Sephora Fields

Product Reviews · Beauty Insights

Beauty / Reviews

See how a product performs for real people. This workflow pulls structured Sephora reviews into clean data: the shade chosen, whether they'd recommend it, the reviewer's skin profile, verified purchases, helpful votes, and full text. So you can see what works, for whom, and why.

Ready to run! No login required — explore the use cases, preview the sample data below, and download a free sample set.

Code

📋 Available Fields

Field

Description

review-title

Headline of the customer review

review-body

Full text of the customer review

shade

Product shade / variant the reviewer chose

recommended

Whether the reviewer recommends the product

reviewer-name

Display name of the reviewer

skin-profile

Reviewer's self-reported eye color, skin tone & type

verified-purchase

Whether the review is from a verified purchase

review-date

Date the review was posted

helpful-yes

Number of "helpful" up-votes the review received

helpful-no

Number of "not helpful" votes the review received

💡 Use Cases

Shade & Formula Feedback — Break reviews down by shade and variant to see which colors and formulas win, and which draw complaints about texture, wear, or color accuracy.

Skin-Profile Segmentation — Segment sentiment by the reviewer's eye color, skin tone, and skin type to learn how a product performs across different people — invaluable for matching and recommendations.

Ingredient & Ethics Sentiment — Surface recurring themes such as cruelty-free, fragrance, or sensitivity concerns from review text to inform product and messaging decisions.

Incentivized-Review Detection & Social Proof — Separate gifted or incentivized reviews from organic ones, then feature your highest-voted "recommended" reviews as testimonials.

▶ Try it for Free