McDonald's fries and data.
McDonald? Data?
Before you call me insane, hear me out. Before you ask, no, I do not endorse McDonald’s and in fact, I haven’t been one in probably 10 years.
So I have a dirty secret: I do most of my work days with the TV on, in the background. usually Netflix, some crime shows with 1294747 seasons. I ran out of shows to watch recently so I to Hulu for the week.
Hulu free trial has advertisements that may or may not be blocked by my Adblocker. But one single ads always manages to go through: McDonald’s.
Worse. McDonald’s ads has data in it. One data point to be exact. And it’s hella efficient, so I figured I’d walk you through how brilliant the data use is.
If you are curious, you can see the ads here.
The single data point story
The story starts with one single value - also the name of the campaign:
1 in 8 people have worked at a McDonald’s
1 in 8.
Not 12.5 %.
Not 41,000,000 Americans.
Why? Because research shows that people, specifically if they have a lower data literacy, relate to 1 onto X better than a percentage. And people are even worse at processing large numbers.
“1 in 8” is such a simple number that one could start wondering: how many of my friends started at McDonald’s? how many people that I cross in the street have worked at McDonald’s?
It’s a simple, small number that puts a whole crowd in our mind.
A human story
The ads continue with some cool marketing language, giving us no additional context. It doesn’t say who those people are, what ethnicity they are, how old they are or even how long they worked there.
Because it shows them instead.
Right after the big data statement, the video follows up with shots of people interacting with McDonald’s, as employees or consumers. One after the other. There’s a plane pilot, a a group of young dressed up friends who looks like they just came from a party, a child in a car. The cast is diverse in who they are, gender, body shape, ethnicities, professions… and in what they’re doing at the moment they came into McDonald’s.
Those faces feel familiar. They could be you or me. They are the perfect context to illustrate McDonald’s point: we are everywhere and everyone.
We talk a lot about context in data visualization and it is often confused with adding - writing - annotations and long description about all the nuances and details of the data.
This ads is great example of using visual evidence, instead of textual information *that no one would read because the font size is too small anyway*. Next time you make a data story, replace how will I write this. Start thinking, how will I show this?
This is the secret recipe to make a good story. Don’t believe me, believe Johnny Harris recipes who made some of the most viral journalist videos (explained by David Mora with data sonification!).
Is this number B.S?
Maybe. Maybe not. Reddit has opinion though.
Does it even matter to most people seeing this ad? Probably not. The truth is, most people won’t double check the data. And McDonald’s knows it: Believe it or not they say.
Yet another reminder that it comes to us, people designing with data, to ensure the number we show are correct.
Join Alli Torban, Valentina D’Efilippo and I next month for a creative dataviz workshop!
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Music of the day
Data of the month
Patients of male surgeons were 25% more likely to die within 90 days and 24% more likely to die within a year than patients treated by female surgeons.
from Caroline Criado Perez’s latest newsletter
Photo the month
Taken in the Upper Peninsula of Michigan. Dear client, you will never have to complain about me not meeting my deadlines.
The way I been seeing those McD ads like MAD lately! And I was so... turned off? by them. Like they tried to PR spin as if they are some social good company and just... ugh.
But I'm seeing that a bit with big companies: these 'data' ads trying to humanize their workers (even though they treat them as anything but). They talk about the % that goes to school and gets tuition covered or how they are "moms like you" or whatever.
"Patients of male surgeons".... what a terrifying fact lol
This is a super insightful piece, Gabby! Specially the research around how people perceive data and charts. It’s an area I have been obsessing about a lot lately.
Also, the Johnny Harris explainer reminded me of what my editor used to say when I was a journalist - “Show, not tell.” . Very similar principles in practice.