Beauty is one of the richest data verticals in retail. Sephora’s US catalog carries thousands of SKUs across hundreds of brands, with product attributes - shade, finish, ingredients, skin type compatibility, active ingredients, ratings, and reviews - that are core to how customers actually choose products. If your product touches beauty in any way, Sephora data is one of the highest-signal sources available.
Happy Endpoint provides one live Sephora API and four datasets at different depth levels.
Sephora API
The live API returns current Sephora product data on demand:
Product search - keyword search across the full Sephora catalog. Filter by category, brand, price range, skin type, and rating. Returns product ID, name, brand, price, rating, review count, and availability.
Product reviews - review data per product. Includes star rating, review title, review text, reviewer attributes (skin type, skin tone, age range), verified purchase flag, and helpfulness votes.
Brand directory - full list of brands carried by Sephora with brand IDs for systematic catalog work.
Category browse - Sephora’s category hierarchy from top level (makeup, skincare, fragrance, hair, body) down to sub-categories (foundation, moisturizer, serum, etc.).
Real-time availability - in-stock status and shade/size availability.
Store locator - Sephora store locations by city or zip code.
Keyword autocomplete - search suggestions as the user types.
Response times average under 400ms.
Sephora Datasets
Four datasets are available for different use cases:
Sephora US Full Product Catalog
30,000+ SKUs covering all categories. Each product record includes:
- Full product name, brand, and category hierarchy
- Retail price and current sale price
- Average rating and review count
- Key product attributes (shade, finish, skin type, active ingredients where available)
- Product images
Best for catalog ingestion, recommendation engine training, and competitive analysis. Paid - contact us for pricing.
Sephora Customer Reviews Dataset
500,000+ verified customer reviews. Each review includes:
- Full review text (title and body)
- Star rating
- Reviewer skin type, skin tone, and age range
- Helpfulness votes (positive and total)
- Product ID and product name
Best for NLP and sentiment analysis, recommendation personalisation, and beauty attribute analysis. Paid - contact us.
Sephora Top 500 Bestsellers (Free)
The top 500 best-selling Sephora products across all categories, ranked by sales velocity. Includes retail price, current sale price, rating, and brand. Updated monthly. Free - download here.
Sephora Skincare Sample (Free)
1,000 skincare products with full ingredient lists as parsed arrays, skin type compatibility flags, and customer ratings. Designed for ML pipeline testing. Free - download here.
Use cases
Beauty catalog - ingest the full product catalog to power a search experience you control. The dataset gives you every SKU once; the API gives you live prices and availability.
Price monitoring - track price changes and sale events across Sephora’s catalog. Beauty pricing moves with promotional cycles (Sephora’s twice-yearly sale events drive significant price changes).
Shade and ingredient matching - the rich product attributes enable shade-matching tools, ingredient-avoidance filters (for sensitivity or allergy use cases), and skin type compatibility recommendations.
NLP and sentiment analysis - the reviews dataset is one of the largest publicly available beauty review corpora. It is well-suited for training sentiment models, extracting product claims, or analysing attribute sentiment (texture, scent, lasting power).
Competitive intelligence - track which brands are gaining shelf space, which products are climbing the bestseller list, and how pricing compares across categories.