Don't Believe Everything You Think

  |  December 22, 2011   |  Comments

Twelve ways your mind is working against you when measuring business outcomes.

The best thing about working with metrics and measuring outcomes is that wonderful feeling that we're being scientific. We're dealing with facts and figures and not conjecture and superstition.

It certainly is pretty to think so.

Unfortunately, humans are a hodge-podge of delusions, false impressions, and erroneous beliefs. "Oh no! Not me. I remain objective and open-minded and consistently make fact-based decisions."

It certainly is pretty to think so.

But the fact is that people suffer from inbred cognitive bias rooted in culture, education, age, gender, and what we had for breakfast. People are elastic; we learn and adapt and change - but we have a more casual relationship to facts than we care to admit.

There are a number of ways your mind plays tricks on you. This becomes overwhelmingly complex when dealing with a committee, a review board, or just a boss who isn't from your neighborhood, age range, and life experience. Take the ways your brain fools you and multiply that by all the people in the room and you begin to see the convolutions of decision making.

In no particular order, here are some ways your mind is working against you:

Familiarity bias. I've worked in television advertising all my life, and I can tell you without any doubt that it's the most powerful branding medium there is.

Hindsight or outcome bias. If they'd only asked me, I would have told them that the blue button would not convert as well as the red one. It was obvious all along.

Attribution bias. Of course I should have turned left at that light. But I was distracted by the sun in my eyes and the phone ringing. That guy missed the turn because he's a dim-wit.

Representativeness bias. Everybody who clicks on that link must be like everybody else who clicked on that link in the past.

Anchoring bias (when a small detail gets in the way of the big picture). We shouldn't invest in social media because nobody cares what you had for lunch.

Availability bias (the first example that comes to mind). That'll never work - let me tell you what happened to my brother-in-law...

Bandwagon bias. We should run a Foursquare campaign because everybody else is doing it.

Confirmation bias. I'm a conservative, so I only watch Fox News.
I'm a liberal, so I only watch Jon Stewart on The Daily Show.
I've been in advertising all my life, so I count on Nielsen, Hitwise, and comScore.
I started out grepping log files, so I only trust my Coremetrics/Omniture/Webtrends numbers.

Projection Bias. I would never click on a product demo without a long list of testimonials, so we can assume that's true of everybody else.

Expectancy bias. Your report must be wrong because it doesn't show the results I expected.

Normalcy bias. Back-ups? We've never had a data loss problem yet, I don't see it happening this quarter, so we won't have to budget for it.

Semmelweis reflex. I don't care what your numbers say, we've always had better conversions from search than social media, so we're not going to change our investment.

If any of the above sounds familiar, congratulations - you've been paying attention. The hard part is convincing others that there may be a cognitive problem.

You could try overwhelming them with the long list of cognitive biases, but if they balk at Wikipedia as a trusted source, they might react better to Mr. Wray.

Mr. Wray teaches advanced placement psychology and offers up this little ditty on YouTube called the Cognitive Bias VideoSong.

Thank you, Mr. Wray. All teachers can be like you if they try.

It certainly is pretty to think so.

This column was originally published June 9, 2011.

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ABOUT THE AUTHOR

Jim Sterne

Jim Sterne is an international consultant focused on measuring the value of the online marketing for creating and strengthening customer relationships. Sterne has written eight books on using the Internet for marketing, produces the eMetrics Marketing Optimization Summit and is co-founder and current chairman of the Digital Analytics Association.

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