing consumers in their homes, spending a day listening in at a call centre, or working in-store for a week.

Hands-on help

Or it might be something News UK could help with. In the past, I’ve worked with them to organise sessions for planners to meet their readers.

The set up was simple. We selected readers who met certain demographic criteria.

For example, we ran a session for finance brands that were interested in an older audience all the participants were 50+.

We then invited a dozen readers into the agency for a morning. We arranged the tables in reception so that a reader was seated at each one.

The planners could then go from table to table, chatting with the readers and gleaning how people in the actual target audience felt about the brand and category. Simple, quick and costless.

So, that’s three potential solutions. If you apply a mix of them you should avoid the worst effect of this bias.