anyone else a data nerd about their fragrances?
i’d love to hear what details you keep track of and how!
for me, some of the most useful data are:
- source (e.g., online platform or person’s name)
- estimated fill level at time of acquisition (i often get partial bottles)
- cost/mL
- bottle’s full volume
- size (sample, mini, travel, full)
- dispenser (atomizer, splash, dabber vial, applicator wand)
- date decanted
- date gifted or returned to someone
- date emptied
@berryjam
i also have a column for Luca Turin’s and/or Tania Sanchez’s rating of the perfume if applicable, and i can see many perfumes i’ve bought for myself have been highly ranked by them. this is because when i first started looking into fragrance, i browsed some of their books and chose to sample perfumes if the LT/TS reviews were interesting.
@berryjam
my data collection has been useful for generating (via pivot table) various lists of fragrances meeting certain criteria, if i’m looking for something in particular.
lately, i’ve been filtering for splash bottles of fragrances i’ve never decanted, from which i’ll select what to fill my emptied sample vials with atomizers with - in an attempt to approximate the scent of a full size bottle with atomizer and to test for differences between dabbed and sprayed.
@berryjam
i’ll pull a unique list of perfumes (no extra weight given to duplicates), filtering out emptied or removed scents, which i then pass to a randomizer formula to pick a perfume to wear.
generally speaking, i can grab a list based on any of the aforementioned characteristics to make a new “pool” from which i want to select my scent(s) of the day, like if i want focus on a certain segment of my collection (e.g., low-fill mini splash bottles that i got for free).
@berryjam
overall, lots of these things could be garnered without quantative data, but the fun part for me is that it’s more concrete :)