Earlier this week I came across Kehoe’s post about some analysis he did on his LinkedIn Messaging inbox (which mirrored a similar analysis that _Benjamin _ Kane had done). I decided I’d go ahead and take a look at my own LinkedIn messages over time:
This diverges from Kehoe & Kane’s work in a couple of ways.
First of all: I generated the chart in a spreadsheet. (It was just plain the simplest way to get what I wanted in ~10-15 minutes.)
Also, I didn’t leave any messages out; i.e., this includes every message I’ve either received or sent. This is significant, as I supported Messaging (and it’s predecessor “Inbox”) for several years. I suspect some of the upticks (e.g., the sharpish one in mid-2018) were likely due to some new feature launch, during which I was messaging back-and-forth with other folks on the Messaging team to test out that new feature…but I’m also lazy, so I haven’t vetted out this ramp timeline theory.
Anyhow, this was a fun way to blow an hour or so fiddling with my member data, and I may go back and check out some of the rest of it. For instance, I think tracking connection count over time could be interesting (if it’s even possible).
Worth calling out: If you’re interested in doing similar but you’re unsure about how to go about it, Kane provides some nice instructions in his post. Go grab your data and see what interesting things you can find.
Happy fiddling, folks!