Everyday Data Vis — Vanity

Maxy Lotherington
5 min readOct 1, 2019

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Last month, I tried to determine how popular company-branded merch was around the office. September posed a bit of a challenge though — I was going to be on holiday in the US for half of the month, which meant that whatever I tracked had to be doable there as well as back home.

A lot of my friends (and coworkers) will know me as a bit materialistic. I love clothes and fashion, and I colour my hair a lot so I stand out a bit. So for September, I decided to track comments about my physical appearance.

Super-Serious Methodology

As with a lot of these projects, I usually just start trying to collect information and then work out the visualisation types later. I mean, I don’t know what sort of patterns are going to emerge, so might as well leave it open!

For this experiment, I just wrote down on my phone every time I got a compliment about my appearance. I recorded who said it and what the item mentioned was, as well as the date. In total, I recorded 65 separate comments — a bit over 2 per day.

There were three main categories that people fell into: they were friends or my partner, coworkers, or I didn’t know them. (No, nobody in my family said anything about my appearance for a whole month!)

Comments split up by relationship.

The trip to the US definitely affects how this turned out, fairly predictably:

  • I didn’t work for two weeks, so my coworkers didn’t see me at all during that time,
  • I was staying with my partner overseas, when I normally don’t, and
  • I was on holiday to see my friends, so I saw friends more frequently than usual.

One cool thing that happened was that I didn’t end up having to worry about comments being negative or positive — nobody said anything rude to me for the whole month!

In hindsight, it also would’ve been pretty cool to record everything I wore on a given day, just to see how that compared. I don’t have any numbers to back it up, but I’m pretty sure I can conclude that my more boring, staple clothing items never get complimented.

Americans are really friendly.

Below you can see the comments I got over time, split up by the three relationship groups.

Comments over time, split up by relationship.

It’s pretty obvious how my trip went — I didn’t interact with any coworkers until the 16th because I wasn’t in the office. Strangely, though, strangers would comment a lot in the US, but didn’t at all in Australia!

(Sometimes I get comments in Melbourne, too, but it definitely is quite rare.)

Part of this makes sense considering we were doing more activities than I would back home — visiting museums, eating out more, etc — but also I got a lot of comments from people I’d pass on the street.

Why was the 2nd of September so high? Well, I wore my ice cream earrings to the Museum of Ice Cream, and almost every employee we came across thought they were just the best thing since sliced bread.

Most of my clothing is interesting, I guess?

I split up the comments into three categories: face (makeup and hair), accessories (earrings, necklaces, and bags), and clothing (tops, bottoms, full-body outfits, and shoes). I didn’t get any comments about my actual face.

Comment breakdown by item categories.

The Face and Accessory categories are pretty clearly dominated, but clothing is fairly spread across all the types.

As I mentioned earlier, nothing ‘staple’ ever got brought up. Nobody ever told me they loved my blue jeans or black flats, which also isn’t that surprising.

So what’s hot, and what’s not?

Over the month, 25 different individual items were commented on. Over half of those items were single-comment items.

Here are my top 5 most commented:

Top 5 commented items for September.

My most popular item was my ice cream earrings, with a total of 14 individual comments. They were one of the only earrings I took to the US, and they’re pretty large, so they definitely stand out!

Next up was my hair, which is currently blue and purple. This was actually mostly commented on by strangers, probably because my coworkers and friends are just used to this colour by now.

Tied for third place were the ice cream sweater I got at the Museum of Ice Cream, these unicorn skeleton earrings, and these floral combat boots. Two of these I took to the US with me, and I picked up the sweater while I was there, so it’s pretty obvious that my travel wardrobe dominated this study a bit.

(Also, #notsponsored — but I do really love all of these things.)

Take it with a grain of salt…

Like all casual, month-long data collection projects, this one is definitely far from perfect. Here’s a few things that affect the data I got:

  • As mentioned earlier, I switched environments halfway through, removing me from my coworkers and affecting what I ended up doing.
  • Since I went overseas for a holiday, I only took a subset of my closet with me, which meant that some items were worn significantly more than others during the month. When I got home, I fell back into my normal routine of switching it up.
  • Not having a longer timeframe affects what people comment on, massively. Usually comments on my hair go up a lot when it’s freshly coloured, but it stayed the same all month. I’d also guess that when seasons change and my wardrobe changes (eg. when it started getting cold and I started wearing coats), that would affect what people comment on. My coworkers are pretty used to a lot of the things I’ve been wearing for the last few months.

Long live fashion.

Coolest finding

I’m not too surprised by which items of clothing were super popular, so the coolest thing was really seeing just how different strangers in the US would talk to me versus strangers in Melbourne. I have to be dressed pretty wackily to have a stranger come up to me on the street here.

Most difficult thing

Hiding this from my partner was pretty tough, since he was with me constantly for two weeks! I’d want to write things down before I forgot, but didn’t want to tip him off when I went for my phone.

What’s next?

I’m venturing out of the world of recording people I know for October, for a change!

Thanks for reading! Give this post a 👏 if you enjoyed it, and feel free to check out A Cloud Guru or say hi to me on LinkedIn 🎉

Past data vis projects:

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