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In looking closely at the astonishingly wide variety of ways our users have chosen to represent themselves, we discovered much of the collective wisdom about profile pictures was wrong.
For interested readers, I explain our measurement process, and how we collected our data, at the end of the post.
All my bar charts are zeroed on the average picture. One of the first things we noticed when diving into our pool of photos is that men and women have very different approaches to the camera.
Now, you’re always told to look happy and make eye contact in social situations, but at least for your online dating photo, that’s just not optimal advice.
For a 31 year-old ab shower, that ratio has regressed to much closer to the average.
Because of our restricted data set for this post, we can only make confident claims for 19 to 31 year-olds right now, but it’s our strong suspicion that this downward trend continues with age.
For women, a smile isn’t strictly better: she actually gets the most messages by flirting directly into the camera, like the center and right-hand subjects above.
Instead, they increasingly choose to show themselves in non-sexual contexts, like being outdoors: For women in their late teens and early twenties, body pictures are the most popular type of shot; outdoor pictures are second. To wrap up our cleavage discussion, let’s assess the of messages the cleavage-showers are getting.The pictures do all the work: in different ways, they pique the viewer’s curiosity and say a lot about who the subject is (or wants to be).Of course, we wouldn’t recommend that you meet someone without first seeing a full photo of them, that still seems like a recipe for disaster.But since the Cleavage Shot is the feminine analogue of the Ab Shot, and an undisputed online dating archetype, we thought we should discuss it.Like the Ab Shot, the Cleavage Shot is very successful, drawing 12.9 new contacts per month, or 49% more than average.
A message like “Hey nice rack” isn’t really gonna lead anywhere, and isn’t very valuable to the recipient. We didn’t go through anyone’s inbox to do this; we mathematically modeled a “conversation,” based number of messages back and forth.