Reviews Dataset
96K+ reviews collected directly from cerave.com — the dermatologist-developed skincare brand's own DTC storefront, a first-party view of its cleanser and moisturizer lines.
Nearly every review in this source has incentivized_review set true — CeraVe's DTC review program runs heavily through sampling/influencer campaigns (Influenster and similar), so this is a source where that field actually needs to be checked, not one where it can be assumed false as it can on most other retailers.
A representative slice of the review shape collected from cerave.com — real fields, illustrative rows.
| Product | Rating | Title | Verified | Review |
|---|---|---|---|---|
| AM Facial Moisturizing Lotion SPF 50 | 5 | PERFECT FOR UNDER MAKEUP | No | I've been struggling to find a moisturizer that's hydrating enough but still looks good under makeup and I've finally found it. Plus spf 50 is a huge plus |
| Acne Foaming Cream Wash | 5 | Holy grail! | No | I have been looking for a gentle acne wash for years... I have known as significant improvements in the acne on my chin. I'm so happy I found this product. |
| Acne Foaming Cream Wash | 5 | Really nice | No | This product did great for my skin. It's a great every day cleanser that kept my face under control. |
| Clay To Foam Cleanser | 5 | Awesome 3 in 1 Face Wash | No | I love how it's not only a face wash, but can be used as a mask and spot treatment so you're getting this really cool diverse product. |
| AM Facial Moisturizing Lotion SPF 50 | 4 | Good facial moistening lotion with sunscreen SPF50 | No | It takes sometimes to absorb into skin. It's lightweight and not greasy. Very mild and good lotion to have. However it doesn't have tone up or tinted. |
| Acne Foaming Cream Wash | 4 | Works well | No | This seems pretty good so far. Have used for about a week and have noticed some small differences in my face. Good texture and lather. |
Every cerave.com review is collected as its own record across 36 fields — the same schema used for every retailer BeautyFeeds tracks, so it joins cleanly against reviews from any other site.
review_idproduct_idsku_idsku_nameproduct_urlsite_namecountrylanguageratingtitlereview_textprosconssubmission_timeauthor_idauthor_nameuser_locationis_recommendedis_verified_purchaseis_staffincentivized_reviewhelpful_votesnot_helpful_votestotal_feedback_countskin_typeskin_toneage_rangeskin_concerneye_colorhair_colorbadgesphotosvideosscraped_atuniq_idother_information
Three of the most common ways this specific slice of the dataset gets used — each links to the full use case with a deeper workflow breakdown and field reference.
incentivized_review is populated (not just default-false) here, so it's an actually meaningful filter for isolating unprompted feedback.
Compare first-party DTC sentiment for cleansers and moisturizers against the same SKUs' reviews on Ulta or Amazon.
A focused, single-brand, derm-skincare review set — a clean baseline before mixing in noisier multi-brand sources.
Want to run one of these yourself? Sign in to app.beautyfeeds.io to filter cerave.com reviews and pull a sample before committing to a full export.
On the BeautyFeeds platform, preview the matching cerave.com review count before buying — filter by rating, submission date, verified purchase, and recommended status, then export exactly that slice.
The CeraVe reviews dataset contains individual customer reviews collected from cerave.com, including ratings, review titles, full review text, submission dates, verified purchase indicators, reviewer attributes, product IDs, SKUs, and product URLs where available.
BeautyFeeds currently has 96,497+ CeraVe reviews. The available review count changes as new reviews are collected.
Yes. Reviews can be filtered by dimensions including site, country, rating, submission date, verified purchase status, and recommended status before export.
Yes. CeraVe review data can be exported for analysis after filtering the dataset down to the records you need.
When disclosed by the reviewer, the dataset can include skin type, skin tone, age range, skin concern, eye color, and hair color — the same optional fields tracked across every retailer BeautyFeeds covers.
Review & Sentiment Analysis, Market Research & Trend Analysis, and ML & AI Model Training are the most common uses teams put this dataset to — see the breakdown below for how each works in practice.
Reviews from cerave.com are one slice of the full BeautyFeeds reviews dataset.
Filter, preview the matching count, and download or connect via API on the BeautyFeeds platform.