Why do people find it so hard to change their behavior, despite evidence that they have been operating under assumptions that turned out to be false? Maybe I have simply been lucky enough to spend much of my life in a world where data flows in a nearly unlimited stream, to be recorded and calculated by computers. Answers to questions, and more numbers and information than we will ever have time to analyze are never more than a few clicks away at this point. Yet still, once an idea has become entrenched, it is surprisingly hard to pry it loose.
An example which immediately shows my bias is the difficulty in getting companies to recognize the value, or even the necessity of devoting a portion of their marketing dollars to paid search, or even general digital advertising. Plenty of studies have been done demonstrating the beneficial effects of having both online and offline media, or how search captures the interest generated by television, etc.. Nielsen itself, the king of measuring TV advertising reach and effectiveness, has produced these studies, even specifically calling for TV dollars to be re-allocated to online media for a more efficient marketing mix. Yet still, in the face of overwhelming statistical evidence, marketing professionals who are used to traditional media don’t acknowledge what’s right in front of them.
The best parallel that I can draw comes from baseball, which in many ways reminds me of search marketing. In both cases, compared to either other sports or other media channels, baseball/search is much more easily measured and quantifiable. Between engine data and onsite tracking, the consumer journey through search can be quantified as a series of discrete actions, just like a game of baseball. Looking at football or TV commercials, there are just too many variables to accurately attribute the effect of any one moving part. With baseball however, like search, every play is recorded, and has been for a hundred years.
Where am I going with this? Bunting. I have made this speech a million times, but I will make it again for the one person who reads this who hasn’t heard it before. If you watch enough baseball, especially in the NL, chances are you have seen a fair few sacrifice bunts in your time. It has been a respected tool in the managers toolbox for a long time, and is celebrated by baseball purists everywhere. The problem is that it is a bad decision, and it turns out that it always has been.
With so much available data, it turns out that you can really learn a lot about a subject. By using linear weights based on every single play over a given period of time, you can create a very accurate run expectancy matrix (it turns out that you want a sample size of at least 3 years to get a model that follows the real results closely). What this matrix does is tell you what the expected number of runs a team will score on average in any given game state (i.e. ‘a man on second base with two outs’).
Brass tacks: With a man on second and no one out (the most common, and conventionally ‘best,’ time for a sacrifice bunt) the run expectancy is around 1.166, which means that a team in that situation will on average score 1.166 runs in the inning. With a runner on third and one out, which would be the result of a successful sacrifice bunt, the run expectancy is 0.976. So if the sac bunt is executed perfectly and all goes according to the manager’s plan, he has created a situation in which his team’s run expectancy has dropped by 16.3%. Keep in mind, that’s about the most defensible situation in which to bunt. When starting with one out, or a man on first, the decline becomes much sharper.
Now, I am not saying that no one should ever under any circumstances order a bunt. There are a variety of factors that come into play and they all need to be considered. My point is simply that most of the time when you see a sacrifice bunt it is the product of a mindset that simply refuses to acknowledge the value of the data. When no one had done the math it was an interesting argument, and now it just seems quaint and a little backwards, like chewing tobacco or fights where no one gets punched.
This is what I think of when companies believe that they are doing fine because they run some TV commercials and newspaper inserts. A study found that about 90% of the CPG (consumer packaged goods) target audience watches TV, and about 81% go online. Yet about 80% of CPG companies’ marketing dollars go to TV ads, compared to about 3% spent on OLA (online advertising).
Why do people and industries insist on being behind the curve? Not wanting to fall for a fad is one thing, but this here internet isn’t exactly new, or a flash in the pan. In 1915, you could make a case for building horse carriages, in case those darn automobiles didn’t catch on. In 1940, not so much. What about the guys who swore that the talking pictures would never replace radio dramas? Or dinosaurs that figured mammals were never going to be a big deal?
Not knowing something because the information wasn’t available to you is one thing, but willfully ignoring the data that is right in front of you is another. Consumers are doing everything online, so be there when they are.
And quit bunting so much.
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