The 10 skin metrics, explained

What it measures: How well-hydrated your skin's surface appears — plumpness and moisture-related smoothness.

Why it matters: Well-hydrated skin tends to look more supple and radiant, while dehydration can make fine lines more noticeable and skin look dull.

How we estimate it: We look at light reflection and surface-smoothness patterns across your skin that are associated with moisture content.

What it measures: The presence and density of visible blemishes and breakout-like texture irregularities.

Why it matters: Tracking blemish-prone areas over time can help you notice patterns in flare-ups across different regions of your face.

How we estimate it: The model detects localized color and texture irregularities consistent with blemishes in each facial region.

What it measures: Visible redness or flushing across the skin, particularly on the cheeks, nose, and chin.

Why it matters: Persistent redness affects how even your skin tone looks and can be a useful signal to track for sensitive-feeling areas.

How we estimate it: We analyze color-channel distribution — especially in the red spectrum — relative to your overall skin tone.

What it measures: Surface shine and light reflectivity associated with sebum, most often in the T-zone.

Why it matters: Excess shine can affect how makeup wears through the day and how texture appears in photos.

How we estimate it: We analyze specular highlights — the small bright reflections light makes on oily surfaces — across your face.

What it measures: Localized areas of hyperpigmentation, such as sun spots or marks left behind by past blemishes.

Why it matters: Dark spots are one of the biggest factors in how even a complexion appears cosmetically.

How we estimate it: We measure contrast and color deviation between spots and the surrounding skin tone.

What it measures: Your skin's overall 'glow' — a combination of tone evenness and healthy light reflection.

Why it matters: Radiance is closely linked to how fresh and vital skin appears at a glance.

How we estimate it: We combine tone-uniformity analysis with light-reflection patterns measured across the whole face.

What it measures: How smooth or rough the skin's surface appears, including visible pores and fine bumps.

Why it matters: Smoother, more even texture is generally associated with a healthier-looking complexion.

How we estimate it: Fine-grained surface pattern analysis looks for high-frequency detail that indicates roughness.

What it measures: How taut the skin appears along the jawline, cheeks, and contours of the face.

Why it matters: Firmness is one of the more visible cosmetic markers people associate with a youthful look.

How we estimate it: We analyze facial contours and edges around key landmarks to estimate visible tautness versus laxity.

What it measures: The presence and depth of visible fine lines and wrinkles, particularly around the eyes, forehead, and mouth.

Why it matters: Wrinkles are a classic, easily visible marker of cosmetic skin aging that many people like to track over time.

How we estimate it: Edge-detection analysis traces fine-line patterns in the regions where wrinkles most commonly form.

What it measures: Darkness or discoloration in the skin under your eyes, relative to the rest of your face.

Why it matters: Under-eye darkness strongly affects how rested or tired someone appears to look.

How we estimate it: We compare color and contrast in the under-eye region against your surrounding skin tone.