MaIA Scan blog
Blog
Articles on selfie-based skin analysis, photo-based makeup try-on and AI beauty advice for brands, retailers and e-commerce.
Virtual Makeup Try-On for Paid Social Campaigns: Turning Ad Clicks Into Shade Decisions
Paid social sends traffic to a product page where the visitor still cannot tell if the shade suits them. Here is how to build a virtual makeup try-on campaign landing page that answers the shade question in the first seconds.
Read article →Skin Analysis API for Brazilian Skin Tones: Why Training Data Decides the Result
Shade matching and skincare recommendations fail at the edges of a model's training data. Here is what a skin analysis API for Brazilian skin tones returns, how to test it before you integrate, and where it fits in the customer journey.
Read article →Selfie Skin Analysis for Foundation Shade Matching: From Undertone to the Right SKU
Foundation is the hardest category to buy online. Here is how selfie skin analysis for foundation shade matching turns a photo into tone, undertone and a short list of SKUs your customer can actually preview.
Read article →Virtual Try-On for Beauty Marketplaces: One Integration, Many Brand Palettes
Marketplaces sell hundreds of makeup brands with inconsistent shade data. Here is how virtual try-on for beauty marketplaces can be structured so each seller keeps its own calibrated palette behind a single integration.
Read article →Build vs Buy a Beauty API: When to Train Your Own Model and When to Integrate
Train your own skin and hair analysis model, or integrate a beauty API? A practical breakdown of the data, evaluation and maintenance costs behind each path — and the middle road most beauty brands end up taking.
Read article →Haircare Product Recommendations From a Selfie: Matching Hair Attributes to Your Catalog
Most beauty personalization stops at skin. Here is how to build haircare product recommendations from a selfie — mapping hair attributes to your catalog, handling low confidence and shipping it on product pages, WhatsApp and CRM.
Read article →Beauty Profile in Loyalty Programs: Turning One Selfie Into a Member Benefit
Loyalty programs collect points but rarely collect anything useful about the member's skin or hair. Here is how to use a beauty profile in loyalty programs as a real benefit — enrollment, re-scans, profile-aware rewards and consent.
Read article →Virtual Beauty Advisor KPIs: What to Measure in the First 90 Days
A practical measurement plan for teams launching a virtual beauty advisor: the four layers of KPIs that matter, what to instrument before go-live, and the metrics that mislead.
Read article →Virtual Makeup Try-On for Product Launches: Shade Previews Before the First Shipment
A new lipstick or foundation range launches without testers, without stock in stores and often without photography that shows the shade on real skin. Here is how to plan virtual makeup try-on for product launches, from palette calibration to launch-week channels.
Read article →Skin Analysis API Integration: From First Call to Production
A practical walkthrough of skin analysis API integration for beauty teams: what the response contains, how to plan capture and consent, where the call belongs in your stack, and how to handle low confidence before launch.
Read article →Selfie Skin Analysis Image Requirements: Lighting, Framing and What to Do With Low Confidence
Before you integrate, know what kind of photo your skin analysis actually needs. A practical guide to selfie skin analysis image requirements — lighting, framing, capture UX and how to handle low confidence fields.
Read article →In-Store Virtual Try-On: Makeup Previews at the Beauty Counter Without a Tester
How beauty brands and retailers can run in-store virtual try-on on a tablet at the counter: live camera mode, photo mode, shade coverage, staff workflow and what to decide before the first store.
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