The Story Behind ScentGraph: A Data Geek Goes Deep on Scent
How a broken fragrance spreadsheet, a self-hosted database, and an obsession with scent data turned into a product.
Published 25 March 2026·1 min read
How It Started
I've been into fragrance since I was a kid. My earliest scent memory is Dad coming back from a trip to Disneyland with Disney gear for my sisters and a bottle of DKNY New York for Men for me. I'm pretty sure he grabbed it last minute from duty free, but it didn't matter. I loved it. I wore it every single day in high school, kept the bottle in my bag to reapply, and shared it with friends between classes. It became my teenage signature.
When that bottle got harder to find, I started shopping my dad's shelf instead. I'd sneak sprays from his collection, and the one that really stuck with me was Bvlgari Black. From there, I drifted through the usual designer suspects like Joop(never again), YSL, and Givenchy. But it wasn't until my late thirties that the hobby really lit up.
One day, a colleague at work pulled a handful of sample vials out of her purse and started talking us through each one. That simple moment, someone casually sharing samples they loved, flipped a switch for me. I went home, ordered my first proper sample set from Libertine, and fell hard. Ganymede by Marc-Antoine Barrois was the first one that really rewired my brain. Then came AmouageReflection Man, Creed Green Irish Tweed, and Xerjoff Torino 24, my first serious "I need the full bottle" purchases.
The moment it stops being casual and starts being a hobby.
From Scent Geek to Spreadsheet Geek
Of course, I couldn't just enjoy it. I'm a geek at heart. I love numbers, patterns, and systems. So naturally, the first thing I did was spin up a fragrance spreadsheet. I logged every sample and bottle, my impressions on paper and on skin, what I loved, what I hated. The logging became a ritual. It started with the love of the smell, but the act of writing it down became part of the hobby.
Fragrances mentioned
Tap through to explore each scent in the ScentGraph app.
As the sheet grew, I hit a wall. It was getting impossible to navigate. I enjoyed putting data in, but once it was logged, it was hard to go back to when I actually wanted to find something. The bigger it got, the more it felt like a graveyard of entries.
That's when the idea of adding an AI layer clicked. I moved from a basic spreadsheet to a self-hosted cloud setup with a proper database. On top of that, I built automations that could enrich my collection for me, pulling in notes, houses, and extra info on each fragrance so I could learn the "why" behind what I liked.
Pretty quickly, it stopped being just "why" and also became "who". I realised I was often favouring scents from the same perfumers again and again. Hello, Quentin Bisch. That sent me down another rabbit hole, exploring more of his work to see what else would click for me.
The more I wore and the more I logged, the better the recommendations got. That was the moment it stopped feeling like a spreadsheet and started feeling like a brain. Patterns were emerging that I wouldn't have spotted on my own.
When the System Broke
At the same time, I was still deep in the content side of the hobby. I watch creators like MilanScents, Perfumerism, and Justin Copeland regularly. They've introduced me to countless scents and given me hours of entertainment. Early on, I'd think "I have to try that" and sometimes blind buy on the spot, only to regret it later. Now I add the scent to my own database and run it against my taste profile instead. One thing you learn quickly in the smelly water space: things get expensive fast.
That first system was a bit janky, but it showed me something important. Despite having a ton of fragrances, I kept coming back to the same half-dozen bottles, then cycling them with the seasons. The recommendation layer helped me break those patterns, try more of what I already owned, and rotate things more intentionally. It also gave me a way to filter hype through my own data. Instead of buying because a video was convincing, I could ask: "Does this actually look like something I'll wear?"
Eventually, I blew past 60+ bottles and 500 plus samples. The database was getting messy. The automations I'd cobbled together were fragile. And underneath all that, a bigger question had formed. What if this didn't have to be duct tape, databases, and spreadsheets? What if it could be a real product, something I wanted to use every day, and maybe something other frag heads would want to use too?
Why ScentGraph Exists
One of the things I love about the fragrance community is how passionate and generous it is. People are in this for the love of scent, not just flexing bottles. So if I was obsessively hacking together a personal "fragrance brain", there had to be others quietly doing the same in their own way.
ScentGraph is my attempt to take that messy spreadsheet, the self-hosted experiments, the automations, and my obsession with both scent and data and turn it into something focused. A tool built for people who don't just want to track what they own, but actually want to understand how they wear it.
Log your scent, and we'll do the rest. We'll show you what you're wearing, when, how often, which perfumers and houses you actually gravitate toward, and use that to help you discover more of what you really like.
If any of this sounds like your kind of chaos, that's exactly who I built it for.
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ScentGraph is now in early access. Join the waitlist and claim your spot at https://scentgraph.app. Founding members get a permanent profile badge and early access.
