Fragrance & Beauty,
according to AI
Every week we ask ChatGPT, Claude and Gemini the questions real UK consumers ask about fragrance & beauty — and record exactly which brands they put forward. Right now, Charlotte Tilbury owns the conversation.
0 AI answers this run · 0 brands named · measured, never estimated
Charlotte Tilbury is the default answer.
Named in 7% of fragrance & beauty answers, typically in position 2.5. La Mer follows at 5%, Clé de Peau Beauté at 3%.
Every brand AI names, ranked.
Visibility is the share of answers naming the brand; citation share is its slice of all brand-owned pages cited; read→cited is how often its pages convert a read into a citation.
| # | Brand | Visibility | Avg. position | Citation share | Read→cited |
|---|---|---|---|---|---|
| 1 | Charlotte Tilbury | 7% | 2.5 | 50% | 0% |
| 2 | La Mer | 5% | 1.7 | 0% | — |
| 3 | Clé de Peau Beauté | 3% | 1.5 | 0% | — |
| 4 | Elemis | 3% | 1.5 | 0% | — |
| 5 | Estée Lauder | 3% | 2.0 | 25% | — |
| 6 | MAC Cosmetics | 3% | 3.0 | 0% | — |
| 7 | Maison Francis Kurkdjian | 3% | 4.5 | 0% | — |
| 8 | Dior | 3% | 5.5 | 0% | — |
| 9 | Jo Malone London | 3% | 6.0 | 0% | — |
| 10 | Maison Margiela | 3% | 6.0 | 0% | — |
| 11 | Chanel | 3% | 6.5 | 0% | — |
| 12 | Diptyque | 3% | 7.0 | 0% | — |
| 13 | Creed | 2% | 1.0 | 0% | — |
| 14 | Augustinus Bader | 2% | 2.0 | 0% | — |
| 15 | La Prairie | 2% | 2.0 | 0% | — |
Charlotte Tilbury is named most. That is not the same as being wanted.
Being named is visibility. Underneath it, every answer describes a brand in three ways — how much it stands out, how much it belongs, and how much it is returned to. In fragrance & beauty, Maison Francis Kurkdjian leads attraction at 135 against Elizabeth Arden at 97, indexed on the category at 100.
Each whorl lights one ring per index threshold cleared. See the full fragrance & beauty desire edition →
The referees of fragrance & beauty.
The independent sources AI models cite when answering fragrance & beauty questions — the places a brand needs to be seen, reviewed and ranked.
The citation gap.
When Claude or ChatGPT opens a brand's own pages while answering, does the page make the cited-sources list? Too little read data in this category so far — the weekly runs will fill this in.
Full data table
| # | Brand | Visibility | Avg. position | Citation share | Read→cited |
|---|---|---|---|---|---|
| 1 | Charlotte Tilbury | 7% | 2.5 | 50% | 0% |
| 2 | La Mer | 5% | 1.7 | 0% | — |
| 3 | Clé de Peau Beauté | 3% | 1.5 | 0% | — |
| 4 | Elemis | 3% | 1.5 | 0% | — |
| 5 | Estée Lauder | 3% | 2.0 | 25% | — |
| 6 | MAC Cosmetics | 3% | 3.0 | 0% | — |
| 7 | Maison Francis Kurkdjian | 3% | 4.5 | 0% | — |
| 8 | Dior | 3% | 5.5 | 0% | — |
| 9 | Jo Malone London | 3% | 6.0 | 0% | — |
| 10 | Maison Margiela | 3% | 6.0 | 0% | — |
| 11 | Chanel | 3% | 6.5 | 0% | — |
| 12 | Diptyque | 3% | 7.0 | 0% | — |
| 13 | Creed | 2% | 1.0 | 0% | — |
| 14 | Augustinus Bader | 2% | 2.0 | 0% | — |
| 15 | La Prairie | 2% | 2.0 | 0% | — |
Three models. Three different answers.
Ask about fragrance & beauty and the brand you are shown depends on the assistant: Claude → Maison Margiela, Gemini → Charlotte Tilbury, ChatGPT → Maison Francis Kurkdjian. Their top-five lists share just 0% of names.
Brands whose visibility swings most between models — the bar per model, widest gap on the right.
The data behind this chart
| Brand | Claude | Gemini | ChatGPT | Spread |
|---|---|---|---|---|
| Charlotte Tilbury | 5% | 15% | 0% | 15pp |
| Diptyque | 0% | 10% | 0% | 10pp |
| Maison Margiela | 5% | 5% | 0% | 5pp |
| Lancôme | 5% | 0% | 0% | 5pp |
| Clinique | 5% | 0% | 0% | 5pp |
| MAC Cosmetics | 5% | 5% | 0% | 5pp |
| Jo Malone London | 5% | 5% | 0% | 5pp |
| Clé de Peau Beauté | 5% | 0% | 5% | 5pp |
| La Prairie | 5% | 0% | 0% | 5pp |
| Chanel | 5% | 5% | 0% | 5pp |
How-to guides carry fragrance & beauty.
Every page AI opened while answering, classified by what kind of page it is. How-to guides supply the most citations; Comparisons convert best — 100% of the ones models opened were actually cited.
The data behind this chart
| Page type | Cited | Read but not cited | Conversion |
|---|---|---|---|
| How-to guides | 89 | 8 | 92% |
| Editorial | 67 | 15 | 82% |
| Comparisons | 29 | 0 | 100% |
| Other | 14 | 9 | 61% |
| Listicles | 9 | 0 | 100% |
| category-page | 8 | 0 | 100% |
| Product pages | 7 | 1 | 88% |
| Documentation | 0 | 9 | 0% |
Structured data is what separates cited from ignored.
Of the fragrance & beauty pages models actually opened, how much more often each feature's pages ended up in the cited sources. Structured data is worth 27 percentage points; hard statistics pages fare 18pp worse. Measured within the read population, so selection can't flatter it.
The data behind this chart
| Feature | Pages with | Cited % | Pages without | Cited % | Difference |
|---|---|---|---|---|---|
| Structured data | 231 | 89% | 55 | 62% | +27pp |
| Named author | 168 | 90% | 118 | 75% | +15pp |
| Updated this year | 68 | 81% | 218 | 84% | -4pp |
| Answer up front | 114 | 81% | 172 | 85% | -5pp |
| Comparison table | 57 | 70% | 229 | 87% | -17pp |
| Hard statistics | 63 | 70% | 223 | 87% | -18pp |
Estée Lauder builds pages AI can quote.
Readiness scores each brand's own pages on the structure models reward — a direct answer up front, tables, hard numbers, named authors, structured data, recency, specifications. SkinCeuticals is the widest gap: well-built pages that still aren't converting into citations.
| Brand | Readiness | Pages cited | Pages profiled |
|---|---|---|---|
| Estée Lauder | 29 | 33% | 3 |
| SkinCeuticals | 25 | 0% | 5 |
| Augustinus Bader | 14 | 0% | 95 |
| Charlotte Tilbury | 9 | 0% | 100 |
Readiness is the share of eight measurable structural signals present on a brand's profiled pages. It is a build-quality measure, not a ranking of the brand.
The questions fragrance & beauty pages have to settle.
Read straight off the pages AI cited: the consumer questions cited content answers most often. Content that fails to settle these is content models have no reason to quote.
Nineteen more categories.
Method: 20 unbranded consumer prompts per category, spread across the buying journey, run weekly against ChatGPT, Claude and Gemini. Read→cited uses Claude and ChatGPT only (Gemini does not separate the two). Correlational observations of model behaviour at the time of the run. Data from the run completed Sat, 12 Sep 2026 08:45:03 GMT.