Why 85% of Marketing Statistics are Just Bad Advice

Why 85% of Marketing Statistics are Just Bad Advice

Marketers constantly crunch data to try to determine what works (or doesn’t) and how we can improve or optimise our efforts. Unfortunately, most marketers aren’t data analysts or statisticians. If you want to use maths to answer meaningful questions, you have to know which are the right numbers, how to find them, how to interpret them and which insights to draw.

“They’re pretty high mountains,” said Azhural, his voice now edged with doubt.
“Slope go up, slope go down'” said M’Bu gnomically.
“That’s true,” said Azhural. “Like, on average, it’s flat all the way.”

Terry Pratchett: Moving Pictures, p141

That remains one of my favourite Discworld gags because I come across variants of this quite regularly in the marketing world. It reflects how statistical information is constantly oversimplified, misinterpreted (or sometimes manipulated) to support an ideal view or draw meaningless conclusions. This is why I get so frustrated with simplistic claims, such as: “Headlines with odd numbers generate 20% more clicks than headlines with even numbers” (Hubspot: The Anatomy of a Highly Shareable List Post).

That’s not an insight. Saying that most leaves are green doesn’t help anyone understand how chlorophyl works. The article and infographic tell me nothing about why odd-numbered lists may (or, indeed, may not) drive more traffic, which would be far more useful to know. It sticks purely to the numbers as if that’s all the information we need. Follow the formula and the numbers will save you. Except, they won’t. Statistics always need context and interpretation.

Some Very Odd Numbers

I’m pretty certain modern society hasn’t developed an irrational and unexplained bias against half of all numbers “just because…”. There has to be more to it. When I posted my disbelief on Twitter it prompted an interesting discussion that concluded it isn’t about odds or evens at all. We decided a more likely explanation would be that some numbers seem accurate and authentic while others seem rounded up. 100 Tips to… seems artificial and neat, while 87 Tips to… suggests a more exhaustive, detailed and selective list that has clearly determined there isn’t an 88th tip worth mentioning.

This isn’t a new insight. It’s why Mount Everest was long considered to be 29,002 feet high. In 1856, Andrew Waugh—then British Surveyor General of India—first calculated the height of Everest as exactly 29,000 feet. Convinced that no one would believe his calculations were accurate, Waugh added two feet to the final figure in his report to avoid the impression of having rounded up and thereby protect his reputation. Hence, Waugh became the rather unfair answer to the question; “Who was the first person to put two feet on top of Mount Everest?”.

Yet Waugh still used an even number to suggest accuracy. While adding three feet may have been too much inaccuracy for Waugh to bear, history fails to record why he didn’t choose to write 29,001 feet instead. Does a headline promising 88 tips… really seem any less exhaustive and specific than one offering 87? I don’t think so—and I doubt any data can definitively show so. And, of course, any odd number that ends in a five can similarly give the appearance of inaccurate rounding, such as 25.

This is why the claim about odd numbers just has to be bogus, probably due to someone asking the wrong questions of the available data, and failing to correctly interpret or even validate the results. The original research, and every article that has since repeated the statistic, failed to look beyond the numbers to investigate what may really be going on. Instead, the article and infographic takes the statistic at face value: Odd numbers are better than even numbers—now on to the next simplified, untested claim.

“High quality images get 121% more shares”. Unless you let us in on how ‘high quality’ is defined—and that’s a whole topic of its own—such a statistic is meaningless. You can’t have detailed statistical accuracy at one end of a claim and vaguely defined terms at the other (‘engagement’, I’m also looking at you!)

“Floating share buttons increase social traffic by 27%”. Okay, but even Twitter has admitted—and Chartbeat has proven—that there is absolutely no correlation between social shares/social traffic and whether people actually read your content, which must surely be your goal as a content marketer. Cherry-picking one stat as circumstantial evidence to imply success, while ignoring more relevant and representative data, is real head-in-the-sand stuff.

I could go on, but I won’t. There’s another important issue that becomes obvious once we dig a little deeper into some of these pearls of statistical wisdom.

Is Your Source a Goose, or Can I Have a Gander?

Where do these stats originate? Let’s take my first example about odd-numbered list headlines and trace it back.

While Hubspot highlighted this stat in its social media updates and blog post, the writer was drawing from an infographic from Siege Media—an SEO and content marketing agency. The infographic lists some sources at the bottom and it seems this particular stat is taken from an article posted by my mates at the Content Marketing Institute way back in 2011.

Already we can say that this information is five years old, at least. That doesn’t mean the stat is wrong—some trends and behaviours hold true no matter how old—but content styles have changed a lot in the last five years, driven by Google updates, changing social media behaviours and more. The numbers may still hold true, but they may not. Either way, I’d want to see some more recent data before I repeated the same stat in my articles.

Even the 2011 article isn’t the original source. Written by the Senior Marketing Manager at Outbrain, the post discusses Outbrain’s recent research. “To learn more about what makes readers actually click through, Outbrain […] looked through data on 150,000 article headlines or titles that were recommended across our platform.”

Okay, so we know a little more about the sample size, but still not enough to help us interpret and assess the meagre and sweeping conclusions we’re given. Where are the numbers? What was the methodology? Above all, where is the link to this study? I spent an hour searching Google for the original source. While I found a number of posts by Outbrain employees on various major websites that referenced the same statistics, and even more blog posts that then referenced those, I was unable to find any original research or any more detailed background to these claims.

This raises a couple of other issues. If Outbrain used unreleased internal research as a PR exercise to get some vague headline-worthy findings into articles on big sites such as Mashable, why does hardly anyone question their conclusions or ask for more evidence? I found only one commenter who asked for a link to the source material (no answer was given). Alternatively, maybe the Outbrain research was once available but has since been taken down. After all, it was five years ago; web pages come and go. Over the years, the various guest posts may have identified and removed the broken link. If so, I’ve no problem with that. If anything, the removal of the link (if there ever was one) is just another indicator to a pedant like me that the information is outdated or no longer relevant.

Either way, both the date and the lack of an original source mean an infographic from December 2015 shouldn’t be repeating a questionable stat from 2011. Without an original source, stripped of context and devoid of meaningful insight, it is no more than anecdotal hokum. Yet marketing blogs and white papers are full of such unworthy claims, given a veneer of authenticity because of our industry’s obsession with data.

Let’s Play Numberwang!

Honestly, I’m not picking on Hubspot, Siege Media and Outbrain. The above is just one example of a problem that plagues the entire industry.

Marketing’s obsession with finding a silver bullet formula for success means we are bombarded with advice that is often contradictory, drawing on insufficient data or distorted by generic assumptions. Should our blog post headlines contain eight or fourteen words? Should blog posts be 250 or 2500 words? Is it better to send your email newsletter on a Monday or a Tuesday?

Yes, most of the above examples advise caution; there is no definitive answer, there are many other variables in play, don’t take these stats as gospel. In short: “We’re not entirely sure about these findings either.” Unfortunately, that doesn’t stop the same stats from being circulated without those caveats and warnings; reduced to basic graphs in infographics, summarised into bite-sized advice in listicles, and truncated into ever fewer characters for social media.

We’re surrounded by unsourced, outdated or plain meaningless findings and statistics that are constantly recycled and amplified around the echo chamber until they become conventional wisdom. Ironically, by the time this happens, such wisdom may have very little to do with reality.

Comments

  1. “We’re surrounded by unsourced, outdated or plain meaningless findings and statistics…” sounds just like news&current affairs – and I thought I’d left such things behind when I moved into marketing. Thanks for the post – wish everyone realised how important it is to source, and rigorously interrogate, all information.

  2. Thanks for siting our article when talking about blog size 🙂 Even if you’re saying it’s over-generalizing. Perhaps the overgeneralization / strong assertions come from the fact they DO get eyeballs, which is something that’s hard to ignore when you’re a marketer. Thank you again.

    • Jonathan Crossfield says:

      Ha, glad you realised I wasn’t taking a pop at you but instead was trying to illustrate why marketers need to always question the numbers and, even better, look at their own numbers instead of taking some of these stats at face value.

      • You may indeed be taking a pop, but we can take it! 🙂 There is absolutely a ton of value of questioning things and making experiments. Super important to be discerning.

  3. Ah, marketers! Selling the sizzle when the sausage is out of date…
    Even scarier is when they actually have the data and don’t give it context and interpretation. See example 2 in this piece I wrote recently: http://nobullmarketing.com.au/marketing-data-trend-vs-blip/
    (BTW I love your cartoons.)

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