Smellmaps for perfume
We took the visual grammar Dr Kate McLean developed for mapping the smell of cities and applied it to every perfume we hold. This page explains what we borrowed, exactly which of our data drives it, where the analogy stops - and what we added.
On this page
The research
Dr Kate McLean is an artist, designer and researcher, an honorary research fellow at the University of Kent, and is writing her first book, an Atlas of Scents, Smells and Stinks, for Laurence King, expected in 2027. Over the past fifteen years she has produced smellmaps of cities including Paris, Amsterdam, New York, Singapore, Milan, Marseille and Kyiv. Each one is built from participatory smellwalks, in which local people log the odours they meet and rate each one for intensity, pleasantness and familiarity.
What makes the work matter to us is the encoding. A smellmap is not decoration. Hue carries which smell it is. The size and density of a bloom carry intensity and dominance. Diffusion across the map carries how the smell travels on the air, and a base-versus-episodic distinction carries persistence. It is a visual language for a thing you cannot see, and it is honest about being an impression rather than a measurement - which is exactly the discipline a perfume visualisation needs.
- McLean, K. Smellmap: Amsterdam - Olfactory Art and Smell Visualization. Leonardo 50(1), MIT Press (2017)
- Perkins, C. and McLean, K. Smell walking and mapping (2020)
- Sensory Maps - McLean's project site
What we mapped it onto
Every perfume in our catalogue carries a structured profile: its notes, each with a phase and a weight, a colour and a scent family per note, and three performance scores rated one to five. The map reads most but not all of that: notes, phases, weights, colours, and two of the three scores. Intensity scales the marks and projection scales the rings. Longevity it never looks at. Where a value is missing it falls back - a note with no phase is treated as a heart note, a note with no colour takes its family's, and a missing score is read as three out of five.
| McLean's encoding | Our data | On the smellmap |
|---|---|---|
| Hue - which smell it is | Note colour, falling back to its scent family | The colour of each bloom |
| Size and density - intensity and dominance | Note weight within the perfume, scaled by the perfume's intensity score | Mark radius and opacity - and the stronger a note, the higher it sits within its lane |
| Diffusion - how far it travels | Projection score, one to five | The number of contour rings and how far they reach. Reach is also scaled by the mark itself, so a big note carries further than a small one at the same projection |
| Base versus episodic - persistence | Note phase: base, heart or top | Three lanes across the canvas, top at the left through to base at the right. Top notes are crisp round marks, base notes pool into soft flat washes. Within a lane the horizontal position is random, so it carries nothing |
| Impressionistic register - honesty about precision | A stylistic choice, not a data field | Soft edges and translucency throughout - the map never claims to be a measurement |
Scroll the table sideways to see every column
Where the analogy stops
McLean's maps are hand-crafted artworks built from crowd-sourced human perception on a specific day in a specific place. Ours are generated deterministically from a structured profile, the same every time, across thousands of perfumes. We have borrowed her grammar, not her method, and we make no claim to her craft. The colour, size, form, ring reach, phase lane and height within the lane all carry data. The position within a lane does not, and neither does the small jitter that stops marks landing on a grid.
The soft register is deliberate and load-bearing. A separate strand of research, Kateřina Milatová's 2025 thesis on visualising fragrance online, found that a vivid scent visualisation raises a buyer's confidence without reliably raising their accuracy. An obviously impressionistic map makes a promise it can keep. See our page on that work.
What we added
Three departures are ours, made deliberately rather than by drift.
Time in place of space. A smellwalk traverses a city. A perfume traverses hours on skin. We kept McLean's grammar and swapped the dimension it maps. Our canvas reads left to right, first spray to drydown - a smellwalk through a perfume rather than through a place. Milatová's usability work independently points the same way: she replaced the vertical note pyramid with a horizontal evolution timeline, and her participants rated it the second most helpful cue on the page.
Named marks. McLean's participants walk the streets her maps describe. A perfume buyer has no such ground truth. Milatová found that colour alone is not enough to make a scent legible online: her participants preferred images to colours, and not one of them reached for abstraction when asked to draw a scent. So every note is named directly on the map, sized by its weight in the composition. A separate study of AI-made scent images reached the same conclusion from the other direction: an abstract picture with no words attached was the worst of every option they tested. See our page on that work.
One grammar, every perfume. Because the encoding is fixed and the rendering deterministic, the same perfume redraws identically and every map in the catalogue uses the same key. That makes two maps comparable as impressions. It does not make any single mark a scale you can read off: a bloom's size combines the note's weight with the perfume's intensity, and its rings inherit that size as well as the projection score. It is the difference between borrowing her paintings and learning her grammar.
It has never met the perfume. There is no formula behind it, no measured evaporation curve, and nothing about how it behaves on your skin rather than anyone else's. It draws our stored profile through three broad phase lanes and a fixed seed, so it shows you the shape of what we hold, not a record of what happens hour by hour. That is also why every mark stays soft-edged.
See it
Six perfumes spanning the families, each rendered live from its own data.
- Dior Sauvage - a bright citrus opening over woody amber
- Gucci Flora Gorgeous Gardenia - a white floral
- Acqua di Gio Profondo - a fresh aquatic that stays close to the skin
- Louis Vuitton Ombre Nomade - a dense oud, our most diffusive example
- Lattafa Khamrah - a sweet gourmand
- Lattafa Asad - a woody spice, sixteen notes deep
Every perfume on ScentVerdict has one - append /smellmap to any perfume URL.