With the volume of online content growing at an exponential rate, it’s becoming more and more difficult to separate the good from the bad. As fact manipulation becomes increasingly tolerated by the mainstream, how can we trust the marketing data being published by businesses?
As it doesn’t look like the “fake news” era is going to end any time soon, you’ve got to be able to spot when a company is twisting things to make things look more attractive than they actually are.
Haven’t heard this term before? Lucky you. In the last few years, fake news has become a hot buzzword. Popularized by both Donald Trump and his critics, the term was even made one of Collins Dictionary’s words of the year in 2017. Here’s their official definition:
fake news (ˌfeɪk ˈnjuːz) noun: false, often sensational, information disseminated under the guise of news reporting
Fake news exists to manipulate or lead people to think a certain way by exaggerating or fabricating facts. Social media is often marked as the biggest culprit spreading false information because of the lack of detail in short tweets and posts. But the reaction to fake news has also caused more people to question where marketing data is coming from.
How do we know we’re being duped? Keep a critical eye out for these five common issues:
The last time you read a piece of content with numbers and statistics in it, did you click on the hyperlink to see where those numbers appeared from?
It’s boring and time-consuming, but if you’re going to be sharing or using content from an external source, you NEED to check the sources. There’s nothing worse than sharing content with your boss then realizing it links back to a Reddit comment written by @fortnite4ever69.
Make sure the information is actually credible. Spending 5 minutes to dig into who gathered the data and why could save you a world of pain in the long run.
Hot tip: Use a backlink checker to see who else has been linking to the page. If the other pages linking to that piece of content are low quality, then that should give you a good idea of how credible the data is.
Lots of brands will display their marketing data in colorful, dynamic graphs and charts as they’re more visually appealing than fractions and percentages.
But they can also be used to distort the truth.
Let’s take a look at this graph:
Did you know McDonalds and KFC were so much healthier than other fast-food restaurants?
Take a look at the X-axis. The baseline doesn’t start at zero. It starts at 590 calories, which in reality is only about 100 calories less than the “unhealthiest” restaurants. We’ve been duped.
By not showing the full range along the axis, KFC used this colorful visually-appealing graph to make you think there are half the calories in their crispy chicken twister than in Burger King’s equivalent.
To give yourself some more trust issues with graphs, check out here.
How many times have you read something along the lines of:
90%* of women found their hair had 73%* more bounce than with other shampoos.
Sounds great, right? Bouncy hair? Take my money.
But what does that claim actually mean?
The key is in the asterisk. The next time you see one of these marketing statements, try reading the fine print the brand tries to make illegible in the corner of the advert. You’ll probably find that the data was pulled from a group of around 10 women and that they actually said “slightly bouncier” or some other equally vague statement.
You have to be aware that the survey that produced the data might not actually have been that significant.
Not to be confused with cherry-popping (which is a whole other thing), cherry-picking is when you select the best things for yourself and discard the rest. It’s something you’ll see a lot in marketing. The most attractive data is pushed front and center while the ugly data is locked out of sight.
It can also mean presenting or wording our data in a way that influences our audience.
Let’s take this data on the UK national debt.
If you wanted to give the impression of a debt crisis, you could create something like this:
Yikes. Looks really bad, right? Debt has almost tripled since 2002.
But, if you wanted to make things look better, all you have to do is expand the dates we’re looking at:
Sure, there’s definitely been an increase lately, but it’s nothing like what debt used to be like in the mid 20th century. Suddenly the “debt crisis” we were just worrying about doesn’t seem all that bad after all.
It’s way too easy to distort perspective like this. If marketing data makes you feel a certain way, be aware that context or lack of context could be massively influencing your opinion.
It’s tempting for marketers to draw bold conclusions from a piece of data.
If you see a correlation in the numbers, your brain wants to make connections that explain it.
Data is incredibly valuable to both marketers and consumers, but understanding that correlations might exist because of some other unknown or unmeasured factor is key to making sure you’re not being fooled.
Data interpretation is a tricky art and conclusions drawn from it should always be taken with a pinch of salt.
Numbers don’t lie, but they can be twisted or presented in a way that’s designed to make you feel or act a certain way.
If you’re a consumer, always remember that the data is open to interpretation.
If you’re a marketer, misleading consumers with your data is not going to build long-term trust. And if your product is good enough, you won’t need to trick people.
Let the numbers speak for themselves.
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