Key terms: a concern is a visible skin topic the scan scores (for example redness or pores). Attributes are the finer readings behind those scores. Product mapping links your SKUs to concerns and severity levels.
Not a medical diagnosis; does not replace a dermatologist. Face Age is based in Dubai and built for beauty ecommerce, not clinic charts.
What are the 13 skin concerns?
These are the live concern labels Face Age shows on results and in product mapping (from the product FAQ and consultation pages, checked with the live site on Nov 5, 2026):
- Fine wrinkles
- Eye wrinkles
- Deep wrinkles
- Dark circles
- Eye bags
- Pores
- Pigment
- Redness
- Oiliness
- Dryness (beta)
- Sagginess (beta)
- Dullness (beta)
- Acne
Beta means the reading is available but still flagged as beta in the product UI. Treat beta concerns carefully in aggressive ad claims; they are fine to map when a product is genuinely positioned for that topic.
Plain-language glossary (store copy, not medical)
Use these as customer-facing explanations. Keep them cosmetic.
Fine wrinkles. Shallow lines that show up with expression and time. Often mapped to gentle retinoids, peptides or hydrating serums — whatever your brand actually sells for early lines.
Eye wrinkles. Lines around the eyes. Map eye creams and targeted serums here, and watch exclusions if a product is not meant for the eye area.
Deep wrinkles. More pronounced folds. Usually a smaller set of SKUs; do not force every moisturizer into this bucket.
Dark circles. Discolouration under the eyes that can look like shadows. Map eye products positioned for tone, not every under-eye balm by default.
Eye bags. Puffiness under the eyes. Separate from dark circles in mapping even if some SKUs claim both.
Pores. How visible pore openings look on the surface. Common home for cleansers, BHA liquids and clarifying products.
Pigment. Uneven tone or spots as the scan reads them. Map brightening and tone products you already describe that way on PDPs.
Redness. Flushed or visibly red areas. Useful for calming and barrier products; check exclusions for strong actives you do not want on reactive-looking skin.
Oiliness. Shine and sebum-looking surface oil. Gel cleansers, lightweight moisturizers and mattifying products often live here.
Dryness (beta). Tight, lack-of-moisture look. Hydrating serums and richer creams. Because it is beta, keep internal notes honest with your team.
Sagginess (beta). Loss of firmness look. Firming-positioned SKUs only; do not dump your whole anti-age line here.
Dullness (beta). Lack of radiance. Exfoliating toners, vitamin C serums and glow products if that is how you sell them.
Acne. Pimples, blackheads and whiteheads as visible on the photo. Map your acne-positioned SKUs and use severity so a mild reading does not pull your strongest actives by default.
For how severity and exclusions work in the app, see how AI skin analysis picks products.
What does "250+ attributes" mean for a store team?
You will spend most of your time on the 13 concerns. The 250+ attributes sit underneath as a richer feature set the engine uses when it scores a face. Merchandisers do not need to name all 250 in the catalog. What you do need is consistent concern tags on products and severity rules that match how you sell.
Think of attributes as the reason two shoppers with "redness" can still get different routines: the underlying readings differ, and your rules decide which SKUs qualify.
Skin Age and Skin Health, briefly
Skin Age is a single glanceable number shoppers recognize from consumer apps. It is a summary from the analysis, not a passport age and not a medical finding. Useful on the results screen; optional in email subject lines if you stay tasteful.
Skin Health is a companion summary score for overall look of the skin in the analysis. Same rules: cosmetic, explanatory, never a diagnosis.
Neither replaces concern-level mapping. Products still attach to concerns like oiliness or pigment.
| Score / group | What store teams use it for | Caveat |
|---|---|---|
| 13 concerns | Product tags, severity, exclusions, result copy | Three are beta: dryness, sagginess, dullness |
| 250+ attributes | Engine detail behind the scores | You do not tag products with all of them |
| Skin Age | Shopper-friendly summary on results | Not a medical age test |
| Skin Health | Quick overall summary | Cosmetic reading only |
How should merchandising use this glossary?
Open your top 30 SKUs. For each, write the one or two concerns you already claim on the PDP. Enter those in Face Age with a severity band that matches the product strength. Add exclusions where needed (eye area, rich oils on acne-prone mappings, fragrance-heavy products if you ask about sensitivity in the quiz).
Then write result microcopy that matches the glossary tone: short, visible-skin language, no disease claims. If your brand voice is playful, keep the science-y words out of the H1 and in a footnote.
CX and chat teams should get the same list. When a shopper asks "why did I get this serum?", the answer is "your scan showed higher X and this product is mapped for X at that severity" — not "our AI diagnosed you."
Training a new hire in 20 minutes
- Show one live scan on staging (disclaimer visible).
- Walk the 13 concerns with this glossary.
- Open three mapped products and three unmapped ones.
- Change one severity rule and rescan with a test photo.
- Read the privacy and disclaimer lines out loud.
Pair this with the virtual skin consultation post for journey context, and the consultation solution page for how concerns appear on the face in the UI.
Copy examples you can adapt
For a results tooltip on redness: "Redness here means areas that look flushed on your photo. We use it to suggest calming products from our shelf — not to name a skin disease."
For oiliness: "Oiliness is about visible shine on the surface in this photo. If you already know you prefer gel textures, the quiz answer still matters alongside this score."
For acne: "Acne on this scan means visible blemishes the analysis picked up. Strength of the products we show depends on the severity band we set in the catalog, which you can ask us to explain."
Those three lines keep legal and brand safer than anything with diagnose, treat or clinical. If a shopper needs medical care, your human reply should say so plainly and point them to a qualified professional — the scan stays a store tool.
FAQ
What are the 13 Face Age skin concerns?
Fine wrinkles, eye wrinkles, deep wrinkles, dark circles, eye bags, pores, pigment, redness, oiliness, dryness, sagginess, dullness and acne. Dryness, sagginess and dullness are currently in beta.
What does 250+ attributes mean?
Finer readings behind the 13 headline concerns. Store teams mostly tag products with the 13 concerns.
Is this glossary medical advice?
No. Cosmetic AI skin analysis only. Not a medical diagnosis; does not replace a dermatologist.
What are Skin Age and Skin Health?
Glanceable summary scores beside the concern list. Mapping still runs on concerns and your rules.
Which concerns should I map first?
The ones your catalog already talks about on PDPs — often acne, dryness, oiliness, pigment, redness and wrinkles — then the rest.
