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Home » Annual Reminder that Correlation is not Causation

Annual Reminder that Correlation is not Causation

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Just because sales were happening while you were doing digital marketing doesn’t mean those sales were caused by the digital marketing you were doing. If you’re not actively measuring incrementality — i.e. did your marketing activity drive any incremental sales that would not have occurred without the marketing? — then you’re looking at correlation at best, and you’re very likely getting ripped off too. The sales you saw were CORRELATED in time to the digital marketing you were doing, not CAUSED by it. 

 One of the funniest ways to illustrate correlation vs causation comes from Tyler Vigen’s Spurious Correlations website. Did “Nicholas Cage appearing in more films” cause more people to “drown by falling into a pool?” Of course not, but those things were correlated in time over a period of 10 years! Correlation is not causation. 

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 I was asked recently if the “performance” seen in digital marketing over the last decade was all fake if much of the analytics and attribution were faked. That’s where the concept of correlation vs causation comes in handy. There were real sales, but they were not necessarily caused by the digital marketing. The sales of soup, soda, and soap, by some of the largest CPG companies correlated to the large spending they were doing in digital; but most or all of those sales would have happened anyway. This was clear when P&G turned off $200 million in digital ad spend and saw no change in sales. The sales happened anyway, without the digital advertising. In a very few select cases, the marketers were doing good incrementality measurement. But in most cases the biggest brands were not doing any incrementality measurement; in fact, many of the largest marketers claimed they were “just doing branding” with their digital ads and didn’t make the effort to connect that with the sales that occurred in offline stores. It blew me away that they didn’t even know what incremenatility was, let alone how to calculate it. There are a number of known DTC (“direct to consumer”) success stories, however, where new brands launched entirely in digital and could track the direct causation of sales by the digital marketing they were doing. Large brand advertisers’ digital marketing campaigns were the opposite of that. 

 Digital marketing throws off a lot of data. But just because you can measure it doesn’t mean it’s right, good, or useful. Your ads shown on millions of long-tail sites (“scale”) doesn’t mean they are useful, since most of the traffic on those long tail sites are not humans. You know that showing ads to bots won’t produce any business outcomes right? Chase confirmed this when they reduced their programmatic reach from 400,000 sites showing their ads to just 5,000 sites (a 99% decrease) and saw no change in business outcomes. Further, you know that just because the fraud detection tech companies you paid for can’t detect the bots, it doesn’t mean there are no bots. It just means they couldn’t detect them. I challenge you to use FouAnalytics to take a closer look. Or are you afraid to find out? 

 Just because you paid lower CPM prices for the ads (“cost efficiency”), doesn’t mean you got a better deal, if most of your dollar went into the pockets of the ad tech middlemen instead of toward showing ads and your ads were shown on crappy long tail sites that had very few human visitors. Those sites can afford to sell ads at low CPMs because unlike real publishers they don’t have any costs of content — those long tail sites just plagiarized all the content or generated it with algorithms. I challenge you to get a list of domains your ads were shown on and run PageXrays on them to see how crappy they are. Vast majority of the sites are auto-generated using wordpress templates and stuffed to the gills with ads, not to mention other shenanigans like stacked ads, pixel stuffing, pop-unders/ups, off-page ads, auto-refreshing, self-clicking ads, etc.

 Just because…

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