Description
This extensive dataset presents over 95,117,432 records of beauty product reviews, offering unparalleled depth into consumer experiences. Sourced from numerous leading online beauty retailers and review platforms, each entry includes essential identifiers such as product_id, sku_id, product_url, and the original site_name. Delve into granular user feedback with detailed rating, title, review_text, pros, and cons, alongside crucial consumer demographics like skin_type, age_range, and skin_concern. This rich collection is perfect for deep market research, competitive analysis, and understanding shifting beauty retail trends. Leverage these insights to inform product development, enhance marketing strategies, and gain a competitive edge in the dynamic Beauty & Personal Care sector. Covering submissions from 2010 through 2024, this dataset provides a comprehensive and current view of the global beauty consumer.
Highlights
Extensive collection of 95 million+ beauty product reviews.
Global beauty product reviews spanning diverse categories and demographics.
Data collected from 2010 to 2024, offering recent insights.
Captures user skin type, age range, pros, and cons.
Sample Data
Preview of available data:
| Cons | Pros | Title | Badges | Photos | Rating | Sku Id | Videos | Country | Uniq Id | Version | Is Staff | Language | Sku Name | Age Range | Author Id | Eye Color | Review Id | Site Name | Skin Tone | Skin Type | Hair Color | Product Id | Scraped At | Author Name | Product Url | Review Text | Imported At | Skin Concern | Helpful Votes | User Location | Is Recommended | Submission Time | Not Helpful Votes | Other Information | Incentivized Review | Is Verified Purchase | Total Feedback Count |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| \N | \N | \N | ["incentivizedReview"] | ["https://photos-us.bazaarv... | 5 | 2881324 | [] | us | 0000003a9666a90c | 0 | false | en | Golden Hour 24HR Lightweigh... | — | 32900294467 | hazel | 352186301 | sephora.com | — | comboSk | blonde | P517007 | 2026-08-02T08:13:11.626260+... | Paige411 | https://www.sephora.com/pro... | This product exceeds my exp... | 1970-01-01 00:00:00 | — | 0 | \N | true | 2025-07-18T18:05:30.000+00:00 | 0 | \N | true | false | 0 |
| \N | \N | — | \N | \N | 5.0 | \N | \N | us | 00000128464adc13 | 0 | false | en-US | \N | \N | jas3108 | \N | a5940b60-c994-497e-9de1-7c2... | iherb.com | \N | \N | \N | 26938 | 2026-08-14T08:25:22.374140+... | Jas | https://www.iherb.com/pr/pa... | Good quality. It smells ple... | 1970-01-01 00:00:00 | \N | 0 | \N | \N | 2022-10-10T20:12:14.912Z | 0 | \N | true | true | 0 |
| \N | \N | Advance night repair | ["incentivizedReview"] | [] | 5 | 121227 | [] | uk | 00000384c30aeba4 | 0 | false | en | Advanced Night Repair Serum... | — | z6dixdnlck3y0klwk3rh1klr0p | — | 261668708 | sephora.co.uk | — | — | — | 121227 | 2026-08-02T16:14:06.215830+... | Kiffy | https://www.sephora.co.uk/p... | This has been the best faci... | 1970-01-01 00:00:00 | — | 0 | Indianapolis, IN | true | 2023-10-19T07:00:00.000+00:00 | 0 | \N | true | false | 0 |
| \N | \N | Great spf | \N | \N | 5.0 | \N | \N | us | 00000398bf1c5c8b | 0 | false | en-US | \N | \N | 12EDBFF01C | \N | 7fa63d98-6b11-4e19-9797-be3... | iherb.com | \N | \N | \N | 150397 | 2026-08-10T20:27:28.616030+... | iHerb customer | https://www.iherb.com/pr/he... | Great moisturising spf, no ... | 1970-01-01 00:00:00 | \N | 0 | New Zealand | \N | 2026-04-22T04:32:57.361Z | 0 | \N | true | true | 0 |
| \N | \N | \N | ["incentivizedReview"] | [] | 5 | 54078 | [] | uk | 000003bdfcd95aec | 0 | false | en | Checks and Balances? Frothy... | — | 1874407257 | — | 201604778 | sephora.co.uk | — | — | — | 54078 | 2026-08-02T12:06:41.403670+... | Misha17K | https://www.sephora.co.uk/p... | This cleanser gives you the... | 1970-01-01 00:00:00 | — | 0 | \N | true | 2022-02-17T21:46:03.000+00:00 | 0 | \N | true | false | 0 |
| \N | \N | — | \N | \N | 5.0 | \N | \N | us | 0000044382d36842 | 0 | false | en-US | \N | \N | 2BF5188339 | \N | 91905d16-d3e8-4149-81a6-5fd... | iherb.com | \N | \N | \N | 76031 | 2026-08-15T02:49:30.093501+... | iHerb customer | https://www.iherb.com/pr/ce... | it\'s very good for my baby... | 1970-01-01 00:00:00 | \N | 0 | Saudi Arabia | \N | 2021-03-09T10:39:09.873Z | 1 | \N | true | true | 1 |
| \N | \N | My new favorite eyeliner! | ["incentivizedReview"] | [] | 5 | 183587 | [] | uk | 00000539f73b7f60 | 0 | false | en | Clear Cut Waterproof Liquid... | — | 6912103166 | — | 316992436 | sephora.co.uk | — | — | — | 183587 | 2026-08-02T15:49:57.127494+... | SimpliStaci | https://www.sephora.co.uk/p... | This liquid Eyeliner by Hau... | 1970-01-01 00:00:00 | — | 0 | \N | true | 2024-08-18T23:15:21.000+00:00 | 0 | \N | true | false | 0 |
| \N | \N | Great Product. Must try !! | [] | [] | 4 | 118143 | [] | uk | 0000058d46649223 | 0 | false | en | Blonde Perfecting Purple Sh... | — | 9372902554 | — | 160985149 | sephora.co.uk | — | — | — | 118143 | 2026-08-02T10:03:42.793020+... | Kpaoni | https://www.sephora.co.uk/p... | Loved Product! I have alway... | 1970-01-01 00:00:00 | — | 0 | \N | true | 2020-08-09T12:31:09.000+00:00 | 0 | \N | false | false | 0 |
Data Fields
This dataset includes the following data points:
Why This Data
This beauty retail dataset from provides comprehensive market intelligence and competitive insights. Perfect for:
- Market Research: Understand market trends and customer preferences
- Competitive Analysis: Compare pricing, products, and strategies
- Business Intelligence: Make data-driven decisions
- Price Monitoring: Track price changes and optimize your pricing
Use Cases
This dataset is perfect for various applications:
Product Formulation Insights: Beauty product developers leverage aggregated Review Text, Pros, Cons, and associated user Skin Type, Skin Concern, and Age Range to identify specific ingredient efficacy, common irritants, or desired benefits for new product development or existing formula refinement.
Market Opportunity & Trend Forecasting: Market researchers analyze changes in Rating, Review Text sentiment, and mentions of ingredients or product types over Submission Time across different Country and Language groups to identify emerging beauty trends, unmet consumer needs, and geographic market opportunities.
Personalized Recommendation Engine Training: E-commerce data scientists train machine learning models using Author Id's Ratings, Is Recommended status, and demographic attributes like Skin Type, Skin Tone, Age Range, and Skin Concern to deliver highly personalized product recommendations to individual users.
Competitive Product Benchmarking: Business intelligence analysts compare competitor Sku Name performance, average Rating, Helpful Votes, and recurring Pros/Cons from Review Text to identify strengths, weaknesses, and areas for strategic advantage against similar products in the market.
SEO & Content Strategy Development: Content marketers extract popular keywords, common questions, and pain points from Title and Review Text related to Skin Concern, Skin Type, and product usage to inform blog posts, FAQ sections, and product descriptions that address user queries directly.
Customer Lifetime Value Enhancement: CRM teams utilize Author Id history, Is Recommended status, and detailed Skin Type/Skin Concern information to segment customers and tailor loyalty programs, exclusive offers, and personalized communication strategies to increase engagement and retention.
Fraud Detection & Review Authenticity: Trust and safety teams develop algorithms to flag potentially incentivized or fraudulent reviews by analyzing patterns in Incentivized Review flags, Helpful Votes ratios, Author Id history, Submission Time spikes, and text similarity across Review Text for suspicious activity.
Get Access to This Dataset
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