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Sephora Product Details & Reviews Scraper (with Demographics) 💬

👁 SIÁN Agency Store
👁 Sephora Catalog
👁 Beauty

🎉 Sephora reviews scraper + product details extractor — pull reviews with demographics (skin type, age, verified purchase) OR full product specs by Sephora Product ID

Built for beauty research teams, sentiment-analysis platforms, brand monitors, and product-intelligence pipelines who need Sephora.com reviews + ingredient + variant data — no Sephora API, no setup

📋 Overview

Two modes in one actor:

• 💬 Product Reviews — full BazaarVoice review records with skin type, skin tone, eye color, hair color, age range, verified purchase, helpfulness score, and photo URLs for any Sephora product ID
• 📋 Product Details — full SKU + variants + ingredients + descriptions + highlights + images + videos for any Sephora product ID

Paste one or more Sephora Product IDs (e.g. P507574), choose a mode, and get a flat structured dataset. One run, one tidy dataset out.

Why teams choose SIÁN for Sephora reviews + product data:

• ✅ Demographic filters on reviews — skinType, skinTone, eyeColor, hairColor, ageRange populated per review (the input-shape moat — no other Sephora actor exposes these)
• ✅ Two modes, one actor — productReviews and productDetails cover both major buy-side queries in a single listing
• ✅ Verified-purchase + helpfulness filters — surface the reviews that actually move conversion
• ✅ Bulk Product IDs supported — process a list of productIds from your catalog dataset in one run
• 🧼 HTML stripped from descriptions — long descriptions, suggested usage, ingredient lists arrive as clean text, not raw <br><p> markup
• ⚡ 23-field review records (rating, title, text, demographics, photos, helpfulness, verified-purchase, recommendation rate)
• ⚡ 35+ field product detail records (SKUs, variants, prices, ingredients, descriptions, highlights, images, videos)
• 💰 Pay-per-result pricing — only charged for successful extractions
• 💎 No Sephora API key, no setup, no proxies — paste a product ID and run
• 📊 HTML run report — rating distribution pie, top reviews, success stats

✨ Features

Product Reviews Mode (action: "productReviews")

• 💬 Full review records — rating (1–5★), title, body, username, submission time
• 👤 Demographics — skinType (Combination / Dry / Normal / Oily), skinTone, eyeColor, hairColor, ageRange
• ✅ Verified purchase flag — separate genuine buyers from anonymous reviewers
• 👍 Helpfulness score + positive/negative feedback counts + total feedback count
• 📷 Photo URLs — array of reviewer-uploaded photos (when present)
• ⭐ Rating filter — only return reviews at or above N stars (1–5)
• 🔄 Sort by — MOST_HELPFUL (default), HIGHEST_RATING, LOWEST_RATING, NEWEST, OLDEST
• 📄 Pagination — limit (1–1000 per call) + offset for full review-history pulls

Product Details Mode (action: "productDetails")

• 📦 All SKUs / variants — full size + price + stock arrays
• 💰 Min / max price range computed across variants
• 🧪 Ingredients list — currentSku.ingredientDesc, HTML-stripped to clean text
• 📝 Descriptions — shortDescription, longDescription, suggestedUsage all HTML-stripped
• ⭐ Highlights — ["Good for: Dry Skin", "Clean at Sephora", "Cruelty-Free", ...]
• 🖼️ Hero image + alternate images array (HTTPS URLs)
• 🎥 Product video URLs when present
• 🏷️ Stock + availability flags — isOutOfStock, isOnlineOnly, isLimitedEdition
• 🗂️ Parent category — links back to the catalog taxonomy
• 📊 Variant count + flattened allVariants array (skuId, size, price, stock)

🎬 Quick Start

Paste any Sephora Product ID (find it in any Sephora URL after /product/).

{
"productId":"P507574",
"action":"productReviews"
}

Returns the top 10 most-helpful reviews for that product with full demographics and photo URLs.

🚀 Getting Started (4 Simple Steps)

Step 1: Find a Sephora Product ID

Open any product page on sephora.com — the URL ends with -P{ID} (e.g. https://www.sephora.com/product/the-dewy-skin-cream-P441101 → P441101).

You can also pipe IDs straight from the Sephora Product Catalog Scraper — every row has productId ready to paste.

Step 2: Pick a mode

• productReviews — customer reviews with demographics
• productDetails — full product spec, variants, ingredients, media

Step 3: (Reviews) Add filters

Minimum rating, sort order, limit (1–1000), offset for pagination.

Step 4: Click "Start"

Reviews or details stream into the Apify dataset. JSON, CSV, Excel ready.

📥 Input Configuration

Example — Top 50 most-helpful 4★+ reviews for a product:

{
"productId":"P441101",
"action":"productReviews",
"reviewRating":4,
"reviewSortBy":"MOST_HELPFUL",
"reviewLimit":50
}

Example — Full product details for one Sephora SKU:

{
"productId":"P507574",
"action":"productDetails"
}

Example — Bulk reviews for an entire bestseller list:

{
"bulkProductIds":["P507574","P441101","P393151","P520773"],
"action":"productReviews",
"reviewLimit":20,
"reviewRating":1
}

📤 Output

Reviews Mode (itemType: "product-review")

Details Mode (itemType: "product-detail")

35+ fields per product. Key fields:

Plus an HTML run report saved to the key-value store.

💼 Use Cases & Examples

• Scrape Sephora reviews for sentiment analysis — Pull reviews by skin type or age range, then run NLP over reviewText
• Sephora reviews API alternative — Programmatic access to BazaarVoice review data without a vendor contract
• Sephora ingredient data extraction — Pull ingredients field for INCI auditing, allergen detection, formulation research
• Sephora product details API — Full SKU + variant + price spec for catalog enrichment
• Extract Sephora customer reviews with skin type filter — Build a "reviews from people with my skin type" tool
• Sephora verified purchase reviews — Filter for verifiedPurchase: true to discard non-buyers
• Sephora review sentiment analysis pipeline — Schedule daily pulls, run sentiment scoring, surface trending issues
• Sephora rating data export — Per-product rating distribution for retail dashboards
• Sephora SKU and variant data export — Full variant matrix for retail allocation planning
• Beauty review aggregator alternative — Build your own review aggregator from a clean Sephora data feed
• Influencer marketing research — Pair with our Catalog Scraper — find bestsellers in a category, then pull their reviews to see what real buyers say
• Product launch monitoring — Track review velocity and rating trajectory in the first 30 days after launch

📊 Performance & Pricing

• Speed: ~3–8 seconds per Product ID (single upstream call + transform)
• Throughput: bulk-paste up to hundreds of Product IDs per run
• Reviews limit: up to 1000 reviews per product per call (paginate beyond with reviewOffset)
• FREE tier: 5 products per run for evaluation
• PAID tier: unlimited products, priority infrastructure
• Pay-per-result: only charged for successful extractions

🔗 View current pricing

❓ Frequently Asked Questions

Q: Does Sephora have a reviews API? A: Sephora doesn't publish a public reviews API. This actor reads from a structured Sephora-data feed and exposes both review and product-detail surfaces.

Q: How do I find a Sephora Product ID? A: Open any product page on sephora.com — the URL ends with -P{ID} (e.g. P441101). Or pipe IDs directly from our Sephora Product Catalog Scraper.

Q: Can I scrape all reviews for a product? A: Yes — set reviewLimit: 1000 and paginate via reviewOffset if a product has more than 1000 reviews.

Q: What demographic data is exposed? A: skinType, skinTone, eyeColor, hairColor, ageRange — populated when the reviewer filled them in on Sephora's site (most reviews do).

Q: Is there a free Sephora reviews scraper? A: This actor's FREE tier returns 5 products per run with full feature access — enough for evaluation and small audits. Upgrade for unlimited.

Q: How much does the Sephora reviews scraper cost? A: Pay-per-result pricing. You're billed per successful review or product detail extracted. See the current rate on the actor page.

Q: Can I scrape Sephora data legally? A: We only extract data Sephora has chosen to publish publicly (no user logins, no private contact data). See the Legal section below.

Q: Are HTML tags stripped from descriptions? A: Yes — shortDescription, longDescription, suggestedUsage, and ingredientDesc arrive as clean text with <br>/<p> normalized to line breaks and HTML entities decoded.

Q: What output formats are available? A: JSON, CSV, Excel, RSS, HTML, XML — export directly from the Apify dataset UI or via API.

Q: Where can I find a Sephora review dataset on GitHub? A: Most GitHub Sephora review datasets are months-stale snapshots. This actor returns live reviews on demand — schedule it for fresh data daily.

🐛 Troubleshooting

Empty review dataset

• The product may have no reviews at or above your reviewRating floor. Set reviewRating: 1 to fetch all reviews.
• Some new products have zero reviews — verify on sephora.com.

Only 5 results when I expected more

• You're on the FREE tier. Upgrade for unlimited.

HTML tags appearing in description fields

• Should never happen on shortDescription / longDescription / suggestedUsage / ingredients — they're stripped automatically. If you see tags in another field, open an Issue.

productId not found

• The product may have been delisted. Open the URL https://www.sephora.com/product/anything-{productId} in a browser to confirm.

Pagination cuts off early

• reviewLimit caps at 1000 per call. For >1000 reviews, increment reviewOffset across multiple runs.

⚠️ Trademark Disclaimer

This actor is an independent scraping tool and is not affiliated with, endorsed by, or sponsored by Sephora USA, Inc. or any of its subsidiaries. "Sephora" is used solely in a descriptive sense to identify the public data source the actor reads from. Sephora® and all brand names appearing in product records are trademarks of their respective owners. All other trademarks are the property of their respective owners.

⚖️ Is it legal to scrape data?

Our actors are ethical and do not extract any private user data, such as email addresses or contact information. They only extract what Sephora has chosen to share publicly on sephora.com. Review data is published publicly by reviewers who explicitly consented to public display. We therefore believe that our actors, when used for ethical purposes by Apify users, are safe.

However, you should be aware that your results could contain personal data. Personal data is protected by the GDPR in the European Union, the CCPA in California, and by other regulations around the world. Review demographics (skinType, ageRange, etc.) are non-PII but the combination of nickname + photo + demographics may raise privacy considerations in some jurisdictions. Consult your lawyers when processing review data at scale.

You can also read Apify's blog post on the legality of web scraping.

✨ More by SIÁN Agency

Part of the SIÁN Agency Apify portfolio — production-grade scrapers used by agencies, research teams, and brands. A few that pair well with this Sephora reviews actor:

Beauty & E-commerce

• Sephora Product Catalog Scraper — Brands, Categories & Filters — Pull catalog by brand / category / keyword, then pipe productIds here for full enrichment
• Taobao & Tmall Product Scraper — China's #1 beauty marketplace
• TikTok Shop Scraper — TikTok Shop beauty product reviews

Social Discovery & Sentiment

• Best TikTok AI Transcript Extractor — Find creator-mentioned Sephora bestsellers
• Instagram AI Transcript Extractor — Reels + Stories transcription
• YouTube AI Comments Scraper — Beauty influencer comment sentiment

Browse all SIÁN actors →

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🤝 Support

👁 Telegram Support

Join our active support community

• For issues or questions, open an issue in the actor's Apify Console Issues tab
• 📧 apify@sian-agency.online

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