The one-night stand, quantified and visualized by Uber

In the latest dispatch from the stuff-you-knew-about-human-behavior-but-still-love-to-read-about bureau, on-demand ride service Uber has calculated the prevalence of one-night stands (it calls them “Rides of Glory”) among its customer base, right down to the dates and neighborhoods in which they most frequently occur. It’s not a very scientific study, but it is data science — and yet another example of the type of insights companies can find if they’re just able to think of the question.
I say it’s not too scientific because Uber’s study is based on a hypothesis that it has all but deemed true from the get-go: “[A]nyone who took a ride between 10pm and 4am on a Friday or Saturday night, and then took a second ride from within 1/10th of a mile of the previous nights’ drop-off point 4-6 hours later (enough for a quick night’s sleep) [has engaged in a one-night stand].” But then Uber goes on to prove its hypothesis right, kind of.
The chart below is worth a thousand words:

But in case you want a little explanation, Uber gives some possible reasons for these results:

The patterns are fascinating. The highest peak is right around tax day (April 15)…. and this one might make sense. Lots of people are getting an influx of cash in the form of a tax refund and—as we’ve already shown—an influx of cash might be making people more… “frisky”. And science has shown us that a man’s wealth correlates with the number of orgasms his partner has. Thanks Science! #themoreyouknow
Amusingly, after tax day there’s a sharp drop again right around 4/20. Is there something happening that day such that people are otherwise too preoccupied? There’s another big spike on Cinco de Mayo, and then not much happens until mid-June when there’s another big peak. …
Finally, there’s a small lull right around the end of July. Either people are being too lazy in the mid-summer heat, or everyone’s gone off to Comic-Con.

One could say this type of information is useless, but, in theory, everything a company knows about its customers can help improve the service it offers. Uber has actually done quite a bit of interesting analysis over the past year, including determining riding patterns between San Franciscans based on sex and mobile operating system, and drawing a correlation between population density, crime rates and Uber ridership.
Uber is hardly the only company to give its blog readers insights into users’ private lives, though. Last April, dating site OkCupid released a series of graphs showing users’ sexual preferences and habits across a wide section of demographic variables. Some might find OkCupid’s study a bit offensive, but as with Uber’s research, there’s a clear method to its madness: If you’re trying to help create a lasting relationship, you really have to know what both parties really want.